Sample records for landslide susceptibility mapping

  1. A landslide susceptibility map of Africa

    NASA Astrophysics Data System (ADS)

    Broeckx, Jente; Vanmaercke, Matthias; Duchateau, Rica; Poesen, Jean

    2017-04-01

    Studies on landslide risks and fatalities indicate that landslides are a global threat to humans, infrastructure and the environment, certainly in Africa. Nonetheless our understanding of the spatial patterns of landslides and rockfalls on this continent is very limited. Also in global landslide susceptibility maps, Africa is mostly underrepresented in the inventories used to construct these maps. As a result, predicted landslide susceptibilities remain subject to very large uncertainties. This research aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. As a first step, we compiled all available landslide inventories for Africa. This data was supplemented by additional landslide mapping with Google Earth in underrepresented regions. This way, we compiled 60 landslide inventories from the literature (ca. 11000 landslides) and an additional 6500 landslides through mapping in Google Earth (including 1500 rockfalls). Various environmental variables such as slope, lithology, soil characteristics, land use, precipitation and seismic activity, were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in our dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides, tested the significance of the considered environmental variables and evaluated the performance of the fitted multiple logistic regression model against another subset of mapped landslides. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding rockfalls. In both maps, topography, lithology and seismic activity were the most significant variables. The latter factor may be surprising, given the overall limited degree of seismicity in Africa. However, its significance indicates that frequent seismic events may serve as in important

  2. Mapping landslide susceptibility using data-driven methods.

    PubMed

    Zêzere, J L; Pereira, S; Melo, R; Oliveira, S C; Garcia, R A C

    2017-07-01

    Most epistemic uncertainty within data-driven landslide susceptibility assessment results from errors in landslide inventories, difficulty in identifying and mapping landslide causes and decisions related with the modelling procedure. In this work we evaluate and discuss differences observed on landslide susceptibility maps resulting from: (i) the selection of the statistical method; (ii) the selection of the terrain mapping unit; and (iii) the selection of the feature type to represent landslides in the model (polygon versus point). The work is performed in a single study area (Silveira Basin - 18.2km 2 - Lisbon Region, Portugal) using a unique database of geo-environmental landslide predisposing factors and an inventory of 82 shallow translational slides. The logistic regression, the discriminant analysis and two versions of the information value were used and we conclude that multivariate statistical methods perform better when computed over heterogeneous terrain units and should be selected to assess landslide susceptibility based on slope terrain units, geo-hydrological terrain units or census terrain units. However, evidence was found that the chosen terrain mapping unit can produce greater differences on final susceptibility results than those resulting from the chosen statistical method for modelling. The landslide susceptibility should be assessed over grid cell terrain units whenever the spatial accuracy of landslide inventory is good. In addition, a single point per landslide proved to be efficient to generate accurate landslide susceptibility maps, providing the landslides are of small size, thus minimizing the possible existence of heterogeneities of predisposing factors within the landslide boundary. Although during last years the ROC curves have been preferred to evaluate the susceptibility model's performance, evidence was found that the model with the highest AUC ROC is not necessarily the best landslide susceptibility model, namely when terrain

  3. Landslide susceptibility map: from research to application

    NASA Astrophysics Data System (ADS)

    Fiorucci, Federica; Reichenbach, Paola; Ardizzone, Francesca; Rossi, Mauro; Felicioni, Giulia; Antonini, Guendalina

    2014-05-01

    Susceptibility map is an important and essential tool in environmental planning, to evaluate landslide hazard and risk and for a correct and responsible management of the territory. Landslide susceptibility is the likelihood of a landslide occurring in an area on the basis of local terrain conditions. Can be expressed as the probability that any given region will be affected by landslides, i.e. an estimate of "where" landslides are likely to occur. In this work we present two examples of landslide susceptibility map prepared for the Umbria Region and for the Perugia Municipality. These two maps were realized following official request from the Regional and Municipal government to the Research Institute for the Hydrogeological Protection (CNR-IRPI). The susceptibility map prepared for the Umbria Region represents the development of previous agreements focused to prepare: i) a landslide inventory map that was included in the Urban Territorial Planning (PUT) and ii) a series of maps for the Regional Plan for Multi-risk Prevention. The activities carried out for the Umbria Region were focused to define and apply methods and techniques for landslide susceptibility zonation. Susceptibility maps were prepared exploiting a multivariate statistical model (linear discriminant analysis) for the five Civil Protection Alert Zones defined in the regional territory. The five resulting maps were tested and validated using the spatial distribution of recent landslide events that occurred in the region. The susceptibility map for the Perugia Municipality was prepared to be integrated as one of the cartographic product in the Municipal development plan (PRG - Piano Regolatore Generale) as required by the existing legislation. At strategic level, one of the main objectives of the PRG, is to establish a framework of knowledge and legal aspects for the management of geo-hydrological risk. At national level most of the susceptibility maps prepared for the PRG, were and still are obtained

  4. Landslides susceptibility mapping at Gunung Ciremai National Park

    NASA Astrophysics Data System (ADS)

    Faizin; Nur, Bambang Azis

    2018-02-01

    In addition to agriculture, tourism became one of primary economic income for communities around Mount Ciremai, West, Java. Unfortunately, the landscape of West Java has many potential causes to disasters, mainly landslides. Mapping of disaster susceptibility area is needed as a consideration of tourism planning. The study was conducted in Gunung Ciremai National Park, West Java. This paper propose a methodology to map landslides susceptibilities based on spatial data. Using Geographic Information System tools, several environmental parameters such as slope, land use, elevation, and lithology are scored to build a landslide susceptibility map. Then, susceptibility map is overlaid with Utilization Zone.

  5. A Heuristic Approach to Global Landslide Susceptibility Mapping

    NASA Technical Reports Server (NTRS)

    Stanley, Thomas; Kirschbaum, Dalia B.

    2017-01-01

    Landslides can have significant and pervasive impacts to life and property around the world. Several attempts have been made to predict the geographic distribution of landslide activity at continental and global scales. These efforts shared common traits such as resolution, modeling approach, and explanatory variables. The lessons learned from prior research have been applied to build a new global susceptibility map from existing and previously unavailable data. Data on slope, faults, geology, forest loss, and road networks were combined using a heuristic fuzzy approach. The map was evaluated with a Global Landslide Catalog developed at the National Aeronautics and Space Administration, as well as several local landslide inventories. Comparisons to similar susceptibility maps suggest that the subjective methods commonly used at this scale are, for the most part, reproducible. However, comparisons of landslide susceptibility across spatial scales must take into account the susceptibility of the local subset relative to the larger study area. The new global landslide susceptibility map is intended for use in disaster planning, situational awareness, and for incorporation into global decision support systems.

  6. Landslide susceptibility mapping using a neuro-fuzzy

    NASA Astrophysics Data System (ADS)

    Lee, S.; Choi, J.; Oh, H.

    2009-12-01

    This paper develops and applied an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment using landslide-related factors and location for landslide susceptibility mapping. A neuro-fuzzy system is based on a fuzzy system that is trained by a learning algorithm derived from the neural network theory. The learning procedure operates on local information, and causes only local modifications in the underlying fuzzy system. The study area, Boun, suffered much damage following heavy rain in 1998 and was selected as a suitable site for the evaluation of the frequency and distribution of landslides. Boun is located in the central part of Korea. Landslide-related factors such as slope, soil texture, wood type, lithology, and density of lineament were extracted from topographic, soil, forest, and lineament maps. Landslide locations were identified from interpretation of aerial photographs and field surveys. Landslide-susceptible areas were analyzed by the ANFIS method and mapped using occurrence factors. In particular, we applied various membership functions (MFs) and analysis results were verified using the landslide location data. The predictive maps using triangular, trapezoidal, and polynomial MFs were the best individual MFs for modeling landslide susceptibility maps (84.96% accuracy), proving that ANFIS could be very effective in modeling landslide susceptibility mapping. Various MFs were used in this study, and after verification, the difference in accuracy according to the MFs was small, between 84.81% and 84.96%. The difference was just 0.15% and therefore the choice of MFs was not important in the study. Also, compared with the likelihood ratio model, which showed 84.94%, the accuracy was similar. Thus, the ANFIS could be applied to other study areas with different data and other study methods such as cross-validation. The developed ANFIS learns the if-then rules between landslide-related factors and landslide

  7. Multiscale/multiresolution landslides susceptibility mapping

    NASA Astrophysics Data System (ADS)

    Grozavu, Adrian; Cătălin Stanga, Iulian; Valeriu Patriche, Cristian; Toader Juravle, Doru

    2014-05-01

    Within the European strategies, landslides are considered an important threatening that requires detailed studies to identify areas where these processes could occur in the future and to design scientific and technical plans for landslide risk mitigation. In this idea, assessing and mapping the landslide susceptibility is an important preliminary step. Generally, landslide susceptibility at small scale (for large regions) can be assessed through qualitative approach (expert judgements), based on a few variables, while studies at medium and large scale requires quantitative approach (e.g. multivariate statistics), a larger set of variables and, necessarily, the landslide inventory. Obviously, the results vary more or less from a scale to another, depending on the available input data, but also on the applied methodology. Since it is almost impossible to have a complete landslide inventory on large regions (e.g. at continental level), it is very important to verify the compatibility and the validity of results obtained at different scales, identifying the differences and fixing the inherent errors. This paper aims at assessing and mapping the landslide susceptibility at regional level through a multiscale-multiresolution approach from small scale and low resolution to large scale and high resolution of data and results, comparing the compatibility of results. While the first ones could be used for studies at european and national level, the later ones allows results validation, including through fields surveys. The test area, namely the Barlad Plateau (more than 9000 sq.km) is located in Eastern Romania, covering a region where both the natural environment and the human factor create a causal context that favor these processes. The landslide predictors were initially derived from various databases available at pan-european level and progressively completed and/or enhanced together with scale and the resolution: the topography (from SRTM at 90 meters to digital

  8. Mapping Landslides Susceptibility in a Traditional Northern Nigerian City

    NASA Astrophysics Data System (ADS)

    Oluwafemi, Olawale A.; Yakubu, Tahir A.; Muhammad, Mahmud U.; Shitta, Nyofo; Akinwumiju, Akinola S.

    2018-05-01

    As a result of dearth of relevant information about Landslides Susceptibility in Nigeria, the monitoring and assessment appears intractable. Hence, the study developed a Remote Sensing approach to mapping landslides susceptibility, landuse and landcover analysis in Jos South LGA, Plateau State, Nigeria. Field Observation, SPOT 5 2009 and 2012, ASTER DEM 2009, Geological Map 2006, Topographical Map 1966 were used to map Landslide Susceptibility and Landuse /Lancover Analysis in the study area. Geospatial Analytical Operations employed using ArcGIS 10.3 and Erdas Imagine 2014 include Spatial Modeling, Vectorization, Pre-lineament Extraction, Image Processing among others. Result showed that 72.38 % of the study area is underlain by granitic rocks. The landuse/cover types delineated for the study area include floodplain (29.27 %), farmland (23.96 %), sparsely vegetated land (15.43 %), built up area (13.65 %), vegetated outcrop (8.48 %), light vegetation (5.37 %), thick vegetation (2.39 %), water body (0.58 %), plantation (0.50 %) and mining pond (0.37 %). Landslide Susceptibility Analysis also revealed that 87 % of the study area is relatively at low to very low risk of landslide event. While only 13 % of the study area is at high to very high risk of landslide event. The study revealed that the susceptibility of landslide event is very low in the study area. However, possible landslide event in the hot spots could be pronounced and could destabilize the natural and man-made environmental systems of the study area.

  9. Landslide Inventory and Susceptibility Mapping in Tropical Areas - Southern Mexico

    NASA Astrophysics Data System (ADS)

    Gaidzik, K.; Ramirez-Herrera, M. T.; Regmi, N. R.; Leshchinsky, B. A.

    2016-12-01

    Landslides are one of the common catastrophic phenomena in the world. In regions of humid-warm tropical climate they are triggered by extreme storms causing loss of life and economic devastation. In this study we mapped susceptibility to landslides in the tropical mountains of Guerrero (South Mexico) based on the inventory of landslide features triggered by the hurricane Manuel of September 2013. Landslide inventory was produced using interpretation of satellite images and automatic identification of landslides employing the Contour Connection Method (CCM). A map of susceptibility to landslides was developed by computing probability of landslide occurrence from statistical relationships of existing landslides using LiDAR elevation model and derived landslide-causing factors using a logistic regression method. Landslide inventory includes 419 features produced by the hurricane Manuel on the area of 22 km2, and > 1,000 older features, suggesting high landslide activity in this area. Most landslides in the region are small, but some large slides exist, such as the catastrophic landslide in La Pintada that caused 71 fatalities and destroyed a large part of the village. Our results indicate that the distance to streams, human activity, presence or absence of dense vegetation and orientation of slopes (on some areas) strongly influence the spatial distribution of landslides. Results showed high susceptibility zones encompass 30% of the study area and occur mostly along topographic convergence. Applied approach identified most of the landslides within the high susceptibility zone and suggested that it is a valid applicable method to map areas susceptible to landslides in southern Mexico but also on other humid-warm tropical regions.

  10. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area

    NASA Astrophysics Data System (ADS)

    Oh, Hyun-Joo; Pradhan, Biswajeet

    2011-09-01

    This paper presents landslide-susceptibility mapping using an adaptive neuro-fuzzy inference system (ANFIS) using a geographic information system (GIS) environment. In the first stage, landslide locations from the study area were identified by interpreting aerial photographs and supported by an extensive field survey. In the second stage, landslide-related conditioning factors such as altitude, slope angle, plan curvature, distance to drainage, distance to road, soil texture and stream power index (SPI) were extracted from the topographic and soil maps. Then, landslide-susceptible areas were analyzed by the ANFIS approach and mapped using landslide-conditioning factors. In particular, various membership functions (MFs) were applied for the landslide-susceptibility mapping and their results were compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curve for all landslide susceptibility maps were drawn and the areas under curve values were calculated. The ROC curve technique is based on the plotting of model sensitivity — true positive fraction values calculated for different threshold values, versus model specificity — true negative fraction values, on a graph. Landslide test locations that were not used during the ANFIS modeling purpose were used to validate the landslide susceptibility maps. The validation results revealed that the susceptibility maps constructed by the ANFIS predictive models using triangular, trapezoidal, generalized bell and polynomial MFs produced reasonable results (84.39%), which can be used for preliminary land-use planning. Finally, the authors concluded that ANFIS is a very useful and an effective tool in regional landslide susceptibility assessment.

  11. Progress in landslide susceptibility mapping over Europe using Tier-based approaches

    NASA Astrophysics Data System (ADS)

    Günther, Andreas; Hervás, Javier; Reichenbach, Paola; Malet, Jean-Philippe

    2010-05-01

    The European Thematic Strategy for Soil Protection aims, among other objectives, to ensure a sustainable use of soil. The legal instrument of the strategy, the proposed Framework Directive, suggests identifying priority areas of several soil threats including landslides using a coherent and compatible approach based on the use of common thematic data. In a first stage, this can be achieved through landslide susceptibility mapping using geographically nested, multi-step tiered approaches, where areas identified as of high susceptibility by a first, synoptic-scale Tier ("Tier 1") can then be further assessed and mapped at larger scale by successive Tiers. In order to identify areas prone to landslides at European scale ("Tier 1"), a number of thematic terrain and environmental data sets already available for the whole of Europe can be used as input for a continental scale susceptibility model. However, since no coherent landslide inventory data is available at the moment over the whole continent, qualitative heuristic zonation approaches are proposed. For "Tier 1" a preliminary, simplified model has been developed. It consists of an equally weighting combination of a reduced, continent-wide common dataset of landslide conditioning factors including soil parent material, slope angle and land cover, to derive a landslide susceptibility index using raster mapping units consisting of 1 x 1 km pixels. A preliminary European-wide susceptibility map has thus been produced at 1:1 Million scale, since this is compatible with that of the datasets used. The map has been validated by means of a ratio of effectiveness using samples from landslide inventories in Italy, Austria, Hungary and United Kingdom. Although not differentiated for specific geomorphological environments or specific landslide types, the experimental model reveals a relatively good performance in many European regions at a 1:1 Million scale. An additional "Tier 1" susceptibility map at the same scale and using

  12. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

    NASA Astrophysics Data System (ADS)

    Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

    2014-12-01

    Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

  13. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

    PubMed

    Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

    2014-12-01

    Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

  14. Manifestation of a neuro-fuzzy model to produce landslide susceptibility map using remote sensing data derived parameters

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred

    Landslides are the most common natural hazards in Malaysia. Preparation of landslide suscep-tibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. In this study, a new attempt is tried to produce landslide susceptibility map of a part of Cameron Valley of Malaysia. This paper develops an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment for landslide susceptibility mapping. To ob-tain the neuro-fuzzy relations for producing the landslide susceptibility map, landslide locations were identified from interpretation of aerial photographs and high resolution satellite images, field surveys and historical inventory reports. Landslide conditioning factors such as slope, plan curvature, distance to drainage lines, soil texture, lithology, and distance to lineament were extracted from topographic, soil, and lineament maps. Landslide susceptible areas were analyzed by the ANFIS model and mapped using the conditioning factors. Furthermore, we applied various membership functions (MFs) and fuzzy relations to produce landslide suscep-tibility maps. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. Results show that, triangular, trapezoidal, and polynomial MFs were the best individual MFs for modelling landslide susceptibility maps (86

  15. Weights of Evidence Method for Landslide Susceptibility Mapping in Takengon, Central Aceh, Indonesia

    NASA Astrophysics Data System (ADS)

    Pamela; Sadisun, Imam A.; Arifianti, Yukni

    2018-02-01

    Takengon is an area prone to earthquake disaster and landslide. On July 2, 2013, Central Aceh earthquake induced large numbers of landslides in Takengon area, which resulted in casualties of 39 people. This location was chosen to assess the landslide susceptibility of Takengon, using a statistical method, referred to as the weight of evidence (WoE). This WoE model was applied to indicate the main factors influencing the landslide susceptible area and to derive landslide susceptibility map of Takengon. The 251 landslides randomly divided into two groups of modeling/training data (70%) and validation/test data sets (30%). Twelve thematic maps of evidence are slope degree, slope aspect, lithology, land cover, elevation, rainfall, lineament, peak ground acceleration, curvature, flow direction, distance to river and roads used as landslide causative factors. According to the AUC, the significant factor controlling the landslide is the slope, the slope aspect, peak ground acceleration, elevation, lithology, flow direction, lineament, and rainfall respectively. Analytical result verified by using test data of landslide shows AUC prediction rate is 0.819 and AUC success rate with all landslide data included is 0.879. This result showed the selective factors and WoE method as good models for assessing landslide susceptibility. The landslide susceptibility map of Takengon shows the probabilities, which represent relative degrees of susceptibility for landslide proneness in Takengon area.

  16. The landslide susceptibility mapping and assessment with ZY satellite data

    NASA Astrophysics Data System (ADS)

    Zhang, R.; Zhang, Z.; Zhao, Y.

    2012-12-01

    Natural hazards can result in enormous property damage and casualties in mountainous regions. In China, the direct loss of hazards is about 400 million yuan in 2011. Especially the landslide, the most common natural hazards, got the wide attention of each country. Landslide susceptibility mapping is of great importance for landslide hazard mitigation efforts throughout the world. In Southwest Hubei, there are much mineral mining activities, which may trigger the landslide. In addition the Three Gorges reservoir is located in this area, and the storage changed the geological and hydrological environment, which may increase the frequency of the ancient landslide reactivation, and the new landslide occurrence. There are more than 200 landslide hazards happened since 2003. So producing a regional-scaled landslide susceptibility map is necessary. For the above purpose, the landslide susceptibility mapping was produced by using the ZY-3 and ZY-1-02C satellite data, the DEMs and the conventional topographic data.(1) The DEM derivatives slope gradient, the slope aspect and the topographic wetness index (TWI) ; (2) in order to acquire the spatially continuous vegetation information, Normalized Difference Vegetation Index (NDVI) was computed using ZY-1-02C and ZY-3; (3) the regional lithologic information (i.e. mineral distribution) and the tectonic information obtained from remote sensing data in combination with regional geological survey; (4) the regional hydrogeological information was produced by using the remote sensing data in combination with the DEMs; (5) the existed landslides information obtained from remote sensing. To model the landslide hazard assessment using variety of statistic methods and evaluation methods, the cross application model yields reasonable results which can be applied for preliminary landslide hazard mapping and the hazard grade division.

  17. Spatially explicit shallow landslide susceptibility mapping over large areas

    USGS Publications Warehouse

    Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

  18. Landslide susceptibility mapping for a landslide-prone area (Findikli, NE of Turkey) by likelihood-frequency ratio and weighted linear combination models

    NASA Astrophysics Data System (ADS)

    Akgun, Aykut; Dag, Serhat; Bulut, Fikri

    2008-05-01

    Landslides are very common natural problems in the Black Sea Region of Turkey due to the steep topography, improper use of land cover and adverse climatic conditions for landslides. In the western part of region, many studies have been carried out especially in the last decade for landslide susceptibility mapping using different evaluation methods such as deterministic approach, landslide distribution, qualitative, statistical and distribution-free analyses. The purpose of this study is to produce landslide susceptibility maps of a landslide-prone area (Findikli district, Rize) located at the eastern part of the Black Sea Region of Turkey by likelihood frequency ratio (LRM) model and weighted linear combination (WLC) model and to compare the results obtained. For this purpose, landslide inventory map of the area were prepared for the years of 1983 and 1995 by detailed field surveys and aerial-photography studies. Slope angle, slope aspect, lithology, distance from drainage lines, distance from roads and the land-cover of the study area are considered as the landslide-conditioning parameters. The differences between the susceptibility maps derived by the LRM and the WLC models are relatively minor when broad-based classifications are taken into account. However, the WLC map showed more details but the other map produced by LRM model produced weak results. The reason for this result is considered to be the fact that the majority of pixels in the LRM map have high values than the WLC-derived susceptibility map. In order to validate the two susceptibility maps, both of them were compared with the landslide inventory map. Although the landslides do not exist in the very high susceptibility class of the both maps, 79% of the landslides fall into the high and very high susceptibility zones of the WLC map while this is 49% for the LRM map. This shows that the WLC model exhibited higher performance than the LRM model.

  19. Landslide susceptibility mapping using a bivariate statistical model in a tropical hilly area of southeastern Brazil

    NASA Astrophysics Data System (ADS)

    Araújo, J. P. C.; DA Silva, L. M.; Dourado, F. A. D.; Fernandes, N.

    2015-12-01

    Landslides are the most damaging natural hazard in the mountainous region of Rio de Janeiro State in Brazil, responsible for thousands of deaths and important financial and environmental losses. However, this region has currently few landslide susceptibility maps implemented on an adequate scale. Identification of landslide susceptibility areas is fundamental in successful land use planning and management practices to reduce risk. This paper applied the Bayes' theorem based on weight of evidence (WoE) using 8 landslide-related factors in a geographic information system (GIS) for landslide susceptibility mapping. 378 landslide locations were identified and mapped on a selected basin in the city of Nova Friburgo, triggered by the January 2011 rainfall event. The landslide scars were divided into two subsets: training and validation subsets. The 8 landslide-related factors weighted by WoE were performed using chi-square test to indicate which variables are conditionally independent of each other to be used in the final map. Finally, the maps of weighted factors were summed up to construct the landslide susceptibility map and validated by the validation landslide subset. According to the results, slope, aspect and contribution area showed the higher positive spatial correlation with landslides. In the landslide susceptibility map, 21% of the area presented very low and low susceptibilities with 3% of the validation scars, 41% presented medium susceptibility with 22% of the validation scars and 38% presented high and very high susceptibilities with 75% of the validation scars. The very high susceptibility class stands for 16% of the basin area and has 54% of the all scars. The approach used in this study can be considered very useful since 75% of the area affected by landslides was included in the high and very high susceptibility classes.

  20. Map showing landslide susceptibility in Prince Georges County, Maryland

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pomeroy, J.S.

    1989-01-01

    Prince Georges County was identified during a statewide investigation of landslide susceptibility (MF-2048) as the county with the most serious slope-stability problems. This map uses a ranking system ranging from 1 (nil to very low susceptibility) to 4 (moderate to severe susceptibility). Geologic factors and precipitation are major elements in the initiation of landslides in the county. The Potomac Group and the Marlboro Clay are the most slideprone units. This map should enable users to make a rapid, generalized evaluation of the potential for mass movement. Planners, engineers, soil scientists, geologist, university faculty, and elected officials should find it usefulmore » in the assessment of slope hazards for county-wide analyses.« less

  1. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

    PubMed Central

    Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

  2. Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand

    NASA Astrophysics Data System (ADS)

    Oh, Hyun-Joo; Lee, Saro; Chotikasathien, Wisut; Kim, Chang Hwan; Kwon, Ju Hyoung

    2009-04-01

    For predictive landslide susceptibility mapping, this study applied and verified probability model, the frequency ratio and statistical model, logistic regression at Pechabun, Thailand, using a geographic information system (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and maps of the topography, geology and land cover were constructed to spatial database. The factors that influence landslide occurrence, such as slope gradient, slope aspect and curvature of topography and distance from drainage were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite image. The frequency ratio and logistic regression coefficient were overlaid for landslide susceptibility mapping as each factor’s ratings. Then the landslide susceptibility map was verified and compared using the existing landslide location. As the verification results, the frequency ratio model showed 76.39% and logistic regression model showed 70.42% in prediction accuracy. The method can be used to reduce hazards associated with landslides and to plan land cover.

  3. GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

    NASA Astrophysics Data System (ADS)

    Mancini, F.; Ceppi, C.; Ritrovato, G.

    2010-09-01

    This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

  4. Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

    NASA Technical Reports Server (NTRS)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2007-01-01

    Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

  5. Recent developments in machine learning applications in landslide susceptibility mapping

    NASA Astrophysics Data System (ADS)

    Lun, Na Kai; Liew, Mohd Shahir; Matori, Abdul Nasir; Zawawi, Noor Amila Wan Abdullah

    2017-11-01

    While the prediction of spatial distribution of potential landslide occurrences is a primary interest in landslide hazard mitigation, it remains a challenging task. To overcome the scarceness of complete, sufficiently detailed geomorphological attributes and environmental conditions, various machine-learning techniques are increasingly applied to effectively map landslide susceptibility for large regions. Nevertheless, limited review papers are devoted to this field, particularly on the various domain specific applications of machine learning techniques. Available literature often report relatively good predictive performance, however, papers discussing the limitations of each approaches are quite uncommon. The foremost aim of this paper is to narrow these gaps in literature and to review up-to-date machine learning and ensemble learning techniques applied in landslide susceptibility mapping. It provides new readers an introductory understanding on the subject matter and researchers a contemporary review of machine learning advancements alongside the future direction of these techniques in the landslide mitigation field.

  6. An application of adaptive neuro-fuzzy inference system to landslide susceptibility mapping (Klang valley, Malaysia)

    NASA Astrophysics Data System (ADS)

    Sezer, Ebru; Pradhan, Biswajeet; Gokceoglu, Candan

    2010-05-01

    Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. Recently, the Klang Valley area of Selangor state has faced numerous landslide and mudflow events and much damage occurred in these areas. However, only little effort has been made to assess or predict these events which resulted in serious damages. Through scientific analyses of these landslides, one can assess and predict landslide-susceptible areas and even the events as such, and thus reduce landslide damages through proper preparation and/or mitigation. For this reason , the purpose of the present paper is to produce landslide susceptibility maps of a part of the Klang Valley areas in Malaysia by employing the results of the adaptive neuro-fuzzy inference system (ANFIS) analyses. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments and NDVI were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, plan curvature, distance from drainage, soil type, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to construct the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were obtained by using ANFIS results. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values was calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 98% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient

  7. Object-based Classification for Detecting Landslides and Stochastic Procedure to landslide susceptibility maps - A Case at Baolai Village, SW Taiwan

    NASA Astrophysics Data System (ADS)

    Lin, Ying-Tong; Chang, Kuo-Chen; Yang, Ci-Jian

    2017-04-01

    As the result of global warming in the past decades, Taiwan has experienced more and more extreme typhoons with hazardous massive landslides. In this study, we use object-oriented analysis method to classify landslide area at Baolai village by using Formosat-2 satellite images. We used for multiresolution segmented to generate the blocks, and used hierarchical logic to classified 5 different kinds of features. After that, classification the landslide into different type of landslide. Beside, we use stochastic procedure to integrate landslide susceptibility maps. This study assumed that in the extreme event, 2009 Typhoon Morakot, which precipitation goes to 1991.5mm in 5 days, and the highest landslide susceptible area. The results show that study area's landslide area was greatly changes, most of landslide was erosion by gully and made dip slope slide, or erosion by the stream, especially at undercut bank. From the landslide susceptibility maps, we know that the old landslide area have high potential to occur landslides in the extreme event. This study demonstrates the changing of landslide area and the landslide susceptible area. Keywords: Formosat-2, object-oriented, segmentation, classification, landslide, Baolai Village, SW Taiwan, FS

  8. Implementation of landslide susceptibility maps in Lower Austria as part of risk governance

    NASA Astrophysics Data System (ADS)

    Bell, Rainer; Petschko, Helene; Bauer, Christian; Glade, Thomas; Granica, Klaus; Heiss, Gerhard; Leopold, Philip; Pomaroli, Gilbert; Proske, Herwig; Schweigl, Joachim

    2013-04-01

    Landslides frequently cause damage to agricultural land and infrastructure in Lower Austria - a province of Austria. Also settlements and people are threatened by landslides. To reduce landslide risks and to prevent the establishment of new settlements in highly landslide prone areas, the project "MoNOE" (Method development for landslide susceptibility modeling in Lower Austria) was set up by the provincial government. The main aim of the project is the development of methods to model rock fall and slide susceptibility for an area of approx. 15,900 km2 and to implement the resulting susceptibility maps into the spatial planning strategies of the state. Right from the beginning of the project a close cooperation between the involved scientists and the stakeholders from the Geological Survey of Lower Austria and the Department of Spatial Planning and Regional Policy of Lower Austria was established to ensure that method development and final susceptibility maps meet exactly the needs and demands of the stakeholders. This posed huge challenges, together with its realization in the large study area and a (heterogeneous) complex geological situation,. Limitations were given by restricted data availability (e.g. for geology or landslide inventories) in such a large study area. Rock fall susceptibility was modeled by a combined approach of determining rock fall release areas by empirical slope thresholds (dependent on geology) followed by empirical run-out modeling. Slide susceptibility was modeled based on the statistical approaches of weights of evidence (WofE) and generalized additive models (GAM) by two different research groups. Huge efforts were spent on the validation of all susceptibility models. In a later stage of the project we found that the best scientific maps are not necessarily the best maps to be implemented in spatial planning strategies. Thus, in close cooperation with the stakeholders, decisions had to be taken to find the best resolution of the maps

  9. Landslide susceptibility mapping in three selected target zones in Afghanistan

    NASA Astrophysics Data System (ADS)

    Schwanghart, Wolfgang; Seegers, Joe; Zeilinger, Gerold

    2015-04-01

    In May 2014, a large and mobile landslide destroyed the village Ab Barek, a village in Badakshan Province, Afghanistan. The landslide caused several hundred fatalities and once again demonstrated the vulnerability of Afghanistan's population to extreme natural events following more than 30 years of civil war and violent conflict. Increasing the capacity of Afghanistan's population by strengthening the disaster preparedness and management of responsible government authorities and institutions is thus a major component of international cooperation and development strategies. Afghanistan is characterized by high relief and widely varying rock types that largely determine the spatial distribution as well as emplacement modes of mass movements. The major aim of our study is to characterize this variability by conducting a landslide susceptibility analysis in three selected target zones: Greater Kabul Area, Badakhshan Province and Takhar Province. We expand on an existing landslide database by mapping landforms diagnostic for landslides (e.g. head scarps, normal faults and tension cracks), and historical landslide scars and landslide deposits by visual interpretation of high-resolution satellite imagery. We conduct magnitude frequency analysis within subregional physiogeographic classes based on geological maps, climatological and topographic data to identify regional parameters influencing landslide magnitude and frequency. In addition, we prepare a landslide susceptibility map for each area using the Weight-of-Evidence model. Preliminary results show that the three selected target zones vastly differ in modes of landsliding. Low magnitude but frequent rockfall events are a major hazard in the Greater Kabul Area threatening buildings and infrastructure encroaching steep terrain in the city's outskirts. Mass movements in loess covered areas of Badakshan are characterized by medium to large magnitudes. This spatial variability of characteristic landslide magnitudes and

  10. Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

    NASA Astrophysics Data System (ADS)

    Kumar, Deepak; Thakur, Manoj; Dubey, Chandra S.; Shukla, Dericks P.

    2017-10-01

    In recent years, various machine learning techniques have been applied for landslide susceptibility mapping. In this study, three different variants of support vector machine viz., SVM, Proximal Support Vector Machine (PSVM) and L2-Support Vector Machine - Modified Finite Newton (L2-SVM-MFN) have been applied on the Mandakini River Basin in Uttarakhand, India to carry out the landslide susceptibility mapping. Eight thematic layers such as elevation, slope, aspect, drainages, geology/lithology, buffer of thrusts/faults, buffer of streams and soil along with the past landslide data were mapped in GIS environment and used for landslide susceptibility mapping in MATLAB. The study area covering 1625 km2 has merely 0.11% of area under landslides. There are 2009 pixels for past landslides out of which 50% (1000) landslides were considered as training set while remaining 50% as testing set. The performance of these techniques has been evaluated and the computational results show that L2-SVM-MFN obtains higher prediction values (0.829) of receiver operating characteristic curve (AUC-area under the curve) as compared to 0.807 for PSVM model and 0.79 for SVM. The results obtained from L2-SVM-MFN model are found to be superior than other SVM prediction models and suggest the usefulness of this technique to problem of landslide susceptibility mapping where training data is very less. However, these techniques can be used for satisfactory determination of susceptible zones with these inputs.

  11. Landslide susceptibility mapping for a part of North Anatolian Fault Zone (Northeast Turkey) using logistic regression model

    NASA Astrophysics Data System (ADS)

    Demir, Gökhan; aytekin, mustafa; banu ikizler, sabriye; angın, zekai

    2013-04-01

    The North Anatolian Fault is know as one of the most active and destructive fault zone which produced many earthquakes with high magnitudes. Along this fault zone, the morphology and the lithological features are prone to landsliding. However, many earthquake induced landslides were recorded by several studies along this fault zone, and these landslides caused both injuiries and live losts. Therefore, a detailed landslide susceptibility assessment for this area is indispancable. In this context, a landslide susceptibility assessment for the 1445 km2 area in the Kelkit River valley a part of North Anatolian Fault zone (Eastern Black Sea region of Turkey) was intended with this study, and the results of this study are summarized here. For this purpose, geographical information system (GIS) and a bivariate statistical model were used. Initially, Landslide inventory maps are prepared by using landslide data determined by field surveys and landslide data taken from General Directorate of Mineral Research and Exploration. The landslide conditioning factors are considered to be lithology, slope gradient, slope aspect, topographical elevation, distance to streams, distance to roads and distance to faults, drainage density and fault density. ArcGIS package was used to manipulate and analyze all the collected data Logistic regression method was applied to create a landslide susceptibility map. Landslide susceptibility maps were divided into five susceptibility regions such as very low, low, moderate, high and very high. The result of the analysis was verified using the inventoried landslide locations and compared with the produced probability model. For this purpose, Area Under Curvature (AUC) approach was applied, and a AUC value was obtained. Based on this AUC value, the obtained landslide susceptibility map was concluded as satisfactory. Keywords: North Anatolian Fault Zone, Landslide susceptibility map, Geographical Information Systems, Logistic Regression Analysis.

  12. TRIGRS Application for landslide susceptibility mapping

    NASA Astrophysics Data System (ADS)

    Sugiarti, K.; Sukristiyanti, S.

    2018-02-01

    Research on landslide susceptibility has been carried out using several different methods. TRIGRS is a modeling program for landslide susceptibility by considering pore water pressure changes due to infiltration of rainfall. This paper aims to present a current state-of-the-art science on the development and application of TRIGRS. Some limitations of TRIGRS, some developments of it to improve its modeling capability, and some examples of the applications of some versions of it to model the effect of rainfall variation on landslide susceptibility are reviewed and discussed.

  13. Methods for landslide susceptibility modelling in Lower Austria

    NASA Astrophysics Data System (ADS)

    Bell, Rainer; Petschko, Helene; Glade, Thomas; Leopold, Philip; Heiss, Gerhard; Proske, Herwig; Granica, Klaus; Schweigl, Joachim; Pomaroli, Gilbert

    2010-05-01

    Landslide susceptibility modelling and implementation of the resulting maps is still a challenge for geoscientists, spatial and infrastructure planners. Particularly on a regional scale landslide processes and their dynamics are poorly understood. Furthermore, the availability of appropriate spatial data in high resolution is often a limiting factor for modelling high quality landslide susceptibility maps for large study areas. However, these maps form an important basis for preventive spatial planning measures. Thus, new methods have to be developed, especially focussing on the implementation of final maps into spatial planning processes. The main objective of the project "MoNOE" (Method development for landslide susceptibility modelling in Lower Austria) is to design a method for landslide susceptibility modelling for a large study area (about 10.200 km²) and to produce landslide susceptibility maps which are finally implemented in the spatial planning strategies of the Federal state of Lower Austria. The project focuses primarily on the landslide types fall and slide. To enable susceptibility modelling, landslide inventories for the respective landslide types must be compiled and relevant data has to be gathered, prepared and homogenized. Based on this data new methods must be developed to tackle the needs of the spatial planning strategies. Considerable efforts will also be spent on the validation of the resulting maps for each landslide type. A great challenge will be the combination of the susceptibility maps for slides and falls in just one single susceptibility map (which is requested by the government) and the definition of the final visualisation. Since numerous landslides have been favoured or even triggered by human impact, the human influence on landslides will also have to be investigated. Furthermore possibilities to integrate respective findings in regional susceptibility modelling will be explored. According to these objectives the project is

  14. An innovative tool for landslide susceptibility mapping in Kyrgyzstan, Central Asia

    NASA Astrophysics Data System (ADS)

    Saponaro, Annamaria; Pilz, Marco; Wieland, Marc; Bindi, Dino; Parolai, Stefano

    2013-04-01

    Kyrgyzstan is among the most exposed countries in the world to landslide susceptibility. The high seismicity of the area, the presence of high mountain ridges and topographic relieves, the geology of the local materials and the occurrence of heavy precipitations represent the main factors responsible for slope failures. In particular, the large variability of material properties and slope conditions as well as the difficulties in forecasting heavy precipitations locally and in quantifying the level of ground shaking call for harmonized procedures for reducing the negative impact of these factors. Several studies have recently been carried out aiming at preparing landslide susceptibility and hazard maps; however, some of them - qualitative-based - suffer from the application of subjective decision rules from experts in the classification of parameters that influence the occurrence of a landslide. On the other hand, statistical methods provide objectivity over qualitative ones since they allow a numerical evaluation of landslide spatial distribution with landslide potential factors. For this reason, we will make use of a bivariate technique known as Weight-Of-Evidence method to evaluate the influence of landslide predictive factors. The aim of this study is to identify areas in Kyrgyzstan being more prone to earthquake-triggered landslides. An innovative approach which exploits the new advances of GIS technology together with statistical concepts is presented. A range of conditioning factors and their potential impact on landslide activation is quantitatively assessed on the basis of landslide spatial distribution and seismic zonation. Results show areas which are more susceptible to landslides induced by earthquakes. Our approach can be used to fill the gap of subjectivity that typically affects already performed qualitative analysis. The resulting landslide susceptibility map represents a potentially supportive tool for disaster management and planning activities

  15. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

    NASA Astrophysics Data System (ADS)

    Yilmaz, Işık

    2009-06-01

    The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

  16. Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps

    NASA Astrophysics Data System (ADS)

    Steger, Stefan; Brenning, Alexander; Bell, Rainer; Petschko, Helene; Glade, Thomas

    2016-06-01

    Empirical models are frequently applied to produce landslide susceptibility maps for large areas. Subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models. This study hypothesizes that such direct deductions can be misleading. The main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results. The study was conducted within the Flysch Zone of Lower Austria (1,354 km2) which is known to be highly susceptible to landslides of the slide-type movement. Sixteen susceptibility models were generated by applying two statistical classifiers (logistic regression and generalized additive model) and two machine learning techniques (random forest and support vector machine) separately for two landslide inventories of differing completeness and two predictor sets. The results were validated quantitatively by estimating the area under the receiver operating characteristic curve (AUROC) with single holdout and spatial cross-validation technique. The heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis, an estimation of odds ratios and an evaluation of the spatial structure of the final maps. The results showed that maps generated by different inventories, classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances. Spatial cross-validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning-based models. However, the highest predictive performances were obtained for

  17. An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic

    NASA Astrophysics Data System (ADS)

    Zhu, A.-Xing; Wang, Rongxun; Qiao, Jianping; Qin, Cheng-Zhi; Chen, Yongbo; Liu, Jing; Du, Fei; Lin, Yang; Zhu, Tongxin

    2014-06-01

    This paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km2) and the Three Gorges study area (about 4600 km2). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the

  18. Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS

    NASA Astrophysics Data System (ADS)

    Tien Bui, Dieu; Pradhan, Biswajeet; Lofman, Owe; Revhaug, Inge; Dick, Oystein B.

    2012-08-01

    The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps. The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.

  19. Progress in national-scale landslide susceptibility mapping in Romania using a combined statistical-heuristical approach

    NASA Astrophysics Data System (ADS)

    Bălteanu, Dan; Micu, Mihai; Malet, Jean-Philippe; Jurchescu, Marta; Sima, Mihaela; Kucsicsa, Gheorghe; Dumitrică, Cristina; Petrea, Dănuţ; Mărgărint, Ciprian; Bilaşco, Ştefan; Văcăreanu, Radu; Georgescu, Sever; Senzaconi, Francisc

    2017-04-01

    Landslide processes represent a very widespread geohazard in Romania, affecting mainly the hilly and plateau regions as well as the mountain sectors developed on flysch formations. Two main projects provided the framework for improving the existing national landslide susceptibility map (Bălteanu et al. 2010): the ELSUS (Pan-European and nation-wide landslide susceptibility assessment, EC-CERG) and the RO-RISK (Disaster Risk Evaluation at National Level, ESF-POCA) projects. The latter one, a flagship project aiming at strengthening risk prevention and management in Romania, focused on a national-level evaluation of the main risks in the country including landslides. The strategy for modeling landslide susceptibility was designed based on the experience gained from continental and national level assessments conducted in the frame of the International Programme on Landslides (IPL) project IPL-162, the European Landslides Expert Group - JRC and the ELSUS project. The newly proposed landslide susceptibility model used as input a reduced set of landslide conditioning factor maps available at scales of 1:100,000 - 1:200,000 and consisting of lithology, slope angle and land cover. The input data was further differentiated for specific natural environments, defined here as morpho-structural units in order to incorporate differences induced by elevation (vertical climatic zonation), morpho-structure as well as neotectonic features. In order to best discern the specific landslide conditioning elements, the analysis has been carried out for one single process category, namely slides. The existence of a landslide inventory covering the whole country's territory ( 30,000 records, Micu et al. 2014), although affected by incompleteness and lack of homogeneity, allowed for the application of a semi-quantitative, mixed statistical-heuristical approach having the advantage of combining the objectivity of statistics with expert-knowledge in calibrating class and factor weights. The

  20. Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

    NASA Astrophysics Data System (ADS)

    Tazik, E.; Jahantab, Z.; Bakhtiari, M.; Rezaei, A.; Kazem Alavipanah, S.

    2014-10-01

    Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

  1. Rainfall thresholds and susceptibility mapping for shallow landslides and debris flows in Scotland

    NASA Astrophysics Data System (ADS)

    Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

    2017-04-01

    Shallow translational slides and debris flows (hereafter 'landslides') pose a significant threat to life and cause significant annual economic impacts (e.g. by damage and disruption of infrastructure). The focus of this research is on the definition of objective rainfall thresholds using a weather radar system and landslide susceptibility mapping. In the study area Scotland, an inventory of 75 known landslides was used for the period 2003 to 2016. First, the effect of using different rain records (i.e. time series length) on two threshold selection techniques in receiver operating characteristic (ROC) analysis was evaluated. The results show that thresholds selected by 'Threat Score' (minimising false alarms) are sensitive to rain record length and which is not routinely considered, whereas thresholds selected using 'Optimal Point' (minimising failed alarms) are not; therefore these may be suited to establishing lower limit thresholds and be of interest to those developing early warning systems. Robust thresholds are found for combinations of normalised rain duration and accumulation at 1 and 12 day's antecedence respectively; these are normalised using the rainy-day normal and an equivalent measure for rain intensity. This research indicates that, in Scotland, rain accumulation provides a better indicator than rain intensity and that landslides may be generated by threshold conditions lower than previously thought. Second, a landslide susceptibility map is constructed using a cross-validated logistic regression model. A novel element of the approach is that landslide susceptibility is calculated for individual hillslope sections. The developed thresholds and susceptibility map are combined to assess potential hazards and impacts posed to the national highway network in Scotland.

  2. Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides

    NASA Astrophysics Data System (ADS)

    Lee, Saro; Dan, Nguyen Tu

    2005-09-01

    This study evaluates the susceptibility of landslides in the Lai Chau province of Vietnam using Geographic Information System (GIS) and remote sensing data to focus on the relationship between tectonic fractures and landslides. Landslide locations were identified from aerial photographs and field surveys. Topographic, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image-processing techniques. A scheme of the tectonic fracturing of crust in the Lai Chau region was established. Lai Chau was identified as a region with many crustal fractures, where the grade of tectonic fracture is closely related to landslide occurrence. The influencing factors of landslide occurrence were: distance from a tectonic fracture, slope, aspect, curvature, soil, and vegetative land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using landslide location data and showed 83.47% prediction accuracy. That emphasized a strong relationship between the susceptibility map and the existing landslide location data. The results of this study can form a basis stable development and land use planning for the region.

  3. Integration of landslide susceptibility products in the environmental plans

    NASA Astrophysics Data System (ADS)

    Fiorucci, Federica; Reichenbach, Paola; Rossi, Mauro; Cardinali, Mauro; Guzzetti, Fausto

    2015-04-01

    Landslides are one of the most destructive natural hazard that causes damages to urban area worldwide. The knowledge of where a landslide could occur is essential for the strategic management of the territory and for a good urban planning . In this contest landslide susceptibility zoning (LSZ) is crucial to provide information on the degree to which an area can be affected by future slope movements. Despite landslide susceptibility maps have been prepared extensively during the last decades, there are few examples of application is in the environmental plans (EP). In this work we present a proposal for the integration of the landslide inventory map with the following landslide susceptibility products: (i) landslide susceptibility zonation , (ii) the associated error map and (iii) the susceptibility uncertainty map. Moreover we proposed to incorporate detailed morphological studies for the evaluation of landslide risk associated to local parceling plan. The integration of all this information is crucial for the management of landslide risk in urban expansions forecasts. Municipality, province and regional administration are often not able to support the costs of landslide risk evaluation for extensive areas but should concentrate their financial resources to specific hazardous and unsafe situations defined by the result of the integration of landslide susceptibility products. Zonation and detail morphological analysis should be performed taking into account the existing laws and regulations, and could become a starting point to discuss new regulations for the landslide risk management.

  4. Utilizing NASA Earth Observations to Assess Landslide Characteristics and Devlelop Susceptibility and Exposure Maps in Malawi

    NASA Astrophysics Data System (ADS)

    Klug, M.; Cissell, J.; Grossman, M.

    2017-12-01

    Malawi has become increasingly prone to landslides in the past few decades. This can be attributed to the terrain, types of soil and vegetation, increased human interference, and heavy flooding after long periods of drought. In addition to the floods and droughts, landslides cause extra stress to farmlands, thus exacerbating the current food security crisis in the country. It can be difficult to pinpoint just how many people are affected by landslides in Malawi because landslides often occur in rural areas or are grouped with other disasters, such as floods or earthquakes. This project created a Landslide Susceptibility Map to assess landslide-prone areas in Malawi using variables such as slope, distance to roads, distance to streams, soil type, and precipitation. These variables were derived using imagery from Landsat 8 Operational Land Imager (OLI), Shuttle Radar Topography Mission Version 3 (SRTM-v3), Global Precipitation Measurement (GPM), and Tropical Rainfall Measuring Mission (TRMM) satellites. Furthermore, this project created a Landslide Exposure Map to estimate how much of the local population lives in susceptible areas by intersecting population data with the Landslide Susceptibility Map. Additionally, an assessment of GPM and TRMM precipitation measurements was generated to better understand the reliability of both measurements for landslide monitoring. Finally, this project updated NASA SERVIR's Global Landslide Catalog (GLC) for Malawi by using WorldView data from Google Earth and Landsat 8 OLI. These end products were used by NASA SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for aiding in disaster management throughout Malawi.

  5. Landslide Hazard Assessment and Mapping in the Guil Catchment (Queyras, Southern French Alps): From Landslide Inventory to Susceptibility Modelling

    NASA Astrophysics Data System (ADS)

    Roulleau, Louise; Bétard, François; Carlier, Benoît; Lissak, Candide; Fort, Monique

    2016-04-01

    Landslides are common natural hazards in the Southern French Alps, where they may affect human lives and cause severe damages to infrastructures. As a part of the SAMCO research project dedicated to risk evaluation in mountain areas, this study focuses on the Guil river catchment (317 km2), Queyras, to assess landslide hazard poorly studied until now. In that area, landslides are mainly occasional, low amplitude phenomena, with limited direct impacts when compared to other hazards such as floods or snow avalanches. However, when interacting with floods during extreme rainfall events, landslides may have indirect consequences of greater importance because of strong hillslope-channel connectivity along the Guil River and its tributaries (i.e. positive feedbacks). This specific morphodynamic functioning reinforces the need to have a better understanding of landslide hazards and their spatial distribution at the catchment scale to prevent local population from disasters with multi-hazard origin. The aim of this study is to produce a landslide susceptibility mapping at 1:50 000 scale as a first step towards global estimation of landslide hazard and risk. The three main methodologies used for assessing landslide susceptibility are qualitative (i.e. expert opinion), deterministic (i.e. physics-based models) and statistical methods (i.e. probabilistic models). Due to the rapid development of geographical information systems (GIS) during the last two decades, statistical methods are today widely used because they offer a greater objectivity and reproducibility at large scales. Among them, multivariate analyses are considered as the most robust techniques, especially the logistic regression method commonly used in landslide susceptibility mapping. However, this method like others is strongly dependent on the accuracy of the input data to avoid significant errors in the final results. In particular, a complete and accurate landslide inventory is required before the modelling

  6. GIS-aided Statistical Landslide Susceptibility Modeling And Mapping Of Antipolo Rizal (Philippines)

    NASA Astrophysics Data System (ADS)

    Dumlao, A. J.; Victor, J. A.

    2015-09-01

    Slope instability associated with heavy rainfall or earthquake is a familiar geotechnical problem in the Philippines. The main objective of this study is to perform a detailed landslide susceptibility assessment of Antipolo City. The statistical method of assessment used was logistic regression. Landslide inventory was done through interpretation of aerial photographs and satellite images with corresponding field verification. In this study, morphologic and non-morphologic factors contributing to landslide occurrence and their corresponding spatial relationships were considered. The analysis of landslide susceptibility was implemented in a Geographic Information System (GIS). The 17320 randomly selected datasets were divided into training and test data sets. K- cross fold validation is done with k= 5. The subsamples are then fitted five times with k-1 training data set and the remaining fold as the validation data set. The AUROC of each model is validated using each corresponding data set. The AUROC of the five models are; 0.978, 0.977, 0.977, 0.974, and 0.979 respectively, implying that the models are effective in correctly predicting the occurrence and nonoccurrence of landslide activity. Field verification was also done. The landslide susceptibility map was then generated from the model. It is classified into four categories; low, moderate, high and very high susceptibility. The study also shows that almost 40% of Antipolo City has been assessed to be potentially dangerous areas in terms of landslide occurrence.

  7. An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping.

    PubMed

    Feizizadeh, Bakhtiar; Blaschke, Thomas

    2014-03-04

    GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster-Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster-Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation

  8. An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

    PubMed Central

    Feizizadeh, Bakhtiar; Blaschke, Thomas

    2014-01-01

    GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC

  9. Mapping of risk and susceptibility of shallow-landslide in the city of São Paulo, Brazil

    NASA Astrophysics Data System (ADS)

    Listo, Fabrizio de Luiz Rosito; Carvalho Vieira, Bianca

    2012-10-01

    In the city of São Paulo, where about 11 million people live, landslides and flooding occur frequently, especially during the summer. These landslides cause the destruction of houses and urban equipment, economic damage, and the loss of lives. The number of areas threatened by landslides has been increasing each year. The objective of this article is to analyze the probability of risk and susceptibility to shallow landslides in the Limoeiro River basin, which is located at the head of the Aricanduva River basin, one of the main hydrographic basins in the city of São Paulo. To map areas of risk, we created a cadastral survey form to evaluate landslide risk in the field. Risk was categorized into four levels based on natural and anthropogenic factors: R1 (low risk), R2 (average risk), R3 (high risk), and R4 (very high risk). To analyze susceptibility to shallow landslides, we used the SHALSTAB (Shallow Landsliding Stability) mathematical model and calculated the Distribution Frequency (DF) of the susceptibility classes for the entire basin. Finally, we performed a joint analysis of the average Risk Concentration (RC) and Risk Potential (RP). We mapped 14 risk sectors containing approximately 685 at-risk homes, more than half of which presented a high (R3) or very high (R4) probability of risk to the population. In the susceptibility map, 41% of the area was classified as stable and 20% as unconditionally unstable. Although the latter category accounted a smaller proportion of the total area, it contained a concentration (RC) of 41% of the mapped risk areas with a risk potential (RP) of 12%. We found that the locations of areas predicted to be unstable by the model coincided with the risk areas mapped in the field. This combination of methods can be applied to evaluate the risk of shallow landslides in densely populated areas and can assist public managers in defining areas that are unstable and inappropriate for occupation.

  10. Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment

    PubMed Central

    Hashim, Mazlan

    2015-01-01

    This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning. PMID:25898919

  11. Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment.

    PubMed

    Shahabi, Himan; Hashim, Mazlan

    2015-04-22

    This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.

  12. Validating national landslide susceptibility and hazard maps for Caribbean island countries: the case of Dominica and tropical storm Erika.

    NASA Astrophysics Data System (ADS)

    van Westen, Cees; Jetten, Victor; Alkema, Dinand

    2016-04-01

    The aim of this study was to generate national-scale landslide susceptibility and hazard maps for four Caribbean islands, as part of the World Bank project CHARIM (Caribbean Handbook on Disaster Geoinformation Management, www.charim.net). This paper focuses on the results for the island country of Dominica, located in the Eastern part of the Caribbean, in-between Guadalupe and Martinique. The available data turned out to be insufficient to generate reliable results. We therefore generated a new database of disaster events for Dominica using all available data, making use of many different sources. We compiled landslide inventories for five recent rainfall events from the maintenance records of the Ministry of Public Works, and generated a completely new landslide inventory using multi-temporal visual image interpretation, and generated an extensive landslide database for Dominica. We analyzed the triggering conditions for landslides as far as was possible given the available data, and generated rainfall magnitude-frequency relations. We applied a method for landslide susceptibility assessment which combined bi-variate statistical analysis, that provided indications on the importance of the possible contributing factors, with an expert-based iterative weighing approach using Spatial Multi-Criteria Evaluation. The method is transparent, as the stakeholders (e.g. the engineers and planners from the four countries) and other consultants can consult the criteria trees and evaluate the standardization and weights, and make adjustments. The landslide susceptibility map was converted into a landslide hazard map using landslide density and frequencies for so called major, moderate and minor triggering events. The landslide hazard map was produced in May 2015. A major rainfall event occurred on Dominica following the passage of tropical storm Erika on 26 to 28 August 2015. An event-based landslide inventory for this event was produced by UNOSAT using very high resolution

  13. Landslide Susceptibility Mapping Using Geospatial Technology in South Eastern Part of Nilgiri District, Tamilnadu, India

    NASA Astrophysics Data System (ADS)

    Thangasamy, N.; Varathan, R.

    2013-05-01

    Landslides are often destructive and periodically affect the Nilgiris district. Two method viz., Frequency ratio (FR) and Weights of evidence (WofE) were used to reclassify the sub-variables and the landslide susceptibility index (LSI) was calculated by weighted sum overlay analysis. The final LS Zonation map was prepared from the LSI and the area was classified into two zones. Validation of the LSM was the next step and was accomplished by excluding some landslide points in the GIS analyses and overlying the unused landslides points over the LSM. The LSMs prepared using the FR and WofE methods are reliable as more than 75% of the excluded slides fall in high and very high landslide susceptibility zones and the error of mismatch in the two maps is negligible.During the course of this study landslides devastated the Kethi, Coonoor, Barliyar and Kothagiri areas due to an extreme event with 374 to 1,171 mm rainfall received in these stations in just three days on 8th to 10th November, 2009. The rainfall event is unprecedented and such extreme rainfall has not occurred in the region since meteorological records are maintained. Over 100 landslides took place in the area of which 75 are major slides and more 43 people died and 200 houses were damaged. The event was documented and a data base containing the location, details of death, slide characteristics and photographs was prepared. Further, the probability of landslide occurrence may change over time due to changes in land use, unscientific massive developmental activities and establishing settlements without adopting proper safety measures. The study also highlights the need for maintenance of landslide database and installation of more rain gauge stations to update and improve the LSM so as to reduce the risk of landslide hazard faced by the Community. NaveenRaj.T INDIA LANDSLIDE SUSCEPTIBILITY MAPPING USING GEOSPATIAL TECHNOLOGY IN SOUTH EASTERN PART OF NILGIRI DISTRICT, TAMILNADU, INDIA.

  14. Non-Susceptible Landslide Areas in Italy and in the Mediterranean Region

    NASA Astrophysics Data System (ADS)

    Alvioli, Massimiliano; Ardizzone, Francesca; Guzzetti, Fausto; Marchesini, Ivan; Rossi, Mauro

    2014-05-01

    Landslide susceptibility is the likelihood of a landslide occurring in a given area. Over the past three decades, researchers, and planning and environmental organisations have worked to assess landslide susceptibility at different geographical scales, and to produce maps portraying landslide susceptibility zonation. Little effort was made to determine where landslides are not expected, where susceptibility is null, or negligible. This is surprising because planners and decision makers are also interesting in knowing where landslides are not foreseen, or cannot occur in an area. We propose a method for the definition of non-susceptible landslide areas, at the synoptic scale. We applied the method in Italy and to the territory surrounding the Mediterranean Sea and we produced two synoptic-scale maps showing areas where landslides are not expected in Italy and in the Mediterranean area. To construct the method we used digital terrain elevation and landslide information. The digital terrain consisted in the 3-arc-second SRTM DEM, the landslide information was obtained for 13 areas in Italy where landslide inventory maps were available to us. We tested three different models to determine the non-susceptible landslide areas, including a linear model (LR), a quantile linear model (QLR), and a quantile non-linear model (QNL). Model performances have been evaluated using independent landslide information represented by the Italian Landslide Inventory (Inventario Fenomeni Franosi in Italia - IFFI). Best results were obtained using the QNL model. The corresponding zonation of non- susceptible landslide areas was intersected in a GIS with geographical census data for Italy. The results show that the 57.5% of the population of Italy (in 2001) was located in areas where landslide susceptibility was expected to be null or negligible, while the remaining 42.5% in areas where some landslide susceptibility was significant or not negligible. We applied the QNL model to the

  15. Comparison of two landslide susceptibility assessments in the Champagne-Ardenne region (France)

    NASA Astrophysics Data System (ADS)

    Den Eeckhaut, M. Van; Marre, A.; Poesen, J.

    2010-02-01

    The vineyards of the Montagne de Reims are mostly planted on steep south-oriented cuesta fronts receiving a maximum of sun radiation. Due to the location of the vineyards on steep hillslopes, the viticultural activity is threatened by slope failures. This study attempts to better understand the spatial patterns of landslide susceptibility in the Champagne-Ardenne region by comparing a heuristic (qualitative) and a statistical (quantitative) model in a 1120 km² study area. The heuristic landslide susceptibility model was adopted from the Bureau de Recherches Géologiques et Minières, the GEGEAA - Reims University and the Comité Interprofessionnel du Vin de Champagne. In this model, expert knowledge of the region was used to assign weights to all slope classes and lithologies present in the area, but the final susceptibility map was never evaluated with the location of mapped landslides. For the statistical landslide susceptibility assessment, logistic regression was applied to a dataset of 291 'old' (Holocene) landslides. The robustness of the logistic regression model was evaluated and ROC curves were used for model calibration and validation. With regard to the variables assumed to be important environmental factors controlling landslides, the two models are in agreement. They both indicate that present and future landslides are mainly controlled by slope gradient and lithology. However, the comparison of the two landslide susceptibility maps through (1) an evaluation with the location of mapped 'old' landslides and through (2) a temporal validation with spatial data of 'recent' (1960-1999; n = 48) and 'very recent' (2000-2008; n = 46) landslides showed a better prediction capacity for the statistical model produced in this study compared to the heuristic model. In total, the statistically-derived landslide susceptibility map succeeded in correctly classifying 81.0% of the 'old' and 91.6% of the 'recent' and 'very recent' landslides. On the susceptibility map

  16. Multidisciplinary approach to evaluate landslide susceptibility along highway in northern Calabria, Italy

    NASA Astrophysics Data System (ADS)

    Muto, Francesco; Conforti, Massimo; Critelli, Salvatore; Fabbricatore, Davide; Filomena, Luciana; Rago, Valeria; Robustelli, Gaetano; Scarciglia, Fabio; Versace, Pasquale

    2014-05-01

    The interaction of landslides with linear infrastructures is often the cause of disasters. In Italy landslide impact on roads, railways and buildings cause millions of Euro per year in damage and restoration as well. The proposed study is aimed to the landslide susceptibility evaluation using a multidisciplinary approach: geological and geomorphological survey, statistical analysis and GIS technique, along a section of highway "A3 (Salerno-Reggio Calabria)" between Cosenza Sud and Altilia, northern Calabria. This study is included in a wider research project, named: PON01-01503, Landslides Early Warning-Sistemi integrati per il monitoraggio e la mitigazione del rischio idrogeologico lungo le grandi vie di comunicazione - aimed at the hydrogeological risk mitigation and at the early warning along the highways. The work was first based on air-photo interpretations and field investigations, in order to realize the geological map, geomorphological map and landslide inventory map. In the study area the geomorphology is strongly controlled by its bedrock geology and tectonics. The bedrock geology consists of Neogene sedimentary rocks that cover a thick stack of allochthonous nappes. These nappes consist of crystalline rocks mainly gneiss, phyllite and schist. A total of 835 landslides were mapped and the type of movement are represented mainly by slides and complex and subordinately flow. In order to estimate and validate landslide susceptibility the landslides were divided in two group. One group (training set) was used to prepare susceptibility map and the second group (validation set) to validate the map. Then, the selection of predisposing factors was performed, according with the geological and geomorphological settings of the study area: lithology, distance from tectonic elements, land use, slope, aspect, stream power index (SPI) and plan curvature. In order to evaluate landslide susceptibility Conditional Analysis was applied to Unique Conditions Units (UCUs

  17. Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

    NASA Astrophysics Data System (ADS)

    Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

    2014-06-01

    This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

  18. Susceptibility and triggering scenarios at a regional scale for shallow landslides

    NASA Astrophysics Data System (ADS)

    Gullà, G.; Antronico, L.; Iaquinta, P.; Terranova, O.

    2008-07-01

    The work aims at identifying susceptible areas and pluviometric triggering scenarios at a regional scale in Calabria (Italy), with reference to shallow landsliding events. The proposed methodology follows a statistical approach and uses a database linked to a GIS that has been created to support the various steps of spatial data management and manipulation. The shallow landslide predisposing factors taken into account are derived from (i) the 40-m digital terrain model of the region, an ˜ 15,075 km 2 extension; (ii) outcropping lithology; (iii) soils; and (iv) land use. More precisely, a map of the slopes has been drawn from the digital terrain model. Two kinds of covers [prevalently coarse-grained (CG cover) or fine-grained (FG cover)] were identified, referring to the geotechnical characteristics of geomaterial covers and to the lithology map; soilscapes were drawn from soil maps; and finally, the land use map was employed without any prior processing. Subsequently, the inventory maps of some shallow landsliding events, totaling more than 30,000 instabilities of the past and detected by field surveys and photo aerial restitution, were employed to calibrate the relative importance of these predisposing factors. The use of single factors (first level analysis) therefore provides three different susceptibility maps. Second level analysis, however, enables better location of areas susceptible to shallow landsliding events by crossing the single susceptibility maps. On the basis of the susceptibility map obtained by the second level analysis, five different classes of susceptibility to shallow landsliding events have been outlined over the regional territory: 8.9% of the regional territory shows very high susceptibility, 14.3% high susceptibility, 15% moderate susceptibility, 3.6% low susceptibility, and finally, about 58% very low susceptibility. Finally, the maps of two significant shallow landsliding events of the past and their related rainfalls have been

  19. Comparison of the landslide susceptibility models in Taipei Water Source Domain, Taiwan

    NASA Astrophysics Data System (ADS)

    WU, C. Y.; Yeh, Y. C.; Chou, T. H.

    2017-12-01

    Taipei Water Source Domain, locating at the southeast of Taipei Metropolis, is the main source of water resource in this region. Recently, the downstream turbidity often soared significantly during the typhoon period because of the upstream landslides. The landslide susceptibilities should be analysed to assess the influence zones caused by different rainfall events, and to ensure the abilities of this domain to serve enough and quality water resource. Generally, the landslide susceptibility models can be established based on either a long-term landslide inventory or a specified landslide event. Sometimes, there is no long-term landslide inventory in some areas. Thus, the event-based landslide susceptibility models are established widely. However, the inventory-based and event-based landslide susceptibility models may result in dissimilar susceptibility maps in the same area. So the purposes of this study were to compare the landslide susceptibility maps derived from the inventory-based and event-based models, and to interpret how to select a representative event to be included in the susceptibility model. The landslide inventory from Typhoon Tim in July, 1994 and Typhoon Soudelor in August, 2015 was collected, and used to establish the inventory-based landslide susceptibility model. The landslides caused by Typhoon Nari and rainfall data were used to establish the event-based model. The results indicated the high susceptibility slope-units were located at middle upstream Nan-Shih Stream basin.

  20. Effects of Inventory Bias on Landslide Susceptibility Calculations

    NASA Technical Reports Server (NTRS)

    Stanley, T. A.; Kirschbaum, D. B.

    2017-01-01

    Many landslide inventories are known to be biased, especially inventories for large regions such as Oregon's SLIDO or NASA's Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modeling landslide susceptibility with heavily biased inventories.

  1. Effects of Inventory Bias on Landslide Susceptibility Calculations

    NASA Technical Reports Server (NTRS)

    Stanley, Thomas; Kirschbaum, Dalia B.

    2017-01-01

    Many landslide inventories are known to be biased, especially inventories for large regions such as Oregons SLIDO or NASAs Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modelling landslide susceptibility with heavily biased inventories.

  2. Landslide Susceptibility Statistical Methods: A Critical and Systematic Literature Review

    NASA Astrophysics Data System (ADS)

    Mihir, Monika; Malamud, Bruce; Rossi, Mauro; Reichenbach, Paola; Ardizzone, Francesca

    2014-05-01

    Landslide susceptibility assessment, the subject of this systematic review, is aimed at understanding the spatial probability of slope failures under a set of geomorphological and environmental conditions. It is estimated that about 375 landslides that occur globally each year are fatal, with around 4600 people killed per year. Past studies have brought out the increasing cost of landslide damages which primarily can be attributed to human occupation and increased human activities in the vulnerable environments. Many scientists, to evaluate and reduce landslide risk, have made an effort to efficiently map landslide susceptibility using different statistical methods. In this paper, we do a critical and systematic landslide susceptibility literature review, in terms of the different statistical methods used. For each of a broad set of studies reviewed we note: (i) study geography region and areal extent, (ii) landslide types, (iii) inventory type and temporal period covered, (iv) mapping technique (v) thematic variables used (vi) statistical models, (vii) assessment of model skill, (viii) uncertainty assessment methods, (ix) validation methods. We then pulled out broad trends within our review of landslide susceptibility, particularly regarding the statistical methods. We found that the most common statistical methods used in the study of landslide susceptibility include logistic regression, artificial neural network, discriminant analysis and weight of evidence. Although most of the studies we reviewed assessed the model skill, very few assessed model uncertainty. In terms of geographic extent, the largest number of landslide susceptibility zonations were in Turkey, Korea, Spain, Italy and Malaysia. However, there are also many landslides and fatalities in other localities, particularly India, China, Philippines, Nepal and Indonesia, Guatemala, and Pakistan, where there are much fewer landslide susceptibility studies available in the peer-review literature. This

  3. Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda.

    PubMed

    Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng

    2018-01-31

    Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model's performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management.

  4. Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda

    PubMed Central

    Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng

    2018-01-01

    Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management. PMID:29385096

  5. GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region

    NASA Astrophysics Data System (ADS)

    Kamp, Ulrich; Growley, Benjamin J.; Khattak, Ghazanfar A.; Owen, Lewis A.

    2008-11-01

    The Mw 7.6 October 8, 2005 Kashmir earthquake triggered several thousand landslides throughout the Himalaya of northern Pakistan and India. These were concentrated in six different geomorphic-geologic-anthropogenic settings. A spatial database, which included 2252 landslides, was developed and analyzed using ASTER satellite imagery and geographical information system (GIS) technology. A multi-criterion evaluation was applied to determine the significance of event-controlling parameters in triggering the landslides. The parameters included lithology, faults, slope gradient, slope aspect, elevation, land cover, rivers and roads. The results showed four classes of landslide susceptibility. Furthermore, they indicated that lithology had the strongest influence on landsliding, particularly when the rock is highly fractured, such as in shale, slate, clastic sediments, and limestone and dolomite. Moreover, the proximity of the landslides to faults, rivers, and roads was also an important factor in helping to initiate failures. In addition, landslides occurred particularly in moderate elevations on south facing slopes. Shrub land, grassland, and also agricultural land were highly susceptible to failures, while forested slopes had few landslides. One-third of the study area was highly or very highly susceptible to future landsliding and requires immediate mitigation action. The rest of the region had a low or moderate susceptibility to landsliding and remains relatively stable. This study supports the view that (1) earthquake-triggered landslides are concentrated in specific zones associated with event-controlling parameters; and (2) in the western Himalaya deforestation and road construction contributed significantly to landsliding during and shortly after earthquakes.

  6. Landslide susceptibility revealed by LIDAR imagery and historical records, Seattle, Washington

    USGS Publications Warehouse

    Schulz, W.H.

    2007-01-01

    Light detection and ranging (LIDAR) data were used to visually map landslides, headscarps, and denuded slopes in Seattle, Washington. Four times more landslides were mapped than by previous efforts that used aerial photographs. The mapped landforms (landslides, headscarps, and denuded slopes) were created by many individual landslides. The spatial distribution of mapped landforms and 1308 historical landslides show that historical landslide activity has been concentrated on the mapped landforms, and that most of the landslide activity that created the landforms was prehistoric. Thus, the spatial densities of historical landslides on the landforms provide approximations of the landforms' relative susceptibilities to future landsliding. Historical landslide characteristics appear to be closely related to landform type so relative susceptibilities were determined for landslides with various characteristics. No strong relations were identified between stratigraphy and landslide occurrence; however, landslide characteristics and slope morphology appear to be related to stratigraphic conditions. Human activity is responsible for causing about 80% of historical Seattle landslides. The distribution of mapped landforms and human-caused landslides suggests the probable characteristics of future human-caused landslides on each of the landforms. The distribution of mapped landforms and historical landslides suggests that erosion of slope-toes by surface water has been a necessary condition for causing Seattle landslides. Human activity has largely arrested this erosion, which implies that landslide activity will decrease with time as hillsides naturally stabilize. However, evaluation of glacial-age analogs of areas of recent slope-toe erosion suggests that landslide activity in Seattle will continue for the foreseeable future. ?? 2006 Elsevier B.V. All rights reserved.

  7. A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet

    2013-02-01

    The purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at Penang Hill area, Malaysia. The necessary input parameters for the landslide susceptibility assessments were obtained from various sources. At first, landslide locations were identified by aerial photographs and field surveys and a total of 113 landslide locations were constructed. The study area contains 340,608 pixels while total 8403 pixels include landslides. The landslide inventory was randomly partitioned into two subsets: (1) part 1 that contains 50% (4000 landslide grid cells) was used in the training phase of the models; (2) part 2 is a validation dataset 50% (4000 landslide grid cells) for validation of three models and to confirm its accuracy. The digitally processed images of input parameters were combined in GIS. Finally, landslide susceptibility maps were produced, and the performances were assessed and discussed. Total fifteen landslide susceptibility maps were produced using DT, SVM and ANFIS based models, and the resultant maps were validated using the landslide locations. Prediction performances of these maps were checked by receiver operating characteristics (ROC) by using both success rate curve and prediction rate curve. The validation results showed that, area under the ROC curve for the fifteen models produced using DT, SVM and ANFIS varied from 0.8204 to 0.9421 for success rate curve and 0.7580 to 0.8307 for prediction rate curves, respectively. Moreover, the prediction curves revealed that model 5 of DT has slightly higher prediction performance (83.07), whereas the success rate showed that model 5 of ANFIS has better prediction (94.21) capability among all models. The results of this study showed that landslide susceptibility mapping in the Penang Hill area using the three approaches (e

  8. Assessments on landslide susceptibility in the Tseng-wen reservoir watershed, Taiwan

    NASA Astrophysics Data System (ADS)

    Chen, Yu-Chin; Chen, Yung-Chau; Chen, Wen-Fu

    2014-05-01

    Typhoon Morakot under the strong influence of southwestern monsoon wind struck Taiwan on 8 August 2009, and dumped record-breaking rains in southern Taiwan. It triggered enormous landslides in mountains and severe flooding in low-lying areas. In addition, it destroyed or damaged houses, agricultural fields, roads, bridges, and other infrastructure facilities, causing massive economic loss and, more tragically, human casualties. In order to evaluate landslide hazard and risk assessment, it is important to understand the potential sites of landslide and their spatial distribution. Multi-temporal satellite images and geo-spatial data are used to build landslide susceptibility map for the post-disaster in the Tseng-wen reservoir watershed in this research. Elevation, slope, aspect, NDVI (normalized differential vegetation index), relief, roughness, distance to river, and distance to road are the considered factors for estimating landslide susceptibility. Maximum hourly rainfall and total rainfall, accompanied with typhoon event, are selected as the trigger factors of landslide events. Logistic regression analysis is adopted as the statistical method to model landslide susceptibility. The assessed susceptibility is represented in 4 levels which are high, high-intermediate, intermediate, and low level, respectively. Landslide spatial distribution can be depicted as a landslide susceptibility map with respect to each considered influence factors for a specified susceptible level. The landslide areas are about 358 ha and 1,485 ha before and after typhoon Morakot. The new landslide area, induced by typhoon Morakot, is as almost 4 times as the landslide area before typhoon Morakot. In addition, there is about 44.56% landslide area elevation ranging from 500m to 1000m and about 57.22% average slope ranging from 30° to 45° of landslide area. Furthermore, the devastating landslides were happened at those sites close to rivers, exposed area, and area with big land cover change

  9. ANFIS modeling for the assessment of landslide susceptibility for the Cameron Highland (Malaysia)

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet; Sezer, Ebru; Gokceoglu, Candan; Buchroithner, Manfred F.

    2010-05-01

    Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. In landslide literature, there are several approaches such as probabilistic, bivariate and multivariate statistical models, fuzzy and artificial neural network models etc. However, a neuro-fuzzy application on the landslide susceptibility assessment has not been encountered in the literature. For this reason, this study presents the results of an adaptive neuro-fuzzy inference system (ANFIS) using remote sensing data and GIS for landslide susceptibility analysis in a part of the Cameron Highland areas in Malaysia. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments, NDVI and land cover were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, curvature, distance from drainage, lithology, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to produce the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were constructed. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values were calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 97% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient agreement between the obtained susceptibility map and the existing data on landslide areas. Qualitatively, the model yields reasonable results which can be used for preliminary land

  10. Susceptibility Evaluation and Mapping of CHINA'S Landslide Disaster Based on Multi-Temporal Ground and Remote Sensing Satellite Data

    NASA Astrophysics Data System (ADS)

    Liu, C.; Li, W.; Lu, P.; Sang, K.; Hong, Y.; Li, R.

    2012-07-01

    Under the circumstances of global climate change, nowadays landslide occurs in China more frequently than ever before. The landslide hazard and risk assessment remains an international focus on disaster prevention and mitigation. It is also an important approach for compiling and quantitatively characterizing landslide damages. By integrating empirical models for landslide disasters, and through multi-temporal ground data and remote sensing data, this paper will perform a landslide susceptibility assessment throughout China. A landslide susceptibility (LS) map will then be produced, which can be used for disaster evaluation, and provide basis for analyzing China's major landslide-affected regions. Firstly, based on previous research of landslide susceptibility assessment, this paper collects and analyzes the historical landslide event data (location, quantity and distribution) of past sixty years in China as a reference for late-stage studies. Secondly, this paper will make use of regional GIS data of the whole country provided by the National Geomatics Centre and China Meteorological Administration, including regional precipitation data, and satellite remote sensing data such as from TRMM and MODIS. By referring to historical landslide data of past sixty years, it is possible to develop models for assessing LS, including producing empirical models for prediction, and discovering both static and dynamic key factors, such as topography and landforms (elevation, curvature and slope), geologic conditions (lithology of the strata), soil type, vegetation cover, hydrological conditions (flow distribution). In addition, by analyzing historical data and combining empirical models, it is possible to synthesize a regional statistical model and perform a LS assessment. Finally, based on the 1km×1km grid, the LS map is then produced by ANN learning and multiplying the weighted factor layers. The validation is performed with reference to the frequency and distribution of

  11. A multi-annual landslide inventory for the assessment of shallow landslide susceptibility - Two test cases in Vorarlberg, Austria

    NASA Astrophysics Data System (ADS)

    Zieher, Thomas; Perzl, Frank; Rössel, Monika; Rutzinger, Martin; Meißl, Gertraud; Markart, Gerhard; Geitner, Clemens

    2016-04-01

    Geomorphological landslide inventories provide crucial input data for any study on the assessment of landslide susceptibility, hazard or risk. Several approaches for assessing landslide susceptibility have been proposed to identify areas particularly vulnerable to this natural hazard. What they have in common is the need for data of observed landslides. Therefore the first step of any study on landslide susceptibility is usually the compilation of a geomorphological landslide inventory using a geographical information system. Recent research has proved the feasibility of orthophoto interpretation for the preparation of an inventory aimed at the delineation of landslides with the use of distinctive signs in the imagery data. In this study a multi-annual landslide inventory focusing on shallow landslides (i.e. translational soil slides of 0-2 m in depth) was compiled for two study areas in Vorarlberg (Austria) from the interpretation of nine orthophoto series. In addition, derivatives of two generations of airborne laser scanning data aided the mapping procedure. Landslide scar areas were delineated on the basis of a high-resolution differential digital terrain model. The derivation of landslide volumes, depths and depth-to-length ratios are discussed. Results show that most mapped landslides meet the definition of a shallow landslide. The inventory therefore provides the data basis for the assessment of shallow landslide susceptibility and allows for the application of various modelling techniques.

  12. Landslide susceptibility mapping in Mawat area, Kurdistan Region, NE Iraq: a comparison of different statistical models

    NASA Astrophysics Data System (ADS)

    Othman, A. A.; Gloaguen, R.; Andreani, L.; Rahnama, M.

    2015-03-01

    During the last decades, expansion of settlements into areas prone to landslides in Iraq has increased the importance of accurate hazard assessment. Susceptibility mapping provides information about hazardous locations and thus helps to potentially prevent infrastructure damage due to mass wasting. The aim of this study is to evaluate and compare frequency ratio (FR), weight of evidence (WOE), logistic regression (LR) and probit regression (PR) approaches in combination with new geomorphological indices to determine the landslide susceptibility index (LSI). We tested these four methods in Mawat area, Kurdistan Region, NE Iraq, where landslides occur frequently. For this purpose, we evaluated 16 geomorphological, geological and environmental predicting factors mainly derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite. The available reference inventory includes 351 landslides representing a cumulative surface of 3.127 km2. This reference inventory was mapped from QuickBird data by manual delineation and partly verified by field survey. The areas under curve (AUC) of the receiver operating characteristic (ROC), and relative landslide density (R index) show that all models perform similarly and that focus should be put on the careful selection of proxies. The results indicate that the lithology and the slope aspects play major roles for landslide occurrences. Furthermore, this paper demonstrates that using hypsometric integral as a prediction factor instead of slope curvature gives better results and increases the accuracy of the LSI.

  13. Landslide Susceptibility Mapping of Tegucigalpa, Honduras Using Artificial Neural Network, Bayesian Network and Decision Trees

    NASA Astrophysics Data System (ADS)

    Garcia Urquia, E. L.; Braun, A.; Yamagishi, H.

    2016-12-01

    Tegucigalpa, the capital city of Honduras, experiences rainfall-induced landslides on a yearly basis. The high precipitation regime and the rugged topography the city has been built in couple with the lack of a proper urban expansion plan to contribute to the occurrence of landslides during the rainy season. Thousands of inhabitants live at risk of losing their belongings due to the construction of precarious shelters in landslide-prone areas on mountainous terrains and next to the riverbanks. Therefore, the city is in the need for landslide susceptibility and hazard maps to aid in the regulation of future development. Major challenges in the context of highly dynamic urbanizing areas are the overlap of natural and anthropogenic slope destabilizing factors, as well as the availability and accuracy of data. Data-driven multivariate techniques have proven to be powerful in discovering interrelations between factors, identifying important factors in large datasets, capturing non-linear problems and coping with noisy and incomplete data. This analysis focuses on the creation of a landslide susceptibility map using different methods from the field of data mining, Artificial Neural Networks (ANN), Bayesian Networks (BN) and Decision Trees (DT). The input dataset of the study contains geomorphological and hydrological factors derived from a digital elevation model with a 10 m resolution, lithological factors derived from a geological map, and anthropogenic factors, such as information on the development stage of the neighborhoods in Tegucigalpa and road density. Moreover, a landslide inventory map that was developed in 2014 through aerial photo interpretation was used as target variable in the analysis. The analysis covers an area of roughly 100 km2, while 8.95 km2 are occupied by landslides. In a first step, the dataset was explored by assessing and improving the data quality, identifying unimportant variables and finding interrelations. Then, based on a training

  14. A GIS-based automated procedure for landslide susceptibility mapping by the Conditional Analysis method: the Baganza valley case study (Italian Northern Apennines)

    NASA Astrophysics Data System (ADS)

    Clerici, Aldo; Perego, Susanna; Tellini, Claudio; Vescovi, Paolo

    2006-08-01

    Among the many GIS based multivariate statistical methods for landslide susceptibility zonation, the so called “Conditional Analysis method” holds a special place for its conceptual simplicity. In fact, in this method landslide susceptibility is simply expressed as landslide density in correspondence with different combinations of instability-factor classes. To overcome the operational complexity connected to the long, tedious and error prone sequence of commands required by the procedure, a shell script mainly based on the GRASS GIS was created. The script, starting from a landslide inventory map and a number of factor maps, automatically carries out the whole procedure resulting in the construction of a map with five landslide susceptibility classes. A validation procedure allows to assess the reliability of the resulting model, while the simple mean deviation of the density values in the factor class combinations, helps to evaluate the goodness of landslide density distribution. The procedure was applied to a relatively small basin (167 km2) in the Italian Northern Apennines considering three landslide types, namely rotational slides, flows and complex landslides, for a total of 1,137 landslides, and five factors, namely lithology, slope angle and aspect, elevation and slope/bedding relations. The analysis of the resulting 31 different models obtained combining the five factors, confirms the role of lithology, slope angle and slope/bedding relations in influencing slope stability.

  15. Landslide Susceptibility Index Determination Using Aritificial Neural Network

    NASA Astrophysics Data System (ADS)

    Kawabata, D.; Bandibas, J.; Urai, M.

    2004-12-01

    The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic features, rock types and geologic structure are especially important base factors of the landslide occurrence. Generating landslide susceptibility index by defining the relationship between landslide occurrence and that base factors using conventional mathematical and statistical methods is very difficult and inaccurate. This study focuses on generating landslide susceptibility index using artificial neural networks in Southern Japanese Alps. The training data are geomorphic (e.g. altitude, slope and aspect) and geologic parameters (e.g. rock type, distance from geologic boundary and geologic dip-strike angle) and landslides. Artificial neural network structure and training scheme are formulated to generate the index. Data from areas with and without landslide occurrences are used to train the network. The network is trained to output 1 when the input data are from areas with landslides and 0 when no landslide occurred. The trained network generates an output ranging from 0 to 1 reflecting the possibility of landslide occurrence based on the inputted data. Output values nearer to 1 means higher possibility of landslide occurrence. The artificial neural network model is incorporated into the GIS software to generate a landslide susceptibility map.

  16. Producing landslide susceptibility maps by utilizing machine learning methods. The case of Finikas catchment basin, North Peloponnese, Greece.

    NASA Astrophysics Data System (ADS)

    Tsangaratos, Paraskevas; Ilia, Ioanna; Loupasakis, Constantinos; Papadakis, Michalis; Karimalis, Antonios

    2017-04-01

    The main objective of the present study was to apply two machine learning methods for the production of a landslide susceptibility map in the Finikas catchment basin, located in North Peloponnese, Greece and to compare their results. Specifically, Logistic Regression and Random Forest were utilized, based on a database of 40 sites classified into two categories, non-landslide and landslide areas that were separated into a training dataset (70% of the total data) and a validation dataset (remaining 30%). The identification of the areas was established by analyzing airborne imagery, extensive field investigation and the examination of previous research studies. Six landslide related variables were analyzed, namely: lithology, elevation, slope, aspect, distance to rivers and distance to faults. Within the Finikas catchment basin most of the reported landslides were located along the road network and within the residential complexes, classified as rotational and translational slides, and rockfalls, mainly caused due to the physical conditions and the general geotechnical behavior of the geological formation that cover the area. Each landslide susceptibility map was reclassified by applying the Geometric Interval classification technique into five classes, namely: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The comparison and validation of the outcomes of each model were achieved using statistical evaluation measures, the receiving operating characteristic and the area under the success and predictive rate curves. The computation process was carried out using RStudio an integrated development environment for R language and ArcGIS 10.1 for compiling the data and producing the landslide susceptibility maps. From the outcomes of the Logistic Regression analysis it was induced that the highest b coefficient is allocated to lithology and slope, which was 2.8423 and 1.5841, respectively. From the

  17. Application of LiDAR Date to Assess the Landslide Susceptibility Map Using Weights of Evidence Method - AN Example from Podhale Region (southern Poland)

    NASA Astrophysics Data System (ADS)

    Kamiński, Mirosław

    2016-06-01

    Podhale is a region in southern Poland, which is the northernmost part of the Central Carpathian Mountains. It is characterized by the presence of a large number of landslides that threaten the local infrastructure. In an article presents application of LiDAR data and geostatistical methods to assess landslides susceptibility map. Landslide inventory map were performed using LiDAR data and field work. The Weights of Evidence method was applied to assess landslides susceptibility map. Used factors for modeling: slope gradient, slope aspect, elevation, drainage density, faults density, lithology and curvature. All maps were subdivided into different classes. Then were converted to grid format in the ArcGIS 10.0. The conditional independence test was carried out to determine factors that are conditionally independent of each other with landslides. As a result, chi-square test for further GIS analysis used only five factors: slope gradient, slope aspect, elevation, drainage density and lithology. The final prediction results, it is concluded that the susceptibility map gives useful information both on present instability of the area and its possible future evolution in agreement with the morphological evolution of the area.

  18. Comparison of non-landslide sampling strategies to counteract inventory-based biases within national-scale statistical landslide susceptibility models

    NASA Astrophysics Data System (ADS)

    Lima, Pedro; Steger, Stefan; Glade, Thomas

    2017-04-01

    Landslides can represent a significant threat for people and infrastructure in hilly and mountainous landscapes worldwide. The understanding and prediction of those geomorphic processes is crucial to avoid economic loses or even casualties to people and their properties. Statistical based landslide susceptibility models are well known for being highly reliant on the quality, representativeness and availability of input data. In this context, several studies indicate that the landslide inventory represents the most important input data. However each landslide mapping technique or data collection has its drawbacks. Consequently, biased landslide inventories may be commonly introduced into statistical models, especially at regional or even national scale. It remains to the researcher to be aware of potential limitations and design strategies to avoid or reduce the potential propagation of input data errors and biases influences on the modelling outcomes. Previous studies have proven that such erroneous landslide inventories may lead to unrealistic landslide susceptibility maps. We assume that one possibility to tackle systematic landslide inventory-based biases might be a concentration on sampling strategies that focus on the distribution of non-landslide locations. For this purpose, we test an approach for the Austrian territory that concentrates on a modified non-landslide sampling strategy, instead the traditional applied random sampling. It is expected that the way non-landslide locations are represented (e.g. equally over the area or within those areas where mapping campaigns have been conducted) is important to reduce a potential over- or underestimation of landslide susceptibility within specific areas caused by bias. As presumably each landslide inventory is known to be systematically incomplete, especially in those areas where no mapping campaign was previously conducted. This is also applicable to the one currently available for the Austrian territory

  19. Assessing Landslide Characteristics and Developing a Landslide Potential Hazard Map in Rwanda and Uganda Using NASA Earth Observations

    NASA Astrophysics Data System (ADS)

    Sinclair, L.; Conner, P.; le Roux, J.; Finley, T.

    2015-12-01

    The International Emergency Disasters Database indicates that a total of 482 people have been killed and another 27,530 have been affected by landslides in Rwanda and Uganda, although the actual numbers are thought to be much higher. Data for individual countries are poorly tracked, but hotspots for devastating landslides occur throughout Rwanda and Uganda due to the local topography and soil type, intense rainfall events, and deforestation. In spite of this, there has been little research in this region that utilizes satellite imagery to estimate areas susceptible to landslides. This project utilized Landsat 8 Operational Land Imager (OLI) data and Google Earth to identify landslides that occurred within the study area. These landslides were then added to SERVIR's Global Landslide Catalog (GLC). Next, Landsat 8 OLI, the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), and Shuttle Radar Topography Mission Version 2 (SRTM V2) data were used to create a Landslide Susceptibility Map. This was combined with population data from the Socioeconomic Data and Applications Center (SEDAC) to create a Landslide Hazard map. A preliminary assessment of the relative performance of GPM and TRMM in identifying landslide conditions was also performed. The additions to the GLC, the Landslide Susceptibility Map, the Landslide Hazard Map, and the preliminary assessment of satellite rainfall performance will be used by SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for disaster risk management, land use planning, and determining landslide conditions and moisture thresholds.

  20. A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping

    NASA Astrophysics Data System (ADS)

    Crozier, M. J.

    2017-10-01

    Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock. The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity

  1. Integration of data-driven and physically-based methods to assess shallow landslides susceptibility

    NASA Astrophysics Data System (ADS)

    Lajas, Sara; Oliveira, Sérgio C.; Zêzere, José Luis

    2016-04-01

    Approaches used to assess shallow landslides susceptibility at the basin scale are conceptually different depending on the use of statistic or deterministic methods. The data-driven methods are sustained in the assumption that the same causes are likely to produce the same effects and for that reason a present/past landslide inventory and a dataset of factors assumed as predisposing factors are crucial for the landslide susceptibility assessment. The physically-based methods are based on a system controlled by physical laws and soil mechanics, where the forces which tend to promote movement are compared with forces that tend to promote resistance to movement. In this case, the evaluation of susceptibility is supported by the calculation of the Factor of safety (FoS), and dependent of the availability of detailed data related with the slope geometry and hydrological and geotechnical properties of the soils and rocks. Within this framework, this work aims to test two hypothesis: (i) although conceptually distinct and based on contrasting procedures, statistic and deterministic methods generate similar shallow landslides susceptibility results regarding the predictive capacity and spatial agreement; and (ii) the integration of the shallow landslides susceptibility maps obtained with data-driven and physically-based methods, for the same study area, generate a more reliable susceptibility model for shallow landslides occurrence. To evaluate these two hypotheses, we select the Information Value data-driven method and the physically-based Infinite Slope model to evaluate shallow landslides in the study area of Monfalim and Louriceira basins (13.9 km2), which is located in the north of Lisbon region (Portugal). The landslide inventory is composed by 111 shallow landslides and was divide in two independent groups based on temporal criteria (age ≤ 1983 and age > 1983): (i) the modelling group (51 cases) was used to define the weights for each predisposing factor

  2. Landfill site selection for municipal solid wastes in mountainous areas with landslide susceptibility.

    PubMed

    Eskandari, Mahnaz; Homaee, Mehdi; Falamaki, Amin

    2016-06-01

    Several cities across the world are located in mountainous and landslide prone areas. Any landfill siting without considering landslide susceptibility in such regions may impose additional environmental adversity. This study was aimed to propose a practical method for selecting waste disposal site that accounts for landslide exposure. The proposed method was applied to a city which is highly proneness to landslide due to its geology, morphology, and climatic conditions. First, information on the previously occurred landslides of the region was collected. Based on this information, proper landslide causative factors were selected and their thematic maps were prepared. Factors' classes were then standardized in 0-1 domain, and thematic layers were weighted by using analytical hierarchy process (AHP). The landslide susceptibility map was prepared afterwards. Unsuitable areas for landfill location were masked in GIS environment by Boolean method, retaining sufficient areas for further evaluation. Nine remaining alternatives were selected through comprehensive field visits and were ranked by using AHP. Consequently, 17 factors in three environmental, economical, and social perspectives were employed. Sensitivity analyses were performed to assess the stability of the alternatives ranking with respect to variations in criterion weights. Based on the obtained landslide susceptible map, nearly 36 % of the entire region is proneness to landslide. The prepared Boolean map indicates that potential areas for landfill construction cover 11 % of the whole region. The results further indicated that if landslide susceptible areas are not considered in landfill site selection, the potential landfill sites would become more than twice. It can be concluded that if any of these landslide prone sites are selected for landfilling, further environmental disaster would be terminated in the future. It can be further concluded that the proposed method could reasonably well be adjusted to

  3. Landslide susceptibility mapping in the coastal region in the State of São Paulo, Brazil

    NASA Astrophysics Data System (ADS)

    Alvala, R. C.; Camarinha, P. I.; Canavesi, V.

    2013-05-01

    , land use and pedology. As a result, we obtain 5 susceptibility classes: very low, low, medium, high and very high. To validate the methodology, there was overlapped the Landslides Susceptibility Map with real risk areas previously mapped, provided by the National Centre for Monitoring and Alert of Natural Disasters. This step is important especially to assess the methodology adherence to evaluate the classes that was mapped with high and very high susceptibility. The preliminary results indicate that over 70% of the the mapped risks areas are located into the classes more susceptible. We observed small inconsistencies that are related with spatial displacement of the various databases considered, which has different resolutions and scales. Therefore, the results indicated that the methodology is robust and showed the high vulnerability of the counties analyzed, which further highlights that the landslides susceptibility should be monitored carefully by the decision makers in order to prevent and minimize the natural disasters impact, so that provide better territorial planning.

  4. Landslide inventory maps: New tools for an old problem

    NASA Astrophysics Data System (ADS)

    Guzzetti, Fausto; Mondini, Alessandro Cesare; Cardinali, Mauro; Fiorucci, Federica; Santangelo, Michele; Chang, Kang-Tsung

    2012-04-01

    Landslides are present in all continents, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. Despite their importance, we estimate that landslide maps cover less than 1% of the slopes in the landmasses, and systematic information on the type, abundance, and distribution of landslides is lacking. Preparing landslide maps is important to document the extent of landslide phenomena in a region, to investigate the distribution, types, pattern, recurrence and statistics of slope failures, to determine landslide susceptibility, hazard, vulnerability and risk, and to study the evolution of landscapes dominated by mass-wasting processes. Conventional methods for the production of landslide maps rely chiefly on the visual interpretation of stereoscopic aerial photography, aided by field surveys. These methods are time consuming and resource intensive. New and emerging techniques based on satellite, airborne, and terrestrial remote sensing technologies, promise to facilitate the production of landslide maps, reducing the time and resources required for their compilation and systematic update. In this work, we first outline the principles for landslide mapping, and we review the conventional methods for the preparation of landslide maps, including geomorphological, event, seasonal, and multi-temporal inventories. Next, we examine recent and new technologies for landslide mapping, considering (i) the exploitation of very-high resolution digital elevation models to analyze surface morphology, (ii) the visual interpretation and semi-automatic analysis of different types of satellite images, including panchromatic, multispectral, and synthetic aperture radar images, and (iii) tools that facilitate landslide field mapping. Next, we discuss the advantages and the limitations of the new remote sensing data and technology for the production of geomorphological, event, seasonal, and multi-temporal inventory maps

  5. Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

    NASA Astrophysics Data System (ADS)

    Mahalingam, R.; Olsen, M. J.

    2014-12-01

    Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities to plan and prepare for these damaging events. Mapping landslide susceptible locations using GIS and remote sensing techniques is gaining popularity in the past three decades. These efforts use a wide variety of procedures and consider a wide range of factors. Unfortunately, each study is often completed differently and independently of others. Further, the quality of the datasets used varies in terms of source, data collection, and generation, which can propagate errors or inconsistencies into the resulting output maps. Light detection and ranging (LiDAR) has proved to have higher accuracy in representing the continuous topographic surface, which can help minimize this uncertainty. The primary objectives of this paper are to investigate the applicability and performance of terrain factors in landslide hazard mapping, determine if LiDAR-derived datasets (slope, slope roughness, terrain roughness, stream power index and compound topographic index) can be used for predictive mapping without data representing other common landslide conditioning factors, and evaluate the differences in landslide susceptibility mapping using widely-used statistical approaches. The aforementioned factors were used to produce landslide susceptibility maps for a 140 km2 study area in northwest Oregon using six representative techniques: frequency ratio, weights of evidence, logistic regression, discriminant analysis, artificial neural network, and support vector machine. Most notably, the research showed an advantage in selecting fewer critical conditioning factors. The most reliable factors all could be derived from a single LiDAR DEM, reducing the need for laborious and costly data gathering. Most of the six techniques showed similar statistical results; however, ANN showed less accuracy for predictive mapping. Keywords : Li

  6. Application of Physically based landslide susceptibility models in Brazil

    NASA Astrophysics Data System (ADS)

    Carvalho Vieira, Bianca; Martins, Tiago D.

    2017-04-01

    Shallow landslides and floods are the processes responsible for most material and environmental damages in Brazil. In the last decades, some landslides events induce a high number of deaths (e.g. Over 1000 deaths in one event) and incalculable social and economic losses. Therefore, the prediction of those processes is considered an important tool for land use planning tools. Among different methods the physically based landslide susceptibility models having been widely used in many countries, but in Brazil it is still incipient when compared to other ones, like statistical tools and frequency analyses. Thus, the main objective of this research was to assess the application of some Physically based landslide susceptibility models in Brazil, identifying their main results, the efficiency of susceptibility mapping, parameters used and limitations of the tropical humid environment. In order to achieve that, it was evaluated SHALSTAB, SINMAP and TRIGRS models in some studies in Brazil along with the Geotechnical values, scales, DEM grid resolution and the results based on the analysis of the agreement between predicted susceptibility and the landslide scar's map. Most of the studies in Brazil applied SHALSTAB, SINMAP and to a lesser extent the TRIGRS model. The majority researches are concentrated in the Serra do Mar mountain range, that is a system of escarpments and rugged mountains that extends more than 1,500 km along the southern and southeastern Brazilian coast, and regularly affected by heavy rainfall that generates widespread mass movements. Most part of these studies used conventional topographic maps with scales ranging from 1:2000 to 1:50000 and DEM-grid resolution between 2 and 20m. Regarding the Geotechnical and hydrological values, a few studies use field collected data which could produce more efficient results, as indicated by international literature. Therefore, even though they have enormous potential in the susceptibility mapping, even for comparison

  7. A simple landslide susceptibility analysis for hazard and risk assessment in developing countries

    NASA Astrophysics Data System (ADS)

    Guinau, M.; Vilaplana, J. M.

    2003-04-01

    In recent years, a number of techniques and methodologies have been developed for mitigating natural disasters. The complexity of these methodologies and the scarcity of material and data series justify the need for simple methodologies to obtain the necessary information for minimising the effects of catastrophic natural phenomena. The work with polygonal maps using a GIS allowed us to develop a simple methodology, which was developed in an area of 473 Km2 in the Departamento de Chinandega (NW Nicaragua). This area was severely affected by a large number of landslides (mainly debris flows), triggered by the Hurricane Mitch rainfalls in October 1998. With the aid of aerial photography interpretation at 1:40.000 scale, amplified to 1:20.000, and detailed field work, a landslide map at 1:10.000 scale was constructed. The failure zones of landslides were digitized in order to obtain a failure zone digital map. A terrain unit digital map, in which a series of physical-environmental terrain factors are represented, was also used. Dividing the studied area into two zones (A and B) with homogeneous physical and environmental characteristics, allows us to develop the proposed methodology and to validate it. In zone A, the failure zone digital map is superimposed onto the terrain unit digital map to establish the relationship between the different terrain factors and the failure zones. The numerical expression of this relationship enables us to classify the terrain by its landslide susceptibility. In zone B, this numerical relationship was employed to obtain a landslide susceptibility map, obviating the need for a failure zone map. The validity of the methodology can be tested in this area by using the degree of superposition of the susceptibility map and the failure zone map. The implementation of the methodology in tropical countries with physical and environmental characteristics similar to those of the study area allows us to carry out a landslide susceptibility

  8. Landslide susceptibility assessment and validation in the framework of municipal planning in Portugal: the case of Loures Municipality.

    PubMed

    Guillard, Clemence; Zezere, Jose

    2012-10-01

    The legislation that demands the evaluation of landslide susceptibility in Portugal at the municipal level is the National Ecological Reserve (NER). A methodology for the evaluation of landslide susceptibility to be used in municipal planning is applied in Loures Municipality (169.3 km²) located north of Lisbon (Portugal). A landslide inventory was made for the whole area interpreting orthophoto maps and aerial photographs and using standard geomorphologic techniques in field work. It consists of 686 polygons, each polygon representing a rotational, a deep translational or a shallow translational slide, and is integrated into a GIS database. Landslide susceptibility is evaluated using algorithms based on statistical/probabilistic analysis (Information Value Method) over unique-condition terrain units in a raster basis. Three susceptibility models are elaborated independently according to the type of slide (rotational, deep translational, shallow translational). The landslide susceptibility maps are prepared by sorting all pixels according to the pixel susceptibility value in descending order. The robustness and accuracy of the landslide susceptibility models are evaluated by prediction-rate curves, which are used for the quantitative interpretation of the landslide susceptibility maps. Unstable slopes that have to be included into the National Ecological Reserve are extracted from the three susceptibility maps following the general rules to draw the NER that state that the area to be included in the NER should guarantee the inclusion of at least 70 % of the landslides identified in the landslide inventory. The obtained results allow us to conclude that 70 % of the future landslides should occur in these areas, classified as most susceptible to landslides corresponding to 20.3 % of the total area of Municipality. Thus, the consideration of these 20.3 % as regards prevention and protection of landslide risk could potentially reduce damage resulting from 70

  9. Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility

    NASA Astrophysics Data System (ADS)

    Wang, H. B.; Li, J. W.; Zhou, B.; Yuan, Z. Q.; Chen, Y. P.

    2013-03-01

    In the last few decades, the development of Geographical Information Systems (GIS) technology has provided a method for the evaluation of landslide susceptibility and hazard. Slope units were found to be appropriate for the fundamental morphological elements in landslide susceptibility evaluation. Following the DEM construction in a loess area susceptible to landslides, the direct-reverse DEM technology was employed to generate 216 slope units in the studied area. After a detailed investigation, the landslide inventory was mapped in which 39 landslides, including paleo-landslides, old landslides and recent landslides, were present. Of the 216 slope units, 123 involved landslides. To analyze the mechanism of these landslides, six environmental factors were selected to evaluate landslide occurrence: slope angle, aspect, the height and shape of the slope, distance to river and human activities. These factors were extracted in terms of the slope unit within the ArcGIS software. The spatial analysis demonstrates that most of the landslides are located on convex slopes at an elevation of 100-150 m with slope angles from 135°-225° and 40°-60°. Landslide occurrence was then checked according to these environmental factors using an artificial neural network with back propagation, optimized by genetic algorithms. A dataset of 120 slope units was chosen for training the neural network model, i.e., 80 units with landslide presence and 40 units without landslide presence. The parameters of genetic algorithms and neural networks were then set: population size of 100, crossover probability of 0.65, mutation probability of 0.01, momentum factor of 0.60, learning rate of 0.7, max learning number of 10 000, and target error of 0.000001. After training on the datasets, the susceptibility of landslides was mapped for the land-use plan and hazard mitigation. Comparing the susceptibility map with landslide inventory, it was noted that the prediction accuracy of landslide occurrence

  10. The comparison between a ground based and a space based probabilistic landslide susceptibility assessment

    NASA Astrophysics Data System (ADS)

    Reichenbach, P.; Mondini, A.; Guzzetti, F.; Rossi, M.; Ardizzone, F.; Cardinali, M.

    2009-04-01

    Probabilistic landslide susceptibility assessments attempt to predict the location and threat posed by known landslides. Under the assumption that landslides will occur in the future because of the same conditions that produced them in the past, geomorphologists use susceptibility assessments to predict the location of future landslides. We present an attempt to exploit satellite data to prepare a landslide susceptibility zonation for a the Collazzone area that extends for 79 sq km in the Umbria region, Central Italy. For the study area we have prepared a map of the Normalized Difference Vegetation Index (NDVI) obtained by processing raw NIR and RED channels (b2 and b3 bands) at 15 m x 15 m resolution of an image acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), on board the TERRA satellite, and a map of Land Surface Temperature (LST) obtained by processing raw TIR channels (b11 to b15 bands) at 90 m × 90 m resolution from the same image. Both maps, in general proxy for soil moisture maps, were obtained through standard algorithms. As expected, there is a strong correspondence between NDVI and LST, but, when the NDVI does not change, elevation effects and others are predominant in LST. For the Collazzone area we prepared two different susceptibility models. The first was prepared through multivariate analysis of thematic data (including morphometry, lithology, structure and land use) obtained through traditional methods, primarily the interpretation of aerial photographs and field work. The second susceptibility model was prepared using terrain morphology and information obtained processing satellite data. The two models were compared in term of model fit and model performance and were validated exploiting landslide inventories not used to build the models. The two susceptibility models are very similar from a geographic and a classification point of view. This is good news, as it tells us that for landslide susceptibility

  11. Landslide risk mapping and modeling in China

    NASA Astrophysics Data System (ADS)

    Li, W.; Hong, Y.

    2015-12-01

    Under circumstances of global climate change, tectonic stress and human effect, landslides are among the most frequent and severely widespread natural hazards on Earth, as demonstrated in the World Atlas of Natural Hazards (McGuire et al., 2004). Every year, landslide activities cause serious economic loss as well as casualties (Róbert et al., 2005). How landslides can be monitored and predicted is an urgent research topic of the international landslide research community. Particularly, there is a lack of high quality and updated landslide risk maps and guidelines that can be employed to better mitigate and prevent landslide disasters in many emerging regions, including China (Hong, 2007). Since the 1950s, landslide events have been recorded in the statistical yearbooks, newspapers, and monographs in China. As disasters have been increasingly concerned by the government and the public, information about landslide events is becoming available from online news reports (Liu et al., 2012).This study presents multi-scale landslide risk mapping and modeling in China. At the national scale, based on historical data and practical experiences, we carry out landslide susceptibility and risk mapping by adopting a statistical approach and pattern recognition methods to construct empirical models. Over the identified landslide hot-spot areas, we further evaluate the slope-stability for each individual site (Sidle and Hirotaka, 2006), with the ultimate goal to set up a space-time multi-scale coupling system of Landslide risk mapping and modeling for landslide hazard monitoring and early warning.

  12. Comparing physically-based and statistical landslide susceptibility model outputs - a case study from Lower Austria

    NASA Astrophysics Data System (ADS)

    Canli, Ekrem; Thiebes, Benni; Petschko, Helene; Glade, Thomas

    2015-04-01

    By now there is a broad consensus that due to human-induced global change the frequency and magnitude of heavy precipitation events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as the most common triggering agent for landslide initiation, also an increased landside activity can be expected there. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled. The present and well known problems in modelling landslide susceptibility and hazard give uncertain results in the prediction. This includes the lack of a universal applicable modelling solution for adequately assessing landslide susceptibility (which can be seen as the relative indication of the spatial probability of landslide initiation). Generally speaking, there are three major approaches for performing landslide susceptibility analysis: heuristic, statistical and deterministic models, all with different assumptions, its distinctive data requirements and differently interpretable outcomes. Still, detailed comparison of resulting landslide susceptibility maps are rare. In this presentation, the susceptibility modelling outputs of a deterministic model (Stability INdex MAPping - SINMAP) and a statistical modelling approach (generalized additive model - GAM) are compared. SINMAP is an infinite slope stability model which requires parameterization of soil mechanical parameters. Modelling with the generalized additive model, which represents a non-linear extension of a generalized linear model, requires a high quality landslide inventory that serves as the dependent variable in the statistical approach. Both methods rely on topographical data derived from the DTM. The comparison has been carried out in a study area located in the district of Waidhofen/Ybbs in Lower Austria. For the whole district (ca. 132 km²), 1063 landslides have been mapped and partially used within the analysis and the validation of the model outputs. The respective

  13. Reprint of "A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping"

    NASA Astrophysics Data System (ADS)

    Crozier, M. J.

    2018-04-01

    Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock. The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity

  14. A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

    PubMed Central

    Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

    2016-01-01

    In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

  15. A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

    PubMed

    Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

    2016-05-11

    In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

  16. Landslide susceptibility and risk assessment: specificities for road networks

    NASA Astrophysics Data System (ADS)

    Pellicani, Roberta; Argentiero, Ilenia; Parisi, Alessandro; Spilotro, Giuseppe

    2017-04-01

    A regional-scale assessment of landslide susceptibility and risk along the main road corridors crossing the provincial territory of Matera (Basilicata Region, Southern Italy) was carried out. The entire provincial road network extends for about 1,320 km through a territory, of which represents the main connection infrastructure among thirty-one municipalities due to the lack of an efficient integrated transportation system through the whole regional territory. For this reason, the strategic importance of these roads consists in their uniqueness in connecting every urban center with the socio-economic surrounding context. These roads and their vehicular traffic are continuously exposed to instability processes (about the 40% of the total length is disrupted by landslides), characterized both by high intensity and low frequency and by low intensity and high frequency. This last typology, consisting in small shallow landslides, is particularly hazardous for the roads since it is widespread along the road network, its occurrence is connected to rainfalls and determines high vulnerability conditions for the road in terms of interruption of vehicular traffic. A GIS-based heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area, by using a polynomial function of eight predisposing factors, weighted according to their influence on the landslide phenomena, recognized and collected in an inventory. Susceptibility associated to small shallow phenomena was assessed by using a polynomial function of specific factors, such as slope angle and aspect, lithological outcrops, rainfalls, etc. In absence of detailed input data, the spatial distribution of landslide risk along the road corridors was assessed and mapped using a qualitative hazard-consequence matrix approach, by which risk is obtained by combining hazard categories with consequence classes pairwise in a two-dimensional table or matrix. Landslide

  17. GIS-based support vector machine modeling of earthquake-triggered landslide susceptibility in the Jianjiang River watershed, China

    NASA Astrophysics Data System (ADS)

    Xu, Chong; Dai, Fuchu; Xu, Xiwei; Lee, Yuan Hsi

    2012-04-01

    Support vector machine (SVM) modeling is based on statistical learning theory. It involves a training phase with associated input and target output values. In recent years, the method has become increasingly popular. The main purpose of this study is to evaluate the mapping power of SVM modeling in earthquake triggered landslide-susceptibility mapping for a section of the Jianjiang River watershed using a Geographic Information System (GIS) software. The river was affected by the Wenchuan earthquake of May 12, 2008. Visual interpretation of colored aerial photographs of 1-m resolution and extensive field surveys provided a detailed landslide inventory map containing 3147 landslides related to the 2008 Wenchuan earthquake. Elevation, slope angle, slope aspect, distance from seismogenic faults, distance from drainages, and lithology were used as the controlling parameters. For modeling, three groups of positive and negative training samples were used in concert with four different kernel functions. Positive training samples include the centroids of 500 large landslides, those of all 3147 landslides, and 5000 randomly selected points in landslide polygons. Negative training samples include 500, 3147, and 5000 randomly selected points on slopes that remained stable during the Wenchuan earthquake. The four kernel functions are linear, polynomial, radial basis, and sigmoid. In total, 12 cases of landslide susceptibility were mapped. Comparative analyses of landslide-susceptibility probability and area relation curves show that both the polynomial and radial basis functions suitably classified the input data as either landslide positive or negative though the radial basis function was more successful. The 12 generated landslide-susceptibility maps were compared with known landslide centroid locations and landslide polygons to verify the success rate and predictive accuracy of each model. The 12 results were further validated using area-under-curve analysis. Group 3 with

  18. Map and map database of susceptibility to slope failure by sliding and earthflow in the Oakland area, California

    USGS Publications Warehouse

    Pike, R.J.; Graymer, R.W.; Roberts, Sebastian; Kalman, N.B.; Sobieszczyk, Steven

    2001-01-01

    Map data that predict the varying likelihood of landsliding can help public agencies make informed decisions on land use and zoning. This map, prepared in a geographic information system from a statistical model, estimates the relative likelihood of local slopes to fail by two processes common to an area of diverse geology, terrain, and land use centered on metropolitan Oakland. The model combines the following spatial data: (1) 120 bedrock and surficial geologic-map units, (2) ground slope calculated from a 30-m digital elevation model, (3) an inventory of 6,714 old landslide deposits (not distinguished by age or type of movement and excluding debris flows), and (4) the locations of 1,192 post-1970 landslides that damaged the built environment. The resulting index of likelihood, or susceptibility, plotted as a 1:50,000-scale map, is computed as a continuous variable over a large area (872 km2) at a comparatively fine (30 m) resolution. This new model complements landslide inventories by estimating susceptibility between existing landslide deposits, and improves upon prior susceptibility maps by quantifying the degree of susceptibility within those deposits. Susceptibility is defined for each geologic-map unit as the spatial frequency (areal percentage) of terrain occupied by old landslide deposits, adjusted locally by steepness of the topography. Susceptibility of terrain between the old landslide deposits is read directly from a slope histogram for each geologic-map unit, as the percentage (0.00 to 0.90) of 30-m cells in each one-degree slope interval that coincides with the deposits. Susceptibility within landslide deposits (0.00 to 1.33) is this same percentage raised by a multiplier (1.33) derived from the comparative frequency of recent failures within and outside the old deposits. Positive results from two evaluations of the model encourage its extension to the 10-county San Francisco Bay region and elsewhere. A similar map could be prepared for any area

  19. Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

    NASA Astrophysics Data System (ADS)

    Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

    2017-12-01

    Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall

  20. A Geomorphological Approach To Landslide Susceptibility Assessment and Its Application To The Virginio River Basin

    NASA Astrophysics Data System (ADS)

    Casagli, N.; Catani, F.; Delmonaco, G.; Ermini, L.; Margottini, C.; Puglisi, C.

    The present note presents the results of a research project aimed at developing a ge- omorphology based method for the assessment of landslide susceptibility. The work has been carried out in the Virginio River basin, a tributary of the Arno river with confluence located 20 km downstream from Florence (Italy). Starting from a detailed landslide inventory, essentially carried out by aerial-photograph survey, the first phase of the research was directed to geomorphic field investigations, aimed at determining those hillslope factors influencing landslide triggering. This analysis was carried out for a significant sub-sample of the inventoried landslides, allowing the distinction of the most relevant hillslope factors affecting each type of mass movement. Selected factors are a) the past slope gradient in which landslide originated, b) litology and 3) land use. Once defined as thematic vector data, these factors have been handled by GIS overlay mapping, allowing to single out, for the entire Virginio River basin, homogeneous domains (Unique Condition Units) that contain, for each landslide ty- pology, unique combinations of the selected hillslope factors. Those domains are the basic Terrain Units for the following phase of landslide susceptibility assessment and mapping. The hillslope factors not selected in the first phase, however playing an im- portant role in contributing to the activation of the mass movements, have been taken into account for the definition of a landslide susceptibility function. This function is es- sentially a logic function based on the presence/absence of preparatory factors within the previous selected Unique Condition Terrain Units. The final mapping of the ar- eas characterized by different landslide susceptibility levels was performed by vector and raster based GIS techniques on the basis of the number and rank of predisposing factors. These landslide susceptibility classes, defined by a logic and easily replicable function, can be

  1. Rainfall-induced Landslide Susceptibility assessment at the Longnan county

    NASA Astrophysics Data System (ADS)

    Hong, Haoyuan; Zhang, Ying

    2017-04-01

    Landslides are a serious disaster in Longnan county, China. Therefore landslide susceptibility assessment is useful tool for government or decision making. The main objective of this study is to investigate and compare the frequency ratio, support vector machines, and logistic regression. The Longnan county (Jiangxi province, China) was selected as the case study. First, the landslide inventory map with 354 landslide locations was constructed. Then landslide locations were then randomly divided into a ratio of 70/30 for the training and validating the models. Second, fourteen landslide conditioning factors were prepared such as slope, aspect, altitude, topographic wetness index (TWI), stream power index (SPI), sediment transport index (STI), plan curvature, lithology, distance to faults, distance to rivers, distance to roads, land use, normalized difference vegetation index (NDVI), and rainfall. Using the frequency ratio, support vector machines, and logistic regression, a total of three landslide susceptibility models were constructed. Finally, the overall performance of the resulting models was assessed and compared using the Receiver operating characteristic (ROC) curve technique. The result showed that the support vector machines model is the best model in the study area. The success rate is 88.39 %; and prediction rate is 84.06 %.

  2. Climate-physiographically differentiated Pan-European landslide susceptibility assessment using spatial multi-criteria evaluation and transnational landslide information

    NASA Astrophysics Data System (ADS)

    Günther, Andreas; Van Den Eeckhaut, Miet; Malet, Jean-Philippe; Reichenbach, Paola; Hervás, Javier

    2014-11-01

    With the adoption of the EU Thematic Strategy for Soil Protection in 2006, small-scale (1:1 M) assessments of threats affecting soils over Europe received increasing attention. As landslides have been recognized as one of eight threats requiring a Pan-European evaluation, we present an approach for landslide susceptibility evaluation at the continental scale over Europe. Unlike previous continental and global scale landslide susceptibility studies not utilizing spatial information on the events, we collected more than 102,000 landslide locations in 22 European countries. These landslides are heterogeneously distributed over Europe, but are indispensable for the evaluation and classification of Pan-European datasets used as spatial predictors, and the validation of the resulting assessments. For the analysis we subdivided the European territory into seven different climate-physiographical zones by combining morphometric and climatic data for terrain differentiation, and adding a coastal zone defined as a 1 km strip inland from the coastline. Landslide susceptibility modeling was performed for each zone using heuristic spatial multicriteria evaluations supported by analytical hierarchy processes, and validated with the inventory data using the receiver operating characteristics. In contrast to purely data-driven statistical modeling techniques, our semi-quantitative approach is capable to introduce expert knowledge into the analysis, which is indispensable considering quality and resolution of the input data, and incompleteness and bias in the inventory information. The reliability of the resulting susceptibility map ELSUS 1000 Version 1 (1 km resolution) was examined on an administrative terrain unit level in areas with landslide information and through the comparison with available national susceptibility zonations. These evaluations suggest that although the ELSUS 1000 is capable for a correct synoptic prediction of landslide susceptibility in the majority of the

  3. Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

    NASA Astrophysics Data System (ADS)

    Yusof, Norbazlan M.; Pradhan, Biswajeet

    2014-06-01

    PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for data

  4. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan.

    PubMed

    Dou, Jie; Tien Bui, Dieu; Yunus, Ali P; Jia, Kun; Song, Xuan; Revhaug, Inge; Xia, Huan; Zhu, Zhongfan

    2015-01-01

    This paper assesses the potentiality of certainty factor models (CF) for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED) was split into two subsets: (i) 70% of the landslides in the inventory to be used for building the CF based model; (ii) 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI) and logistic regression (LR) models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC). The result shows that the area under the ROC curve (AUC) for the LR model (AUC = 0.817) is slightly higher than those obtained from the SI model (AUC = 0.801). Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner.

  5. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan

    PubMed Central

    Dou, Jie; Tien Bui, Dieu; P. Yunus, Ali; Jia, Kun; Song, Xuan; Revhaug, Inge; Xia, Huan; Zhu, Zhongfan

    2015-01-01

    This paper assesses the potentiality of certainty factor models (CF) for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED) was split into two subsets: (i) 70% of the landslides in the inventory to be used for building the CF based model; (ii) 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI) and logistic regression (LR) models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC). The result shows that the area under the ROC curve (AUC) for the LR model (AUC = 0.817) is slightly higher than those obtained from the SI model (AUC = 0.801). Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner. PMID:26214691

  6. Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

    NASA Astrophysics Data System (ADS)

    Hong, H.; Zhu, A. X.

    2017-12-01

    Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic

  7. The contribution of PSInSAR interferometry to landslide susceptibility assessment in weak rock-dominated areas

    NASA Astrophysics Data System (ADS)

    Oliveira, Sérgio C.; Zêzere, José L.; Catalão, João; Nico, Giovanni

    2015-04-01

    In the Grande da Pipa river basin (north of Lisbon, Portugal), 64% of the landslides inventoried occur on a particular weak rock lithological unit composed by clay and with sandstone intercalations, that is present in 58% of the study (Oliveira et al., 2014). Deep-seated slow moving rotational slides occur essentially on this lithological unit and are responsible for the major damages verified along roads and buildings in the study area. Within this context, landslide hazard assessment, is limited by two major constrains: (i) the slope instability signs may not be sufficiently clear and observable and consequently may not be correctly identifiable through traditional geomorphologic survey techniques and (ii) the non-timely recognition of precursor signs of instability both in landslides activated for the first time and in previously landslide-affected areas (landslide reactivation). To encompass these limitations, the Persistent Scatterer synthetic aperture radar interferometry technique is applied to a data set of 16 TerraSAR-X SAR images, from April of 2010 to March of 2011, available for a small test site of 12.5 square kilometers (Laje-Salema) located on south-central part of the study area. This work's specific objectives are the following: (i) to evaluate the capacity of the Persistent Scatterer displacement maps in assessing landslide susceptibility at the regional scale, and (ii) to assess the capacity of landslide susceptibility maps based on historical landslide inventories to predict the location of actual terrain displacement measured by the Persistent Scatterers technique. Landslide susceptibility was assessed for the test site using the Information Value bivariate statistical method and the susceptibility scores were exported to the Grande da Pipa river basin. The independent validation of the landslide susceptibility maps was made using the historical landslide inventory and the Persistent Scatterer displacement map. Results are compared by computing

  8. Landslide susceptibility and early warning model for shallow landslide in Taiwan

    NASA Astrophysics Data System (ADS)

    Huang, Chun-Ming; Wei, Lun-Wei; Chi, Chun-Chi; Chang, Kan-Tsun; Lee, Chyi-Tyi

    2017-04-01

    This study aims to development a regional susceptibility model and warning threshold as well as the establishment of early warning system in order to prevent and reduce the losses caused by rainfall-induced shallow landslides in Taiwan. For the purpose of practical application, Taiwan is divided into nearly 185,000 slope units. The susceptibility and warning threshold of each slope unit were analyzed as basic information for disaster prevention. The geological characteristics, mechanism and the occurrence time of landslides were recorded for more than 900 cases through field investigation and interview of residents in order to discuss the relationship between landslides and rainfall. Logistic regression analysis was performed to evaluate the landslide susceptibility and an I3-R24 rainfall threshold model was proposed for the early warning of landslides. The validations of recent landslide cases show that the model was suitable for the warning of regional shallow landslide and most of the cases can be warned 3 to 6 hours in advanced. We also propose a slope unit area weighted method to establish local rainfall threshold on landslide for vulnerable villages in order to improve the practical application. Validations of the local rainfall threshold also show a good agreement to the occurrence time reported by newspapers. Finally, a web based "Rainfall-induced Landslide Early Warning System" is built and connected to real-time radar rainfall data so that landslide real-time warning can be achieved. Keywords: landslide, susceptibility analysis, rainfall threshold

  9. Shallow-landslide hazard map of Seattle, Washington

    USGS Publications Warehouse

    Harp, Edwin L.; Michael, John A.; Laprade, William T.

    2006-01-01

    Landslides, particularly debris flows, have long been a significant cause of damage and destruction to people and property in the Puget Sound region. Following the years of 1996 and 1997, the Federal Emergency Management Agency (FEMA) designated Seattle as a 'Project Impact' city with the goal of encouraging the city to become more disaster resistant to the effects of landslides and other natural hazards. A major recommendation of the Project Impact council was that the city and the U.S. Geological Survey (USGS) collaborate to produce a landslide hazard map of the city. An exceptional data set archived by the city, containing more than 100 years of landslide data from severe storm events, allowed comparison of actual landslide locations with those predicted by slope-stability modeling. We used an infinite-slope analysis, which models slope segments as rigid friction blocks, to estimate the susceptibility of slopes to shallow landslides which often mobilize into debris flows, water-laden slurries that can form from shallow failures of soil and weathered bedrock, and can travel at high velocities down steep slopes. Data used for analysis consisted of a digital slope map derived from recent Light Detection and Ranging (LIDAR) imagery of Seattle, recent digital geologic mapping, and shear-strength test data for the geologic units in the surrounding area. The combination of these data layers within a Geographic Information System (GIS) platform allowed the preparation of a shallow landslide hazard map for the entire city of Seattle.

  10. Landslides susceptibility change over time according to terrain conditions in a mountain area of the tropic region.

    PubMed

    Pineda, M C; Viloria, J; Martínez-Casasnovas, J A

    2016-04-01

    Susceptibility to landslides in mountain areas results from the interaction of various factors related to relief formation and soil development. The assessment of landslide susceptibility has generally taken into account individual events, or it has been aimed at establishing relationships between landslide-inventory maps and maps of environmental factors, without considering that such relationships can change in space and time. In this work, temporal and space changes in landslides were analysed in six different combinations of date and geomorphological conditions, including two different geological units, in a mountainous area in the north-centre of Venezuela, in northern South America. Landslide inventories from different years were compared with a number of environmental factors by means of logistic regression analysis. The resulting equations predicted landslide susceptibility from a range of geomorphometric parameters and a vegetation index, with diverse accuracy, in the study area. The variation of the obtained models and their prediction accuracy between geological units and dates suggests that the complexity of the landslide processes and their explanatory factors changed over space and time in the studied area. This calls into question the use of a single model to evaluate landslide susceptibility over large regions.

  11. Landslide susceptibility analysis with logistic regression model based on FCM sampling strategy

    NASA Astrophysics Data System (ADS)

    Wang, Liang-Jie; Sawada, Kazuhide; Moriguchi, Shuji

    2013-08-01

    Several mathematical models are used to predict the spatial distribution characteristics of landslides to mitigate damage caused by landslide disasters. Although some studies have achieved excellent results around the world, few studies take the inter-relationship of the selected points (training points) into account. In this paper, we present the Fuzzy c-means (FCM) algorithm as an optimal method for choosing the appropriate input landslide points as training data. Based on different combinations of the Fuzzy exponent (m) and the number of clusters (c), five groups of sampling points were derived from formal seed cells points and applied to analyze the landslide susceptibility in Mizunami City, Gifu Prefecture, Japan. A logistic regression model is applied to create the models of the relationships between landslide-conditioning factors and landslide occurrence. The pre-existing landslide bodies and the area under the relative operative characteristic (ROC) curve were used to evaluate the performance of all the models with different m and c. The results revealed that Model no. 4 (m=1.9, c=4) and Model no. 5 (m=1.9, c=5) have significantly high classification accuracies, i.e., 90.0%. Moreover, over 30% of the landslide bodies were grouped under the very high susceptibility zone. Otherwise, Model no. 4 and Model no. 5 had higher area under the ROC curve (AUC) values, which were 0.78 and 0.79, respectively. Therefore, Model no. 4 and Model no. 5 offer better model results for landslide susceptibility mapping. Maps derived from Model no. 4 and Model no. 5 would offer the local authorities crucial information for city planning and development.

  12. Spatial Resolution Effects of Digital Terrain Models on Landslide Susceptibility Analysis

    NASA Astrophysics Data System (ADS)

    Chang, K. T.; Dou, J.; Chang, Y.; Kuo, C. P.; Xu, K. M.; Liu, J. K.

    2016-06-01

    The purposes of this study are to identify the maximum number of correlated factors for landslide susceptibility mapping and to evaluate landslide susceptibility at Sihjhong river catchment in the southern Taiwan, integrating two techniques, namely certainty factor (CF) and artificial neural network (ANN). The landslide inventory data of the Central Geological Survey (CGS, MOEA) in 2004-2014 and two digital elevation model (DEM) datasets including a 5-meter LiDAR DEM and a 30-meter Aster DEM were prepared. We collected thirteen possible landslide-conditioning factors. Considering the multi-collinearity and factor redundancy, we applied the CF approach to optimize these thirteen conditioning factors. We hypothesize that if the CF values of the thematic factor layers are positive, it implies that these conditioning factors have a positive relationship with the landslide occurrence. Therefore, based on this assumption and positive CF values, seven conditioning factors including slope angle, slope aspect, elevation, terrain roughness index (TRI), terrain position index (TPI), total curvature, and lithology have been selected for further analysis. The results showed that the optimized-factors model provides a better accuracy for predicting landslide susceptibility in the study area. In conclusion, the optimized-factors model is suggested for selecting relative factors of landslide occurrence.

  13. Propagation of landslide inventory errors on data driven landslide susceptibility models

    NASA Astrophysics Data System (ADS)

    Henriques, C. S.; Zezere, J. L.; Neves, M.; Garcia, R. A. C.; Oliveira, S. C.; Piedade, A.

    2009-04-01

    Research on landslide susceptibility assessment developed recently worldwide has shown that quality and reliability of modelling results are more sensitive to the quality and consistence of the cartographic database than to statistical tools used in the modelling process. Particularly, the quality of the landslide inventory is of crucial importance, because data-driven models used for landside susceptibility evaluation are based on the spatial correlation between past landslide occurrences and a data set of thematic layers representing independent landslide predisposing factors. Uncertainty within landslide inventorying may be very high and is usually related to: (i) the geological and geomorphological complexity of the study area; (ii) the dominant land use and the rhythm and magnitude of land use change; (iii) the conservation level of landslide evidences (e.g., topography, vegetation, drainage) both in the field and aerial photographs; and (iv) the experience of the geomorphologist(s) that build the landslide inventory. Traditionally, landslide inventory has been made through aerial-photo interpretation and field work surveying by using standard geomorphological techniques. More recently, the interpretation of detailed geo-referenced digital ortophotomaps (pixel = 0.5 m), combined with the accurate topography, as become an additional analytical tool for landslide identification at the regional scale. The present study was performed in a test site (256 km2) within Caldas da Rainha County, located in the central part of Portugal. Detailed geo-referenced digital ortophotomaps obtained in 2004 were used to build three different landslide inventories. The landslide inventory #1 was constructed by a single regular trained geomorphologist using photo-interpretation. 408 probable slope movements were identified and geo-referenced by a point marked in the central part of the probable landslide rupture zone. The landslide inventory #2 was obtained through the examination

  14. Spatially explicit shallow landslide susceptibility mapping over large areas

    Treesearch

    Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

  15. Improving Landslide Susceptibility Modeling Using an Empirical Threshold Scheme for Excluding Landslide Deposition

    NASA Astrophysics Data System (ADS)

    Tsai, F.; Lai, J. S.; Chiang, S. H.

    2015-12-01

    Landslides are frequently triggered by typhoons and earthquakes in Taiwan, causing serious economic losses and human casualties. Remotely sensed images and geo-spatial data consisting of land-cover and environmental information have been widely used for producing landslide inventories and causative factors for slope stability analysis. Landslide susceptibility, on the other hand, can represent the spatial likelihood of landslide occurrence and is an important basis for landslide risk assessment. As multi-temporal satellite images become popular and affordable, they are commonly used to generate landslide inventories for subsequent analysis. However, it is usually difficult to distinguish different landslide sub-regions (scarp, debris flow, deposition etc.) directly from remote sensing imagery. Consequently, the extracted landslide extents using image-based visual interpretation and automatic detections may contain many depositions that may reduce the fidelity of the landslide susceptibility model. This study developed an empirical thresholding scheme based on terrain characteristics for eliminating depositions from detected landslide areas to improve landslide susceptibility modeling. In this study, Bayesian network classifier is utilized to build a landslide susceptibility model and to predict sequent rainfall-induced shallow landslides in the Shimen reservoir watershed located in northern Taiwan. Eleven causative factors are considered, including terrain slope, aspect, curvature, elevation, geology, land-use, NDVI, soil, distance to fault, river and road. Landslide areas detected using satellite images acquired before and after eight typhoons between 2004 to 2008 are collected as the main inventory for training and verification. In the analysis, previous landslide events are used as training data to predict the samples of the next event. The results are then compared with recorded landslide areas in the inventory to evaluate the accuracy. Experimental results

  16. Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

    USGS Publications Warehouse

    McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

    2008-01-01

    Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

  17. Landslide susceptibility in the Tully Valley area, Finger Lakes region, New York

    USGS Publications Warehouse

    Jager, Stefan; Wieczorek, Gerald E.

    1994-01-01

    As a consequence of a large landslide in the Tully Valley, Onondaga County, New York, an investigation was undertaken to determine the factors responsible for the landslide in order to develop a model for regional landslide susceptibility. The April 27, 1993 Tully Valley landslide occurred within glacial lake clays overlain by till and colluvium on gentle slopes of 9-12 degrees. The landslide was triggered by extreme climatic events of prolonged heavy rainfall combined with rapid melting of a winter snowpack. A photoinventory and field checking of landslides within a 415 km2 study area, including the Tully Valley, revealed small recently-active landslides and other large dormant prehistoric landslides, probably Pleistocene in age. Similar to the larger Tully Valley landslide, the smaller recently-active landslides occurred in red, glacial lake clays very likely triggered by seasonal rainfall. The large dormant landslides have been stable for long periods as evidenced by slope denudational processes that have modified the landslides. These old and ancient landslides correspond with proglacial lake levels during the Pleistocene, suggesting that either inundation or rapid drainage was responsible for triggering these landslides. A logistic regression analysis was performed within a Geographic Information System (GIS) environment to develop a model of landslide susceptibility for the Tully Valley study area. Presence of glacial clays, slope angle, and glacial lake levels were used as explanatory variables for landslide incidence. The spatial probability of landsliding, categorized as low, moderate and high, is portrayed within 90-m square cells on the susceptibility map.

  18. Analysis of training sample selection strategies for regression-based quantitative landslide susceptibility mapping methods

    NASA Astrophysics Data System (ADS)

    Erener, Arzu; Sivas, A. Abdullah; Selcuk-Kestel, A. Sevtap; Düzgün, H. Sebnem

    2017-07-01

    All of the quantitative landslide susceptibility mapping (QLSM) methods requires two basic data types, namely, landslide inventory and factors that influence landslide occurrence (landslide influencing factors, LIF). Depending on type of landslides, nature of triggers and LIF, accuracy of the QLSM methods differs. Moreover, how to balance the number of 0 (nonoccurrence) and 1 (occurrence) in the training set obtained from the landslide inventory and how to select which one of the 1's and 0's to be included in QLSM models play critical role in the accuracy of the QLSM. Although performance of various QLSM methods is largely investigated in the literature, the challenge of training set construction is not adequately investigated for the QLSM methods. In order to tackle this challenge, in this study three different training set selection strategies along with the original data set is used for testing the performance of three different regression methods namely Logistic Regression (LR), Bayesian Logistic Regression (BLR) and Fuzzy Logistic Regression (FLR). The first sampling strategy is proportional random sampling (PRS), which takes into account a weighted selection of landslide occurrences in the sample set. The second method, namely non-selective nearby sampling (NNS), includes randomly selected sites and their surrounding neighboring points at certain preselected distances to include the impact of clustering. Selective nearby sampling (SNS) is the third method, which concentrates on the group of 1's and their surrounding neighborhood. A randomly selected group of landslide sites and their neighborhood are considered in the analyses similar to NNS parameters. It is found that LR-PRS, FLR-PRS and BLR-Whole Data set-ups, with order, yield the best fits among the other alternatives. The results indicate that in QLSM based on regression models, avoidance of spatial correlation in the data set is critical for the model's performance.

  19. Shallow landslide hazard map of Seattle, Washington

    USGS Publications Warehouse

    Harp, Edwin L.; Michael, John A.; Laprade, William T.

    2008-01-01

    Landslides, particularly debris flows, have long been a significant cause of damage and destruction to people and property in the Puget Sound region. Following the years of 1996 and 1997, the Federal Emergency Management Agency designated Seattle as a “Project Impact” city with the goal of encouraging the city to become more disaster resistant to landslides and other natural hazards. A major recommendation of the Project Impact council was that the city and the U.S. Geological Survey collaborate to produce a landslide hazard map. An exceptional data set archived by the city containing more than 100 yr of landslide data from severe storm events allowed comparison of actual landslide locations with those predicted by slope-stability modeling. We used an infinite-slope analysis, which models slope segments as rigid friction blocks, to estimate the susceptibility of slopes to debris flows, which are water-laden slurries that can form from shallow failures of soil and weathered bedrock and can travel at high velocities down steep slopes. Data used for the analysis consisted of a digital slope map derived from recent light detection and ranging (LiDAR) imagery of Seattle, recent digital geologic mapping of the city, and shear-strength test data for the geologic units found in the surrounding area. The combination of these data layers within a geographic information system (GIS) platform allowed us to create a shallow landslide hazard map for Seattle.

  20. Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

    NASA Astrophysics Data System (ADS)

    Duman, T. Y.; Can, T.; Gokceoglu, C.; Nefeslioglu, H. A.; Sonmez, H.

    2006-11-01

    As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas.

  1. Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods

    NASA Astrophysics Data System (ADS)

    Pourghasemi, Hamid Reza; Rossi, Mauro

    2017-10-01

    Landslides are identified as one of the most important natural hazards in many areas throughout the world. The essential purpose of this study is to compare general linear model (GLM), general additive model (GAM), multivariate adaptive regression spline (MARS), and modified analytical hierarchy process (M-AHP) models and assessment of their performances for landslide susceptibility modeling in the west of Mazandaran Province, Iran. First, landslides were identified by interpreting aerial photographs, and extensive field works. In total, 153 landslides were identified in the study area. Among these, 105 landslides were randomly selected as training data (i.e. used in the models training) and the remaining 48 (30 %) cases were used for the validation (i.e. used in the models validation). Afterward, based on a deep literature review on 220 scientific papers (period between 2005 and 2012), eleven conditioning factors including lithology, land use, distance from rivers, distance from roads, distance from faults, slope angle, slope aspect, altitude, topographic wetness index (TWI), plan curvature, and profile curvature were selected. The Certainty Factor (CF) model was used for managing uncertainty in rule-based systems and evaluation of the correlation between the dependent (landslides) and independent variables. Finally, the landslide susceptibility zonation was produced using GLM, GAM, MARS, and M-AHP models. For evaluation of the models, the area under the curve (AUC) method was used and both success and prediction rate curves were calculated. The evaluation of models for GLM, GAM, and MARS showed 90.50, 88.90, and 82.10 % for training data and 77.52, 70.49, and 78.17 % for validation data, respectively. Furthermore, The AUC value of the produced landslide susceptibility map using M-AHP showed a training value of 77.82 % and validation value of 82.77 % accuracy. Based on the overall assessments, the proposed approaches showed reasonable results for landslide

  2. Comparative analysis of rainfall and landslide damage for landslide susceptibility zonation

    NASA Astrophysics Data System (ADS)

    Petrucci, O.; Pasqua, A. A.

    2009-04-01

    In the present work we applied a methodology tested in previous works to a regional sector of Calabria (Southern Italy), aiming to obtain a zonation of this area according to the susceptibility to develop landslides, as inferred from the combined analysis of past landslide events and cumulate rainfall which triggered them. The complete series of both historical landslides and daily rainfall have been organised in two databases. For each landslide event, damage, mainly defined in relation to the reimbursement requests sent to the Department of Public Works, has been quantified using a procedure based on a Local Damage Index. Rainfall has been described by the Maximum Return Period of cumulative rainfall recorded during the landslide events. Damage index and population density, presumed to represent the location of vulnerable elements, have been referred to Thiessen polygons associated to rain gauges working at the time of the event. The procedure allowed us to carry out a classification of the polygons composing the study area according to their susceptibility to damage during DHEs. In high susceptibility polygons, severe damage occurs during rainfall characterised by low return periods; in medium susceptibility polygons, maximum return period rainfall and induced damage show equal levels of exceptionality; in low susceptibility polygons, high return period rainfall induces a low level of damage. The results can prove useful in establishing civil defence plans, emergency management, and prioritizing hazard mitigation measures.

  3. Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera

    NASA Astrophysics Data System (ADS)

    Sdao, F.; Lioi, D. S.; Pascale, S.; Caniani, D.; Mancini, I. M.

    2013-02-01

    The complete assessment of landslide susceptibility needs uniformly distributed detailed information on the territory. This information, which is related to the temporal occurrence of landslide phenomena and their causes, is often fragmented and heterogeneous. The present study evaluates the landslide susceptibility map of the Natural Archaeological Park of Matera (Southern Italy) (Sassi and area Rupestrian Churches sites). The assessment of the degree of "spatial hazard" or "susceptibility" was carried out by the spatial prediction regardless of the return time of the events. The evaluation model for the susceptibility presented in this paper is very focused on the use of innovative techniques of artificial intelligence such as Neural Network, Fuzzy Logic and Neuro-fuzzy Network. The method described in this paper is a novel technique based on a neuro-fuzzy system. It is able to train data like neural network and it is able to shape and control uncertain and complex systems like a fuzzy system. This methodology allows us to derive susceptibility maps of the study area. These data are obtained from thematic maps representing the parameters responsible for the instability of the slopes. The parameters used in the analysis are: plan curvature, elevation (DEM), angle and aspect of the slope, lithology, fracture density, kinematic hazard index of planar and wedge sliding and toppling. Moreover, this method is characterized by the network training which uses a training matrix, consisting of input and output training data, which determine the landslide susceptibility. The neuro-fuzzy method was integrated to a sensitivity analysis in order to overcome the uncertainty linked to the used membership functions. The method was compared to the landslide inventory map and was validated by applying three methods: a ROC (Receiver Operating Characteristic) analysis, a confusion matrix and a SCAI method. The developed neuro-fuzzy method showed a good performance in the

  4. Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

    NASA Astrophysics Data System (ADS)

    Ceppi, C.; Mancini, F.; Ritrovato, G.

    2009-04-01

    This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was

  5. Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models

    NASA Astrophysics Data System (ADS)

    Hong, Haoyuan; Pourghasemi, Hamid Reza; Pourtaghi, Zohre Sadat

    2016-04-01

    Landslides are an important natural hazard that causes a great amount of damage around the world every year, especially during the rainy season. The Lianhua area is located in the middle of China's southern mountainous area, west of Jiangxi Province, and is known to be an area prone to landslides. The aim of this study was to evaluate and compare landslide susceptibility maps produced using the random forest (RF) data mining technique with those produced by bivariate (evidential belief function and frequency ratio) and multivariate (logistic regression) statistical models for Lianhua County, China. First, a landslide inventory map was prepared using aerial photograph interpretation, satellite images, and extensive field surveys. In total, 163 landslide events were recognized in the study area, with 114 landslides (70%) used for training and 49 landslides (30%) used for validation. Next, the landslide conditioning factors-including the slope angle, altitude, slope aspect, topographic wetness index (TWI), slope-length (LS), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, annual precipitation, land use, normalized difference vegetation index (NDVI), and lithology-were derived from the spatial database. Finally, the landslide susceptibility maps of Lianhua County were generated in ArcGIS 10.1 based on the random forest (RF), evidential belief function (EBF), frequency ratio (FR), and logistic regression (LR) approaches and were validated using a receiver operating characteristic (ROC) curve. The ROC plot assessment results showed that for landslide susceptibility maps produced using the EBF, FR, LR, and RF models, the area under the curve (AUC) values were 0.8122, 0.8134, 0.7751, and 0.7172, respectively. Therefore, we can conclude that all four models have an AUC of more than 0.70 and can be used in landslide susceptibility mapping in the study area; meanwhile, the EBF and FR models had the best performance for Lianhua

  6. Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods

    NASA Astrophysics Data System (ADS)

    Lee, Jung-Hyun; Sameen, Maher Ibrahim; Pradhan, Biswajeet; Park, Hyuck-Jin

    2018-02-01

    This study evaluated the generalizability of five models to select a suitable approach for landslide susceptibility modeling in data-scarce environments. In total, 418 landslide inventories and 18 landslide conditioning factors were analyzed. Multicollinearity and factor optimization were investigated before data modeling, and two experiments were then conducted. In each experiment, five susceptibility maps were produced based on support vector machine (SVM), random forest (RF), weight-of-evidence (WoE), ridge regression (Rid_R), and robust regression (RR) models. The highest accuracy (AUC = 0.85) was achieved with the SVM model when either the full or limited landslide inventories were used. Furthermore, the RF and WoE models were severely affected when less landslide samples were used for training. The other models were affected slightly when the training samples were limited.

  7. Assessment of landslide distribution map reliability in Niigata prefecture - Japan using frequency ratio approach

    NASA Astrophysics Data System (ADS)

    Rahardianto, Trias; Saputra, Aditya; Gomez, Christopher

    2017-07-01

    Research on landslide susceptibility has evolved rapidly over the few last decades thanks to the availability of large databases. Landslide research used to be focused on discreet events but the usage of large inventory dataset has become a central pillar of landslide susceptibility, hazard, and risk assessment. Indeed, extracting meaningful information from the large database is now at the forth of geoscientific research, following the big-data research trend. Indeed, the more comprehensive information of the past landslide available in a particular area is, the better the produced map will be, in order to support the effective decision making, planning, and engineering practice. The landslide inventory data which is freely accessible online gives an opportunity for many researchers and decision makers to prevent casualties and economic loss caused by future landslides. This data is advantageous especially for areas with poor landslide historical data. Since the construction criteria of landslide inventory map and its quality evaluation remain poorly defined, the assessment of open source landslide inventory map reliability is required. The present contribution aims to assess the reliability of open-source landslide inventory data based on the particular topographical setting of the observed area in Niigata prefecture, Japan. Geographic Information System (GIS) platform and statistical approach are applied to analyze the data. Frequency ratio method is utilized to model and assess the landslide map. The outcomes of the generated model showed unsatisfactory results with AUC value of 0.603 indicate the low prediction accuracy and unreliability of the model.

  8. Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)

    NASA Astrophysics Data System (ADS)

    Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele

    2015-11-01

    The aim of this work is to define reliable susceptibility models for shallow landslides using Logistic Regression and Random Forests multivariate statistical techniques. The study area, located in North-East Sicily, was hit on October 1st 2009 by a severe rainstorm (225 mm of cumulative rainfall in 7 h) which caused flash floods and more than 1000 landslides. Several small villages, such as Giampilieri, were hit with 31 fatalities, 6 missing persons and damage to buildings and transportation infrastructures. Landslides, mainly types such as earth and debris translational slides evolving into debris flows, were triggered on steep slopes and involved colluvium and regolith materials which cover the underlying metamorphic bedrock. The work has been carried out with the following steps: i) realization of a detailed event landslide inventory map through field surveys coupled with observation of high resolution aerial colour orthophoto; ii) identification of landslide source areas; iii) data preparation of landslide controlling factors and descriptive statistics based on a bivariate method (Frequency Ratio) to get an initial overview on existing relationships between causative factors and shallow landslide source areas; iv) choice of criteria for the selection and sizing of the mapping unit; v) implementation of 5 multivariate statistical susceptibility models based on Logistic Regression and Random Forests techniques and focused on landslide source areas; vi) evaluation of the influence of sample size and type of sampling on results and performance of the models; vii) evaluation of the predictive capabilities of the models using ROC curve, AUC and contingency tables; viii) comparison of model results and obtained susceptibility maps; and ix) analysis of temporal variation of landslide susceptibility related to input parameter changes. Models based on Logistic Regression and Random Forests have demonstrated excellent predictive capabilities. Land use and wildfire

  9. The propagation of inventory-based positional errors into statistical landslide susceptibility models

    NASA Astrophysics Data System (ADS)

    Steger, Stefan; Brenning, Alexander; Bell, Rainer; Glade, Thomas

    2016-12-01

    There is unanimous agreement that a precise spatial representation of past landslide occurrences is a prerequisite to produce high quality statistical landslide susceptibility models. Even though perfectly accurate landslide inventories rarely exist, investigations of how landslide inventory-based errors propagate into subsequent statistical landslide susceptibility models are scarce. The main objective of this research was to systematically examine whether and how inventory-based positional inaccuracies of different magnitudes influence modelled relationships, validation results, variable importance and the visual appearance of landslide susceptibility maps. The study was conducted for a landslide-prone site located in the districts of Amstetten and Waidhofen an der Ybbs, eastern Austria, where an earth-slide point inventory was available. The methodological approach comprised an artificial introduction of inventory-based positional errors into the present landslide data set and an in-depth evaluation of subsequent modelling results. Positional errors were introduced by artificially changing the original landslide position by a mean distance of 5, 10, 20, 50 and 120 m. The resulting differently precise response variables were separately used to train logistic regression models. Odds ratios of predictor variables provided insights into modelled relationships. Cross-validation and spatial cross-validation enabled an assessment of predictive performances and permutation-based variable importance. All analyses were additionally carried out with synthetically generated data sets to further verify the findings under rather controlled conditions. The results revealed that an increasing positional inventory-based error was generally related to increasing distortions of modelling and validation results. However, the findings also highlighted that interdependencies between inventory-based spatial inaccuracies and statistical landslide susceptibility models are complex. The

  10. Susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, Mexico

    NASA Astrophysics Data System (ADS)

    Legorreta Paulin, G.; Bursik, M. I.; Lugo Hubp, J.; Paredes Mejía, L.; Aceves Quesada, F.

    2013-12-01

    In volcanic terrains, dormant stratovolcanoes are very common and can trigger landslides and debris flows continually along stream systems, thereby affecting human settlements and economic activities. It is important to assess their potential impact and damage through the use of landslide inventory maps and landslide models. This poster provides an overview of the on-going research project (Grant SEP-CONACYT no 167495) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory and produce a landslide susceptibility map by using Geographic Information Systems (GIS). The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 5.2 km2 with elevations ranging from 2676.79 to 4248.2 m a.s.l. and hillslopes between 5° and 56°. The stream system of Río El Estado catchment erodes Tertiary and Quaternary lavas, pyroclastic flows, and fall deposits. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The method encompasses two main levels of analysis to assess landslide susceptibility. The first level builds a historic landslide inventory. In the study area, an inventory of more than 100 landslides was mapped from interpretation of multi-temporal aerial orthophotographs and local field surveys to assess and describe landslide distribution. All landslides were digitized into a GIS, and the spatial geo-database of landslides was constructed from standardized GIS datasets. The second level calculates the susceptibility for the watershed. Multiple Logistic Regression (MLR) was used to examine the relationship between landsliding and several independent variables (elevation, slope, terrain curvature, flow direction, saturation, contributing area, land use, and geology

  11. Combine bivariate statistics analysis and multivariate statistics analysis to assess landslide susceptibility in Chen-Yu-Lan watershed, Nantou, Taiwan.

    NASA Astrophysics Data System (ADS)

    Ngan Nguyen, Thi To; Liu, Cheng-Chien

    2013-04-01

    How landslides occurred and which factors triggered and sped up landslide occurrences were usually asked by researchers in the past decades. Many investigations carried out in many places in the world to finding out methods that predict and prevent damages from landslides phenomena. Chen-Yu-Lan River watershed is reputed as a 'hot pot' of landslide researches in Taiwan by its complicated geological structures with the significant tectonic fault systems and steeply mountainous terrain. Beside annual high precipitation concentration and the abrupt slopes, some natural disaster, as typhoons (Sinlaku-2008, Kalmaegi-2008, and Marakot-2009) and earthquake (Chi-Chi earthquake-1999) are also the triggered factors cause landslides with serious damages in this place. This research expresses the quantitative approaches to generate landslide susceptible map for Chen-Yu-Lan watershed, a mountainous area in the central Taiwan. Landslide inventories data, which were detected from the Formosat-2 imageries for eight years from 2004 to 2011, were applied to carry out landslide susceptibility mapping. Bivariate statistics analysis and multivariate statistics analysis would be applied to calculate susceptible index of landslides. The weights of parameters were computed based on landslide data for eight years from 2004 to 2011. To validate effective levels of factors to landslide occurrences, this method built some multivariate algorithms and compared these results with real landslide occurrences. Besides this method, the historical data of landslides were also used to assess and classify landslide susceptibility levels. From long-term landslide data, relation between landslide susceptibility levels and landslide repetition was assigned. The results demonstrated differently effective levels of potential factors, such as, slope gradient, drainage density, lithology and land use to landslide phenomena. The results also showed logical relationship between weights and characteristics of

  12. Effect of suction-dependent soil deformability on landslide susceptibility maps

    NASA Astrophysics Data System (ADS)

    Lizarraga, Jose J.; Buscarnera, Giuseppe; Frattini, Paolo; Crosta, Giovanni B.

    2016-04-01

    This contribution presents a physically-based, spatially-distributed model for shallow landslides promoted by rainfall infiltration. The model features a set of Factor of Safety values aimed to capture different failure mechanisms, namely frictional slips with limited mobility and flowslide events associated with the liquefaction of the considered soils. Indices of failure associated with these two modes of instability have been derived from unsaturated soil stability principles. In particular, the propensity to wetting-induced collapse of unsaturated soils is quantified through the introduction of a rigid-plastic model with suction-dependent yielding and strength properties. The model is combined with an analytical approach (TRIGRS) to track the spatio-temporal evolution of soil suction in slopes subjected to transient infiltration. The model has been tested to reply the triggering of shallow landslides in pyroclastic deposits in Sarno (1998, Campania Region, Southern Italy). It is shown that suction-dependent mechanical properties, such as soil deformability, have important effects on the predicted landslide susceptibility scenarios, resulting on computed unstable zones that may encompass a wide range of slope inclinations, saturation levels, and depths. Such preliminary results suggest that the proposed methodology offers an alternative mechanistic interpretation to the variability in behavior of rainfall-induced landslides. Differently to standard methods the explanation to this variability is based on suction-dependent soil behavior characteristics.

  13. Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

    NASA Astrophysics Data System (ADS)

    García-Rodríguez, M. J.; Malpica, J. A.

    2010-06-01

    This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs). The computational method used for the training process is a back-propagation learning algorithm. It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred on 13 January 2001 (Mw 7.7) and 13 February 2001 (Mw 6.6). The first one triggered more than 600 landslides (including the most tragic, Las Colinas landslide) and killed at least 844 people. The ANN is designed and programmed to develop landslide susceptibility analysis techniques at a regional scale. This approach uses an inventory of landslides and different parameters of slope instability: slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness. The information obtained from ANN is then used by a Geographic Information System (GIS) to map the landslide susceptibility. In a previous work, a Logistic Regression (LR) was analysed with the same parameters considered in the ANN as independent variables and the occurrence or non-occurrence of landslides as dependent variables. As a result, the logistic approach determined the importance of terrain roughness and soil type as key factors within the model. The results of the landslide susceptibility analysis with ANN are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone. Finally, a comparative analysis of the ANN and LR models are made. The advantages and disadvantages of both approaches are discussed using Receiver Operating Characteristic (ROC) curves.

  14. Landslides in Flanders (Belgium): Where science meets public policy

    NASA Astrophysics Data System (ADS)

    van den Eeckhaut, M.; Poesen, J.; Vandekerckhove, L.

    2009-04-01

    Although scientific research on landslides in the Flemish Ardennes (710 km²; Belgium), has been conducted over the last decades, the Flemish Government only took account of slope failure as a soil degradation process after the occurrence of several damaging landslides in the beginning of the 21st century. Here we aim to present the successful collaboration between the Physical and Regional Geography Research Group (FRG; Dept. Earth and Environmental Sciences K.U.Leuven) and the Environment, Nature and Energy Department (LNE; Flemish Government) in landslide management. We will demonstrate how geomorphologists produced practical tools for landslide management which can be directly applied by LNE as well as other local and regional authorities and planners. Since 2004 three projects on landslide inventory mapping and susceptibility assessment in the Flemish Ardennes have been funded by LNE, and a fourth one on landslide susceptibility assessment in remaining hilly regions in Flanders west of Brussels recently started. Together with a steering committee composed of stakeholders, persons from LNE supervise the research carried out by geomorphologists experienced in landslide studies. For the establishment of the landslide inventory map of the Flemish Ardennes we combined the analysis of LIDAR-derived hillshade and contour line maps with detailed field controls. Additional information was collected through interviews with local authorities and inhabitants and from analysis of newspaper articles and technical reports. Then, a statistical model, logistic regression, was applied to produce a high quality classified landslide susceptibility map. The unique part of this collaboration is that all end products are online available at user-friendly websites designed by LNE. The scientific report containing (1) general information on landslides, (2) a description of the study area, (3) an explanation of the materials and methods used, (4) a presentation of the resulting

  15. Improving accuracy in shallow-landslide susceptibility analyses at regional scale

    NASA Astrophysics Data System (ADS)

    Iovine, Giulio G. R.; Rago, Valeria; Frustaci, Francesco; Bruno, Claudia; Giordano, Stefania; Muto, Francesco; Gariano, Stefano L.; Pellegrino, Annamaria D.; Conforti, Massimo; Pascale, Stefania; Distilo, Daniela; Basile, Vincenzo; Soleri, Sergio; Terranova, Oreste G.

    2015-04-01

    Calabria (southern Italy) is particularly exposed to geo-hydrological risk. In the last decades, slope instabilities, mainly related to rainfall-induced landslides, repeatedly affected its territory. Among these, shallow landslides, characterized by abrupt onset and extremely rapid movements, are among the most destructive and dangerous phenomena for people and infrastructures. In this study, a susceptibility analysis to shallow landslides has been performed by refining a method recently applied in Costa Viola - central Calabria (Iovine et al., 2014), and only focusing on landslide source activations (regardless of their possible evolution as debris flows). A multivariate approach has been applied to estimating the presence/absence of sources, based on linear statistical relationships with a set of causal variables. The different classes of numeric causal variables have been determined by means of a data clustering method, designed to determine the best arrangement. A multi-temporal inventory map of sources, mainly obtained from interpretation of air photographs taken in 1954-1955, and in 2000, has been adopted to selecting the training and the validation sets. Due to the wide extend of the territory, the analysis has been iteratively performed by a step-by-step decreasing cell-size approach, by adopting greater spatial resolutions and thematic details (e.g. lithology, land-use, soil, morphometry, rainfall) for high-susceptible sectors. Through a sensitivity analysis, the weight of the considered factors in predisposing shallow landslides has been evaluated. The best set of variables has been identified by iteratively including one variable at a time, and comparing the results in terms of performance. Furthermore, susceptibility evaluations obtained through logistic regression have been compared to those obtained by applying neural networks. Obtained results may be useful to improve land utilization planning, and to select proper mitigation measures in shallow-landslide

  16. The influence of land use change on landslide susceptibility zonation: the Briga catchment test site (Messina, Italy).

    PubMed

    Reichenbach, P; Busca, C; Mondini, A C; Rossi, M

    2014-12-01

    The spatial distribution of landslides is influenced by different climatic conditions and environmental settings including topography, morphology, hydrology, lithology, and land use. In this work, we have attempted to evaluate the influence of land use change on landslide susceptibility (LS) for a small study area located in the southern part of the Briga catchment, along the Ionian coast of Sicily (Italy). On October 1, 2009, the area was hit by an intense rainfall event that triggered abundant slope failures and resulted in widespread erosion. After the storm, an inventory map showing the distribution of pre-event and event landslides was prepared for the area. Moreover, two different land use maps were developed: the first was obtained through a semi-automatic classification of digitized aerial photographs acquired in 1954, the second through the combination of supervised classifications of two recent QuickBird images. Exploiting the two land use maps and different land use scenarios, LS zonations were prepared through multivariate statistical analyses. Differences in the susceptibility models were analyzed and quantified to evaluate the effects of land use change on the susceptibility zonation. Susceptibility maps show an increase in the areal percentage and number of slope units classified as unstable related to the increase in bare soils to the detriment of forested areas.

  17. Farmers' awareness on landslide susceptibility on their plots: a first step towards household resilience in the Rwenzori region, Western Uganda

    NASA Astrophysics Data System (ADS)

    Mertens, Kewan; Jacobs, Lies; Maes, Jan; Kervyn, Matthieu; Vranken, Liesbet

    2016-04-01

    In the mountainous area of the Rwenzori region, western Uganda, landslides frequently destroy houses and plots of farmers living and cultivating on unstable slopes. The impact of these landslides on the local livelihoods depends on the exposure and the resilience of the households. Both the exposure and the resilience can be modified to a certain extent with specific measures, e.g. planting slope stabilizing trees of paying for (informal) insurance. The adoption of such measures and the willingness to accept measures imposed by local governments crucially depends on the local awareness of landslide risk. The aim of this research is to estimate awareness on landslide susceptibility, as a proxy for landslide risk, among household heads in a landslide prone area in the Rwenzori region, Western Uganda. The objective is to compare household and plot characteristics between aware and unaware households. This will allow us to identify those households which are less aware of landslide susceptibility and therefore most likely to be less resilient when exposed to landslide risk. We use data from a susceptibility map constructed in 2016 and a structured household survey conducted in the Rwenzori region in 2015. The susceptibility map is based on a SRTM 30m DEM and validated with field observations, while the household survey includes the answers of more than 450 households that have been asked to evaluate the landslide susceptibility on their plots. Simple probit models at plot level are used to compare the estimated landslide susceptibility with the modelled susceptibility. We use this comparison to identify the household characteristics of those households that do not correctly estimate the landslide susceptibility on their plots. We will exploit the fact that landslide susceptibility is very space specific and that households can therefore have plots in both susceptible and unsusceptible areas. The research is currently ongoing, but we hypothesize that younger farmers

  18. Is it beneficial to approximate pre-failure topography to predict landslide susceptibility with empirical models?

    NASA Astrophysics Data System (ADS)

    Steger, Stefan; Schmaltz, Elmar; Glade, Thomas

    2017-04-01

    Empirical landslide susceptibility maps spatially depict the areas where future slope failures are likely due to specific environmental conditions. The underlying statistical models are based on the assumption that future landsliding is likely to occur under similar circumstances (e.g. topographic conditions, lithology, land cover) as past slope failures. This principle is operationalized by applying a supervised classification approach (e.g. a regression model with a binary response: landslide presence/absence) that enables discrimination between conditions that favored past landslide occurrences and the circumstances typical for landslide absences. The derived empirical relation is then transferred to each spatial unit of an area. Literature reveals that the specific topographic conditions representative for landslide presences are frequently extracted from derivatives of digital terrain models at locations were past landslides were mapped. The underlying morphology-based landslide identification becomes possible due to the fact that the topography at a specific locality usually changes after landslide occurrence (e.g. hummocky surface, concave and steep scarp). In a strict sense, this implies that topographic predictors used within conventional statistical landslide susceptibility models relate to post-failure topographic conditions - and not to the required pre-failure situation. This study examines the assumption that models calibrated on the basis of post-failure topographies may not be appropriate to predict future landslide locations, because (i) post-failure and pre-failure topographic conditions may differ and (ii) areas were future landslides will occur do not yet exhibit such a distinct post-failure morphology. The study was conducted for an area located in the Walgau region (Vorarlberg, western Austria), where a detailed inventory consisting of shallow landslides was available. The methodology comprised multiple systematic comparisons of models

  19. An overview of a GIS method for mapping landslides and assessing landslide susceptibility in the Río La Carbonera watershed, on the SE flank of Pico de Orizaba Volcano, Mexico.

    NASA Astrophysics Data System (ADS)

    Legorreta Paulin, G.; Bursik, M. I.; Contreras, T.

    2015-12-01

    This poster provides an overview of the on-going research project (Grant PAPIIT # IN102115) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory, produce a landslide susceptibility map, and estimate sediment production by using Geographic Information Systems (GIS). The Río La Carbonera watershed on the southeastern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 71.9 km2 with elevations ranging from 1224 to 3643 m a.s.l. and hillslopes between <5° and 68°. The stream system of Río La Carbonera catchment erodes Tertiary and Quaternary lavas, pyroclastic flows, and fall deposits. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The methodology encompasses three main stages of analysis to assess landslide hazards: Stage 1 builds a historic landslide inventory. In the study area, an inventory of more than 200 landslides is created from multi-temporal aerial-photo-interpretation and local field surveys to assess landslide distribution. All landslides were digitized into a geographic information system (GIS), and a spatial geo-database of landslides was constructed from standardized GIS datasets. Stage 2 calculates the susceptibility for the watershed. During this stage, (SINMAP using default values) is evaluated. Stage 3 Estimate the potential total material delivered to the main stream drainage channel by all landslides in the catchment. Detailed geometric measurements of individual landslides visited during the field work will be carried out to obtain the landslide area and volume. These measurements revealed an empirical relationship between area and volume that took the form of a power law. This relationship will be used to estimate the potential volume of material delivered to the

  20. Characteristics of a Recent and Prehistoric Landslides in the Pine River Valley, BC: a Mapping Effort

    NASA Astrophysics Data System (ADS)

    Heijenk, R.; Geertsema, M.; Miller, B.; de Jong, S. M.

    2015-12-01

    Spreads and other low gradient landslides are common in glacial lake sediments in north eastern British Columbia. Both pre and post glacial lake sediments, largely derived from shale bedrock are susceptible to low-gradient landslides. Bank erosion by rivers and streams and high pore pressures, have contributed to the landslides. We used LiDAR for mapping the extent of the glaciolacustrine sediments and map and characterise landslides in the Pine River valley, near Chetwynd, British Columbia. We included metrics such as travel angle, length, area, and elevation to distinguish rotational and translational landslides. We mapped 45 landslides in the Pine River valley distinguishing between rotational and translational landslides. The rotational landslides commonly have a smaller area and smaller travel length than translational landslides. Most rotational slides involved overlying alluvial fans, while most translational slides involved terraces.

  1. Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (lidar) in Densely Vegetated Areas of Tropics

    NASA Astrophysics Data System (ADS)

    Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.

    2017-10-01

    Landslides are an inescapable natural disaster, resulting in massive social, environmental and economic impacts all over the world. The tropical, mountainous landscape in generally all over Malaysia especially in eastern peninsula (Borneo) is highly susceptible to landslides because of heavy rainfall and tectonic disturbances. The purpose of the Landslide hazard mapping is to identify the hazardous regions for the execution of mitigation plans which can reduce the loss of life and property from future landslide incidences. Currently, the Malaysian research bodies e.g. academic institutions and government agencies are trying to develop a landslide hazard and risk database for susceptible areas to backing the prevention, mitigation, and evacuation plan. However, there is a lack of devotion towards landslide inventory mapping as an elementary input of landslide susceptibility, hazard and risk mapping. The developing techniques based on remote sensing technologies (satellite, terrestrial and airborne) are promising techniques to accelerate the production of landslide maps, shrinking the time and resources essential for their compilation and orderly updates. The aim of the study is to provide a better perception regarding the use of virtual mapping of landslides with the help of LiDAR technology. The focus of the study is spatio temporal detection and virtual mapping of landslide inventory via visualization and interpretation of very high-resolution data (VHR) in forested terrain of Mesilau river, Kundasang. However, to cope with the challenges of virtual inventory mapping on in forested terrain high resolution LiDAR derivatives are used. This study specifies that the airborne LiDAR technology can be an effective tool for mapping landslide inventories in a complex climatic and geological conditions, and a quick way of mapping regional hazards in the tropics.

  2. Landslide overview map of the conterminous United States

    USGS Publications Warehouse

    Radbruch-Hall, Dorothy H.; Colton, Roger B.; Davies, William E.; Lucchitta, Ivo; Skipp, Betty A.; Varnes, David J.

    1982-01-01

    The accompanying landslide overview map of the conterminous United States is one of a series of National Environmental Overview Maps that summarize geologic, hydrogeologic, and topographic data essential to the assessment of national environmental problems. The map delineates areas where large numbers of landslides exist and areas which are susceptible to landsliding. It was prepared by evaluating the geologic map of the United States and classifying the geologic units according to high, medium, or low landslide incidence (number) and high, medium, or low susceptibility to landsliding. Rock types, structures, topography, precipitation, landslide type, and landslide incidence are mentioned for each physical subdivision of the United States. The differences in slope stability between the Colorado Plateau, the Appalachian Highlands, the Coast Ranges of California, and the Southern Rocky Mountains are compared in detail, to illustrate the influence of various natural factors on the types of landsliding that occur in regions having different physical conditions. These four mountainous regions are among the most landslide-prone areas in the United States. The Colorado Plateau is a deformed platform where interbedded sedimentary rocks of varied lithologic properties have been gently warped and deeply eroded. The rocks are extensively fractured. Regional fracture systems, joints associated with individual geologic structures, and joints parallel to topographic surfaces, such as cliff faces, greatly influence slope stability. Detached blocks at the edges of mesas, as well as columns, arched recesses, and many natural arches on the Colorado Plateau, were formed wholly or in part by mass movement. In the Appalachian Highlands, earth flows, debris flows, and debris avalanches predominate in weathered bedrock and colluvium. Damaging debris avalanches result when persistent steady rainfall is followed by a sudden heavy downpour. Landsliding in unweathered bedrock is controlled

  3. Non-susceptible landslide areas in Italy and in the Mediterranean region

    NASA Astrophysics Data System (ADS)

    Marchesini, I.; Ardizzone, F.; Alvioli, M.; Rossi, M.; Guzzetti, F.

    2014-04-01

    We used landslide information for 13 study areas in Italy and morphometric information obtained from the 3 arc-second SRTM DEM to determine areas where landslide susceptibility is expected to be null or negligible in Italy, and in the landmasses surrounding the Mediterranean Sea. The morphometric information consisted in the local terrain slope computed in a square 3 × 3 cell moving window, and in the regional relative relief computed in a circular 15 × 15 cell moving window. We tested three different models to determine the non-susceptible landslide areas, including a linear model (LR), a quantile linear model (QLR), and a quantile non-linear model (QNL). We tested the performance of the three models using independent landslide information represented by the Italian Landslide Inventory (Inventario Fenomeni Franosi in Italia - IFFI). Best results were obtained using the QNL model. The corresponding zonation of non-susceptible landslide areas was intersected in a GIS with geographical census data for Italy. The result allowed determining that 57.5% of the population of Italy (in 2001) was located in areas where landslide susceptibility is expected to be null or negligible, and that the remaining 42.5% was located in areas where some landslide susceptibility is expected. We applied the QNL model to the landmasses surrounding the Mediterranean Sea, and we tested the synoptic non-susceptibility zonation using independent landslide information for three study areas in Spain. Results proved that the QNL model was capable of determining where landslide susceptibility is expected to be negligible in the Mediterranean area. We expect our results to be applicable in similar study areas, facilitating the identification of non-susceptible and susceptible landslide areas, at the synoptic scale.

  4. A hybrid feature selection algorithm integrating an extreme learning machine for landslide susceptibility modeling of Mt. Woomyeon, South Korea

    NASA Astrophysics Data System (ADS)

    Vasu, Nikhil N.; Lee, Seung-Rae

    2016-06-01

    An ever-increasing trend of extreme rainfall events in South Korea owing to climate change is causing shallow landslides and debris flows in mountains that cover 70% of the total land area of the nation. These catastrophic, gravity-driven processes cost the government several billion KRW (South Korean Won) in losses in addition to fatalities every year. The most common type of landslide observed is the shallow landslide, which occurs at 1-3 m depth, and may mobilize into more catastrophic flow-type landslides. Hence, to predict potential landslide areas, susceptibility maps are developed in a geographical information system (GIS) environment utilizing available morphological, hydrological, geotechnical, and geological data. Landslide susceptibility models were developed using 163 landslide points and an equal number of nonlandslide points in Mt. Woomyeon, Seoul, and 23 landslide conditioning factors. However, because not all of the factors contribute to the determination of the spatial probability for landslide initiation, and a simple filter or wrapper-based approach is not efficient in identifying all of the relevant features, a feedback-loop-based hybrid algorithm was implemented in conjunction with a learning scheme called an extreme learning machine, which is based on a single-layer, feed-forward network. Validation of the constructed susceptibility model was conducted using a testing set of landslide inventory data through a prediction rate curve. The model selected 13 relevant conditioning factors out of the initial 23; and the resulting susceptibility map shows a success rate of 85% and a prediction rate of 89.45%, indicating a good performance, in contrast to the low success and prediction rate of 69.19% and 56.19%, respectively, as obtained using a wrapper technique.

  5. Development of potential map for landslides by comparing instability indices of various time periods

    NASA Astrophysics Data System (ADS)

    Chiang, Jie-Lun; Tian, Yu-Qing; Chen, Yie-Ruey; Tsai, Kuang-Jung

    2017-04-01

    In recent years, extreme rainfall events occur frequently and induced serious landslides and debris flow disasters in Taiwan. The instability indices will differ when using landslide maps of different time periods. We analyzed the landslide records during the period year, 2008 2012, the landslide area contributed 0.42% 2.94% of the total watershed area, the 2.94% was caused by the typhoon Morakot in August, 2009, which brought massive rainfall in which the cumulative maximum rainfall was up to 2900 mm. We analyzed the instability factors including elevation, slope, aspect, soil, and geology. And comparing the instability indices by using individual landslide map of 2008 2012, the landslide maps of the union of the five years, and interaction of the five years. The landslide area from union of the five years contributed 3.71%,the landslide area from interaction of the five years contributed 0.14%. In this study, Kriging was used to establish the susceptibility map in selected watershed. From interaction of the five years, we found the instability index above 4.3 can correspond to those landslide records. The potential landslide area of the selected watershed, where collapses occur more likely, belongs to high level and medium-high level; the area is 13.43% and 3.04% respectively.

  6. Extreme rainfall-induced landslide changes based on landslide susceptibility in China, 1998-2015

    NASA Astrophysics Data System (ADS)

    Li, Weiyue; Liu, Chun; Hong, Yang

    2017-04-01

    Nowadays, landslide has been one of the most frequent and seriously widespread natural hazards all over the world. Rainfall, especially heavy rainfall is a trigger to cause the landslide occurrence, by increasing soil pore water pressures. In China, rainfall-induced landslides have risen up over to 90% of the total number. Rainfall events sometimes generate a trend of extremelization named rainfall extremes that induce the slope failure suddenly and severely. This study shows a method to simulate the rainfall-induced landslide spatio-temporal distribution on the basis of the landslide susceptibility index. First, the study on landslide susceptibility in China is introduced. We set the values of the index to the range between 0 and 1. Second, we collected TRMM 3B42 precipitation products spanning the years 1998-2015 and extracted the daily rainfall events greater than 50mm/day as extreme rainfall. Most of the rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate extreme rainfall-induced landslide distribution and illustrate the changes in 17 years. This study shows a useful tool to be part of rainfall-induced landslide simulation methodology for landslide early warning.

  7. Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

    NASA Astrophysics Data System (ADS)

    Jacobs, Liesbet; Dewitte, Olivier; Poesen, Jean; Sekajugo, John; Nobile, Adriano; Rossi, Mauro; Thiery, Wim; Kervyn, Matthieu

    2018-01-01

    landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region.

  8. Non-susceptible landslide areas in Italy and in the Mediterranean region

    NASA Astrophysics Data System (ADS)

    Marchesini, I.; Ardizzone, F.; Alvioli, M.; Rossi, M.; Guzzetti, F.

    2014-08-01

    We used landslide information for 13 study areas in Italy and morphometric information obtained from the 3-arcseconds shuttle radar topography mission digital elevation model (SRTM DEM) to determine areas where landslide susceptibility is expected to be negligible in Italy and in the landmasses surrounding the Mediterranean Sea. The morphometric information consisted of the local terrain slope which was computed in a square 3 × 3-cell moving window, and in the regional relative relief computed in a circular 15 × 15-cell moving window. We tested three different models to classify the "non-susceptible" landslide areas, including a linear model (LNR), a quantile linear model (QLR), and a quantile, non-linear model (QNL). We tested the performance of the three models using independent landslide information presented by the Italian Landslide Inventory (Inventario Fenomeni Franosi in Italia - IFFI). Best results were obtained using the QNL model. The corresponding zonation of non-susceptible landslide areas was intersected in a geographic information system (GIS) with geographical census data for Italy. The result determined that 57.5% of the population of Italy (in 2001) was located in areas where landslide susceptibility is expected to be negligible. We applied the QNL model to the landmasses surrounding the Mediterranean Sea, and we tested the synoptic non-susceptibility zonation using independent landslide information for three study areas in Spain. Results showed that the QNL model was capable of determining where landslide susceptibility is expected to be negligible in the validation areas in Spain. We expect our results to be applicable in similar study areas, facilitating the identification of non-susceptible landslide areas, at the synoptic scale.

  9. Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression

    NASA Astrophysics Data System (ADS)

    García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.; Díaz, M.

    2008-03-01

    This work has evaluated the probability of earthquake-triggered landslide occurrence in the whole of El Salvador, with a Geographic Information System (GIS) and a logistic regression model. Slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness are the predictor variables used to determine the dependent variable of occurrence or non-occurrence of landslides within an individual grid cell. The results illustrate the importance of terrain roughness and soil type as key factors within the model — using only these two variables the analysis returned a significance level of 89.4%. The results obtained from the model within the GIS were then used to produce a map of relative landslide susceptibility.

  10. Establish susceptibility and risk assessment models for rainfall-induced landslide: A case in Central Taiwan

    NASA Astrophysics Data System (ADS)

    Wu, Chunhung; Huang, Jyuntai

    2017-04-01

    .823 for LR. The study normalized the susceptibility value range of three landslide susceptibility models to 0 to 1 to deeply compare the model performance. The normalized landslide susceptibility value > 0.5 and ≦0.5 are regarded as predicted-landslide area and predicted-not-landslide area. The ratio of the area in the predicted-landslide area to the total area is 3.0% for FR, 71.4% for WOE, and 26.5% for LR. And the correct ratio is 65.5% for FR, 61.9% for WOE, 74.5% for LR. The study adopted 14 rainfall stations with more than 20 years daily rainfall data in Renai Township to estimate the 24 hrs accumulated rainfall with different RPYs. Landslide susceptibility map under 24 hrs accumulated rainfall distribution with different RPYs is used to estimate the landslide disaster location and scale. The landslide risk under different RPYs in Renai Township is calculated as 2.62 billion for 5 RPYs, 3.06 billion for 10 RPYs, 4.69 billion for 25 RPYs, 5.97 billion for 50 RPYs, 6.98 billion for 100 RPYs, and 8.23 billion for 200 RPYs, respectively.

  11. Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

    NASA Astrophysics Data System (ADS)

    Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Li, Yuanyao; Catani, Filippo; Pourghasemi, Hamid Reza

    2018-03-01

    Landslide is a common natural hazard and responsible for extensive damage and losses in mountainous areas. In this study, Longju in the Three Gorges Reservoir area in China was taken as a case study for landslide susceptibility assessment in order to develop effective risk prevention and mitigation strategies. To begin, 202 landslides were identified, including 95 colluvial landslides and 107 rockfalls. Twelve landslide causal factor maps were prepared initially, and the relationship between these factors and each landslide type was analyzed using the information value model. Later, the unimportant factors were selected and eliminated using the information gain ratio technique. The landslide locations were randomly divided into two groups: 70% for training and 30% for verifying. Two machine learning models: the support vector machine (SVM) and artificial neural network (ANN), and a multivariate statistical model: the logistic regression (LR), were applied for landslide susceptibility modeling (LSM) for each type. The LSM index maps, obtained from combining the assessment results of the two landslide types, were classified into five levels. The performance of the LSMs was evaluated using the receiver operating characteristics curve and Friedman test. Results show that the elimination of noise-generating factors and the separated modeling of each landslide type have significantly increased the prediction accuracy. The machine learning models outperformed the multivariate statistical model and SVM model was found ideal for the case study area.

  12. A method for producing digital probabilistic seismic landslide hazard maps

    USGS Publications Warehouse

    Jibson, R.W.; Harp, E.L.; Michael, J.A.

    2000-01-01

    The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include: (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24 000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10 m grid spacing using ARC/INFO GIS software on a UNIX computer. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure. ?? 2000 Elsevier Science B.V. All rights reserved.

  13. A zonation technique for landslide susceptibility in southern Taiwan

    NASA Astrophysics Data System (ADS)

    Chiang, Jie-Lun; Tian, Yu-Qing; Chen, Yie-Ruey; Tsai, Kuang-Jung

    2016-04-01

    In recent years, global climate changes violently, extreme rainfall events occur frequently and also cause massive sediment related disasters in Taiwan. The disaster seriously hit the regional economic development and national infrastructures. For example, in August, 2009, the typhoon Morakot brought massive rainfall especially in the mountains in Chiayi County and Kaohsiung County in which the cumulative maximum rainfall was up to 2900 mm; meanwhile, the cumulative maximum rainfall was over 1500m.m. in Nantou County, Tainan County and Pingtung County. The typhoon caused severe damage in southern Taiwan. The study will search for the influence on the sediment hazards caused by the extreme rainfall and hydrological environmental changes focusing on southern Taiwan (including Chiayi, Tainan, Kaohsiung and Pingtung). The instability index and kriging theories are applied to analyze the factors of landslide to determine the susceptibility in southern Taiwan. We collected the landslide records during the period year, 2007~2013 and analyzed the instability factors including elevation, slope, aspect, soil, and geology. Among these factors, slope got the highest weight. The steeper the slope is, the more the landslides occur. As for the factor of aspect, the highest probability falls on the Southwest. However, this factor has the lowest weight among all the factors. Likewise, Darkish colluvial soil holds the highest probability of collapses among all the soils. Miocene middle Ruifang group and its equivalents have the highest probability of collapses among all the geologies. In this study, Kriging was used to establish the susceptibility map in southern Taiwan. The instability index above 4.21 can correspond to those landslide records. The potential landslide area in southern Taiwan, where collapses more likely occur, belongs to high level and medium-high level; the area is 5.12% and 17.81% respectively.

  14. A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

    NASA Astrophysics Data System (ADS)

    Rossi, M.; Apuani, T.; Felletti, F.

    2009-04-01

    The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9

  15. Landsat applied to landslide mapping

    NASA Technical Reports Server (NTRS)

    Sauchyn, D. J.; Trench, N. R.

    1978-01-01

    A variety of features characteristic of rotational landslides may be identified on Landsat imagery. These include tonal mottling, tonal banding, major and secondary scarps, and ponds. Pseudostereoscopic viewing of 9 by 9 in. transparencies was useful for the detailed identification of landslides, whereas 1:250,000 prints enlarged from 70 mm negatives were most suitable for regional analysis. Band 7 is the most useful band for landslide recognition, due to accentuation of ponds and shadows. Examination of both bands 7 and 5, including vegetation information, was found to be most suitable. Although, given optimum terrain conditions, some landslides in Colorado may be recognized, many smaller landslides are not identifiable. Consequently, Landsat is not recommended for detailed regional mapping, or for use in areas similar to Colorado, where alternative (aircraft) imagery is available. However, Landsat may prove useful for preliminary landslide mapping in relatively unknown areas.

  16. Quantitative landslide risk assessment and mapping on the basis of recent occurrences

    NASA Astrophysics Data System (ADS)

    Remondo, Juan; Bonachea, Jaime; Cendrero, Antonio

    A quantitative procedure for mapping landslide risk is developed from considerations of hazard, vulnerability and valuation of exposed elements. The approach based on former work by the authors, is applied in the Bajo Deba area (northern Spain) where a detailed study of landslide occurrence and damage in the recent past (last 50 years) was carried out. Analyses and mapping are implemented in a Geographic Information System (GIS). The method is based on a susceptibility model developed previously from statistical relationships between past landslides and terrain parameters related to instability. Extrapolations based on past landslide behaviour were used to calculate failure frequency for the next 50 years. A detailed inventory of direct damage due to landslides during the study period was carried out and the main elements at risk in the area identified and mapped. Past direct (monetary) losses per type of element were estimated and expressed as an average 'specific loss' for events of a given magnitude (corresponding to a specified scenario). Vulnerability was assessed by comparing losses with the actual value of the elements affected and expressed as a fraction of that value (0-1). From hazard, vulnerability and monetary value, risk was computed for each element considered. Direct risk maps (€/pixel/year) were obtained and indirect losses from the disruption of economic activities due to landslides assessed. The final result is a risk map and table combining all losses per pixel for a 50-year period. Total monetary value at risk for the Bajo Deba area in the next 50 years is about 2.4 × 10 6 Euros.

  17. Directions of the US Geological Survey Landslide Hazards Reduction Program

    USGS Publications Warehouse

    Wieczorek, G.F.

    1993-01-01

    The US Geological Survey (USGS) Landslide Hazards Reduction Program includes studies of landslide process and prediction, landslide susceptibility and risk mapping, landslide recurrence and slope evolution, and research application and technology transfer. Studies of landslide processes have been recently conducted in Virginia, Utah, California, Alaska, and Hawaii, Landslide susceptibility maps provide a very important tool for landslide hazard reduction. The effects of engineering-geologic characteristics of rocks, seismic activity, short and long-term climatic change on landslide recurrence are under study. Detailed measurement of movement and deformation has begun on some active landslides. -from Author

  18. Comparison and validation of shallow landslides susceptibility maps generated by bi-variate and multi-variate linear probabilistic GIS-based techniques. A case study from Ribeira Quente Valley (S. Miguel Island, Azores)

    NASA Astrophysics Data System (ADS)

    Marques, R.; Amaral, P.; Zêzere, J. L.; Queiroz, G.; Goulart, C.

    2009-04-01

    Slope instability research and susceptibility mapping is a fundamental component of hazard assessment and is of extreme importance for risk mitigation, land-use management and emergency planning. Landslide susceptibility zonation has been actively pursued during the last two decades and several methodologies are still being improved. Among all the methods presented in the literature, indirect quantitative probabilistic methods have been extensively used. In this work different linear probabilistic methods, both bi-variate and multi-variate (Informative Value, Fuzzy Logic, Weights of Evidence and Logistic Regression), were used for the computation of the spatial probability of landslide occurrence, using the pixel as mapping unit. The methods used are based on linear relationships between landslides and 9 considered conditioning factors (altimetry, slope angle, exposition, curvature, distance to streams, wetness index, contribution area, lithology and land-use). It was assumed that future landslides will be conditioned by the same factors as past landslides in the study area. The presented work was developed for Ribeira Quente Valley (S. Miguel Island, Azores), a study area of 9,5 km2, mainly composed of volcanic deposits (ash and pumice lapilli) produced by explosive eruptions in Furnas Volcano. This materials associated to the steepness of the slopes (38,9% of the area has slope angles higher than 35°, reaching a maximum of 87,5°), make the area very prone to landslide activity. A total of 1.495 shallow landslides were mapped (at 1:5.000 scale) and included in a GIS database. The total affected area is 401.744 m2 (4,5% of the study area). Most slope movements are translational slides frequently evolving into debris-flows. The landslides are elongated, with maximum length generally equivalent to the slope extent, and their width normally does not exceed 25 m. The failure depth rarely exceeds 1,5 m and the volume is usually smaller than 700 m3. For modelling

  19. Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

    NASA Astrophysics Data System (ADS)

    Chen, Wei; Pourghasemi, Hamid Reza; Panahi, Mahdi; Kornejady, Aiding; Wang, Jiale; Xie, Xiaoshen; Cao, Shubo

    2017-11-01

    The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector machine (SVM), for landslide susceptibility mapping in Hanyuan County, China. In the first step, in accordance with a review of the previous literature, twelve conditioning factors, including slope aspect, altitude, slope angle, topographic wetness index (TWI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, land use, normalized difference vegetation index (NDVI), and lithology, were selected. In the second step, a collinearity test and correlation analysis between the conditioning factors and landslides were applied. In the third step, we used three advanced methods, namely, ANFIS-FR, GAM, and SVM, for landslide susceptibility modeling. Subsequently, the results of their accuracy were validated using a receiver operating characteristic curve. The results showed that all three models have good prediction capabilities, while the SVM model has the highest prediction rate of 0.875, followed by the ANFIS-FR and GAM models with prediction rates of 0.851 and 0.846, respectively. Thus, the landslide susceptibility maps produced in the study area can be applied for management of hazards and risks in landslide-prone Hanyuan County.

  20. Disseminating Landslide Hazard Information for California Local Government

    NASA Astrophysics Data System (ADS)

    Wills, C. J.

    2010-12-01

    landslide susceptibility map to give a single value of susceptibility for each census tract. We then calculated the loss ratio, the cost of landslide damage from the 1978 storms divided by the value of light wood frame structures in the census tract. The comparison suggests three general categories of damage: tracts with low landslide susceptibility have no landslide damage: tracts with moderate susceptibility have loss ratios of about 0.016%: and tracts with high susceptibility have loss ratios of 0.096%. Using these values, the susceptibility map becomes a landslide loss ratio map for the average storm intensity and landslide vulnerability of Los Angeles in 1978. Generalization to other storm intensities uses differences in storm intensity and landslide damage data from the 1982 storm in the Bay Area. In Santa Cruz County, that storm had a recurrence interval of over 100 years, and over 3 times the damage as our projection from the 1978 data. In Sonoma County, that storm had a recurrence interval of only 10 years and damage that was only 2% of our projection. If a relationship between storm intensity and the projections from the 1978 Los Angeles data can be developed, we may be able to estimate landslide losses for any projected storm intensity.

  1. Landslide hazard mapping with selected dominant factors: A study case of Penang Island, Malaysia

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tay, Lea Tien; Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum

    Landslide is one of the destructive natural geohazards in Malaysia. In addition to rainfall as triggering factos for landslide in Malaysia, topographical and geological factors play important role in the landslide susceptibility analysis. Conventional topographic factors such as elevation, slope angle, slope aspect, plan curvature and profile curvature have been considered as landslide causative factors in many research works. However, other topographic factors such as diagonal length, surface area, surface roughness and rugosity have not been considered, especially for the research work in landslide hazard analysis in Malaysia. This paper presents landslide hazard mapping using Frequency Ratio (FR) and themore » study area is Penang Island of Malaysia. Frequency ratio approach is a variant of probabilistic method that is based on the observed relationships between the distribution of landslides and each landslide-causative factor. Landslide hazard map of Penang Island is produced by considering twenty-two (22) landslide causative factors. Among these twenty-two (22) factors, fourteen (14) factors are topographic factors. They are elevation, slope gradient, slope aspect, plan curvature, profile curvature, general curvature, tangential curvature, longitudinal curvature, cross section curvature, total curvature, diagonal length, surface area, surface roughness and rugosity. These topographic factors are extracted from the digital elevation model of Penang Island. The other eight (8) non-topographic factors considered are land cover, vegetation cover, distance from road, distance from stream, distance from fault line, geology, soil texture and rainfall precipitation. After considering all twenty-two factors for landslide hazard mapping, the analysis is repeated with fourteen dominant factors which are selected from the twenty-two factors. Landslide hazard map was segregated into four categories of risks, i.e. Highly hazardous area, Hazardous area, Moderately

  2. A new concept in seismic landslide hazard analysis for practical application

    NASA Astrophysics Data System (ADS)

    Lee, Chyi-Tyi

    2017-04-01

    A seismic landslide hazard model could be constructed using deterministic approach (Jibson et al., 2000) or statistical approach (Lee, 2014). Both approaches got landslide spatial probability under a certain return-period earthquake. In the statistical approach, our recent study found that there are common patterns among different landslide susceptibility models of the same region. The common susceptibility could reflect relative stability of slopes at a region; higher susceptibility indicates lower stability. Using the common susceptibility together with an earthquake event landslide inventory and a map of topographically corrected Arias intensity, we can build the relationship among probability of failure, Arias intensity and the susceptibility. This relationship can immediately be used to construct a seismic landslide hazard map for the region that the empirical relationship built. If the common susceptibility model is further normalized and the empirical relationship built with normalized susceptibility, then the empirical relationship may be practically applied to different region with similar tectonic environments and climate conditions. This could be feasible, when a region has no existing earthquake-induce landslide data to train the susceptibility model and to build the relationship. It is worth mentioning that a rain-induced landslide susceptibility model has common pattern similar to earthquake-induced landslide susceptibility in the same region, and is usable to build the relationship with an earthquake event landslide inventory and a map of Arias intensity. These will be introduced with examples in the meeting.

  3. Dynamic, physical-based landslide susceptibility modelling based on real-time weather data

    NASA Astrophysics Data System (ADS)

    Canli, Ekrem; Glade, Thomas

    2016-04-01

    By now there seem to be a broad consensus that due to human-induced global change the frequency and magnitude of precipitation intensities within extensive rainstorm events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as one of the most common triggers for landslide initiation, also an increased landside activity might be expected. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled by a variety of concepts, methods, and models. However, most of the research done with respect to landslides deals with retrospect cases, thus classical back-analysis approaches do not incorporate real-time data. This is remarkable, as most destructive landslides are related to immediate events due to external triggering factors. Only few works so far addressed real-time dynamic components for spatial landslide susceptibility and hazard assessment. Here we present an approach for integrating real-time web-based rainfall data from different sources into an automated workflow. Rain gauge measurements are interpolated into a continuous raster which in return is directly utilized in a dynamic, physical-based model. We use the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) model that was modified in a way that it is automatically updated with the most recent rainfall raster for producing hourly landslide susceptibility maps on a regional scale. To account for the uncertainties involved in spatial modelling, the model was further adjusted by not only applying single values for given geotechnical parameters, but ranges instead. The values are determined randomly between user-defined thresholds defining the parameter ranges. Consequently, a slope failure probability from a larger number of model runs is computed rather than just the distributed factor of safety. This will ultimately allow a near-real time spatial landslide alert for a given region.

  4. Landslide Susceptibility Analysis by the comparison and integration of Random Forest and Logistic Regression methods; application to the disaster of Nova Friburgo - Rio de Janeiro, Brasil (January 2011)

    NASA Astrophysics Data System (ADS)

    Esposito, Carlo; Barra, Anna; Evans, Stephen G.; Scarascia Mugnozza, Gabriele; Delaney, Keith

    2014-05-01

    The study of landslide susceptibility by multivariate statistical methods is based on finding a quantitative relationship between controlling factors and landslide occurrence. Such studies have become popular in the last few decades thanks to the development of geographic information systems (GIS) software and the related improved data management. In this work we applied a statistical approach to an area of high landslide susceptibility mainly due to its tropical climate and geological-geomorphological setting. The study area is located in the south-east region of Brazil that has frequently been affected by flood and landslide hazard, especially because of heavy rainfall events during the summer season. In this work we studied a disastrous event that occurred on January 11th and 12th of 2011, which involved Região Serrana (the mountainous region of Rio de Janeiro State) and caused more than 5000 landslides and at least 904 deaths. In order to produce susceptibility maps, we focused our attention on an area of 93,6 km2 that includes Nova Friburgo city. We utilized two different multivariate statistic methods: Logistic Regression (LR), already widely used in applied geosciences, and Random Forest (RF), which has only recently been applied to landslide susceptibility analysis. With reference to each mapping unit, the first method (LR) results in a probability of landslide occurrence, while the second one (RF) gives a prediction in terms of % of area susceptible to slope failure. With this aim in mind, a landslide inventory map (related to the studied event) has been drawn up through analyses of high-resolution GeoEye satellite images, in a GIS environment. Data layers of 11 causative factors have been created and processed in order to be used as continuous numerical or discrete categorical variables in statistical analysis. In particular, the logistic regression method has frequent difficulties in managing numerical continuous and discrete categorical variables

  5. Object-based Landslide Mapping: Examples, Challenges and Opportunities

    NASA Astrophysics Data System (ADS)

    Hölbling, Daniel; Eisank, Clemens; Friedl, Barbara; Chang, Kang-Tsung; Tsai, Tsai-Tsung; Birkefeldt Møller Pedersen, Gro; Betts, Harley; Cigna, Francesca; Chiang, Shou-Hao; Aubrey Robson, Benjamin; Bianchini, Silvia; Füreder, Petra; Albrecht, Florian; Spiekermann, Raphael; Weinke, Elisabeth; Blaschke, Thomas; Phillips, Chris

    2016-04-01

    Over the last decade, object-based image analysis (OBIA) has been increasingly used for mapping landslides that occur after triggering events such as heavy rainfall. The increasing availability and quality of Earth Observation (EO) data in terms of temporal, spatial and spectral resolution allows for comprehensive mapping of landslides at multiple scales. Most often very high resolution (VHR) or high resolution (HR) optical satellite images are used in combination with a digital elevation model (DEM) and its products such as slope and curvature. Semi-automated object-based mapping makes use of various characteristics of image objects that are derived through segmentation. OBIA enables numerous spectral, spatial, contextual and textural image object properties to be applied during an analysis. This is especially useful when mapping complex natural features such as landslides and constitutes an advantage over pixel-based image analysis. However, several drawbacks in the process of object-based landslide mapping have not been overcome yet. The developed classification routines are often rather complex and limited regarding their transferability across areas and sensors. There is still more research needed to further improve present approaches and to fully exploit the capabilities of OBIA for landslide mapping. In this study several examples of object-based landslide mapping from various geographical regions with different characteristics are presented. Examples from the Austrian and Italian Alps are shown, whereby one challenge lies in the detection of small-scale landslides on steep slopes while preventing the classification of false positives with similar spectral properties (construction areas, utilized land, etc.). Further examples feature landslides mapped in Iceland, where the differentiation of landslides from other landscape-altering processes in a highly dynamic volcanic landscape poses a very distinct challenge, and in Norway, which is exposed to multiple

  6. A procedure for landslide susceptibility zonation by the conditional analysis method1

    NASA Astrophysics Data System (ADS)

    Clerici, Aldo; Perego, Susanna; Tellini, Claudio; Vescovi, Paolo

    2002-12-01

    Numerous methods have been proposed for landslide probability zonation of the landscape by means of a Geographic Information System (GIS). Among the multivariate methods, i.e. those methods which simultaneously take into account all the factors contributing to instability, the Conditional Analysis method applied to a subdivision of the territory into Unique Condition Units is particularly straightforward from a conceptual point of view and particularly suited to the use of a GIS. In fact, working on the principle that future landslides are more likely to occur under those conditions which led to past instability, landslide susceptibility is defined by computing the landslide density in correspondence with different combinations of instability factors. The conceptual simplicity of this method, however, does not necessarily imply that it is simple to implement, especially as it requires rather complex operations and a high number of GIS commands. Moreover, there is the possibility that, in order to achieve satisfactory results, the procedure has to be repeated a few times changing the factors or modifying the class subdivision. To solve this problem, we created a shell program which, by combining the shell commands, the GIS Geographical Research Analysis Support System (GRASS) commands and the gawk language commands, carries out the whole procedure automatically. This makes the construction of a Landslide Susceptibility Map easy and fast for large areas too, and even when a high spatial resolution is adopted, as shown by application of the procedure to the Parma River basin, in the Italian Northern Apennines.

  7. A GIS-based susceptibility map for landslides at the Franconian Alb, Germany

    NASA Astrophysics Data System (ADS)

    Jaeger, Daniel; Wilde, Martina; Lorenz, Michael; Terhorst, Birgit; Neuhäuser, Bettina; Damm, Bodo; Bemm, Stefan

    2014-05-01

    In general, slopes of cuesta scarps like the Franconian Alb are highly prone to slide activity due to susceptible geological and geomorphological conditions. The geological setting with alternating permeable and non-permeable bedrock results in the characteristic cuesta landforms of almost flat backslopes and steeper front slopes. Furthermore, this bipartite structure leads to a strong disposition for mass movements. The slopes of the study area near the town of Ebermannstadt are affected by different types of mass movements, such as topples, slides, lateral spreads and flows, either in single or in combined occurrence. In the years 1625, 1957, 1961 and 1979, four large landslides took place in the area of Ebermannstadt, reaching close to the town limits and causing major destructions to traffic facilities. In the study area, slopes are covered by debris and slide masses, thus they are prone to remobilization and further mass movements. In order to assess hazardous areas, a GIS-based susceptibility modelling was generated for the study area. The susceptibtibility modeling was processed with the slope stability model SINMAP (Stability Index Mapping), developed by TARBOTON (1997) and PACK et al. (1999). As SINMAP was particularly designed to model shallow translational slides, it should be well designed for describing the conditions of the study area in a sufficient way. SINMAP is based on the "infinite slope stability model" by HAMMONT et al. (1992) and MONTGOMERY & DIETRICH (1994), which focuses on the relation of stabilizing (cohesiveness, friction angle) and destabilizing (gravitation) factors on a plain surface. By adding a slope gradient, as well as soil mechanical and climatical data, indices of slope stabilities are calculated. For a more detailed modeling of the slope conditions, SINMAP computes different "calibration regions", which merge similar parameters of soil, land-use, vegetation, and geology. Due to the fact that vegetation, land-use, and soils only

  8. Regional landslide susceptibility assessment using multi-stage remote sensing data along the coastal range highway in northeastern Taiwan

    NASA Astrophysics Data System (ADS)

    Lee, Ching-Fang; Huang, Wei-Kai; Chang, Yu-Lin; Chi, Shu-Yeong; Liao, Wu-Chang

    2018-01-01

    Typhoons Megi (2010) and Saola (2012) brought torrential rainfall which triggered regional landslides and flooding hazards along Provincial Highway No. 9 in northeastern Taiwan. To reduce property loss and saving lives, this study combines multi-hazard susceptibility assessment with environmental geology map a rock mass rating system (RMR), remote sensing analysis, and micro-topography interpretation to develop an integrated landslide hazard assessment approach and reflect the intrinsic state of slopeland from the past toward the future. First, the degree of hazard as indicated by historical landslides was used to determine many landslide regions in the past. Secondly, geo-mechanical classification of rock outcroppings was performed by in-situ investigation along the vulnerable road sections. Finally, a high-resolution digital elevation model was extracted from airborne LiDAR and multi-temporal remote sensing images which was analyzed to discover possible catastrophic landslide hotspot shortly. The results of the analysis showed that 37% of the road sections in the study area were highly susceptible to landslide hazards. The spatial distribution of the road sections revealed that those characterized by high susceptibility were located near the boundaries of fault zones and in areas of lithologic dissimilarity. Headward erosion of gullies and concave-shaped topographic features had an adverse effect and was the dominant factor triggering landslides. Regional landslide reactivation on this coastal highway are almost related to the past landslide region based on hazard statistics. The final results of field validation demonstrated that an accuracy of 91% could be achieved for forecasting geohazard followed by intense rainfall events and typhoons.

  9. Rainfall-Triggered Landslides Bury Sri Lankan Villages

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia; Stanley, Thomas

    2016-01-01

    On the afternoon of May 17th, 2016, a major landslide event caused at least 92 deaths, with 109 still missing*. The site was rated highly susceptible to landslides in a new global landslide susceptibility map. GPM precipitation data suggest that both antecedent and current rainfall as well as complex topography played a role in the slope failures.

  10. Root reinforcement and its implications in shallow landsliding susceptibility on a small alpine catchment

    NASA Astrophysics Data System (ADS)

    Morandi, M. C.; Farabegoli, E.; Onorevoli, G.

    2012-04-01

    Roots shear resistance offers a considerable contribution to hill-slope stability on vegetated terrains. Through the pseudo-cohesion of shrubs, trees and turf's roots, the geomechanical properties of soils can be drastically increased, exerting a positive influence on the hillslope stability. We analysed the shallow landsliding susceptibility of a small alpine catchment (Duron valley, Central Dolomites, Italy) that we consider representative of a wide altitude belt of the Dolomites (1800 - 2400 m a.s.l). The catchment is mostly mantled by grass (Nardetum strictae s.l.), with clustered shrubs (Rhododendron hirsutum and Juniperus nana), and trees (Pinus cembra, Larix decidua and Picea abies). The soil depth, investigated with direct and indirect methods, ranges from 0 to 180 cm, with its peak at the hollow axes. Locally, the bedrock, made of Triassic volcanic rocks, is deeply incised by the Holocene drainage network. Intensive grazing of cows and horses pervades the catchment area and cattle-trails occupy ca 20% of the grass cover. We used laboratory and field tests to characterize the geotechnical properties of these alpine soils; moreover we designed and tested an experimental device that measures, in situ, the shear strengths of the grass mantle. In the study area we mapped 18 shallow landslides, mostly related to road cuts and periodically reactivated as retrogressive landslides. The triggering mechanisms of these shallow landslides were qualitatively analysed at large scale and modelled at smaller scale. We used SHALSTAB to model the shallow landsliding susceptibility of the catchment at the basin scale and SLIDE (RocScience) to compute the Safety Factor at the versant scale. Qualitative management solutions are provided, in order to reduce the shallow landsliding susceptibility risk in this alpine context.

  11. A Tool for Modelling the Probability of Landslides Impacting Road Networks

    NASA Astrophysics Data System (ADS)

    Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.; Guzzetti, Fausto

    2014-05-01

    Triggers such as earthquakes or heavy rainfall can result in hundreds to thousands of landslides occurring across a region within a short space of time. These landslides can in turn result in blockages across the road network, impacting how people move about a region. Here, we show the development and application of a semi-stochastic model to simulate how landslides intersect with road networks during a triggered landslide event. This was performed by creating 'synthetic' triggered landslide inventory maps and overlaying these with a road network map to identify where road blockages occur. Our landslide-road model has been applied to two regions: (i) the Collazzone basin (79 km2) in Central Italy where 422 landslides were triggered by rapid snowmelt in January 1997, (ii) the Oat Mountain quadrangle (155 km2) in California, USA, where 1,350 landslides were triggered by the Northridge Earthquake (M = 6.7) in January 1994. For both regions, detailed landslide inventory maps for the triggered events were available, in addition to maps of landslide susceptibility and road networks of primary, secondary and tertiary roads. To create 'synthetic' landslide inventory maps, landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL. The number of landslide areas selected was based on the observed density of landslides (number of landslides km-2) in the triggered event inventories. Landslide shapes were approximated as ellipses, where the ratio of the major and minor axes varies with AL. Landslides were then dropped over the region semi-stochastically, conditioned by a landslide susceptibility map, resulting in a synthetic landslide inventory map. The originally available landslide susceptibility maps did not take into account susceptibility changes in the immediate vicinity of roads, therefore

  12. Landslide Susceptibility Across the Pacific Northwest: The Heavy Influence of Transportation Inventories

    NASA Astrophysics Data System (ADS)

    Stanley, Thomas; Kirschbaum, Dalia

    2017-04-01

    Some of the largest and best landslide databases in the United States of America describe the Pacific Northwest region. Nevertheless, these inventories are not a comprehensive listing of historic landslides. In particular, landslide dates tend to be recorded by state transportation agencies, which imposes a spatial bias upon any subsequent analysis. This reporting bias complicates not only the identification of landslide triggering conditions, but also hinders empirical calculations of landslide susceptibility. Although many strategies for bias mitigation could be employed, the simplest approach delivers generally plausible results that are most reliable in the most critical locations: along major highways and rail lines. This work tests logistic regression models that were fitted in zones with landslide reports, then applied regionally. Due to the destabilizing effects of excavation and other anthropogenic disturbances, the models may overestimate susceptibility in undeveloped areas. However, the susceptibility of developed sites should be as accurate as the modeling technique and input data allow.

  13. Modelling increased landslide susceptibility near highways in the Andes of southern Ecuador

    NASA Astrophysics Data System (ADS)

    Brenning, Alexander; Muenchow, Jannes

    2016-04-01

    Modelling increased landslide susceptibility near highways in the Andes of southern Ecuador A. Brenning (1), J. Muenchow (1) (1) Department of Geography, Friedrich Schiller University Jena, Loebdergraben 32, 07743 Jena, Germany Mountain roads are affected by and also affect themselves landslide suceptibility. Especially in developing countries, inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading are known processes through which road construction and maintenance can enhance landslide activity within the immediate surroundings of road infrastructure. In the Andes of southern Ecuador, strong precipitation gradients as well as lithological differences provide an excellent study site in which the relationship between highways and landslide susceptibility and its regional differentiation can be studied. This study uses Generalized Additive Models (GAM) to investigate patterns of landslide susceptibility along two paved interurban highways in the tropical Andes of southern Ecuador. The relationship of landslides to distance from road is modeled while accounting for topographic, climatic and lithological predictors as possible confounders and modifiers, focusing on the odds ratio of landslide occurrence at 25 m versus 200 m distance from the highway. Spatial attention is given to uncertainties in estimated odds ratios of landslide occurrence using spatial block bootstrap techniques. The GAM is able to represent nonlinear additive terms as well as bivariate smooth interaction terms, providing a good tradeoff between model complexity and interpretability. The estimated odds of landslide occurrence were 18-21 times higher near the highway than at 200 m distance, based on different analyses, with lower 95% confidence limits always >13. (Semi-) parametric estimates confirmed this general range of values but suggests slightly higher odds ratios (95% confidence interval: 15.5-25.3). Highway-related effects were observed to

  14. Presence-only approach to assess landslide triggering-thickness susceptibility. A test for the Mili catchment (North-Eastern Sicily, Italy)

    NASA Astrophysics Data System (ADS)

    Lombardo, Luigi; Fubelli, Giandomenico; Amato, Gabriele; Bonasera, Mauro; Hochschild, Volker; Rotigliano, Edoardo

    2015-04-01

    This study aims at comparing the performances of a presence only approach, namely Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment, located in the north-eastern Sicily, Italy. This catchment has been recently exposed to three main meteorological extreme events, resulting in the activation of multiple fast landslides, which occurred on the 1st October 2009, 10th March 2010 and 1st March 2011. Differently from the 2009 event, which only marginally hit the catchment, the 2010 and 2011 storms fully involved the area of the Mili catchment. Detailed field data was collected to associate the thickness of mobilised materials at the triggering zone to each mass movement within the catchment. This information has been used to model the landslide susceptibility for two classes of processes clustered into shallow failures for maximum depths of 0.5m and deep ones in case of values equal or greater than 0.5m. As the authors believed that the peculiar geomorphometry of this narrow and steep catchment played a fundamental role in generating two distinct patterns of landslide thicknesses during the initiation phase, a HRDEM was used to extract topographic attributes to express near-triggering geomorphological conditions. On the other hand, medium resolution vegetation indexes derived from ASTER scenes were used as explanatory variables pertaining to a wider spatial neighbourhood, whilst a revised geological map, the land use from CORINE and a tectonic map were used to convey an even wider area connected to the slope instability. The choice of a presence-only approach allowed to effectively discriminate between the two types of landslide thicknesses at the triggering zone, producing outstanding prediction skills associated with relatively low variances across a set of 20 randomly generated replicates. The validation phase produced indeed average AUC values of 0.91 with a standard deviation of 0.03 for both the modelled landslide

  15. Using online database for landslide susceptibility assessment with an example from the Veneto Region (north-eastern Italy).

    NASA Astrophysics Data System (ADS)

    Floris, Mario; Squarzoni, Cristina; Zorzi, Luca; D'Alpaos, Andrea; Iafelice, Maria

    2010-05-01

    Landslide susceptibility maps describe landslide-prone areas by the spatial correlation between landslides and related factors, derived from different kinds of datasets: geological, geotechnical and geomechanical maps, hydrogeological maps, landslides maps, vector and raster terrain data, real-time inclinometer and pore pressure data. In the last decade, thanks to the increasing use of web-based tools for management, sharing and communication of territorial information, many Web-based Geographical Information Systems (WebGIS) were created by local governments or nations, University and Research Centres. Nowadays there is a strong proliferation of geological WebGIS or GeoBrowser, allowing free download of spatial information. There are global Cartographical Portals that provide a free download of DTM and other vector data related to the whole planet (http://www.webgis.com). At major scale, there are WebGIS regarding entire nation (http://www.agiweb.org), or specific region of a country (http://www.mrt.tas.gov.au), or single municipality (http://sitn.ne.ch/). Moreover, portals managed by local government and academic government (http://turtle.ags.gov.ab.ca/Peace_River/Site/) or by a private agency (http://www.bbt-se.com) are noteworthy. In Italy, the first national projects for the creation of WebGIS and web-based databases begun during the 1980s, and evolved, through years, to the present number of different WebGIS, which have different territorial extensions: national (Italian National Cartographical Portal, http://www.pcn.minambiente.it; E-GEO Project, http://www.egeo.unisi.it), interregional (River Tiber Basin Authority, www.abtevere.it ), and regional (Veneto Region, www.regione.veneto.it). In this way we investigated most of the Italian WebGIS in order to verify their geographic range and the availability and quality of data useful for landslide hazard analyses. We noticed a large variability of the accessing information among the different browsers. In

  16. Assessing the Agreement Between Eo-Based Semi-Automated Landslide Maps with Fuzzy Manual Landslide Delineation

    NASA Astrophysics Data System (ADS)

    Albrecht, F.; Hölbling, D.; Friedl, B.

    2017-09-01

    Landslide mapping benefits from the ever increasing availability of Earth Observation (EO) data resulting from programmes like the Copernicus Sentinel missions and improved infrastructure for data access. However, there arises the need for improved automated landslide information extraction processes from EO data while the dominant method is still manual delineation. Object-based image analysis (OBIA) provides the means for the fast and efficient extraction of landslide information. To prove its quality, automated results are often compared to manually delineated landslide maps. Although there is awareness of the uncertainties inherent in manual delineations, there is a lack of understanding how they affect the levels of agreement in a direct comparison of OBIA-derived landslide maps and manually derived landslide maps. In order to provide an improved reference, we present a fuzzy approach for the manual delineation of landslides on optical satellite images, thereby making the inherent uncertainties of the delineation explicit. The fuzzy manual delineation and the OBIA classification are compared by accuracy metrics accepted in the remote sensing community. We have tested this approach for high resolution (HR) satellite images of three large landslides in Austria and Italy. We were able to show that the deviation of the OBIA result from the manual delineation can mainly be attributed to the uncertainty inherent in the manual delineation process, a relevant issue for the design of validation processes for OBIA-derived landslide maps.

  17. Geomorphological mapping of shallow landslides using UAVs

    NASA Astrophysics Data System (ADS)

    Fiorucci, Federica; Giordan, Daniele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

    2015-04-01

    The mapping of event shallow landslides is a critical activity, due to the large number of phenomena, mostly with small dimension, affecting extensive areas. This is commonly done through aerial photo-interpretation or through field surveys. Nowadays, landslide maps can be realized exploiting other methods/technologies: (i) airborne LiDARs, (ii) stereoscopic satellite images, and (iii) unmanned aerial vehicles (UAVs). In addition to the landslide maps, these methods/technologies allow the generation of updated Digital Terrain Models (DTM). In December 2013, in the Collazzone area (Umbria, Central Italy), an intense rainfall event triggered a large number of shallow landslides. To map the landslides occurred in the area, we exploited data and images obtained through (A) an airborne LiDAR survey, (B) a remote controlled optocopter (equipped with a Canon EOS M) survey, and (C) a stereoscopic satellite WorldView II MS. To evaluate the mapping accuracy of these methods, we select two landslides and we mapped them using a GPS RTK instrumentation. We consider the GPS survey as the benchmark being the most accurate system. The results of the comparison allow to highlight pros and cons of the methods/technologies used. LiDAR can be considered the most accurate system and in addition it allows the extraction and the classification of the digital surface models from the surveyed point cloud. Conversely, LiDAR requires additional time for the flight planning, and specific data analysis user capabilities. The analysis of the satellite WorldView II MS images facilitates the landslide mapping over large areas, but at the expenses of a minor resolution to detect the smaller landslides and their boundaries. UAVs can be considered the cheapest and fastest solution for the acquisition of high resolution ortho-photographs on limited areas, and the best solution for a multi-temporal analysis of specific landslide phenomena. Limitations are due to (i) the needs of optimal climatic

  18. Automatic mapping of event landslides at basin scale in Taiwan using a Montecarlo approach and synthetic land cover fingerprints

    NASA Astrophysics Data System (ADS)

    Mondini, Alessandro C.; Chang, Kang-Tsung; Chiang, Shou-Hao; Schlögel, Romy; Notarnicola, Claudia; Saito, Hitoshi

    2017-12-01

    We propose a framework to systematically generate event landslide inventory maps from satellite images in southern Taiwan, where landslides are frequent and abundant. The spectral information is used to assess the pixel land cover class membership probability through a Maximum Likelihood classifier trained with randomly generated synthetic land cover spectral fingerprints, which are obtained from an independent training images dataset. Pixels are classified as landslides when the calculated landslide class membership probability, weighted by a susceptibility model, is higher than membership probabilities of other classes. We generated synthetic fingerprints from two FORMOSAT-2 images acquired in 2009 and tested the procedure on two other images, one in 2005 and the other in 2009. We also obtained two landslide maps through manual interpretation. The agreement between the two sets of inventories is given by the Cohen's k coefficients of 0.62 and 0.64, respectively. This procedure can now classify a new FORMOSAT-2 image automatically facilitating the production of landslide inventory maps.

  19. Suitability aero-geophysical methods for generating conceptual soil maps and their use in the modeling of process-related susceptibility maps

    NASA Astrophysics Data System (ADS)

    Tilch, Nils; Römer, Alexander; Jochum, Birgit; Schattauer, Ingrid

    2014-05-01

    In the past years, several times large-scale disasters occurred in Austria, which were characterized not only by flooding, but also by numerous shallow landslides and debris flows. Therefore, for the purpose of risk prevention, national and regional authorities also require more objective and realistic maps with information about spatially variable susceptibility of the geosphere for hazard-relevant gravitational mass movements. There are many and various proven methods and models (e.g. neural networks, logistic regression, heuristic methods) available to create such process-related (e.g. flat gravitational mass movements in soil) suszeptibility maps. But numerous national and international studies show a dependence of the suitability of a method on the quality of process data and parameter maps (f.e. Tilch & Schwarz 2011, Schwarz & Tilch 2011). In this case, it is important that also maps with detailed and process-oriented information on the process-relevant geosphere will be considered. One major disadvantage is that only occasionally area-wide process-relevant information exists. Similarly, in Austria often only soil maps for treeless areas are available. However, in almost all previous studies, randomly existing geological and geotechnical maps were used, which often have been specially adapted to the issues and objectives. This is one reason why very often conceptual soil maps must be derived from geological maps with only hard rock information, which often have a rather low quality. Based on these maps, for example, adjacent areas of different geological composition and process-relevant physical properties are razor sharp delineated, which in nature appears quite rarly. In order to obtain more realistic information about the spatial variability of the process-relevant geosphere (soil cover) and its physical properties, aerogeophysical measurements (electromagnetic, radiometric), carried out by helicopter, from different regions of Austria were interpreted

  20. Sensitivity analysis of conditioning factors for landslide susceptibility evaluation in Santa Marta de Penaguiño (Douro valley - Portugal

    NASA Astrophysics Data System (ADS)

    Pereira, S.; Zêzere, J. L.; Bateira, C.

    2009-04-01

    The MapRisk project intends to develop a landslide hazard and risk analysis to support planning decisions at the municipal level. The municipality of Santa Marta de Penaguião (70 square kilometres) is one of the test sites of the project. The study area has been affected in recent years by destructive landslides that were responsible for deaths and house and roads destruction. Despite these losses, mitigation and zonation landslide programs are missing, and the land use planning at the municipal level did not solve yet the problem. The study area is located in the Douro Valley region, mainly composed by metamorphic rocks (e.g., schist and quartzites). These rocks are strongly fractured, and weathered materials are abundant in clayed schist, mainly in those areas with agricultural terraces. From the geomorphological point of view, the study area is characterized by a transition landscape between the Marão mountain and the transmontano plateau, with deep incised valleys, tectonic depressions and slopes controlled by the geological structure. This area is characterised by the vineyard monoculture cultivated in agricultural terraces over centuries to produce Oporto wine. The main landslide triggering factor is rainfall and the mean annual precipitation ranges from 2500 mm near Marão mountain to 700 mm in the Corgós Valley. In this area there are historical records of destructive landslides, although they were aggregated in a landslide geodatabase only recently. The most complete landslide inventory was performed in 2005-2008 using aerial photographs interpretation at 1/5.000 scale and field work verification. The geodatabase includes 725 landslides, most of shallow translational slide type (80% of total slope movements). The landslide density is 10.5 events/square kilometre, and the average landslide area is 535 square meters. In this work we present the results of GIS based landslide susceptibility assessment for the shallow translational slides using two

  1. Rainfall-induced landslide susceptibility zonation of Puerto Rico

    Treesearch

    Chiara Lepore; Sameer A. Kamal; Peter Shanahan; Rafael L. Bras

    2011-01-01

    Landslides are a major geologic hazard with estimated tens of deaths and $1–2 billion in economic losses per year in the US alone. The island of Puerto Rico experiences one or two large events per year, often triggered in steeply sloped areas by prolonged and heavy rainfall. Identifying areas susceptible to landslides thus has great potential value for Puerto Rico and...

  2. Slope stability susceptibility evaluation parameter (SSEP) rating scheme - An approach for landslide hazard zonation

    NASA Astrophysics Data System (ADS)

    Raghuvanshi, Tarun Kumar; Ibrahim, Jemal; Ayalew, Dereje

    2014-11-01

    In this paper a new slope susceptibility evaluation parameter (SSEP) rating scheme is presented which is developed as an expert evaluation approach for landslide hazard zonation. The SSEP rating scheme is developed by considering intrinsic and external triggering parameters that are responsible for slope instability. The intrinsic parameters which are considered are; slope geometry, slope material (rock or soil type), structural discontinuities, landuse and landcover and groundwater. Besides, external triggering parameters such as, seismicity, rainfall and manmade activities are also considered. For SSEP empirical technique numerical ratings are assigned to each of the intrinsic and triggering parameters on the basis of logical judgments acquired from experience of studies of intrinsic and external triggering factors and their relative impact in inducing instability to the slope. Further, the distribution of maximum SSEP ratings is based on their relative order of importance in contributing instability to the slope. Finally, summation of all ratings for intrinsic and triggering parameter based on actual observation will provide the expected degree of landslide in a given land unit. This information may be utilized to develop a landslide hazard zonation map. The SSEP technique was applied in the area around Wurgessa Kebelle of North Wollo Zonal Administration, Amhara National Regional State in northern Ethiopia, some 490 km from Addis Ababa. The results obtained indicates that 8.33% of the area fall under Moderately hazard and 83.33% fall within High hazard whereas 8.34% of the area fall under Very high hazard. Further, in order to validate the LHZ map prepared during the study, active landslide activities and potential instability areas, delineated through inventory mapping was overlain on it. All active landslide activities and potential instability areas fall within very high and high hazard zone. Thus, the satisfactory agreement confirms the rationality of

  3. Maps Showing Seismic Landslide Hazards in Anchorage, Alaska

    USGS Publications Warehouse

    Jibson, Randall W.; Michael, John A.

    2009-01-01

    The devastating landslides that accompanied the great 1964 Alaska earthquake showed that seismically triggered landslides are one of the greatest geologic hazards in Anchorage. Maps quantifying seismic landslide hazards are therefore important for planning, zoning, and emergency-response preparation. The accompanying maps portray seismic landslide hazards for the following conditions: (1) deep, translational landslides, which occur only during great subduction-zone earthquakes that have return periods of =~300-900 yr; (2) shallow landslides for a peak ground acceleration (PGA) of 0.69 g, which has a return period of 2,475 yr, or a 2 percent probability of exceedance in 50 yr; and (3) shallow landslides for a PGA of 0.43 g, which has a return period of 475 yr, or a 10 percent probability of exceedance in 50 yr. Deep, translational landslide hazard zones were delineated based on previous studies of such landslides, with some modifications based on field observations of locations of deep landslides. Shallow-landslide hazards were delineated using a Newmark-type displacement analysis for the two probabilistic ground motions modeled.

  4. Maps showing seismic landslide hazards in Anchorage, Alaska

    USGS Publications Warehouse

    Jibson, Randall W.

    2014-01-01

    The devastating landslides that accompanied the great 1964 Alaska earthquake showed that seismically triggered landslides are one of the greatest geologic hazards in Anchorage. Maps quantifying seismic landslide hazards are therefore important for planning, zoning, and emergency-response preparation. The accompanying maps portray seismic landslide hazards for the following conditions: (1) deep, translational landslides, which occur only during great subduction-zone earthquakes that have return periods of =300-900 yr; (2) shallow landslides for a peak ground acceleration (PGA) of 0.69 g, which has a return period of 2,475 yr, or a 2 percent probability of exceedance in 50 yr; and (3) shallow landslides for a PGA of 0.43 g, which has a return period of 475 yr, or a 10 percent probability of exceedance in 50 yr. Deep, translational landslide hazards were delineated based on previous studies of such landslides, with some modifications based on field observations of locations of deep landslides. Shallow-landslide hazards were delineated using a Newmark-type displacement analysis for the two probabilistic ground motions modeled.

  5. Pitfalls in statistical landslide susceptibility modelling

    NASA Astrophysics Data System (ADS)

    Schröder, Boris; Vorpahl, Peter; Märker, Michael; Elsenbeer, Helmut

    2010-05-01

    The use of statistical methods is a well-established approach to predict landslide occurrence probabilities and to assess landslide susceptibility. This is achieved by applying statistical methods relating historical landslide inventories to topographic indices as predictor variables. In our contribution, we compare several new and powerful methods developed in machine learning and well-established in landscape ecology and macroecology for predicting the distribution of shallow landslides in tropical mountain rainforests in southern Ecuador (among others: boosted regression trees, multivariate adaptive regression splines, maximum entropy). Although these methods are powerful, we think it is necessary to follow a basic set of guidelines to avoid some pitfalls regarding data sampling, predictor selection, and model quality assessment, especially if a comparison of different models is contemplated. We therefore suggest to apply a novel toolbox to evaluate approaches to the statistical modelling of landslide susceptibility. Additionally, we propose some methods to open the "black box" as an inherent part of machine learning methods in order to achieve further explanatory insights into preparatory factors that control landslides. Sampling of training data should be guided by hypotheses regarding processes that lead to slope failure taking into account their respective spatial scales. This approach leads to the selection of a set of candidate predictor variables considered on adequate spatial scales. This set should be checked for multicollinearity in order to facilitate model response curve interpretation. Model quality assesses how well a model is able to reproduce independent observations of its response variable. This includes criteria to evaluate different aspects of model performance, i.e. model discrimination, model calibration, and model refinement. In order to assess a possible violation of the assumption of independency in the training samples or a possible

  6. Landslide Susceptibility Analysis along Li-Shing Mountain Road in Nantou County, Taiwan

    NASA Astrophysics Data System (ADS)

    Yeh, J. H.; Chan, H. C.; Chen, B. A.

    2016-12-01

    Slopeland hazards are frequently occurred during typhoon periods in the mountain areas of Taiwan. The Li-Shing Mountain Road was suffered from the landslide and erosion of road foundation due to its fragile geological structure, overuse of land, and heavy rainfall. Transportation of agricultural produce in Li-Shing areas was seriously affected while the Li-Shing Mountain Road was blocked by the landslides. To evaluate the landslide susceptibilities along the Li-Shing Mountain Road, this study collected the landslide inventories from Typhoon Mindulle in July, 2004 and Typhoon Kalmaegi in July, 2008. By combining the landslide inventories with hydrological and geological factors, such as rainfall, distance to river, geology, and land slope and aspect, the Instability Index Method was used to specify the landslide susceptibilities of the slopes along the Li-Shing Mountain Road. The accuracy of the present model was evaluated by comparison of the predicted and the typhoon triggered landslides. Finally, the high landslide potential slopes along the Li-Shing Mountain Road were identified. It is expected to provide the information for landslide warning system and engineering countermeasures planning along the Li-Shing Mountain Road. Keywords: Landslide, Instability Index Method, Li-Shing Mountain Road

  7. Towards a Quasi-global precipitation-induced Landslide Detection System using Remote Sensing Information

    NASA Astrophysics Data System (ADS)

    Adler, B.; Hong, Y.; Huffman, G.; Negri, A.; Pando, M.

    2006-05-01

    Landslides and debris flows are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage per year. Currently, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides. In this study, global landslide susceptibility is mapped using USGS GTOPO30 Digital Elevation, hydrological derivatives (slopes and wetness index etc.) from HYDRO1k data, soil type information downscaled from Digital Soil Map of the World (Sand, Loam, Silt, or Clay etc.), and MODIS land cover/use classification data. These variables are then combined with empirical landslide inventory data, if available, to derive a global landslide susceptibility map at elemental resolution of 1 x 1 km. This map can then be overlain with the driving force, namely rainfall estimates from the TRMM-based Multiple-satellite Precipitation Analysis to identify when areas with significant landslide potential receive heavy rainfall. The relations between rainfall intensity and rainstorm duration are regionally specific and often take the form of a power-law relation. Several empirical landslide-triggering Rainfall Intensity-Duration thresholds are implemented regionally using the 8-year TRMM-based precipitation with or without the global landslide susceptibility map at continuous space and time domain. Finally, the effectiveness of this system is validated by studying several recent deadly landslide/mudslide events. This study aims to build up a prototype quasi-global potential landslide warning system. Spatially-distributed landslide susceptibility maps and regional empirical rainfall intensity-duration thresholds, in combination with real-time rainfall measurements from space and rainfall forecasts from models, will be the basis for this experimental system.

  8. Predictive susceptibility analysis of typhoon induced landslides in Central Taiwan

    NASA Astrophysics Data System (ADS)

    Shou, Keh-Jian; Lin, Zora

    2017-04-01

    Climate change caused by global warming affects Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary, such as 2004 Mindulle and 2009 Morakot, hit Taiwan and induced serious flooding and landslides. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the adopted Wu River watershed in Central Taiwan. To assess the spatial hazard of the landslides, landslide susceptibility analysis was also applied. Different types of rainfall factors were tested in the susceptibility models for a better accuracy. In addition, the routes of typhoons were also considered in the predictive analysis. The results of predictive analysis can be applied for risk prevention and management in the study area.

  9. Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

    NASA Astrophysics Data System (ADS)

    Kusratmoko, Eko; Wibowo, Adi; Cholid, Sofyan; Pin, Tjiong Giok

    2017-07-01

    This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng' village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.

  10. Probabilistic, Seismically-Induced Landslide Hazard Mapping of Western Oregon

    NASA Astrophysics Data System (ADS)

    Olsen, M. J.; Sharifi Mood, M.; Gillins, D. T.; Mahalingam, R.

    2015-12-01

    Earthquake-induced landslides can generate significant damage within urban communities by damaging structures, obstructing lifeline connection routes and utilities, generating various environmental impacts, and possibly resulting in loss of life. Reliable hazard and risk maps are important to assist agencies in efficiently allocating and managing limited resources to prepare for such events. This research presents a new methodology in order to communicate site-specific landslide hazard assessments in a large-scale, regional map. Implementation of the proposed methodology results in seismic-induced landslide hazard maps that depict the probabilities of exceeding landslide displacement thresholds (e.g. 0.1, 0.3, 1.0 and 10 meters). These maps integrate a variety of data sources including: recent landslide inventories, LIDAR and photogrammetric topographic data, geology map, mapped NEHRP site classifications based on available shear wave velocity data in each geologic unit, and USGS probabilistic seismic hazard curves. Soil strength estimates were obtained by evaluating slopes present along landslide scarps and deposits for major geologic units. Code was then developed to integrate these layers to perform a rigid, sliding block analysis to determine the amount and associated probabilities of displacement based on each bin of peak ground acceleration in the seismic hazard curve at each pixel. The methodology was applied to western Oregon, which contains weak, weathered, and often wet soils at steep slopes. Such conditions have a high landslide hazard even without seismic events. A series of landslide hazard maps highlighting the probabilities of exceeding the aforementioned thresholds were generated for the study area. These output maps were then utilized in a performance based design framework enabling them to be analyzed in conjunction with other hazards for fully probabilistic-based hazard evaluation and risk assessment. a) School of Civil and Construction

  11. Landslide triggering-thickness susceptibility, a simple proxy for landslide hazard? A test in the Mili catchment (North-Eastern Sicily, Italy)

    NASA Astrophysics Data System (ADS)

    Lombardo, Luigi; Fubelli, Giandomenico; Amato, Gabriele; Bonasera, Mauro; Mai, Martin

    2016-04-01

    This study implements a landslide triggering-thickness susceptibility approach in order to investigate the landslide scenario in the catchment of Mili, this being located in the north-easternmost sector of Sicily (Italy). From a detailed geomorphological campaign, thicknesses of mobilised materials at the triggering zone of each mass movement were collected and subsequently used as a dependent variable to be analysed in the framework of spatial predictive models. The adopted modelling methodology consisted of a presence-only learning algorithm which differently from classic presence-absence methods does not rely on stable conditions in order to derive functional relationships between dependent and independent variables. The dependent was pre-processed by reclassifying the crown thickness spectrum into a binary condition expressing thick (values equal or greater than 1m) and thin (values less than 1m) landslide crown classes. The explanatory variables were selected to express triggering-thickness dependency at different scales, these being in close proximity to the triggering point through primary and secondary attributes from a 2m-cell side Lidar HRDEM, at a medium scale through vegetation indexes from multispectral satellite images (ASTER) and a coarser scale through a geological, land use and tectonic maps. The choice of a presence-only approach allowed to effectively discriminate between the two types of landslide thicknesses at the triggering zone, producing excellent prediction skills associated with relatively low variances across a set of 50 randomly generated replicates. In addition, the role of each predictor was assessed for the two considered classes as relevant differences arose in terms of their contribution to the final models. In this regard, predictor importance, Jack-knife tests and response curves were used to assess the reliability of the models together with their geomorphological reasonability. This work attempts to capitalize on fieldwork data

  12. Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods

    NASA Astrophysics Data System (ADS)

    Pham, Binh Thai; Tien Bui, Dieu; Pourghasemi, Hamid Reza; Indra, Prakash; Dholakia, M. B.

    2017-04-01

    The objective of this study is to make a comparison of the prediction performance of three techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural Nets), and Naïve Bayes (NB) for landslide susceptibility assessment at the Uttarakhand Area (India). Firstly, a landslide inventory map with 430 landslide locations in the study area was constructed from various sources. Landslide locations were then randomly split into two parts (i) 70 % landslide locations being used for training models (ii) 30 % landslide locations being employed for validation process. Secondly, a total of eleven landslide conditioning factors including slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to lineaments, distance to rivers, and rainfall were used in the analysis to elucidate the spatial relationship between these factors and landslide occurrences. Feature selection of Linear Support Vector Machine (LSVM) algorithm was employed to assess the prediction capability of these conditioning factors on landslide models. Subsequently, the NB, MLP Neural Nets, and FT models were constructed using training dataset. Finally, success rate and predictive rate curves were employed to validate and compare the predictive capability of three used models. Overall, all the three models performed very well for landslide susceptibility assessment. Out of these models, the MLP Neural Nets and the FT models had almost the same predictive capability whereas the MLP Neural Nets (AUC = 0.850) was slightly better than the FT model (AUC = 0.849). The NB model (AUC = 0.838) had the lowest predictive capability compared to other models. Landslide susceptibility maps were final developed using these three models. These maps would be helpful to planners and engineers for the development activities and land-use planning.

  13. Potential of SENTINEL-1A for Nation-Wide Routine Updates of Active Landslide Maps

    NASA Astrophysics Data System (ADS)

    Lazecky, M.; Canaslan Comut, F.; Nikolaeva, E.; Bakon, M.; Papco, J.; Ruiz-Armenteros, A. M.; Qin, Y.; de Sousa, J. J. M.; Ondrejka, P.

    2016-06-01

    Slope deformation is one of the typical geohazards that causes an extensive economic damage in mountainous regions. As such, they are usually intensively monitored by means of modern expertise commonly by national geological or emergency services. Resulting landslide susceptibility maps, or landslide inventories, offer an overview of areas affected by previously activated landslides as well as slopes known to be unstable currently. Current slope instabilities easily transform into a landslide after various triggering factors, such as an intensive rainfall or a melting snow cover. In these inventories, the majority of the existing landslide-affected slopes are marked as either stable or active, after a continuous investigative work of the experts in geology. In this paper we demonstrate the applicability of Sentinel-1A satellite SAR interferometry (InSAR) to assist by identifying slope movement activity and use the information to update national landslide inventories. This can be done reliably in cases of semi-arid regions or low vegetated slopes. We perform several analyses based on multitemporal InSAR techniques of Sentinel-1A data over selected areas prone to landslides.

  14. Landslides triggered by Hurricane Mitch in Guatemala -- inventory and discussion

    USGS Publications Warehouse

    Bucknam, Robert C.; Coe, Jeffrey A.; Chavarria, Manuel Mota; Godt, Jonathan W.; Tarr, Arthur C.; Bradley, Lee-Ann; Rafferty, Sharon A.; Hancock, Dean; Dart, Richard L.; Johnson, Margo L.

    2001-01-01

    Upper Polochic valley and surrounding highlands and in the central Sierra de las Minas. The lower rainfall amounts (200 mm to 400 mm) occurred in the hills surrounding La Union, the eastern Sierra de las Minas, and in the border region with Honduras. In general, the rainfall received in these areas is roughly equivalent to the average precipitation received in a 1-year period. We used 10-m digital elevation models (DEMs) generated from contours on two quadrangles in the central Sierra de las Minas to create a map showing areas that were susceptible to landslides during Hurricane Mitch. To create the Hurricane Mitch susceptibility map, we developed a susceptibility threshold equation based on elevation and gradient. The analysis indicates that, at least on two quadrangles, gradients less than 9? were not susceptible to landslides during Hurricane Mitch. The slope of the line defined by the threshold equation indicates that less rainfall was required to initiate landslides on steep gradients than on shallow gradients. Ninety percent of the mapped landslides that were triggered by Hurricane Mitch are within the susceptible zone shown on the map. Eightysix percent of landslides that were mapped as predating Hurricane Mitch, and all landslides mapped as postdating Hurricane Mitch, are within the susceptible zone. We used LAHARZ software to model the potential downstream area affected by debris if a large landslide dam on the Rio La Lima were to fail. The model shows that the area affected would be similar to the area that was affected by a debris flow that mobilized from a large landslide along the Rio La Lima during Hurricane Mitch. The characteristics of rainfall-triggered landslides described in this report can be used as a partial guide to future landslide activity triggered by rainstorms. On the basis of existing data, hazardous areas include: moderate to steep hillslopes and

  15. Mapping Surface Features Produced by an Active Landslide

    NASA Astrophysics Data System (ADS)

    Parise, Mario; Gueguen, Erwan; Vennari, Carmela

    2016-10-01

    A large landslide reactivated on December 2013, at Montescaglioso, southern Italy, after 56 hours of rainfall. The landslide disrupted over 500 m of a freeway, involved a few warehouses, a supermarket, and private homes. After the event, it has been performed field surveys, aided by visual analysis of terrestrial and helicopter photographs, to compile a map of the surface deformations. The geomorphological features mapped included single fractures, sets of fractures, tension cracks, trenches, and pressure ridges. In this paper we present the methodology used, the map obtained through the intensive field work, and discuss the main surface features produced by the landslide.

  16. Landslide Hazard Mapping in Rwanda Using Logistic Regression

    NASA Astrophysics Data System (ADS)

    Piller, A.; Anderson, E.; Ballard, H.

    2015-12-01

    Landslides in the United States cause more than $1 billion in damages and 50 deaths per year (USGS 2014). Globally, figures are much more grave, yet monitoring, mapping and forecasting of these hazards are less than adequate. Seventy-five percent of the population of Rwanda earns a living from farming, mostly subsistence. Loss of farmland, housing, or life, to landslides is a very real hazard. Landslides in Rwanda have an impact at the economic, social, and environmental level. In a developing nation that faces challenges in tracking, cataloging, and predicting the numerous landslides that occur each year, satellite imagery and spatial analysis allow for remote study. We have focused on the development of a landslide inventory and a statistical methodology for assessing landslide hazards. Using logistic regression on approximately 30 test variables (i.e. slope, soil type, land cover, etc.) and a sample of over 200 landslides, we determine which variables are statistically most relevant to landslide occurrence in Rwanda. A preliminary predictive hazard map for Rwanda has been produced, using the variables selected from the logistic regression analysis.

  17. Towards an EO-based Landslide Web Mapping and Monitoring Service

    NASA Astrophysics Data System (ADS)

    Hölbling, Daniel; Weinke, Elisabeth; Albrecht, Florian; Eisank, Clemens; Vecchiotti, Filippo; Friedl, Barbara; Kociu, Arben

    2017-04-01

    National and regional authorities and infrastructure maintainers in mountainous regions require accurate knowledge of the location and spatial extent of landslides for hazard and risk management. Information on landslides is often collected by a combination of ground surveying and manual image interpretation following landslide triggering events. However, the high workload and limited time for data acquisition result in a trade-off between completeness, accuracy and detail. Remote sensing data offers great potential for mapping and monitoring landslides in a fast and efficient manner. While facing an increased availability of high-quality Earth Observation (EO) data and new computational methods, there is still a lack in science-policy interaction and in providing innovative tools and methods that can easily be used by stakeholders and users to support their daily work. Taking up this issue, we introduce an innovative and user-oriented EO-based web service for landslide mapping and monitoring. Three central design components of the service are presented: (1) the user requirements definition, (2) the semi-automated image analysis methods implemented in the service, and (3) the web mapping application with its responsive user interface. User requirements were gathered during semi-structured interviews with regional authorities. The potential users were asked if and how they employ remote sensing data for landslide investigation and what their expectations to a landslide web mapping service regarding reliability and usability are. The interviews revealed the capability of our service for landslide documentation and mapping as well as monitoring of selected landslide sites, for example to complete and update landslide inventory maps. In addition, the users see a considerable potential for landslide rapid mapping. The user requirements analysis served as basis for the service concept definition. Optical satellite imagery from different high resolution (HR) and very high

  18. A seismic landslide susceptibility rating of geologic units based on analysis of characterstics of landslides triggered by the 17 January, 1994 Northridge, California earthquake

    USGS Publications Warehouse

    Parise, M.; Jibson, R.W.

    2000-01-01

    One of the most significant effects of the 17 January, 1994 Northridge, California earthquake (M=6.7) was the triggering of thousands of landslides over a broad area. Some of these landslides damaged and destroyed homes and other tructures, blocked roads, disrupted pipelines, and caused other serious damage. Analysis of the distribution and characteristics of these landslides is important in understanding what areas may be susceptible to landsliding in future earthquakes. We analyzed the frequency, distribution, and geometries of triggered landslides in the Santa Susana 7.5??? quadrangle, an area of intense seismic landslide activity near the earthquake epicenter. Landslides occured primarily in young (Late Miocene through Pleistocene) uncemented or very weakly cemented sediment that has been repeatedly folded, faulted, and uplifted in the past 1.5 million years. The most common types of landslide triggered by the earthquake were highly disrupted, shallow falls and slides of rock and debris. Far less numerous were deeper, more coherent slumps and block slides, primarily occuring in more cohesive or competent materials. The landslides in the Santa Susana quadrangle were divided into two samples: single landslides (1502) and landslide complexes (60), which involved multiple coalescing failures of surficial material. We described landslide, morphologies by computing simple morphometric parameters (area, length, width, aspect ratio, slope angle). To quantify and rank the relative susceptibility of each geologic unit to seismic landsliding, we calculated two indices: (1) the susceptibility index, which is the ratio (given as a percentage) of the area covered by landslide sources within a geologic unit to the total outcrop area of that unit: and (2) the frequency index [given in landslides per square kilometer (ls/km2)], which is the total number of landslides within each geologic unit divided by the outcrop area of that unit. Susceptibility categories include very high

  19. Land subsidence susceptibility and hazard mapping: the case of Amyntaio Basin, Greece

    NASA Astrophysics Data System (ADS)

    Tzampoglou, P.; Loupasakis, C.

    2017-09-01

    Landslide susceptibility and hazard mapping has been applying for more than 20 years succeeding the assessment of the landslide risk and the mitigation the phenomena. On the contrary, equivalent maps aiming to study and mitigate land subsidence phenomena caused by the overexploitation of the aquifers are absent from the international literature. The current study focuses at the Amyntaio basin, located in West Macedonia at Florina prefecture. As proved by numerous studies the wider area has been severely affected by the overexploitation of the aquifers, caused by the mining and the agricultural activities. The intensive ground water level drop has triggered extensive land subsidence phenomena, especially at the perimeter of the open pit coal mine operating at the site, causing damages to settlements and infrastructure. The land subsidence susceptibility and risk maps were produced by applying the semi-quantitative WLC (Weighted Linear Combination) method, especially calibrated for this particular catastrophic event. The results were evaluated by using detailed field mapping data referring to the spatial distribution of the surface ruptures caused by the subsidence. The high correlation between the produced maps and the field mapping data, have proved the great value of the maps and of the applied technique on the management and the mitigation of the phenomena. Obviously, these maps can be safely used by decision-making authorities for the future urban safety development.

  20. Changes and future trends in landslide risk mapping for mountain communities: application to the Vars catchment and Barcelonnette basin (French Alps)

    NASA Astrophysics Data System (ADS)

    Puissant, Anne; Wernert, Pauline; Débonnaire, Nicolas; Malet, Jean-Philippe; Bernardie, Séverine; Thomas, Loic

    2017-04-01

    Landslide risk assessment has become a major research subject within the last decades. In the context of the French-funded ANR Project SAMCO which aims at enhancing the overall resilience of societies on the impacts of mountain risks, we developed a procedure to quantify changes in landslide risk at catchment scales. First, we investigate landslide susceptibility, the spatial component of the hazard, through a weight of evidence probabilistic model. This latter is based on the knowledge of past and current landslides in order to simulate their spatial locations in relation to environmental controlling factors. Second, we studied potential consequences using a semi-quantitative region-scale indicator-based method, called method of the Potential Damage Index (PDI). It allows estimating the possible damages related to landslides by combining weighted indicators reflecting the exposure of the element at risk for structural, functional and socio-economic stakes. Finally, we provide landslide risk maps by combining both susceptibility and potential consequence maps resulting from the two previous steps. The risk maps are produced for the present time and for the future (e.g. period 2050 and 2100) taking into account four scenarios of future landcover and landuse development (based on the Prelude European Project) that are consistent with the likely evolution of mountain communities. Results allow identifying the geographical areas that are likely to be exposed to landslide risk in the future. The results are integrated on a web-based demonstrator, enabling the comparison between various scenarios, and could thus be used as decision-support tools for local stakeholders. The method and the demonstrator will be presented through the analysis of landslide risk in two catchments of the French Alps: the Vars catchment and the Barcelonnette basin, both characterized by a different exposure to landslide hazards.

  1. Debris flows susceptibility mapping under tropical rain conditions in Rwanda.

    NASA Astrophysics Data System (ADS)

    Nduwayezu, Emmanuel; Nsengiyumva, Jean-Baptiste; BUgnon, Pierre-Charles; Jaboyedoff, Michel; Derron, Marc-Henri

    2017-04-01

    Rwanda is a densely populated country. It means that all the space is exploited, including sometimes areas with very steep slopes. This has as for consequences that during the rainy season slopes with human activities are affected by gravitational processes, mostly debris and mud flows and shallow landslides. The events of early May 2016 (May 8 and 9), with more than 50 deaths, are an illustration of these frequents landslides and inundations. The goal of this work is to produce a susceptibility map for debris/mud flows at regional/national scale. Main available pieces of data are a national digital terrain model at 10m resolution, bedrock and soil maps, and information collected during field visits on some specific localities. The first step is the characterization of the slope angle distribution for the different types of bedrock or soils (decomposition in Gaussian populations). Then, the combination of this information with other geomorphic and hydrologic parameters is used to define potential source areas of debris flows. Finally, propagation maps of debris flows are produced using FLOW-R (Horton et al. 2013). Horton, P., Jaboyedoff, M., Rudaz, B., and Zimmermann, M.: Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale, Nat. Hazards Earth Syst. Sci., 13, 869-885, doi:10.5194/nhess-13-869-2013, 2013. The paper is in open access.

  2. Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

    NASA Astrophysics Data System (ADS)

    Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

    2018-02-01

    As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

  3. Landslide susceptibility estimations in the Gerecse hills (Hungary).

    NASA Astrophysics Data System (ADS)

    Gerzsenyi, Dávid; Gáspár, Albert

    2017-04-01

    Surface movement processes are constantly posing threat to property in populated and agricultural areas in the Gerecse hills (Hungary). The affected geological formations are mainly unconsolidated sediments. Pleistocene loess and alluvial terrace sediments are overwhelmingly present, but fluvio-lacustrine sediments of the latest Miocene, and consolidated Eocene and Mesozoic limestones and marls can also be found in the area. Landslides and other surface movement processes are being studied for a long time in the area, but a comprehensive GIS-based geostatistical analysis have not yet been made for the whole area. This was the reason for choosing the Gerecse as the focus area of the study. However, the base data of our study are freely accessible from online servers, so the used method can be applied to other regions in Hungary. Qualitative data was acquired from the landslide-inventory map of the Hungarian Surface Movement Survey and from the Geological Map of Hungary (1 : 100 000). Morphometric parameters derived from the SRMT-1 DEM were used as quantitative variables. Using these parameters the distribution of elevation, slope gradient, aspect and categorized geological features were computed, both for areas affected and not affected by slope movements. Then likelihood values were computed for each parameters by comparing their distribution in the two areas. With combining the likelihood values of the four parameters relative hazard values were computed for each cell. This method is known as the "empirical probability estimation" originally published by Chung (2005). The map created this way shows each cell's place in their ranking based on the relative hazard values as a percentage for the whole study area (787 km2). These values provide information about how similar is a certain area to the areas already affected by landslides based on the four predictor variables. This map can also serve as a base for more complex landslide vulnerability studies involving

  4. Variations in the susceptibility to landslides, as a consequence of land cover changes: A look to the past, and another towards the future.

    PubMed

    Pisano, L; Zumpano, V; Malek, Ž; Rosskopf, C M; Parise, M

    2017-12-01

    Land cover is one of the most important conditioning factors in landslide susceptibility analysis. Usually it is considered as a static factor, but it has proven to be dynamic, with changes occurring even in few decades. In this work the influence of land cover changes on landslide susceptibility are analyzed for the past and for future scenarios. For the application, an area representative of the hilly-low mountain sectors of the Italian Southern Apennines was chosen (Rivo basin, in Molise Region). With this purpose landslide inventories and land cover maps were produced for the years 1954, 1981 and 2007. Two alternative future scenarios were created for 2050, one which follows the past trend (2050-trend), and another one more extreme, foreseeing a decrease of forested and cultivated areas (2050-alternative). The landslide susceptibility analysis was performed using the Spatial Multi-Criteria Evaluation method for different time steps, investigating changes to susceptibility over time. The results show that environmental dynamics, such as land cover change, affect slope stability in time. In fact there is a decrease of susceptibility in the past and in the future 2050-trend scenario. This is due to the increase of forest or cultivated areas, that is probably determined by a better land management, water and soil control respect to other land cover types such as shrubland, pasture or bareland. Conversely the results revealed by the alternative scenario (2050-alternative), show how the decrease in forest and cultivated areas leads to an increase in landslide susceptibility. This can be related to the assumed worst climatic condition leading to a minor agricultural activity and lower extension of forested areas, possibly associated also to the effects of forest fires. The results suggest that conscious landscape management might contribute to determine a significant reduction in landslide susceptibility. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Landslide-susceptibility analysis using light detection and ranging-derived digital elevation models and logistic regression models: a case study in Mizunami City, Japan

    NASA Astrophysics Data System (ADS)

    Wang, Liang-Jie; Sawada, Kazuhide; Moriguchi, Shuji

    2013-01-01

    To mitigate the damage caused by landslide disasters, different mathematical models have been applied to predict landslide spatial distribution characteristics. Although some researchers have achieved excellent results around the world, few studies take the spatial resolution of the database into account. Four types of digital elevation model (DEM) ranging from 2 to 20 m derived from light detection and ranging technology to analyze landslide susceptibility in Mizunami City, Gifu Prefecture, Japan, are presented. Fifteen landslide-causative factors are considered using a logistic-regression approach to create models for landslide potential analysis. Pre-existing landslide bodies are used to evaluate the performance of the four models. The results revealed that the 20-m model had the highest classification accuracy (71.9%), whereas the 2-m model had the lowest value (68.7%). In the 2-m model, 89.4% of the landslide bodies fit in the medium to very high categories. For the 20-m model, only 83.3% of the landslide bodies were concentrated in the medium to very high classes. When the cell size decreases from 20 to 2 m, the area under the relative operative characteristic increases from 0.68 to 0.77. Therefore, higher-resolution DEMs would provide better results for landslide-susceptibility mapping.

  6. Spatial prediction of landslide susceptibility in parts of Garhwal Himalaya, India, using the weight of evidence modelling.

    PubMed

    Guri, Pardeep Kumar; Ray, P K Champati; Patel, Ramesh Chandra

    2015-06-01

    Garhwal Himalaya in northern India has emerged as one of the most prominent hot spots of landslide occurrences in the Himalaya mainly due to geological causes related to mountain building processes, steep topography and frequent occurrences of extreme precipitation events. As this region has many pilgrimage and tourist centres, it is visited by hundreds of thousands of people every year, and in the recent past, there has been rapid development to provide adequate roads and building infrastructure. Additionally, attempts are also made to harness hydropower by constructing tunnels, dams and reservoirs and thus altering vulnerable slopes at many places. As a result, the overall risk due to landslide hazards has increased many folds and, therefore, an attempt was made to assess landslide susceptibility using 'Weights of Evidence (WofE)', a well-known bivariate statistical modelling technique implemented in a much improved way using remote sensing and Geographic Information System. This methodology has dual advantage as it demonstrates how to derive critical parameters related to geology, geomorphology, slope, land use and most importantly temporal landslide distribution in one of the data scarce region of the world. Secondly, it allows to experiment with various combination of parameters to assess their cumulative effect on landslides. In total, 15 parameters related to geology, geomorphology, terrain, hydrology and anthropogenic factors and 2 different landslide inventories (prior to 2007 and 2008-2011) were prepared from high-resolution Indian remote sensing satellite data (Cartosat-1 and Resourcesat-1) and were validated by field investigation. Several combinations of parameters were carried out using WofE modelling, and finally using best combination of eight parameters, 76.5 % of overall landslides were predicted in 24 % of the total area susceptible to landslide occurrences. The study has highlighted that using such methodology landslide susceptibility assessment

  7. Application of Landsat-8 and ALOS-2 data for structural and landslide hazard mapping in Kelantan, Malaysia

    NASA Astrophysics Data System (ADS)

    Beiranvand Pour, Amin; Hashim, Mazlan

    2017-07-01

    Identification of high potential risk and susceptible zones for natural hazards of geological origin is one of the most important applications of advanced remote sensing technology. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan River basin, Peninsular Malaysia. Flooding and subsequent landslide occurrences generated significant damage to livestock, agricultural produce, homes and businesses in the Kelantan River basin. In this study, remote sensing data from the recently launched Landsat-8 and Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) on board the Advanced Land Observing Satellite-2 (ALOS-2) were used to map geologic structural and topographical features in the Kelantan River basin for identification of high potential risk and susceptible zones for landslides and flooding areas. The data were processed for a comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. The analytical hierarchy process (AHP) approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index (NDVI), land cover, distance to drainage, precipitation, distance to fault and distance to the road were extracted from remote sensing satellite data and fieldwork to apply the AHP approach. Directional convolution filters were applied to ALOS-2 data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ) in the west and Lebir Fault Zone in the east of the Kelantan state. The combination of different polarization channels produced image maps that contain important information related to water bodies, wetlands and lithological units. The N-S, NE-SW and NNE-SSW lineament trends and

  8. Landslide databases review in the Geological Surveys of Europe

    NASA Astrophysics Data System (ADS)

    Herrera, Gerardo

    2017-04-01

    Landslides are one of the most widespread geohazards in Europe, producing significant social and economic damages. Rapid population growth in urban areas throughout many countries in Europe and extreme climatic scenarios can considerably increase landslide risk in the near future. However, many European countries do not include landslide risk into their legislation. Countries lack official methodological assessment guidelines and knowledge about landslide impacts. Although regional and national landslide databases exist in most countries, they are often not integrated because they are owed by different institutions. Hence, a European Landslides Directive, that provides a common legal framework for dealing with landslides, is necessary. With this long-term goal in mind, we present a review of the landslide databases from the Geological Surveys of Europe focusing on their interoperability. The same landslide classification was used for the 849,543 landslide records from the Geological Surveys, from which 36% are slides, 10 % falls, 20% flows, 11% complex slides and 24% remain either unclassified or correspond to another typology. A landslide density map was produced from the available records of the Geological Surveys of 17 countries showing the variable distribution of landslides. There are 0.2 million km2 of landslide prone areas. The comparison of this map with the European landslide susceptibility map ELSUS v1 was successful for 73% of the predictions, and permitted identification of 25% of susceptible areas where landslide records are not available from the Geological Surveys. Taking these results into account the completeness of these landslide databases was evaluated, revealing different landslide hazard management approaches between surveys and countries.

  9. Exploiting Synthetic Aperture Radar data to map and observe landslides

    NASA Astrophysics Data System (ADS)

    Bekaert, D. P.; Agram, P. S.; Fattahi, H.; Kirschbaum, D.; Amatya, P. M.; Stanley, T.

    2017-12-01

    Synthetic Aperture Radar instruments onboard satellites or airborne platforms are a powerful means to study landslides. How to best exploit the data and which techniques to apply strongly depend on the region of study and the landslide type which occurs. The amount of vegetation, snowfall, and steepness of the terrain, as well the shadowing effects of the mountain will determine if SAR is suitable to map a given landslide. Fast moving landslides occurring over a large area (e.g. >100 m) could benefit from pixel or feature tracking, while for slower moving landslides Interferometric SAR could be a more favorable approach. However, neither of those methods would work for critical landslide failures which do not preserve surface features. This type of slides would benefit from a change detection approach. Here we look at these three different cases and utilize Sentinel-1 space-borne SAR data and state-of-the-art processing techniques to map multiple landslides along the California State Route 1 and the Trishuli highway in the Langtang valley of Nepal. Our findings correlate with existing landslide catalogues and also identify landslides in regions earlier mapped to be dormant.

  10. Criteria for the optimal selection of remote sensing optical images to map event landslides

    NASA Astrophysics Data System (ADS)

    Fiorucci, Federica; Giordan, Daniele; Santangelo, Michele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

    2018-01-01

    Landslides leave discernible signs on the land surface, most of which can be captured in remote sensing images. Trained geomorphologists analyse remote sensing images and map landslides through heuristic interpretation of photographic and morphological characteristics. Despite a wide use of remote sensing images for landslide mapping, no attempt to evaluate how the image characteristics influence landslide identification and mapping exists. This paper presents an experiment to determine the effects of optical image characteristics, such as spatial resolution, spectral content and image type (monoscopic or stereoscopic), on landslide mapping. We considered eight maps of the same landslide in central Italy: (i) six maps obtained through expert heuristic visual interpretation of remote sensing images, (ii) one map through a reconnaissance field survey, and (iii) one map obtained through a real-time kinematic (RTK) differential global positioning system (dGPS) survey, which served as a benchmark. The eight maps were compared pairwise and to a benchmark. The mismatch between each map pair was quantified by the error index, E. Results show that the map closest to the benchmark delineation of the landslide was obtained using the higher resolution image, where the landslide signature was primarily photographical (in the landslide source and transport area). Conversely, where the landslide signature was mainly morphological (in the landslide deposit) the best mapping result was obtained using the stereoscopic images. Albeit conducted on a single landslide, the experiment results are general, and provide useful information to decide on the optimal imagery for the production of event, seasonal and multi-temporal landslide inventory maps.

  11. PenMap demonstration project, landslide mapping system

    DOT National Transportation Integrated Search

    2002-12-01

    This report documents the findings of a technology transfer project to demonstrate the effectiveness of a portable field mapping system to landslide field reconnaissance work. The objective of this project was to expose the latest field data collecti...

  12. The Rock Engineering System (RES) applied to landslide susceptibility zonation of the northeastern flank of Etna: methodological approach and results

    NASA Astrophysics Data System (ADS)

    Apuani, Tiziana; Corazzato, Claudia

    2015-04-01

    Ground deformations in the northeastern flank of Etna are well known. Despite only a few landslide events have been documented, these have significantly involved and damaged lifelines and buildings. These events are mainly related to the activity of the volcano-tectonic structures and associated seismicity, as in the case of the 2002 reactivation of the Presa landslide during an increased activity of the Pernicana fault system. In order to highlight the areal distribution of potentially unstable slopes based on a detailed, site-specific study of the factors responsible for landslide, and to ultimately contribute to risk management, a landslide susceptibility analysis of the northeastern flank of Etna in the Pernicana area was carried out, and a susceptibility map at 1:10.000 scale was produced, extending over an area of 168 km2. Different methods are proposed in the literature to obtain the regional distribution of potentially unstable slopes, depending on the problem scale, the slope dynamic evolution in the geological context, and the availability of data. Among semi-quantitative approaches, the present research combines the Rock Engineering System (RES) methodology with parameter zonation mapping in a GIS environment. The RES method represents a structured approach to manage a high number of interacting factors involved in the instability problem. A numerically coded, site-specific interaction matrix (IM) analyzes the cause-effect relationship in these factors, and calculates the degree of interactivity of each parameter, normalized by the overall interactivity of the system (weight factor). In the specific Etna case, the considered parameters are: slope attitude, lithotechnical properties (lithology, structural complexity, soil and rock mass quality), land use, tectonic structures, seismic activity (horizontal acceleration) and hydrogeological conditions (groundwater and drainage). Thematic maps are prepared at 1:10.000 scale for each of these parameters, and

  13. Sentinel-2 for rapid operational landslide inventory mapping

    NASA Astrophysics Data System (ADS)

    Stumpf, André; Marc, Odin; Malet, Jean-Philippe; Michea, David

    2017-04-01

    Landslide inventory mapping after major triggering events such as heavy rainfalls or earthquakes is crucial for disaster response, the assessment of hazards, and the quantification of sediment budgets and empirical scaling laws. Numerous studies have already demonstrated the utility of very-high resolution satellite and aerial images for the elaboration of inventories based on semi-automatic methods or visual image interpretation. Nevertheless, such semi-automatic methods are rarely used in an operational context after major triggering events; this is partly due to access limitations on the required input datasets (i.e. VHR satellite images) and to the absence of dedicated services (i.e. processing chain) available for the landslide community. Several on-going initiatives allow to overcome these limitations. First, from a data perspective, the launch of the Sentinel-2 mission offers opportunities for the design of an operational service that can be deployed for landslide inventory mapping at any time and everywhere on the globe. Second, from an implementation perspective, the Geohazards Exploitation Platform (GEP) of the European Space Agency (ESA) allows the integration and diffusion of on-line processing algorithms in a high computing performance environment. Third, from a community perspective, the recently launched Landslide Pilot of the Committee on Earth Observation Satellites (CEOS), has targeted the take-off of such service as a main objective for the landslide community. Within this context, this study targets the development of a largely automatic, supervised image processing chain for landslide inventory mapping from bi-temporal (before and after a given event) Sentinel-2 optical images. The processing chain combines change detection methods, image segmentation, higher-level image features (e.g. texture, shape) and topographic variables. Based on a few representative examples provided by a human operator, a machine learning model is trained and

  14. The comparison of landslide ratio-based and general logistic regression landslide susceptibility models in the Chishan watershed after 2009 Typhoon Morakot

    NASA Astrophysics Data System (ADS)

    WU, Chunhung

    2015-04-01

    The research built the original logistic regression landslide susceptibility model (abbreviated as or-LRLSM) and landslide ratio-based ogistic regression landslide susceptibility model (abbreviated as lr-LRLSM), compared the performance and explained the error source of two models. The research assumes that the performance of the logistic regression model can be better if the distribution of landslide ratio and weighted value of each variable is similar. Landslide ratio is the ratio of landslide area to total area in the specific area and an useful index to evaluate the seriousness of landslide disaster in Taiwan. The research adopted the landside inventory induced by 2009 Typhoon Morakot in the Chishan watershed, which was the most serious disaster event in the last decade, in Taiwan. The research adopted the 20 m grid as the basic unit in building the LRLSM, and six variables, including elevation, slope, aspect, geological formation, accumulated rainfall, and bank erosion, were included in the two models. The six variables were divided as continuous variables, including elevation, slope, and accumulated rainfall, and categorical variables, including aspect, geological formation and bank erosion in building the or-LRLSM, while all variables, which were classified based on landslide ratio, were categorical variables in building the lr-LRLSM. Because the count of whole basic unit in the Chishan watershed was too much to calculate by using commercial software, the research took random sampling instead of the whole basic units. The research adopted equal proportions of landslide unit and not landslide unit in logistic regression analysis. The research took 10 times random sampling and selected the group with the best Cox & Snell R2 value and Nagelkerker R2 value as the database for the following analysis. Based on the best result from 10 random sampling groups, the or-LRLSM (lr-LRLSM) is significant at the 1% level with Cox & Snell R2 = 0.190 (0.196) and Nagelkerke R2

  15. A preliminary regional assessment of earthquake-induced landslide susceptibility for Vrancea Seismic Region

    NASA Astrophysics Data System (ADS)

    Micu, Mihai; Balteanu, Dan; Ionescu, Constantin; Havenith, Hans; Radulian, Mircea; van Westen, Cees; Damen, Michiel; Jurchescu, Marta

    2015-04-01

    ) with head scarps near mountain tops and close to faults is similar to the one of large mass movements for which a seismic origin is proved (such as in the Tien Shan, Pamir, Longmenshan, etc.). Thus, correlations between landslide occurrence and combined seismotectonic and climatic factors are needed to support a regional multi-hazard risk assessment. The purpose of this paper is to harmonize for the first time at a regional scale the landslide predisposing factors and seismotectonic triggers and to present a first qualitative insight into the earthquake-induced landslide susceptibility for the Vrancea Seismic Region in terms of a GIS-based analysis of Newmark displacement (ND). In this way, it aims at better defining spatial and temporal distribution patterns of earthquake-triggered landslides. Arias Intensity calculation involved in the assessment considers both regional seismic hazard aspects and singular earthquake scenarios (adjusted by topography amplification factors). The known distribution of landslides mapped through digital stereographic interpretation of high-resolution aerial photos is compared with digital active fault maps and the computed ND maps to statistically outline the seismotectonic influence on slope stability in the study area. The importance of this approach resides in two main outputs. The fist one, of a fundamental nature, by providing the first regional insight into the seismic landslides triggering framework, is allowing us to understand if deep-focus earthquakes may trigger massive slope failures in an area with a relatively smooth relief (compared to the high mountain regions in Central Asia, the Himalayas), considering possible geologic and topographic site effects. The second one, more applied, will allow a better accelerometer instrumentation and monitoring of slopes and also will provide a first correlation of different levels of seismic shaking with precipitation recurrences, an important relationship within a multi-hazard risk

  16. Integration between ground based and satellite SAR data in landslide mapping: The San Fratello case study

    NASA Astrophysics Data System (ADS)

    Bardi, Federica; Frodella, William; Ciampalini, Andrea; Bianchini, Silvia; Del Ventisette, Chiara; Gigli, Giovanni; Fanti, Riccardo; Moretti, Sandro; Basile, Giuseppe; Casagli, Nicola

    2014-10-01

    The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty-clayey sedimentary cover. In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques. PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14 min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to

  17. Application of PALSAR-2 Remote Sensing Data for Landslide Hazard Mapping in Kelantan River Basin, Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Beiranvand Pour, Amin; Hashim, Mazlan

    2016-06-01

    Yearly, several landslides ensued during heavy monsoons rainfall in Kelantan river basin, peninsular Malaysia, which are obviously connected to geological structures and topographical features of the region. In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), remote sensing data were used to map geological structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides. Adaptive Local Sigma filter was selected and applied to accomplish speckle reduction and preserving both edges and features in PALSAR-2 fine mode observation images. Different polarization images were integrated to enhance geological structures. Additionally, directional filters were applied to the PALSAR-2 Local Sigma resultant image for edge enhancement and detailed identification of linear features. Several faults, drainage patterns and lithological contact layers were identified at regional scale. In order to assess the results, fieldwork and GPS survey were conducted in the landslide affected zones in the Kelantan river basin. Results demonstrate the most of the landslides were associated with N-S, NNW-SSE and NE-SW trending faults, angulated drainage pattern and metamorphic and Quaternary units. Consequently, structural and topographical geology maps were produced for Kelantan river basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping.

  18. Comparison and applicability of landslide susceptibility models based on landslide ratio-based logistic regression, frequency ratio, weight of evidence, and instability index methods in an extreme rainfall event

    NASA Astrophysics Data System (ADS)

    Wu, Chunhung

    2016-04-01

    Few researches have discussed about the applicability of applying the statistical landslide susceptibility (LS) model for extreme rainfall-induced landslide events. The researches focuses on the comparison and applicability of LS models based on four methods, including landslide ratio-based logistic regression (LRBLR), frequency ratio (FR), weight of evidence (WOE), and instability index (II) methods, in an extreme rainfall-induced landslide cases. The landslide inventory in the Chishan river watershed, Southwestern Taiwan, after 2009 Typhoon Morakot is the main materials in this research. The Chishan river watershed is a tributary watershed of Kaoping river watershed, which is a landslide- and erosion-prone watershed with the annual average suspended load of 3.6×107 MT/yr (ranks 11th in the world). Typhoon Morakot struck Southern Taiwan from Aug. 6-10 in 2009 and dumped nearly 2,000 mm of rainfall in the Chishan river watershed. The 24-hour, 48-hour, and 72-hours accumulated rainfall in the Chishan river watershed exceeded the 200-year return period accumulated rainfall. 2,389 landslide polygons in the Chishan river watershed were extracted from SPOT 5 images after 2009 Typhoon Morakot. The total landslide area is around 33.5 km2, equals to the landslide ratio of 4.1%. The main landslide types based on Varnes' (1978) classification are rotational and translational slides. The two characteristics of extreme rainfall-induced landslide event are dense landslide distribution and large occupation of downslope landslide areas owing to headward erosion and bank erosion in the flooding processes. The area of downslope landslide in the Chishan river watershed after 2009 Typhoon Morakot is 3.2 times higher than that of upslope landslide areas. The prediction accuracy of LS models based on LRBLR, FR, WOE, and II methods have been proven over 70%. The model performance and applicability of four models in a landslide-prone watershed with dense distribution of rainfall

  19. Characterization of past landslides and slope susceptibility analysis for Lima and Callao provinces, Peru

    NASA Astrophysics Data System (ADS)

    Tatard, Lucile; Villacorta, Sandra; Metzger, Pascale

    2013-04-01

    85% of people exposed to earthquakes, hurricanes, floods and drought live in developing countries (IPU, 2010). This population is also exposed to the landslide risk as this phenomenon is mainly triggered by earthquakes and rainfall. There is an urgent need to propose methods to evaluate and mitigate the landslide risk for developing countries, where few studies were undergone and data, and information on data, are scarce. In this study, we characterize a landslide inventory set up for the megalopolis of Lima, Peru, by the local geological bureau (INGEMMET). This inventory was set up using satellite images and includes landslides of all ages. It is composed of two landslide types: rockfalls and debris flows (huaycos) that we investigate together and separately. First, we describe qualitatively the landslide occurrences in terms of geology, slope steepness, altitude, etc. We notably find that debris flows occur at altitudes larger than the ones of the rockfalls, probably due to the climatic conditions. Then we find that the rockfalls and debris flows area distributions follow a power law when investigated separately whereas it does not follow a power law when investigated together. This highlights a logical difference of mechanics between the two landslide types. Then, using the dimension of correlation D (Grassberger and Procaccia, 1983) we show that the event spatial occurrences are not uniformly distributed but clustered. It supports the existence of controlling parameters on the spatial occurrence of landslides and the research to identify them. Last, we investigate the relationships between different landslide parameters (geology, altitude, slope steepness, ...) using the linear correlation coefficient r, and we find that all these parameters are independent to each other. This allows us to investigate each parameter separately in terms of landslide susceptibility and to define values for which the landslide susceptibility is low, medium or high for each

  20. Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

    NASA Astrophysics Data System (ADS)

    Schlögel, R.; Marchesini, I.; Alvioli, M.; Reichenbach, P.; Rossi, M.; Malet, J.-P.

    2018-01-01

    We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

  1. Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

    2013-01-01

    The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

  2. Landslide Susceptibility Evaluation on agricultural terraces of DOURO VALLEY (PORTUGAL), using physically based mathematical models.

    NASA Astrophysics Data System (ADS)

    Faria, Ana; Bateira, Carlos; Laura, Soares; Fernandes, Joana; Gonçalves, José; Marques, Fernando

    2016-04-01

    predictive capacity of the models is related with the construction methods of contributory areas. The SHALSTAB susceptibility map shows better discrimination of the unstable areas, which is important to the estates decision makers in order to organize the priority of the hazard mitigation process. References Dietrich, W. E.; Reiss, R.; Hsu, M-L.; Montgomery, D.(1995) - A process-based model for colluvial soil depth and shallow landsliding using digital elevation data. Hydrological Processes. ISSN 1099-1085. Vol. 9, n.° 3-4, pp.383-400. Fawcett, T.(2006) - An introduction to ROC analysis. Pattern Recognition Letters. ISSN 0167-8655. Vol. 27, n.° 8, pp.861-874. Montgomery, David R.; Dietrich, William E.- A physically based model for the topographic control on shallow landsliding. Water Resources Research. ISSN 1944-7973. Vol. 30, n.° 4 (1994), p.1153-1171. Raia, S., [et al.]- Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach. Geoscientific Model Development. ISSN 1991-959X. Vol. 7, n.° 2 (2014), p.495-514.

  3. An Atlas of ShakeMaps for Landslide and Liquefaction Modeling

    NASA Astrophysics Data System (ADS)

    Johnson, K. L.; Nowicki, M. A.; Mah, R. T.; Garcia, D.; Harp, E. L.; Godt, J. W.; Lin, K.; Wald, D. J.

    2012-12-01

    The human consequences of a seismic event are often a result of subsequent hazards induced by the earthquake, such as landslides. While the United States Geological Survey (USGS) ShakeMap and Prompt Assessment of Global Earthquakes for Response (PAGER) systems are, in conjunction, capable of estimating the damage potential of earthquake shaking in near-real time, they do not currently provide estimates for the potential of further damage by secondary processes. We are developing a sound basis for providing estimates of the likelihood and spatial distribution of landslides for any global earthquake under the PAGER system. Here we discuss several important ingredients in this effort. First, we report on the development of a standardized hazard layer from which to calibrate observed landslide distributions; in contrast, prior studies have used a wide variety of means for estimating the hazard input. This layer now takes the form of a ShakeMap, a standardized approach for computing geospatial estimates for a variety of shaking metrics (both peak ground motions and shaking intensity) from any well-recorded earthquake. We have created ShakeMaps for about 20 historical landslide "case history" events, significant in terms of their landslide occurrence, as part of an updated release of the USGS ShakeMap Atlas. We have also collected digitized landslide data from open-source databases for many of the earthquake events of interest. When these are combined with up-to-date topographic and geologic maps, we have the basic ingredients for calibrating landslide probabilities for a significant collection of earthquakes. In terms of modeling, rather than focusing on mechanistic models of landsliding, we adopt a strictly statistical approach to quantify landslide likelihood. We incorporate geology, slope, peak ground acceleration, and landslide data as variables in a logistic regression, selecting the best explanatory variables given the standardized new hazard layers (see Nowicki

  4. Preliminary Map of Landslide Deposits in the Mesa Verde National Park Area, Colorado

    USGS Publications Warehouse

    Carrara, Paul E.

    2009-01-01

    This report presents a preliminary map of landslide deposits in the Mesa Verde National Park area (see map sheet) at a compilation scale of 1:50,000. Landslide is a general term for landforms produced by a wide variety of gravity-driven mass movements, including various types of flows, slides, topples and falls, and combinations thereof produced by the slow to rapid downslope transport of surficial materials or bedrock. The map depicts more than 200 landslides ranging in size from small (0.01 square miles) earthflows and rock slumps to large (greater than 0.50 square miles) translational slides and complex landslides (Varnes, 1978). This map has been prepared to provide a regional overview of the distribution of landslide deposits in the Mesa Verde area, and as such constitutes an inventory of landslides in the area. The map is suitable for regional planning to identify broad areas where landslide deposits and processes are concentrated. It should not be used as a substitute for detailed site investigations. Specific areas thought to be subject to landslide hazards should be carefully studied before development. Many of the landslides depicted on this map are probably stable as they date to the Pleistocene (approximately 1.8-0.011 Ma) and hence formed under a different climate regime. However, the recognition of these landslides is important because natural and human-induced factors can alter stability. Reduction of lateral support (by excavations or roadcuts), removal of vegetation (by fire or development), or an increase in pore pressure (by heavy rains) may result in the reactivation of landslides or parts of landslides.

  5. A method for producing digital probabilistic seismic landslide hazard maps; an example from the Los Angeles, California, area

    USGS Publications Warehouse

    Jibson, Randall W.; Harp, Edwin L.; Michael, John A.

    1998-01-01

    The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24,000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10-m grid spacing in the ARC/INFO GIS platform. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure.

  6. Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba

    NASA Astrophysics Data System (ADS)

    Melchiorre, C.; Castellanos Abella, E. A.; van Westen, C. J.; Matteucci, M.

    2011-04-01

    This paper describes a procedure for landslide susceptibility assessment based on artificial neural networks, and focuses on the estimation of the prediction capability, robustness, and sensitivity of susceptibility models. The study is carried out in the Guantanamo Province of Cuba, where 186 landslides were mapped using photo-interpretation. Twelve conditioning factors were mapped including geomorphology, geology, soils, landuse, slope angle, slope direction, internal relief, drainage density, distance from roads and faults, rainfall intensity, and ground peak acceleration. A methodology was used that subdivided the database in 3 subsets. A training set was used for updating the weights. A validation set was used to stop the training procedure when the network started losing generalization capability, and a test set was used to calculate the performance of the network. A 10-fold cross-validation was performed in order to show that the results are repeatable. The prediction capability, the robustness analysis, and the sensitivity analysis were tested on 10 mutually exclusive datasets. The results show that by means of artificial neural networks it is possible to obtain models with high prediction capability and high robustness, and that an exploration of the effect of the individual variables is possible, even if they are considered as a black-box model.

  7. Remote sensing as tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase

    NASA Astrophysics Data System (ADS)

    Ciampalini, Andrea; Raspini, Federico; Bianchini, Silvia; Frodella, William; Bardi, Federica; Lagomarsino, Daniela; Di Traglia, Federico; Moretti, Sandro; Proietti, Chiara; Pagliara, Paola; Onori, Roberta; Corazza, Angelo; Duro, Andrea; Basile, Giuseppe; Casagli, Nicola

    2015-11-01

    Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province.

  8. Rapid Landslide Mapping by Means of Post-Event Polarimetric SAR Imagery

    NASA Astrophysics Data System (ADS)

    Plank, Simon; Martinis, Sandro; Twele, Andre

    2016-08-01

    Rapid mapping of landslides, quickly providing information about the extent of the affected area and type and grade of damage, is crucial to enable fast crisis response. Reviewing the literature shows that most synthetic aperture radar (SAR) data-based landslide mapping procedures use change detection techniques. However, the required very high resolution (VHR) pre-event SAR imagery, acquired shortly before the landslide event, is commonly not available. Due to limitations in onboard disk space and downlink transmission rates modern VHR SAR missions do not systematically cover the entire world. We present a fast and robust procedure for mapping of landslides, based on change detection between freely available and systematically acquired pre-event optical and post-event polarimetric SAR data.

  9. Landslides in Nicaragua - Mapping, Inventory, Hazard Assessment, Vulnerability Reduction, and Forecasting Attempts

    NASA Astrophysics Data System (ADS)

    Dévoli, G.; Strauch, W.; Álvarez, A.; Muñoz, A.; Kjekstad, O.

    2009-04-01

    access, manage, update and distribute in a short time to all sectors and users; and finally, the need of a comprehensive understanding of landslide processes. Many efforts have been made in the last 10 years to gain a more comprehensive and predictive understanding of landslide processes in Nicaragua. Since 1998, landslide inventory GIS based maps have been produced in different areas of the country, as part of international and multidisciplinary development projects. Landslide susceptibility and hazard maps are available now at INETEŔs Website for all municipalities of the country. The insights on landslide hazard have been transmitted to governmental agencies, local authorities, NGÓs, international agencies to be used in measures for risk reduction. A massive application example was the integration of hazard assessment studies in a large house building program in Nicaragua. Hazards of landslides, and other dangerous phenomena, were evaluated in more than 90 house building projects, each with 50 - 200 houses to be build, sited mainly in rural areas of the country. For more than 7000 families, this program could finally assure that their new houses were build in safe areas. Attempts have been made to develop a strategy for early warning of landslides in Nicaragua. First approaches relied on precipitation gauges with satellite based telemetry which were installed in some Nicaraguan volcanoes where lahars occur frequently. The occurrence of lahars in certain gullies could be detected by seismic stations. A software system gave acoustic alarm at INETEŔs Monitoring Centre when certain trigger levels of the accumulated precipitation were reached. The monitoring and early warning for all areas under risk would have required many rain gauges. A new concept is tested which uses near real time precipitation estimates from NOAA meteorological satellite data. A software system sends out alarm messages if strong or long lasting rains are observed over certain landslide "hot spots

  10. Evaluating performances of simplified physically based landslide susceptibility models.

    NASA Astrophysics Data System (ADS)

    Capparelli, Giovanna; Formetta, Giuseppe; Versace, Pasquale

    2015-04-01

    Rainfall induced shallow landslides cause significant damages involving loss of life and properties. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. This paper presents a package of GIS based models for landslide susceptibility analysis. It was integrated in the NewAge-JGrass hydrological model using the Object Modeling System (OMS) modeling framework. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices (GOF) by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system offers the possibility to investigate and fairly compare the quality and the robustness of models and models parameters, according a procedure that includes: i) model parameters estimation by optimizing each of the GOF index separately, ii) models evaluation in the ROC plane by using each of the optimal parameter set, and iii) GOF robustness evaluation by assessing their sensitivity to the input parameter variation. This procedure was repeated for all three models. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, Average Index (AI) optimization coupled with model M3 is the best modeling solution for our test case. This research was funded by PON Project No. 01_01503 "Integrated Systems for Hydrogeological Risk

  11. An overview of a GIS method for mapping landslides and assessing landslide hazards at Río El Estado watershed, on the SW flank of Pico de Orizaba Volcano, Mexico

    NASA Astrophysics Data System (ADS)

    Legorreta Paulin, G.; Bursik, M. I.; Contreras, T.; Polenz, M.; Ramírez Herrera, M.; Paredes Mejía, L.; Arana Salinas, L.

    2012-12-01

    This poster provides an overview of the on-going research project (Grant SEP-CONACYT no 167495) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory, produce a landslide susceptibility map, and estimate sediment production by using Geographic Information Systems (GIS). The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 5.2 km2 with elevations ranging from 2676.79 to 4248.2 m a.s.l. and hillslopes between 0° and 56°. The stream system of Río El Estado catchment erodes Tertiary and Quaternary lavas, pyroclastic flows, and fall deposits. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The methodology encompasses three main stages of analysis to assess landslide hazards: Stage 1 builds a historic landslide inventory. In the study area, an inventory of more than 170 landslides is created from multi-temporal aerial-photo-interpretation and local field surveys to assess landslide distribution. All landslides were digitized into a geographic information system (GIS), and a spatial geo-database of landslides was constructed from standardized GIS datasets. Stage 2 Calculates the susceptibility for the watershed. During this stage, Multiple Logistic Regression and SINMAP) will be evaluated to select the one that provides scientific accuracy, technical accessibility, and applicability. Stage 3 Estimate the potential total material delivered to the main stream drainage channel by all landslides in the catchment. Detailed geometric measurements of individual landslides visited during the field work will be carried out to obtain the landslide area and volume. These measurements revealed an empirical relationship between area and volume that took the

  12. Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia B.; Adler, Robert; Hone, Yang; Kumar, Sujay; Peters-Lidard, Christa; Lerner-Lam, Arthur

    2010-01-01

    A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve

  13. Preliminary soil-slip susceptibility maps, southwestern California

    USGS Publications Warehouse

    Morton, Douglas M.; Alvarez, Rachel M.; Campbell, Russell H.; Digital preparation by Bovard, Kelly R.; Brown, D.T.; Corriea, K.M.; Lesser, J.N.

    2003-01-01

    This group of maps shows relative susceptibility of hill slopes to the initiation sites of rainfall-triggered soil slip-debris flows in southwestern California. As such, the maps offer a partial answer to one part of the three parts necessary to predict the soil-slip/debris-flow process. A complete prediction of the process would include assessments of “where”, “when”, and “how big”. These maps empirically show part of the “where” of prediction (i.e., relative susceptibility to sites of initiation of the soil slips) but do not attempt to show the extent of run out of the resultant debris flows. Some information pertinent to “when” the process might begin is developed. “When” is determined mostly by dynamic factors such as rainfall rate and duration, for which local variations are not amenable to long-term prediction. “When” information is not provided on the maps but is described later in this narrative. The prediction of “how big” is addressed indirectly by restricting the maps to a single type of landslide process—soil slip-debris flows. The susceptibility maps were created through an iterative process from two kinds of information. First, locations of sites of past soil slips were obtained from inventory maps of past events. Aerial photographs, taken during six rainy seasons that produced abundant soil slips, were used as the basis for soil slip-debris flow inventory. Second, digital elevation models (DEM) of the areas that were inventoried were used to analyze the spatial characteristics of soil slip locations. These data were supplemented by observations made on the ground. Certain physical attributes of the locations of the soil-slip debris flows were found to be important and others were not. The most important attribute was the mapped bedrock formation at the site of initiation of the soil slip. However, because the soil slips occur in surficial materials overlying the bedrocks units, the bedrock formation can only serve as

  14. Object-based landslide mapping on satellite images from different sensors

    NASA Astrophysics Data System (ADS)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens; Blaschke, Thomas

    2015-04-01

    Several studies have proven that object-based image analysis (OBIA) is a suitable approach for landslide mapping using remote sensing data. Mostly, optical satellite images are utilized in combination with digital elevation models (DEMs) for semi-automated mapping. The ability of considering spectral, spatial, morphometric and contextual features in OBIA constitutes a significant advantage over pixel-based methods, especially when analysing non-uniform natural phenomena such as landslides. However, many of the existing knowledge-based OBIA approaches for landslide mapping are rather complex and are tailored to specific data sets. These restraints lead to a lack of transferability of OBIA mapping routines. The objective of this study is to develop an object-based approach for landslide mapping that is robust against changing input data with different resolutions, i.e. optical satellite imagery from various sensors. Two study sites in Taiwan were selected for developing and testing the landslide mapping approach. One site is located around the Baolai village in the Huaguoshan catchment in the southern-central part of the island, the other one is a sub-area of the Taimali watershed in Taitung County near the south-eastern Pacific coast. Both areas are regularly affected by severe landslides and debris flows. A range of very high resolution (VHR) optical satellite images was used for the object-based mapping of landslides and for testing the transferability across different sensors and resolutions: (I) SPOT-5, (II) Formosat-2, (III) QuickBird, and (IV) WorldView-2. Additionally, a digital elevation model (DEM) with 5 m spatial resolution and its derived products (e.g. slope, plan curvature) were used for supporting the semi-automated mapping, particularly for differentiating source areas and accumulation areas according to their morphometric characteristics. A focus was put on the identification of comparatively stable parameters (e.g. relative indices), which could be

  15. Evaluation of LIDAR for landslide mapping.

    DOT National Transportation Integrated Search

    2006-06-01

    The Caltrans GeoResearch Group, in collaboration with the Department of Conservation, successfully : used LIDAR technology to map landslides along two heavily forested highway corridors in Humboldt : and Del Norte Counties. LIDAR (Light Detection ...

  16. Mapping of hazard from rainfall-triggered landslides in developing countries: Examples from Honduras and Micronesia

    USGS Publications Warehouse

    Harp, E.L.; Reid, M.E.; McKenna, J.P.; Michael, J.A.

    2009-01-01

    Loss of life and property caused by landslides triggered by extreme rainfall events demonstrates the need for landslide-hazard assessment in developing countries where recovery from such events often exceeds the country's resources. Mapping landslide hazards in developing countries where the need for landslide-hazard mitigation is great but the resources are few is a challenging, but not intractable problem. The minimum requirements for constructing a physically based landslide-hazard map from a landslide-triggering storm, using the simple methods we discuss, are: (1) an accurate mapped landslide inventory, (2) a slope map derived from a digital elevation model (DEM) or topographic map, and (3) material strength properties of the slopes involved. Provided that the landslide distribution from a triggering event can be documented and mapped, it is often possible to glean enough topographic and geologic information from existing databases to produce a reliable map that depicts landslide hazards from an extreme event. Most areas of the world have enough topographic information to provide digital elevation models from which to construct slope maps. In the likely event that engineering properties of slope materials are not available, reasonable estimates can be made with detailed field examination by engineering geologists or geotechnical engineers. Resulting landslide hazard maps can be used as tools to guide relocation and redevelopment, or, more likely, temporary relocation efforts during severe storm events such as hurricanes/typhoons to minimize loss of life and property. We illustrate these methods in two case studies of lethal landslides in developing countries: Tegucigalpa, Honduras (during Hurricane Mitch in 1998) and the Chuuk Islands, Micronesia (during Typhoon Chata'an in 2002).

  17. Generating landslide inventory by participatory mapping: an example in Purwosari Area, Yogyakarta, Java

    NASA Astrophysics Data System (ADS)

    Samodra, G.; Chen, G.; Sartohadi, J.; Kasama, K.

    2018-04-01

    This paper proposes an approach for landslide inventory mapping considering actual conditions in Indonesia. No satisfactory landslide database exists. What exists is inadequate, focusing, on data response, rather than on pre-disaster preparedness and planning. The humid tropical climate also leads a rapid vegetation growth so past landslides signatures are covered by vegetation or dismantled by erosion process. Generating landslide inventory using standard techniques still seems difficult. A catalog of disasters from local government (village level) was used as a basis of participatory landslide inventory mapping. Eyewitnesses or landslide disaster victims were asked to participate in the reconstruction of past landslides. Field investigation focusing on active participation from communities with the use of an innovative technology was used to verify the landslide events recorded in the disaster catalog. Statistical analysis was also used to obtain the necessary relationships between geometric measurements, including the height of the slope and length of run out, area and volume of displaced materials, the probability distributions of landslide area and volume, and mobilization rate. The result shows that run out distance is proportional to the height of the slope. The frequency distribution calculated by using non-cumulative distribution empirically exhibits a power law (fractal statistic) even though rollover can also be found in the dataset. This cannot be the result of the censoring effect or incompleteness of the data because the landslide inventory dataset can be classified as having complete data or nearly complete data. The so-called participatory landslide inventory mapping method is expected to solve the difficulties of landslide inventory mapping and can be applied to support pre-disaster planning and preparedness action to reduce the landslide disaster risk in Indonesia. It may also supplement the usually incomplete data in a typical landslide inventory.

  18. Map showing inventory and regional susceptibility for Holocene debris flows, and related fast-moving landslides in the conterminous United States

    USGS Publications Warehouse

    Brabb, Earl E.; Colgan, Joseph P.; Best, Timothy C.

    2000-01-01

    Introduction Debris flows, debris avalanches, mud flows and lahars are fast-moving landslides that occur in a wide variety of environments throughout the world. They are particularly dangerous to life and property because they move quickly, destroy objects in their paths, and often strike without warning. This map represents a significant effort to compile the locations of known debris flows in United Stated and predict where future flows might occur. The files 'dfipoint.e00' and 'dfipoly.e00' contain the locations of over 6600 debris flows from published and unpublished sources. The locations are referenced by numbers that correspond to entries in a bibliography, which is part of the pamphlet 'mf2329pamphlet.pdf'. The areas of possible future debris flows are shown in the file 'susceptibility.tif', which is a georeferenced TIFF file that can be opened in an image editing program or imported into a GIS system like ARC/INFO. All other databases are in ARC/INFO export (.e00) format.

  19. Scale and spatial distribution assessment of rainfall-induced landslides in a catchment with mountain roads

    NASA Astrophysics Data System (ADS)

    Tseng, Chih-Ming; Chen, Yie-Ruey; Wu, Szu-Mi

    2018-03-01

    This study focused on landslides in a catchment with mountain roads that were caused by Nanmadol (2011) and Kong-rey (2013) typhoons. Image interpretation techniques were employed to for satellite images captured before and after the typhoons to derive the surface changes. A multivariate hazard evaluation method was adopted to establish a landslide susceptibility assessment model. The evaluation of landslide locations and relationship between landslide and predisposing factors is preparatory for assessing and mapping landslide susceptibility. The results can serve as a reference for preventing and mitigating slope disasters on mountain roads.

  20. Landslides in the Central Coalfield (Cantabrian Mountains, NW Spain): Geomorphological features, conditioning factors and methodological implications in susceptibility assessment

    NASA Astrophysics Data System (ADS)

    Domínguez-Cuesta, María José; Jiménez-Sánchez, Montserrat; Berrezueta, Edgar

    2007-09-01

    A geomorphological study focussing on slope instability and landslide susceptibility modelling was performed on a 278 km 2 area in the Nalón River Basin (Central Coalfield, NW Spain). The methodology of the study includes: 1) geomorphological mapping at both 1:5000 and 1:25,000 scales based on air-photo interpretation and field work; 2) Digital Terrain Model (DTM) creation and overlay of geomorphological and DTM layers in a Geographical Information System (GIS); and 3) statistical treatment of variables using SPSS and development of a logistic regression model. A total of 603 mass movements including earth flow and debris flow were inventoried and were classified into two groups according to their size. This study focuses on the first group with small mass movements (10 0 to 10 1 m in size), which often cause damage to infrastructures and even victims. The detected conditioning factors of these landslides are lithology (soils and colluviums), vegetation (pasture) and topography. DTM analyses show that high instabilities are linked to slopes with NE and SW orientations, curvature values between - 6 and - 0.7, and slope values from 16° to 30°. Bedrock lithology (Carboniferous sandstone and siltstone), presence of Quaternary soils and sediments, vegetation, and the topographical factors were used to develop a landslide susceptibility model using the logistic regression method. Application of "zoom method" allows us to accurately detect small mass movements using a 5-m grid cell data even if geomorphological mapping is done at a 1:25,000 scale.

  1. Plenary: Progress in Regional Landslide Hazard Assessment—Examples from the USA

    USGS Publications Warehouse

    Baum, Rex L.; Schulz, William; Brien, Dianne L.; Burns, William J.; Reid, Mark E.; Godt, Jonathan W.

    2014-01-01

    Landslide hazard assessment at local and regional scales contributes to mitigation of landslides in developing and densely populated areas by providing information for (1) land development and redevelopment plans and regulations, (2) emergency preparedness plans, and (3) economic analysis to (a) set priorities for engineered mitigation projects and (b) define areas of similar levels of hazard for insurance purposes. US Geological Survey (USGS) research on landslide hazard assessment has explored a range of methods that can be used to estimate temporal and spatial landslide potential and probability for various scales and purposes. Cases taken primarily from our work in the U.S. Pacific Northwest illustrate and compare a sampling of methods, approaches, and progress. For example, landform mapping using high-resolution topographic data resulted in identification of about four times more landslides in Seattle, Washington, than previous efforts using aerial photography. Susceptibility classes based on the landforms captured 93 % of all historical landslides (all types) throughout the city. A deterministic model for rainfall infiltration and shallow landslide initiation, TRIGRS, was able to identify locations of 92 % of historical shallow landslides in southwest Seattle. The potentially unstable areas identified by TRIGRS occupied only 26 % of the slope areas steeper than 20°. Addition of an unsaturated infiltration model to TRIGRS expands the applicability of the model to areas of highly permeable soils. Replacement of the single cell, 1D factor of safety with a simple 3D method of columns improves accuracy of factor of safety predictions for both saturated and unsaturated infiltration models. A 3D deterministic model for large, deep landslides, SCOOPS, combined with a three-dimensional model for groundwater flow, successfully predicted instability in steep areas of permeable outwash sand and topographic reentrants. These locations are consistent with locations of

  2. Regional landslide hazard assesment for Kulon Progo Area, Central Java, Indonesia

    NASA Astrophysics Data System (ADS)

    Karnawati, D.

    2009-12-01

    Karanganyar region is situated in a dynamic volcanic region in Java Island, where rain-induced landslides are frequent and widespread. Shallow-rapid earth slides triggered by heavy rainfall are the most common landslide type occurring on the steep slope and had resulted in major casualties, whilst deep soil creeping is more prominant on the gentle slope which creat a lot of damages on the houses and infrastructure. A landslide hazard assessment had been conducted to support the landslide mitigation program in this region. Such assessment was carried out by applying a semi qualitative approach (Analytical Hierarchical Process) where a weighting system was applied to assess the level of importance of each controlling parameter as suggested by Saaty (1980). Existing conditions of each controlling parameters were also assessed based on relative hierarchical system by applying scoring. Geographical Information System was used as a tool in such analysis and mapping process. The isohyet map was also prepared from statistical and spatial analyses on rain fall data. Finally, two different scenarios of landslide hazard maps were established, i.e. the scenario without any rainfall (Scenario 1) and with the reainfall (Scenario 2). It was found that the most susceptible zone of landslide was localised on the steep slope (with the inclination beyond 45o ) of jointed andesitic breccia, which was covered by thinck silty clay and situated close to the stream zone (Scenario 1). However from the hazard map and analysis on scenario 2, it can be identified that the susceptible zone expanded larger due to the rainfall, covering most region of the west-slope area of Lawu Volcano. Therefore, it can be concluded that the rainfall intensity is very crucial to induce the landslide not only in the most susceptible zone, but also in the larger area which also include the less susceptbile zone. This findings is also crucial to support the development of landslide spatial-early-warning system in

  3. Integrating Geo-Spatial Data for Regional Landslide Susceptibility Modeling in Consideration of Run-Out Signature

    NASA Astrophysics Data System (ADS)

    Lai, J.-S.; Tsai, F.; Chiang, S.-H.

    2016-06-01

    This study implements a data mining-based algorithm, the random forests classifier, with geo-spatial data to construct a regional and rainfall-induced landslide susceptibility model. The developed model also takes account of landslide regions (source, non-occurrence and run-out signatures) from the original landslide inventory in order to increase the reliability of the susceptibility modelling. A total of ten causative factors were collected and used in this study, including aspect, curvature, elevation, slope, faults, geology, NDVI (Normalized Difference Vegetation Index), rivers, roads and soil data. Consequently, this study transforms the landslide inventory and vector-based causative factors into the pixel-based format in order to overlay with other raster data for constructing the random forests based model. This study also uses original and edited topographic data in the analysis to understand their impacts to the susceptibility modeling. Experimental results demonstrate that after identifying the run-out signatures, the overall accuracy and Kappa coefficient have been reached to be become more than 85 % and 0.8, respectively. In addition, correcting unreasonable topographic feature of the digital terrain model also produces more reliable modelling results.

  4. The Pliocene Horcón Formation, Central Chile: a case study of earthquake-induced landslide susceptibility

    NASA Astrophysics Data System (ADS)

    Valdivia, D.; Elgueta, S.; Hodgkin, A.; Marquardt, C.; del Valle, F.; Yáñez Morroni, G.

    2017-12-01

    Stability slope analysis is typically focused on modeling using cohesion and friction angle parameters but in earthquake-induced landslides, susceptibility is correlated more to lithological and stratigraphic parameters. In sedimentary deposits whose cohesion and diagenesis are very low, the risk of landslides increases. The Horcón Formation, which crops out continuously along cliffs in Central Chile between 32.5° and 33°S, is a Miocene-Pliocene well preserved, horizontally stratified unit composed of marine strata which overlies Paleozoic-Mesozoic igneous basement. During the Quaternary, the sequence was tectonically uplifted 80 meters and covered by unconsolidated eolian deposits. Given that Seismotectonic and Barrier-Asperity models suggest the occurrence of a forthcoming megathrust earthquake in a segment which includes this area, the Horcón Formation constitutes a good case study to characterize the susceptibility of this type of sediment for mass movements triggered by earthquakes. Field mapping, stratigraphic and sedimentological studies, including petrographic analyses to determine lithological composition and paragenesis of diagenetic events, have been carried out along with limited gravimetric profiling and CPTU drill tests. High resolution digital elevation modeling has also been applied. This work has led to the recognition of a shallow marine lithofacies association composed of weakly lithified fossiliferous and bioturbated medium to fine grained litharenite, mudstone, and fine conglomerate. The low grade of diagenesis in the sedimentary deposits was in response to a short period of burial and a subsequent accelerated uplift evidenced along the coast of Chile during the Quaternary. We have generated a predictive model of landslide susceptibility for the Horcón Formation and for the overlying Quaternary eolian deposits incorporating variables such as composition and diagenesis of lithofacies, slope, structures, weathering and landcover. The model

  5. Communicating Earth Observation (EO)-based landslide mapping capabilities to practitioners

    NASA Astrophysics Data System (ADS)

    Albrecht, Florian; Hölbling, Daniel; Eisank, Clemens; Weinke, Elisabeth; Vecchiotti, Filippo; Kociu, Arben

    2016-04-01

    Current remote sensing methods and the available Earth Observation (EO) data for landslide mapping already can support practitioners in their processes for gathering and for using landslide information. Information derived from EO data can support emergency services and authorities in rapid mapping after landslide-triggering events, in landslide monitoring and can serve as a relevant basis for hazard and risk mapping. These applications also concern owners, maintainers and insurers of infrastructure. Most often practitioners have a rough overview of the potential and limits of EO-based methods for landslide mapping. However, semi-automated image analysis techniques are still rarely used in practice. This limits the opportunity for user feedback, which would contribute to improve the methods for delivering fully adequate results in terms of accuracy, applicability and reliability. Moreover, practitioners miss information on the best way of integrating the methods in their daily processes. Practitioners require easy-to-grasp interfaces for testing new methods, which in turn would provide researchers with valuable user feedback. We introduce ongoing work towards an innovative web service which will allow for fast and efficient provision of EO-based landslide information products and that supports online processing. We investigate the applicability of various very high resolution (VHR), e.g. WorldView-2/3, Pleiades, and high resolution (HR), e.g. Landsat, Sentinel-2, optical EO data for semi-automated mapping based on object-based image analysis (OBIA). The methods, i.e. knowledge-based and statistical OBIA routines, are evaluated regarding their suitability for inclusion in a web service that is easy to use with the least amount of necessary training. The pre-operational web service will be implemented for selected study areas in the Alps (Austria, Italy), where weather-induced landslides have happened in the past. We will test the service on its usability together

  6. Assessing Degree of Susceptibility to Landslide Hazard

    NASA Astrophysics Data System (ADS)

    Sheridan, M. F.; Cordoba, G. A.; Delgado, H.; Stefanescu, R.

    2013-05-01

    The modeling of hazardous mass flows, both dry and water saturated, is currently an area of active research and several stable models have now emerged that have differing degrees of physical and mathematical fidelity. Models based on the early work of Savage and Hutter (1989) assume that very large dense granular flows could be modeled as incompressible continua governed by a Coulomb failure criterion. Based on this concept, Patra et al. (2005) developed a code for dry avalanches, which proposes a thin layer mathematical model similar to shallow-water equations. This concept was implemented in the widely-used TITAN2D program, which integrates the shock-capturing Godunov solution methodology for the equation system. We propose a method to assess the susceptibility of specific locations susceptible to landslides following heavy tephra fall using the TIATN2D code. Successful application requires that the range of several uncertainties must be framed in the selection of model input data: 1) initial conditions, like volume and location of origin of the landslide, 2) bed and internal friction parameters and 3) digital elevation model (DEM) uncertainties. Among the possible ways of coping with these uncertainties, we chose to use Latin Hypercube Sampling (LHS). This statistical technique reduces a computationally intractable problem to such an extent that is it possible to apply it, even with current personal computers. LHS requires that there is only one sample in each row and each column of the sampling matrix, where each row (multi-dimensional) corresponds to each uncertainty. LHS requires less than 10% of the sample runs needed by Monte Carlo approaches to achieve a stable solution. In our application LHS output provides model sampling for 4 input parameters: initial random volumes, UTM location (x and y), and bed friction. We developed a simple Octave script to link the output of LHS with TITAN2D. In this way, TITAN2D can run several times with successively different

  7. Binary Logistic Regression Versus Boosted Regression Trees in Assessing Landslide Susceptibility for Multiple-Occurring Regional Landslide Events: Application to the 2009 Storm Event in Messina (Sicily, southern Italy).

    NASA Astrophysics Data System (ADS)

    Lombardo, L.; Cama, M.; Maerker, M.; Parisi, L.; Rotigliano, E.

    2014-12-01

    This study aims at comparing the performances of Binary Logistic Regression (BLR) and Boosted Regression Trees (BRT) methods in assessing landslide susceptibility for multiple-occurrence regional landslide events within the Mediterranean region. A test area was selected in the north-eastern sector of Sicily (southern Italy), corresponding to the catchments of the Briga and the Giampilieri streams both stretching for few kilometres from the Peloritan ridge (eastern Sicily, Italy) to the Ionian sea. This area was struck on the 1st October 2009 by an extreme climatic event resulting in thousands of rapid shallow landslides, mainly of debris flows and debris avalanches types involving the weathered layer of a low to high grade metamorphic bedrock. Exploiting the same set of predictors and the 2009 landslide archive, BLR- and BRT-based susceptibility models were obtained for the two catchments separately, adopting a random partition (RP) technique for validation; besides, the models trained in one of the two catchments (Briga) were tested in predicting the landslide distribution in the other (Giampilieri), adopting a spatial partition (SP) based validation procedure. All the validation procedures were based on multi-folds tests so to evaluate and compare the reliability of the fitting, the prediction skill, the coherence in the predictor selection and the precision of the susceptibility estimates. All the obtained models for the two methods produced very high predictive performances, with a general congruence between BLR and BRT in the predictor importance. In particular, the research highlighted that BRT-models reached a higher prediction performance with respect to BLR-models, for RP based modelling, whilst for the SP-based models the difference in predictive skills between the two methods dropped drastically, converging to an analogous excellent performance. However, when looking at the precision of the probability estimates, BLR demonstrated to produce more robust

  8. Landslide susceptibility near highways is increased by one order of magnitude in the Andes of southern Ecuador, Loja province

    NASA Astrophysics Data System (ADS)

    Brenning, A.; Schwinn, M.; Ruiz-Páez, A. P.; Muenchow, J.

    2014-03-01

    Mountain roads in developing countries are known to increase landslide occurrence due to often inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading. This study empirically investigates landslide initiation frequency along two paved interurban highways in the tropical Andes of southern Ecuador across different climatic regimes. Generalized additive models (GAM) and generalized linear models (GLM) were used to analyze the relationship between mapped landslide initiation points and distance to highway while accounting for topographic, climatic and geological predictors as possible confounders. A spatial block bootstrap was used to obtain non-parametric confidence intervals for the odds ratio of landslide occurrence near the highways (25 m distance) compared to a 200 m distance. The estimated odds ratio was 18-21 with lower 95% confidence bounds > 13 in all analyses. Spatial bootstrap estimation using the GAM supports the higher odds ratio estimate of 21.2 (95% confidence interval: 15.5-25.3). The highway-related effects were observed to fade at about 150 m distance. Road effects appear to be enhanced in geological units characterized by Holocene gravels and Laramide andesite/basalt. Overall, landslide susceptibility was found to be more than one order of magnitude higher in close proximity to paved interurban highways in the Andes of southern Ecuador.

  9. Landslide susceptibility near highways is increased by 1 order of magnitude in the Andes of southern Ecuador, Loja province

    NASA Astrophysics Data System (ADS)

    Brenning, A.; Schwinn, M.; Ruiz-Páez, A. P.; Muenchow, J.

    2015-01-01

    Mountain roads in developing countries are known to increase landslide occurrence due to often inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading. This study empirically investigates landslide initiation frequency along two paved interurban highways in the tropical Andes of southern Ecuador across different climatic regimes. Generalized additive models (GAM) and generalized linear models (GLM) were used to analyze the relationship between mapped landslide initiation points and distance to highway while accounting for topographic, climatic, and geological predictors as possible confounders. A spatial block bootstrap was used to obtain nonparametric confidence intervals for the odds ratio of landslide occurrence near the highways (25 m distance) compared to a 200 m distance. The estimated odds ratio was 18-21, with lower 95% confidence bounds >13 in all analyses. Spatial bootstrap estimation using the GAM supports the higher odds ratio estimate of 21.2 (95% confidence interval: 15.5-25.3). The highway-related effects were observed to fade at about 150 m distance. Road effects appear to be enhanced in geological units characterized by Holocene gravels and Laramide andesite/basalt. Overall, landslide susceptibility was found to be more than 1 order of magnitude higher in close proximity to paved interurban highways in the Andes of southern Ecuador.

  10. Developing a scientific procedure for community based hazard mapping and risk mitigation

    NASA Astrophysics Data System (ADS)

    Verrier, M.

    2011-12-01

    As an international exchange student from the Geological Sciences Department at San Diego State University (SDSU), I joined the KKN-PPM program at Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia, in July 2011 for 12 days (July 4th to July 16th) of its two month duration (July 4th to August 25th). The KKN-PPM group I was attached was designated 154 and was focused in Plosorejo Village, Karanganyar, Kerjo, Central Java, Indonesia. The mission of KKN-PPM 154 was to survey Plosorejo village for existing landslides, to generate a simple hazard susceptibility map that can be understood by local villagers, and then to begin dissemination of that map into the community. To generate our susceptibility map we first conducted a geological survey of the existing landslides in the field study area, with a focus on determining landslide triggers and gauging areas for susceptibility for future landslides. The methods for gauging susceptibility included lithological observation, the presence of linear cracking, visible loss of structural integrity in structures such as villager homes, as well as collaboration with local residents and with the local rescue and response team. There were three color distinctions used in representing susceptibility which were green, where there is no immediate danger of landslide damage; orange, where transportation routes are at risk of being disrupted by landslides; and red, where imminent landslide potential puts a home in direct danger. The landslide inventory and susceptibility data was compiled into digital mediums such as CorelDraw, ArcGIS and Google Earth. Once a technical map was generated, we presented it to the village leadership for confirmation and modification based on their experience. Finally, we began to use the technical susceptibility map to draft evacuation routes and meeting points in the event of landslides, as well as simple susceptibility maps that can be understood and utilized by local villagers. Landslide mitigation

  11. Assessing Landslide Mobility Using GIS: Application to Kosrae, Micronesia

    NASA Astrophysics Data System (ADS)

    Reid, M. E.; Brien, D. L.; Godt, J.; Schmitt, R. G.; Harp, E. L.

    2015-12-01

    Deadly landslides are often mobile landslides, as exemplified by the disastrous landslide that occurred near Oso, Washington in 2014 killing 43. Despite this association, many landslide susceptibility maps do not identify runout areas. We developed a simple, GIS-based method for identifying areas potentially overrun by mobile slides and debris flows. Our method links three processes within a DEM landscape: landslide initiation, transport, and debris-flow inundation (from very mobile slides). Given spatially distributed shear strengths, we first identify initiation areas using an infinite-slope stability analysis. We then delineate transport zones, or regions of potential entrainment and/or deposition, using a height/length runout envelope. Finally, where these transport zones intersect the channel network, we start debris-flow inundation zones. The extent of inundation is computed using the USGS model Laharz, modified to include many debris-flow locations throughout a DEM. Potential debris-flow volumes are computed from upslope initiation areas and typical slide thicknesses. We applied this approach to the main island of Kosrae State, Federated States of Micronesia (FSM). In 2002, typhoon Chata'an triggered numerous landslides on the neighboring islands of Chuuk State, FSM, resulting in 43 fatalities. Using an infinite-slope stability model calibrated to the Chuuk event, we identified potential landslide initiation areas on Kosrae. We then delineated potential transport zones using a 20º runout envelope, based on runout observations from Chuuk. Potential debris-flow inundation zones were then determined using Laharz. Field inspections on Kosrae revealed that our resulting susceptibility map correctly classified areas covered by previous debris-flow deposits and did not include areas covered by fluvial deposits. Our map has the advantage of providing a visual tool to portray initiation, transport, and runout zones from mobile landslides.

  12. Advances in Landslide Nowcasting: Evaluation of a Global and Regional Modeling Approach

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia Bach; Peters-Lidard, Christa; Adler, Robert; Hong, Yang; Kumar, Sujay; Lerner-Lam, Arthur

    2011-01-01

    The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of nowcasts that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario

  13. Qualitative landslide susceptibility assessment by multicriteria analysis: A case study from San Antonio del Sur, Guantánamo, Cuba

    NASA Astrophysics Data System (ADS)

    Castellanos Abella, Enrique A.; Van Westen, Cees J.

    Geomorphological information can be combined with decision-support tools to assess landslide hazard and risk. A heuristic model was applied to a rural municipality in eastern Cuba. The study is based on a terrain mapping units (TMU) map, generated at 1:50,000 scale by interpretation of aerial photos, satellite images and field data. Information describing 603 terrain units was collected in a database. Landslide areas were mapped in detail to classify the different failure types and parts. Three major landslide regions are recognized in the study area: coastal hills with rockfalls, shallow debris flows and old rotational rockslides denudational slopes in limestone, with very large deep-seated rockslides related to tectonic activity and the Sierra de Caujerí scarp, with large rockslides. The Caujerí scarp presents the highest hazard, with recent landslides and various signs of active processes. The different landforms and the causative factors for landslides were analyzed and used to develop the heuristic model. The model is based on weights assigned by expert judgment and organized in a number of components such as slope angle, internal relief, slope shape, geological formation, active faults, distance to drainage, distance to springs, geomorphological subunits and existing landslide zones. From these variables a hierarchical heuristic model was applied in which three levels of weights were designed for classes, variables, and criteria. The model combines all weights into a single hazard value for each pixel of the landslide hazard map. The hazard map was then divided by two scales, one with three classes for disaster managers and one with 10 detailed hazard classes for technical staff. The range of weight values and the number of existing landslides is registered for each class. The resulting increasing landslide density with higher hazard classes indicates that the output map is reliable. The landslide hazard map was used in combination with existing information

  14. Landslide Inventory Mapping from Bitemporal 10 m SENTINEL-2 Images Using Change Detection Based Markov Random Field

    NASA Astrophysics Data System (ADS)

    Qin, Y.; Lu, P.; Li, Z.

    2018-04-01

    Landslide inventory mapping is essential for hazard assessment and mitigation. In most previous studies, landslide mapping was achieved by visual interpretation of aerial photos and remote sensing images. However, such method is labor-intensive and time-consuming, especially over large areas. Although a number of semi-automatic landslide mapping methods have been proposed over the past few years, limitations remain in terms of their applicability over different study areas and data, and there is large room for improvement in terms of the accuracy and automation degree. For these reasons, we developed a change detection-based Markov Random Field (CDMRF) method for landslide inventory mapping. The proposed method mainly includes two steps: 1) change detection-based multi-threshold for training samples generation and 2) MRF for landslide inventory mapping. Compared with the previous methods, the proposed method in this study has three advantages: 1) it combines multiple image difference techniques with multi-threshold method to generate reliable training samples; 2) it takes the spectral characteristics of landslides into account; and 3) it is highly automatic with little parameter tuning. The proposed method was applied for regional landslides mapping from 10 m Sentinel-2 images in Western China. Results corroborated the effectiveness and applicability of the proposed method especially the capability of rapid landslide mapping. Some directions for future research are offered. This study to our knowledge is the first attempt to map landslides from free and medium resolution satellite (i.e., Sentinel-2) images in China.

  15. Contribution of physical modelling to climate-driven landslide hazard mapping: an alpine test site

    NASA Astrophysics Data System (ADS)

    Vandromme, R.; Desramaut, N.; Baills, A.; Hohmann, A.; Grandjean, G.; Sedan, O.; Mallet, J. P.

    2012-04-01

    The aim of this work is to develop a methodology for integrating climate change scenarios into quantitative hazard assessment and especially their precipitation component. The effects of climate change will be different depending on both the location of the site and the type of landslide considered. Indeed, mass movements can be triggered by different factors. This paper describes a methodology to address this issue and shows an application on an alpine test site. Mechanical approaches represent a solution for quantitative landslide susceptibility and hazard modeling. However, as the quantity and the quality of data are generally very heterogeneous at a regional scale, it is necessary to take into account the uncertainty in the analysis. In this perspective, a new hazard modeling method is developed and integrated in a program named ALICE. This program integrates mechanical stability analysis through a GIS software taking into account data uncertainty. This method proposes a quantitative classification of landslide hazard and offers a useful tool to gain time and efficiency in hazard mapping. However, an expertise approach is still necessary to finalize the maps. Indeed it is the only way to take into account some influent factors in slope stability such as heterogeneity of the geological formations or effects of anthropic interventions. To go further, the alpine test site (Barcelonnette area, France) is being used to integrate climate change scenarios into ALICE program, and especially their precipitation component with the help of a hydrological model (GARDENIA) and the regional climate model REMO (Jacob, 2001). From a DEM, land-cover map, geology, geotechnical data and so forth the program classifies hazard zones depending on geotechnics and different hydrological contexts varying in time. This communication, realized within the framework of Safeland project, is supported by the European Commission under the 7th Framework Programme for Research and Technological

  16. Mapping landslide source and transport areas in VHR images with Object-Based Analysis and Support Vector Machines

    NASA Astrophysics Data System (ADS)

    Heleno, Sandra; Matias, Magda; Pina, Pedro

    2015-04-01

    Visual interpretation of satellite imagery remains extremely demanding in terms of resources and time, especially when dealing with numerous multi-scale landslides affecting wide areas, such as is the case of rainfall-induced shallow landslides. Applying automated methods can contribute to more efficient landslide mapping and updating of existing inventories, and in recent years the number and variety of approaches is rapidly increasing. Very High Resolution (VHR) images, acquired by space-borne sensors with sub-metric precision, such as Ikonos, Quickbird, Geoeye and Worldview, are increasingly being considered as the best option for landslide mapping, but these new levels of spatial detail also present new challenges to state of the art image analysis tools, asking for automated methods specifically suited to map landslide events on VHR optical images. In this work we develop and test a methodology for semi-automatic landslide recognition and mapping of landslide source and transport areas. The method combines object-based image analysis and a Support Vector Machine supervised learning algorithm, and was tested using a GeoEye-1 multispectral image, sensed 3 days after a damaging landslide event in Madeira Island, together with a pre-event LiDAR DEM. Our approach has proved successful in the recognition of landslides on a 15 Km2-wide study area, with 81 out of 85 landslides detected in its validation regions. The classifier also showed reasonable performance (false positive rate 60% and false positive rate below 36% in both validation regions) in the internal mapping of landslide source and transport areas, in particular in the sunnier east-facing slopes. In the less illuminated areas the classifier is still able to accurately map the source areas, but performs poorly in the mapping of landslide transport areas.

  17. Towards the Optimal Pixel Size of dem for Automatic Mapping of Landslide Areas

    NASA Astrophysics Data System (ADS)

    Pawłuszek, K.; Borkowski, A.; Tarolli, P.

    2017-05-01

    Determining appropriate spatial resolution of digital elevation model (DEM) is a key step for effective landslide analysis based on remote sensing data. Several studies demonstrated that choosing the finest DEM resolution is not always the best solution. Various DEM resolutions can be applicable for diverse landslide applications. Thus, this study aims to assess the influence of special resolution on automatic landslide mapping. Pixel-based approach using parametric and non-parametric classification methods, namely feed forward neural network (FFNN) and maximum likelihood classification (ML), were applied in this study. Additionally, this allowed to determine the impact of used classification method for selection of DEM resolution. Landslide affected areas were mapped based on four DEMs generated at 1 m, 2 m, 5 m and 10 m spatial resolution from airborne laser scanning (ALS) data. The performance of the landslide mapping was then evaluated by applying landslide inventory map and computation of confusion matrix. The results of this study suggests that the finest scale of DEM is not always the best fit, however working at 1 m DEM resolution on micro-topography scale, can show different results. The best performance was found at 5 m DEM-resolution for FFNN and 1 m DEM resolution for results. The best performance was found to be using 5 m DEM-resolution for FFNN and 1 m DEM resolution for ML classification.

  18. A review of the 2005 Kashmir earthquake-induced landslides; from a remote sensing prospective

    NASA Astrophysics Data System (ADS)

    Shafique, Muhammad; van der Meijde, Mark; Khan, M. Asif

    2016-03-01

    The 8th October 2005 Kashmir earthquake, in northern Pakistan has triggered thousands of landslides, which was the second major factor in the destruction of the build-up environment, after earthquake-induced ground shaking. Subsequent to the earthquake, several researchers from home and abroad applied a variety of remote sensing techniques, supported with field observations, to develop inventories of the earthquake-triggered landslides, analyzed their spatial distribution and subsequently developed landslide-susceptibility maps. Earthquake causative fault rupture, geology, anthropogenic activities and remote sensing derived topographic attributes were observed to have major influence on the spatial distribution of landslides. These were subsequently used to develop a landslide susceptibility map, thereby demarcating the areas prone to landsliding. Temporal studies monitoring the earthquake-induced landslides shows that the earthquake-induced landslides are stabilized, contrary to earlier belief, directly after the earthquake. The biggest landslide induced dam, as a result of the massive Hattian Bala landslide, is still posing a threat to the surrounding communities. It is observed that remote sensing data is effectively and efficiently used to assess the landslides triggered by the Kashmir earthquake, however, there is still a need of more research to understand the mechanism of intensity and distribution of landslides; and their continuous monitoring using remote sensing data at a regional scale. This paper, provides an overview of remote sensing and GIS applications, for the Kashmir-earthquake triggered landslides, derived outputs and discusses the lessons learnt, advantages, limitations and recommendations for future research.

  19. The use of IFSAR data in GIS-based landslide susceptibility evaluation

    NASA Astrophysics Data System (ADS)

    Floris, M.; Squarzoni, C.; Hundseder, C.; Mason, M.; Genevois, R.

    2010-05-01

    GIS-based landslide susceptibility evaluation is based on the spatial relationships between landslides and their related factors. The analyses are highly conditioned by precision and accuracy of input factors, in particular landslides identification and characterization. Factors influencing landslide spatial hazard consist of geological, geomorphological, hydrogeological and tectonic features, geomechanical and geotechnical properties, land use and management, and DEM-derived factors (elevation, slope, aspect, curvature, superficial flow). The choice of influencing factors depends on: method of analysis, scale of inputs, aim of the outputs, availability and quality of the input data. Then, the choice can be made a priori, on the bases of an in-deep territorial knowledge and experts' judgements, or by performing statistical analyses, finalized to identify the significance of each of the influencing factor. Due to the large availability of terrain data, spatial models often include DEM-derived factors, but the resolution and accuracy of DEMs influence the final outputs. In this work the relationships between landslides occurred in the volcanic area of the Euganean Hills Regional Park (SE of Padua, Veneto region, Italy) and morphometric factors (slope, aspect and curvature) will be examined through a simple probability method. The use of complex and time consuming mathematical or statistical models is not always recommended, because often simple models can lead to more accurate results. Morphometric input factors are derived from DEMs created from vector elevation data of the regional cartography at 1:5.000 scale and with NEXTMap® data (http://www.intermap.com). NEXTMap® Digital Surface Model (DSM) and Digital Terrain Model (DTM) are generated using Intermap's IFSAR (Interferometric Synthetic Aperture Radar) technology mounted on an aircraft at a flight height of 8500 m above Mean Sea Level and under a side viewing angle of about 45°. The DSM represents the first

  20. Landslide Mapping Using Imagery Acquired by a Fixed-Wing Uav

    NASA Astrophysics Data System (ADS)

    Rau, J. Y.; Jhan, J. P.; Lo, C. F.; Lin, Y. S.

    2011-09-01

    In Taiwan, the average annual rainfall is about 2,500 mm, about three times the world average. Hill slopes where are mostly under meta-stable conditions due to fragmented surface materials can easily be disturbed by heavy typhoon rainfall and/or earthquakes, resulting in landslides and debris flows. Thus, an efficient data acquisition and disaster surveying method is critical for decision making. Comparing with satellite and airplane, the unmanned aerial vehicle (UAV) is a portable and dynamic platform for data acquisition. In particularly when a small target area is required. In this study, a fixed-wing UAV that equipped with a consumer grade digital camera, i.e. Canon EOS 450D, a flight control computer, a Garmin GPS receiver and an attitude heading reference system (AHRS) are proposed. The adopted UAV has about two hours flight duration time with a flight control range of 20 km and has a payload of 3 kg, which is suitable for a medium scale mapping and surveying mission. In the paper, a test area with 21.3 km2 in size containing hundreds of landslides induced by Typhoon Morakot is used for landslides mapping. The flight height is around 1,400 meters and the ground sampling distance of the acquired imagery is about 17 cm. The aerial triangulation, ortho-image generation and mosaicking are applied to the acquired images in advance. An automatic landslides detection algorithm is proposed based on the object-based image analysis (OBIA) technique. The color ortho-image and a digital elevation model (DEM) are used. The ortho-images before and after typhoon are utilized to estimate new landslide regions. Experimental results show that the developed algorithm can achieve a producer's accuracy up to 91%, user's accuracy 84%, and a Kappa index of 0.87. It demonstrates the feasibility of the landslide detection algorithm and the applicability of a fixed-wing UAV for landslide mapping.

  1. Methods of Measuring and Mapping of Landslide Areas

    NASA Astrophysics Data System (ADS)

    Skrzypczak, Izabela; Kokoszka, Wanda; Kogut, Janusz; Oleniacz, Grzegorz

    2017-12-01

    The problem of attracting new investment areas and the inability of current zoning areas, allows us to understand why it is impossible to completely rule out building on landslide areas. Therefore, it becomes important issue of monitoring areas at risk of landslides. Only through appropriate monitoring and proper development of measurements resulting as maps of areas at risk of landslides enables us to estimate the risk and the relevant economic calculation for the realization of the anticipated investment in such areas. The results of monitoring of the surface and in-depth of the landslides are supplemented with constant observation of precipitation. The previous analyses and monitoring of landslides show that some of them are continuously active. GPS measurements, especially with laser scanning provide a unique activity data acquired on the surface of each individual landslide. The development of high resolution numerical models of terrain and the creation of differential models based on subsequent measurements, informs us about the size of deformation, both in units of distance (displacements) and volume. The compatibility of the data with information from in-depth monitoring allows the generation of a very reliable in-depth model of landslide, and as a result proper calculation of the volume of colluvium. Programs presented in the article are a very effective tool to generate in-depth model of landslide. In Poland, the steps taken under the SOPO project i.e. the monitoring and description of landslides are absolutely necessary for social and economic reasons and they may have a significant impact on the economy and finances of individual municipalities and also a whole country economy.

  2. Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

    NASA Astrophysics Data System (ADS)

    Strauch, R. L.; Istanbulluoglu, E.

    2017-12-01

    We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

  3. Comparison of event landslide inventories: the Pogliaschina catchment test case, Italy

    NASA Astrophysics Data System (ADS)

    Mondini, A. C.; Viero, A.; Cavalli, M.; Marchi, L.; Herrera, G.; Guzzetti, F.

    2014-07-01

    Event landslide inventory maps document the extent of populations of landslides caused by a single natural trigger, such as an earthquake, an intense rainfall event, or a rapid snowmelt event. Event inventory maps are important for landslide susceptibility and hazard modelling, and prove useful to manage residual risk after a landslide-triggering event. Standards for the preparation of event landslide inventory maps are lacking. Traditional methods are based on the visual interpretation of stereoscopic aerial photography, aided by field surveys. New and emerging techniques exploit remotely sensed data and semi-automatic algorithms. We describe the production and comparison of two independent event inventories prepared for the Pogliaschina catchment, Liguria, Northwest Italy. The two inventories show landslides triggered by an intense rainfall event on 25 October 2011, and were prepared through the visual interpretation of digital aerial photographs taken 3 days and 33 days after the event, and by processing a very-high-resolution image taken by the WorldView-2 satellite 4 days after the event. We compare the two inventories qualitatively and quantitatively using established and new metrics, and we discuss reasons for the differences between the two landslide maps. We expect that the results of our work can help in deciding on the most appropriate method to prepare reliable event inventory maps, and outline the advantages and the limitations of the different approaches.

  4. Landslides triggered by the 1994 Northridge, California, earthquake

    USGS Publications Warehouse

    Harp, E.L.; Jibson, R.W.

    1996-01-01

    The 17 January 1994 Northridge, California, earthquake (Mw, = 6.7) triggered more than 11,000 landslides over an area of about 10,000 km2. Most of the landslides were concentrated in a 1000-km2 area that included the Santa Susana Mountains and the mountains north of the Santa Clara River valley. We mapped landslides triggered by the earthquake in the field and from 1:60,000-nominal-scale aerial photography provided by the U.S. Air Force and taken the morning of the earthquake; these mapped landslides were subsequently digitized and plotted in a GIS-based format. Most of the triggered landslides were shallow (1- to 5-m thick), highly disrupted falls and slides within weakly cemented Tertiary to Pleistocene clastic sediment. Average volumes of these types of landslides were less than 1000 m3, but many had volumes exceeding 100,000 m3. The larger disrupted slides commonly had runout paths of more than 50 m, and a few traveled as far as 200 m from the bases of steep parent slopes. Deeper (>5-m thick) rotational slumps and block slides numbered in the tens to perhaps hundreds, a few of which exceeded 100,000 m3 in volume. Most of these were reactivations of previously existing landslides. The largest single landslide triggered by the earthquake was a rotational slump/block slide having a volume of 8 ?? 106 m3. Analysis of the mapped landslide distribution with respect to variations in (1) landslide susceptibility and (2) strong shaking recorded by hundreds of instruments will form the basis of a seismic landslide hazard analysis of the Los Angeles area.

  5. Geomorphological mapping and geotechnical testing of the March 22, 2014, SR530 landslide near Oso, Washington

    NASA Astrophysics Data System (ADS)

    Collins, B. D.; Reid, M. E.; Vallance, J. W.; Iverson, R. M.; Schmidt, K. M.

    2014-12-01

    The March 22, 2014 landslide near Oso, Washington devastated a community, killing 43 people, destroying dozens of homes, and temporarily closing a section of State Route (SR) 530. The landslide, characterized as a debris avalanche - debris flow - rotational slide, was triggered by heavy precipitation in the region and initiated from a 200 m tall section of Pleistocene glacial deposits. The entire landslide encompassed an area of 1.2 km2. To understand the mobility of this landslide, we performed geological and geomorphological mapping throughout the initiation, transport, and deposition zones. In addition, we mapped a 450-m-long cross-section through the western distal lobe created by the excavation to reopen the SR530 roadbed to temporary traffic. Samples collected during mapping were used for geotechnical testing to evaluate the mobility of the landslide materials. Our detailed (1:300) geological mapping of the excavation revealed the juxtaposition of sand (glacial outwash) and clay (glaciolacustrine) debris avalanche hummocks towards the distal end of the landslide. Further, we found that two sections of the roadbed, having a combined length of at least 150 m, were entrained in the landslide. Throughout the debris avalanche deposit, 1:1200-scale geomorphological mapping identified a preponderance of sand boils located within thinner deposits between hummocks, suggesting that liquefaction played a role in the landslides mobility. In the central distal end of the landslide, we mapped on-lap deposits, wherein distal debris flow material overrode smaller hummocks of the larger debris avalanche deposit. Discovery of these deposits indicates that the run out of the landslide might have been even longer in places had topographic barriers (i.e., the other side of the valley) not reflected the flow back towards itself.

  6. Map of landslides triggered by the January 12, 2010, Haiti earthquake

    USGS Publications Warehouse

    Harp, Edwin L.; Jibson, Randall W.; Schmitt, Robert G.

    2016-04-12

    The magnitude (M) 7.0 Haiti earthquake of January 12, 2010, triggered landslides throughout much of Haiti on the island of Hispaniola in the Caribbean Sea. The epicenter of the quake was located at 18.44°N., 72.57°W. at a depth of 13 kilometers (km) approximately 25 km southwest of the capital, Port-au-Prince. Although estimates vary widely, the most reliable surveys of casualties indicate that the earthquake caused 158,679 fatalities and more than 300,000 injuries. The U.S. Geological Survey compared publicly available satellite imagery acquired both before and after the earthquake and mapped 23,567 landslides that were triggered by the strong shaking. Our mapping from aerial photography and satellite imagery was augmented by field observations.Most of the landslides triggered by the earthquake were south of the Léogâne fault on the footwall and were fairly shallow falls and slides in weathered limestone (2–5 meters [m] thick) and volcanic rock and soil (generally <1 m thick). Landslides extended from the north to the south coasts of the southwestern peninsula (southwest of Port-au-Prince) and almost 60 km to the east and west of the epicenter. The highest concentration of landslides was on the steep limestone slopes of incised river valleys, but large numbers of landslides also occurred on gentler slopes in weathered volcanic rocks. Although some high landslide concentrations did occur near areas of maximum fault slip, the overall distribution of landslides appears to involve complex interactions between geology, topography, and strong shaking with limited spatial correlation between fault slip and landslides.

  7. Ground motions at the outermost limits of seismically triggered landslides

    USGS Publications Warehouse

    Jibson, Randall W.; Harp, Edwin L.

    2016-01-01

    Over the last few decades, we and our colleagues have conducted field investigations in which we mapped the outermost limits of triggered landslides in four earthquakes: 1987 Whittier Narrows, California (M 5.9), 1987 Superstition Hills, California (M 6.5), 1994 Northridge, California (M 6.7), and 2011 Mineral, Virginia (M 5.8). In an additional two earthquakes, 1976 Guatemala (M 7.5) and 1983 Coalinga, California (M 6.5), we determined limits using high‐resolution aerial‐photographic interpretation in conjunction with more limited ground investigation. Limits in these earthquakes were defined by the locations of the very smallest failures (<1  m3) from the most susceptible slopes that can be identified positively as having been triggered by earthquake shaking. Because we and our colleagues conducted all of these investigations, consistent methodology and criteria were used in determining limits. In the six earthquakes examined, we correlated the outermost landslide limits with peak ground accelerations (PGAs) from ShakeMap models of each earthquake. For the four earthquakes studied by field investigation, the minimum PGA values associated with farthest landslide limits ranged from 0.02g to 0.08g. The range for the two earthquakes investigated using aerial‐photographic interpretations was 0.05–0.11g. Although PGA values at landslide limits depend on several factors, including material strength, topographic amplification, and hydrologic conditions, these values provide an empirically useful lower limiting range of PGA needed to trigger the smallest failures on very susceptible slopes. In a well‐recorded earthquake, this PGA range can be used to identify an outer boundary within which we might expect to find landsliding; in earthquakes that are not well recorded, mapping the outermost landslide limits provides a useful clue about ground‐motion levels at the mapped limits.

  8. Ground motions at the outermost limits of seismically triggered landslides

    NASA Astrophysics Data System (ADS)

    Jibson, Randall W.; Harp, Edwin L.

    2016-04-01

    Over the last few decades, we and our colleagues have conducted field investigations in which we mapped the outermost limits of triggered landslides in four earthquakes: 1987 Whittier Narrows, California (M 5.9), 1987 Superstition Hills, California (M 6.5), 1994 Northridge, California (M 6.7), and 2011 Mineral, Virginia (M 5.8). In an additional two earthquakes, 1976 Guatemala (M 7.5) and 1983 Coalinga, California (M 6.5), we determined limits using high-resolution aerial photographic interpretation in conjunction with more limited ground investigation. Limits in these earthquakes were defined by the locations of the very smallest failures (< 1 m^3) from the most susceptible slopes that can be identified positively as having been triggered by earthquake shaking. Because we and our colleagues conducted all of these investigations, consistent methodology and criteria were used in determining limits. In the six earthquakes examined, we correlated the outermost landslide limits with peak ground accelerations (PGA) from ShakeMap models of each earthquake. For the four earthquakes studied by field investigation, the minimum PGA values associated with farthest landslide limits ranged from 0.02-0.08 g. The range for the two earthquakes investigated using aerial photographic interpretations was 0.05-0.11 g. Although PGA values at landslide limits depend on several factors - including material strength, topographic amplification, and hydrologic conditions - these values provide an empirically useful lower limiting range of PGA needed to trigger the smallest failures on very susceptible slopes. In a well-recorded earthquake, this PGA range can be used to identify an outer boundary within which we might expect to find landsliding; in earthquakes that are not well recorded, mapping the outermost landslide limits provides a useful clue about ground-motion levels at the mapped limits.

  9. Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria Region of central Italy

    USGS Publications Warehouse

    Salciarini, D.; Godt, J.W.; Savage, W.Z.; Conversini, P.; Baum, R.L.; Michael, J.A.

    2006-01-01

    We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.

  10. Landslide inventories: The essential part of seismic landslide hazard analyses

    USGS Publications Warehouse

    Harp, E.L.; Keefer, D.K.; Sato, H.P.; Yagi, H.

    2011-01-01

    A detailed and accurate landslide inventory is an essential part of seismic landslide hazard analysis. An ideal inventory would cover the entire area affected by an earthquake and include all of the landslides that are possible to detect down to sizes of 1-5. m in length. The landslides must also be located accurately and mapped as polygons depicting their true shapes. Such mapped landslide distributions can then be used to perform seismic landslide hazard analysis and other quantitative analyses. Detailed inventory maps of landslide triggered by earthquakes began in the early 1960s with the use of aerial photography. In recent years, advances in technology have resulted in the accessibility of satellite imagery with sufficiently high resolution to identify and map all but the smallest of landslides triggered by a seismic event. With this ability to view any area of the globe, we can acquire imagery for any earthquake that triggers significant numbers of landslides. However, a common problem of incomplete coverage of the full distributions of landslides has emerged along with the advent of high resolution satellite imagery. ?? 2010.

  11. A landslide susceptibility prediction on a sample slope in Kathmandu Nepal associated with the 2015's Gorkha Earthquake

    NASA Astrophysics Data System (ADS)

    Kubota, Tetsuya; Prasad Paudel, Prem

    2016-04-01

    In 2013, some landslides induced by heavy rainfalls occurred in southern part of Kathmandu, Nepal which is located southern suburb of Kathmandu, the capital. These landslide slopes hit by the strong Gorkha Earthquake in April 2015 and seemed to destabilize again. Hereby, to clarify their susceptibility of landslide in the earthquake, one of these landslide slopes was analyzed its slope stability by CSSDP (Critical Slip Surface analysis by Dynamic Programming based on limit equilibrium method, especially Janbu method) against slope failure with various seismic acceleration observed around Kathmandu in the Gorkha Earthquake. The CSSDP can detect the landslide slip surface which has minimum Fs (factor of safety) automatically using dynamic programming theory. The geology in this area mainly consists of fragile schist and it is prone to landslide occurrence. Field survey was conducted to obtain topological data such as ground surface and slip surface cross section. Soil parameters obtained by geotechnical tests with field sampling were applied. Consequently, the slope has distinctive characteristics followings in terms of slope stability: (1) With heavy rainfall, it collapsed and had a factor of safety Fs <1.0 (0.654 or more). (2) With seismic acceleration of 0.15G (147gal) observed around Kathmandu, it has Fs=1.34. (3) With possible local seismic acceleration of 0.35G (343gal) estimated at Kathmandu, it has Fs=0.989. If it were very shallow landslide and covered with cedars, it could have Fs =1.055 due to root reinforcement effect to the soil strength. (4) Without seismic acceleration and with no rainfall condition, it has Fs=1.75. These results can explain the real landslide occurrence in this area with the maximum seismic acceleration estimated as 0.15G in the vicinity of Kathmandu by the Gorkha Earthquake. Therefore, these results indicate landslide susceptibility of the slopes in this area with strong earthquake. In this situation, it is possible to predict

  12. Landslide Hazard Zonation and Risk Assessment of Ramganga Basin in Garhwal Himalaya

    NASA Astrophysics Data System (ADS)

    Wasini Pandey, Bindhy; Roy, Nikhil

    2016-04-01

    The Himalaya being unique in its physiographic, tectonic and climatic characteristics coupled with many natural and man-made factors is inherently prone to landslides. These landslides lead to mass loss of property and lives every year in Himalayas. Hence, Landslide Hazard Zonation is important to take quick and safe mitigation measures and make strategic planning for future development. The present study tries to explore the causes of landslides in Ramganga Basin in Garhwal Himalaya, which has an established history and inherent susceptibility to massive landslides has been chosen for landslide hazard zonation and risk assessment. The satellite imageries of LANDSAT, IRS P6, ASTER along with Survey of India (SOI) topographical sheets formed the basis for deriving baseline information on various parameters like slope, aspect, relative relief, drainage density, geology/lithology and land use/land cover. The weighted parametric method will be used to determine the degree of susceptibility to landslides. Finally, a risk map will be prepared from the landslide probability values, which will be classified into no risk, very low to moderate, high, and very high to severe landslide hazard risk zones. Keywords: Landslides, Hazard Zonation, Risk Assessment

  13. Proposed method for hazard mapping of landslide propagation zone

    NASA Astrophysics Data System (ADS)

    Serbulea, Manole-Stelian; Gogu, Radu; Manoli, Daniel-Marcel; Gaitanaru, Dragos Stefan; Priceputu, Adrian; Andronic, Adrian; Anghel, Alexandra; Liviu Bugea, Adrian; Ungureanu, Constantin; Niculescu, Alexandru

    2013-04-01

    Sustainable development of communities situated in areas with landslide potential requires a fully understanding of the mechanisms that govern the triggering of the phenomenon as well as the propagation of the sliding mass, with catastrophic consequences on the nearby inhabitants and environment. Modern analysis methods for areas affected by the movement of the soil bodies are presented in this work, as well as a new procedure to assess the landslide hazard. Classical soil mechanics offer sufficient numeric models to assess the landslide triggering zone, such as Limit Equilibrium Methods (Fellenius, Janbu, Morgenstern-Price, Bishop, Spencer etc.), blocks model or progressive mobilization models, Lagrange-based finite element method etc. The computation methods for assessing the propagation zones are quite recent and have high computational requirements, thus not being sufficiently used in practice to confirm their feasibility. The proposed procedure aims to assess not only the landslide hazard factor, but also the affected areas, by means of simple mathematical operations. The method can easily be employed in GIS software, without requiring engineering training. The result is obtained by computing the first and second derivative of the digital terrain model (slope and curvature maps). Using the curvature maps, it is shown that one can assess the areas most likely to be affected by the propagation of the sliding masses. The procedure is first applied on a simple theoretical model and then used on a representative section of a high exposure area in Romania. The method is described by comparison with Romanian legislation for risk and vulnerability assessment, which specifies that the landslide hazard is to be assessed, using an average hazard factor Km, obtained from various other factors. Following the employed example, it is observed that using the Km factor there is an inconsistent distribution of the polygonal surfaces corresponding to different landslide

  14. Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry

    Treesearch

    J. McKean; J. Roering

    2004-01-01

    A map of extant slope failures is the most basic element of any landslide assessment. Without an accurate inventory of slope instability, it is not possible to analyze the controls on the spatial and temporal patterns of mass movement or the environmental, human, or geomorphic consequences of slides. Landslide inventory maps are tedious to compile, difficult to make in...

  15. A Global Landslide Nowcasting System using Remotely Sensed Information

    NASA Astrophysics Data System (ADS)

    Kirschbaum, Dalia; Stanely, Thomas

    2017-04-01

    A global Landslide Hazard Assessment model for Situational Awareness (LHASA) has been developed that combines susceptibility information with satellite-based precipitation to provide an indication of potential landslide activity at the global scale every 30 minutes. This model utilizes a 1-km global susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. A multi-satellite dataset from the Global Precipitation Measurement (GPM) mission is used to identify the current and antecedent rainfall conditions from the past 7 days. When both rainfall and susceptibility are high, a "nowcast" is issued to indicate areas where a landslide may be likely. The global LHASA model is currently being run in near real-time every 30 minutes and the outputs are available in several different formats at https://pmm.nasa.gov/precip-apps. This talk outlines the LHASA system, discusses the performance metrics and potential applications of the LHASA system.

  16. The National Landslide Database of Great Britain: Acquisition, communication and the role of social media

    NASA Astrophysics Data System (ADS)

    Pennington, Catherine; Freeborough, Katy; Dashwood, Claire; Dijkstra, Tom; Lawrie, Kenneth

    2015-11-01

    The British Geological Survey (BGS) is the national geological agency for Great Britain that provides geoscientific information to government, other institutions and the public. The National Landslide Database has been developed by the BGS and is the focus for national geohazard research for landslides in Great Britain. The history and structure of the geospatial database and associated Geographical Information System (GIS) are explained, along with the future developments of the database and its applications. The database is the most extensive source of information on landslides in Great Britain with over 17,000 records of landslide events to date, each documented as fully as possible for inland, coastal and artificial slopes. Data are gathered through a range of procedures, including: incorporation of other databases; automated trawling of current and historical scientific literature and media reports; new field- and desk-based mapping technologies with digital data capture, and using citizen science through social media and other online resources. This information is invaluable for directing the investigation, prevention and mitigation of areas of unstable ground in accordance with Government planning policy guidelines. The national landslide susceptibility map (GeoSure) and a national landslide domains map currently under development, as well as regional mapping campaigns, rely heavily on the information contained within the landslide database. Assessing susceptibility to landsliding requires knowledge of the distribution of failures, an understanding of causative factors, their spatial distribution and likely impacts, whilst understanding the frequency and types of landsliding present is integral to modelling how rainfall will influence the stability of a region. Communication of landslide data through the Natural Hazard Partnership (NHP) and Hazard Impact Model contributes to national hazard mitigation and disaster risk reduction with respect to weather and

  17. Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey).

    PubMed

    Akgun, Aykut; Kıncal, Cem; Pradhan, Biswajeet

    2012-09-01

    In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.

  18. Landslides density map of S. Miguel Island, Azores archipelago

    NASA Astrophysics Data System (ADS)

    Valadão, P.; Gaspar, J. L.; Queiroz, G.; Ferreira, T.

    The Azores archipelago is located in the Atlantic Ocean and is composed of nine volcanic islands. S. Miguel, the largest one, is formed by three active, E-W trending, trachytic central volcanoes with caldera (Sete Cidades, Fogo and Furnas). Chains of basaltic cinder cones link those major volcanic structures. An inactive trachytic central volcano (Povoação) and an old basaltic volcanic complex (Nordeste) comprise the easternmost part of the island. Since the settlement of the island early in the 15th century, several destructive landslides triggered by catastrophic rainfall episodes, earthquakes and volcanic eruptions occurred in different areas of S. Miguel. One unique event killed thousands of people in 1522. Houses and bridges were destroyed, roads were cut, communications, water and energy supply systems became frequently disrupted and areas of fertile land were often buried by mud. Based on (1) historical documents, (2) aerial photographs and (3) field observations, landslide sites were plotted on a topographic map, in order to establish a landslide density map for the island. Data obtained showed that landslide hazard is higher on (1) the main central volcanoes where the thickness of unconsolidated pyroclastic deposits is considerable high and (2) the old basaltic volcanic complex, marked by deep gullies developed on thick sequences of lava flows. In these areas, caldera walls, fault scarps, steep valley margins and sea cliffs are potentially hazardous.

  19. The National Landslide Database and GIS for Great Britain: construction, development, data acquisition, application and communication

    NASA Astrophysics Data System (ADS)

    Pennington, Catherine; Dashwood, Claire; Freeborough, Katy

    2014-05-01

    The National Landslide Database has been developed by the British Geological Survey (BGS) and is the focus for national geohazard research for landslides in Great Britain. The history and structure of the geospatial database and associated Geographical Information System (GIS) are explained, along with the future developments of the database and its applications. The database is the most extensive source of information on landslides in Great Britain with over 16,500 records of landslide events, each documented as fully as possible. Data are gathered through a range of procedures, including: incorporation of other databases; automated trawling of current and historical scientific literature and media reports; new field- and desk-based mapping technologies with digital data capture, and crowd-sourcing information through social media and other online resources. This information is invaluable for the investigation, prevention and mitigation of areas of unstable ground in accordance with Government planning policy guidelines. The national landslide susceptibility map (GeoSure) and a national landslide domain map currently under development rely heavily on the information contained within the landslide database. Assessing susceptibility to landsliding requires knowledge of the distribution of failures and an understanding of causative factors and their spatial distribution, whilst understanding the frequency and types of landsliding present is integral to modelling how rainfall will influence the stability of a region. Communication of landslide data through the Natural Hazard Partnership (NHP) contributes to national hazard mitigation and disaster risk reduction with respect to weather and climate. Daily reports of landslide potential are published by BGS through the NHP and data collected for the National Landslide Database is used widely for the creation of these assessments. The National Landslide Database is freely available via an online GIS and is used by a

  20. Comparing two models for post-wildfire debris flow susceptibility mapping

    NASA Astrophysics Data System (ADS)

    Cramer, J.; Bursik, M. I.; Legorreta Paulin, G.

    2017-12-01

    Traditionally, probabilistic post-fire debris flow susceptibility mapping has been performed based on the typical method of failure for debris flows/landslides, where slip occurs along a basal shear zone as a result of rainfall infiltration. Recent studies have argued that post-fire debris flows are fundamentally different in their method of initiation, which is not infiltration-driven, but surface runoff-driven. We test these competing models by comparing the accuracy of the susceptibility maps produced by each initiation method. Debris flow susceptibility maps are generated according to each initiation method for a mountainous region of Southern California that recently experienced wildfire and subsequent debris flows. A multiple logistic regression (MLR), which uses the occurrence of past debris flows and the values of environmental parameters, was used to determine the probability of future debris flow occurrence. The independent variables used in the MLR are dependent on the initiation method; for example, depth to slip plane, and shear strength of soil are relevant to the infiltration initiation, but not surface runoff. A post-fire debris flow inventory serves as the standard to compare the two susceptibility maps, and was generated by LiDAR analysis and field based ground-truthing. The amount of overlap between the true locations where debris flow erosion can be documented, and where the MLR predicts high probability of debris flow initiation was statistically quantified. The Figure of Merit in Space (FMS) was used to compare the two models, and the results of the FMS comparison suggest that surface runoff-driven initiation better explains debris flow occurrence. Wildfire can breed conditions that induce debris flows in areas that normally would not be prone to them. Because of this, nearby communities at risk may not be equipped to protect themselves against debris flows. In California, there are just a few months between wildland fire season and the wet

  1. Introduction: Hazard mapping

    USGS Publications Warehouse

    Baum, Rex L.; Miyagi, Toyohiko; Lee, Saro; Trofymchuk, Oleksandr M

    2014-01-01

    Twenty papers were accepted into the session on landslide hazard mapping for oral presentation. The papers presented susceptibility and hazard analysis based on approaches ranging from field-based assessments to statistically based models to assessments that combined hydromechanical and probabilistic components. Many of the studies have taken advantage of increasing availability of remotely sensed data and nearly all relied on Geographic Information Systems to organize and analyze spatial data. The studies used a range of methods for assessing performance and validating hazard and susceptibility models. A few of the studies presented in this session also included some element of landslide risk assessment. This collection of papers clearly demonstrates that a wide range of approaches can lead to useful assessments of landslide susceptibility and hazard.

  2. Rapid Offline-Online Post-Disaster Landslide Mapping Tool: A case study from Nepal

    NASA Astrophysics Data System (ADS)

    Olyazadeh, Roya; Jaboyedoff, Michel; Sudmeier-Rieux, Karen; Derron, Marc-Henri; Devkota, Sanjaya

    2016-04-01

    One of the crucial components of post disaster management is the efficient mapping of impacted areas. Here we present a tool designed to map landslides and affected objects after the earthquakes of 2015 in Nepal as well as for intense rainfall impact. Because internet is not available in many rural areas of Nepal, we developed an offline-online prototype based on Open-Source WebGIS technologies to make data on hazard impacts, including damaged infrastructure, landslides or flooding events available to authorities and the general public. This mobile application was designed as a low-cost, rapid and participatory method for recording impacts from hazard events. It is possible to record such events offline and upload them through a server, where internet connection is available. This application allows user authentication, image capturing, and information collation such as geolocation, event description, interactive mapping and finally storing all the data in the server for further analysis and visualisation. This application can be accessed by a mobile phone (Android) or a tablet as a hybrid version for both offline and online versions. The offline version has an interactive-offline map function which allows users to upload satellites image in order to improve ground truthing interpretation. After geolocation, the user can start mapping and then save recorded data into Geojson-TXT files that can be easily uploaded to the server whenever internet is available. This prototype was tested specifically for a rapid assessment of landslides and relevant land use characteristics such as roads, forest area, rivers in the Phewa Lake watershed near Pokhara, Nepal where a large number landslides were activated or reactivated after the 2015 monsoon season. More than 60 landslides were recorded during two days of field trip. Besides, it is possible to use this application for any other kind of hazard event like flood, avalanche, etc. Keywords: Offline, Online, Open source, Web

  3. Landslide movement mapping by sub-pixel amplitude offset tracking - case study from Corvara landslide

    NASA Astrophysics Data System (ADS)

    Darvishi, Mehdi; Schlögel, Romy; Cuozzo, Giovanni; Callegari, Mattia; Thiebes, Benni; Bruzzone, Lorenzo; Mulas, Marco; Corsini, Alessandro; Mair, Volkmar

    2016-04-01

    Despite the advantages of Differential Synthetic Aperture Radar Interferometry (DInSAR) methods for quantifying landslide deformation over large areas, some limitations remain. These include for example geometric distortions, atmospheric artefacts, geometric and temporal decorrelations, data and scale constraints, and the restriction that only 1-dimentional line-of-sight (LOS) deformations can be measured. At local scale, the major limitations are dense vegetation, as well as large displacement rates which can lead to decorrelation between SAR acquisitions also for high resolution images and temporal baselines. Sub-pixel offset tracking was proposed to overcome some of these limitations. Two of the most important advantages of this technique are the mapping of 2-D displacements (azimuth and range directions), and the fact that there is no need for complex phase unwrapping algorithms which could give wrong results or fail in case of decorrelation or fast ground deformations. As sub-pixel offset tracking is highly sensitive to the spatial resolution of the data, latest generations of SAR sensors such as TerraSAR-X and COSMO-SkyMed providing high resolution data (up to 1m) have great potential to become established methods in the field of ground deformation monitoring. In this study, sub-pixel offset tracking was applied to COSMO SkyMed X-band imagery in order to quantify ground displacements and to evaluate the feasibility of offset tracking for landslide movement mapping and monitoring. The study area is the active Corvara landslide located in the Italian Alps, described as a slow-moving and deep-seated landslide with annual displacement rates of up to 20 m. Corner reflectors specifically designed for X-band were installed on the landslide and used as reference points for sub-pixel offset tracking. Satellite images covering the period from 2013 to 2015 were analyzed with an amplitude tracking tool for calculating the offsets and extracting 2-D displacements. Sub

  4. SINMAP Modeling of an active landslide area in the Swabian Alb

    NASA Astrophysics Data System (ADS)

    Terhorst, Birgit; Jaeger, Daniel

    2015-04-01

    Landslides are a common hazard in German low mountain areas such as the Swabian Alb. As areas of former landslides are highly prone to secondary movements, this study aims to assess the susceptibility for landslide hazard around Mössingen-Öschingen, a region consistently affected by landslides during the last decades. Based on the history and development of mass movements and a detailed geomorphological map, slope stability was calculated using SINMAP (Stability Index Mapping). SINMAP (Pack et al., 1998; Tarboton, 1997) is based on the "infinite slope stability model" by Hammond et al. (1992) and Montgomery and Dietrich (1994) describing the ratio of slope stabilizing factors (e.g. cohesion) and slope destabilizing factors (e.g. gravitation) on a slip surface parallel to the slope. Most input parameters are determined by the relief and therefore, can be calculated from a digital terrain model (DTM, resolution 5 m). Based on the local morphology and geology, a total of 10 'calibration regions', each with similar hydrogeological characteristics, were defined. Further input parameters were: Shear strength via friction angle (Phi), cohesion (C) and hydraulic conductivity (T/R). The data was obtained from soil mechanical assessments and field/laboratory analyses. As a result, a specific stability index is calculated, describing the susceptibility of a slope movement. In a first step, the 'topographic wetness index' (derived from catchment area, slope gradient and hydraulic conductivity) was calculated. Results show several preferred (natural) drainage channels with generally higher water saturations in morphological depressions. Several of them can be linked to the location of damaged houses in the settlement area on the lower slope. The SINMAP calculation clearly revealed the impermeable Callovian clay layers as most prone to slope movements. A comparison of the susceptibility map with slide masses which were mapped during a field survey showed generally good

  5. A new-old approach for shallow landslide analysis and susceptibility zoning in fine-grained weathered soils of southern Italy

    NASA Astrophysics Data System (ADS)

    Cascini, Leonardo; Ciurleo, Mariantonietta; Di Nocera, Silvio; Gullà, Giovanni

    2015-07-01

    Rainfall-induced shallow landslides involve several geo-environmental contexts and different types of soils. In clayey soils, they affect the most superficial layer, which is generally constituted by physically weathered soils characterised by a diffuse pattern of cracks. This type of landslide most commonly occurs in the form of multiple-occurrence landslide phenomena simultaneously involving large areas and thus has several consequences in terms of environmental and economic damage. Indeed, landslide susceptibility zoning is a relevant issue for land use planning and/or design purposes. This study proposes a multi-scale approach to reach this goal. The proposed approach is tested and validated over an area in southern Italy affected by widespread shallow landslides that can be classified as earth slides and earth slide-flows. Specifically, by moving from a small (1:100,000) to a medium scale (1:25,000), with the aid of heuristic and statistical methods, the approach identifies the main factors leading to landslide occurrence and effectively detects the areas potentially affected by these phenomena. Finally, at a larger scale (1:5000), deterministic methods, i.e., physically based models (TRIGRS and TRIGRS-unsaturated), allow quantitative landslide susceptibility assessment, starting from sample areas representative of those that can be affected by shallow landslides. Considering the reliability of the obtained results, the proposed approach seems useful for analysing other case studies in similar geological contexts.

  6. DTMs Assessment to the Definition of Shallow Landslides Prone Areas

    NASA Astrophysics Data System (ADS)

    Martins, Tiago D.; Oka-Fiori, Chisato; Carvalho Vieira, Bianca; Montgomery, David R.

    2017-04-01

    Predictive methods have been developed, especially since the 1990s, to identify landslide prone areas. One of the examples it is the physically based model SHALSTAB (Shallow Landsliding Stability Model), that calculate the potential instability for shallow landslides based on topography and physical soil properties. Normally, in such applications in Brazil, the Digital Terrain Model (DTM), is obtained mainly from conventional contour lines. However, recently the LiDAR (Light Detection and Ranging) system has been largely used in Brazil. Thus, this study aimed to evaluate different DTM's, generated from conventional data and LiDAR, and their influence in generating susceptibility maps to shallow landslides using SHALSTAB model. For that were analyzed the physical properties of soil, the response of the model when applying conventional topographical data and LiDAR's in the generation of DTM, and the shallow landslides susceptibility maps based on different topographical data. The selected area is in the urban perimeter of the municipality of Antonina (PR), affected by widespread landslides in March 2011. Among the results, it was evaluated different LiDAR data interpolation, using GIS tools, wherein the Triangulation/Natural Neighbor presented the best performance. It was also found that in one of evaluation indexes (Scars Concentration), the LiDAR derived DTM presented the best performance when compared with the one originated from contour lines, however, the Landslide Potential index, has presented a small increase. Consequently, it was possible to assess the DTM's, and the one derived from LiDAR improved very little the certitude percentage. It is also noted a gap in researches carried out in Brazil on the use of products generated from LiDAR data on geomorphological analysis.

  7. Mapping basin-wide subaquatic slope failure susceptibility as a tool to assess regional seismic and tsunami hazards

    NASA Astrophysics Data System (ADS)

    Strasser, Michael; Hilbe, Michael; Anselmetti, Flavio S.

    2010-05-01

    occurred. Comparison of reconstructed critical stability conditions with the known distribution of landslide deposits reveals minimum and maximum threshold conditions for slopes that failed or remained stable, respectively. The resulting correlations reveal good agreements and suggest that the slope stability model generally succeeds in reproducing past events. The basin-wide mapping of subaquatic slope failure susceptibility through time thus can also be considered as a promising paleoseismologic tool that allows quantification of past earthquake ground shaking intensities. Furthermore, it can be used to assess the present-day slope failure susceptibility allowing for identification of location and estimation of size of future, potentially tsunamigenic subaquatic landslides. The new approach presented in our comprehensive lake study and resulting conceptual ideas can be vital to improve our understanding of larger marine slope instabilities and related seismic and oceanic geohazards along formerly glaciated ocean margins and closed basins worldwide.

  8. Potential Deep Seated Landslide Mapping from Various Temporal Data - Benchmark, Aerial Photo, and SAR

    NASA Astrophysics Data System (ADS)

    Wang, Kuo-Lung; Lin, Jun-Tin; Lee, Yi-Hsuan; Lin, Meei-Ling; Chen, Chao-Wei; Liao, Ray-Tang; Chi, Chung-Chi; Lin, Hsi-Hung

    2016-04-01

    Landslide is always not hazard until mankind development in highly potential area. The study tries to map deep seated landslide before the initiation of landslide. Study area in central Taiwan is selected and the geological condition is quite unique, which is slate. Major direction of bedding in this area is northeast and the dip ranges from 30-75 degree to southeast. Several deep seated landslides were discovered in the same side of bedding from rainfall events. The benchmarks from 2002 ~ 2009 are in this study. However, the benchmarks were measured along Highway No. 14B and the road was constructed along the peak of mountains. Taiwan located between sea plates and continental plate. The elevation of mountains is rising according to most GPS and benchmarks in the island. The same trend is discovered from benchmarks in this area. But some benchmarks are located in landslide area thus the elevation is below average and event negative. The aerial photos from 1979 to 2007 are used for orthophoto generation. The changes of land use are obvious during 30 years and enlargement of river channel is also observed in this area. Both benchmarks and aerial photos have discovered landslide potential did exist this area but how big of landslide in not easy to define currently. Thus SAR data utilization is adopted in this case. DInSAR and SBAS sar analysis are used in this research and ALOS/PALSAR from 2006 to 2010 is adopted. DInSAR analysis shows that landslide is possible mapped but the error is not easy to reduce. The error is possibly form several conditions such as vegetation, clouds, vapor, etc. To conquer the problem, time series analysis, SBAS, is adopted in this research. The result of SBAS in this area shows that large deep seated landslides are easy mapped and the accuracy of vertical displacement is reasonable.

  9. GIS-based landslide hazard evaluation at the regional scale: some critical points in the permanent displacement approach for seismically-induced landslide maps

    NASA Astrophysics Data System (ADS)

    Vessia, Giovanna; Parise, Mario

    2013-04-01

    Landslide susceptibility and hazard are commonly developed by means of GIS (Geographic Information Systems) tools. Many products such as DTM (Digital Terrain Models), and geological, morphological and lithological layers (often, to be downloaded for free and integrated within GIS) are nowadays available on the web and ready to be used for urban planning purposes. The multiple sources of public information enable the local authorities to use these products for predicting hazards within urban territories by limited investments on technological infrastructures. On the contrary, the necessary expertise required for conducting pertinent hazard analyses is high, and rarely available at the level of the local authorities. In this respect, taking into account the production of seismically-induced landslide hazard maps at regional scale drawn by GIS tool, these can be performed according to the permanent displacement approach derived by Newmark's sliding block method (Newmark, 1965). Some simplified assumptions are considered for occurrence of a seismic mass movement, listed as follows: (1) the Mohr-Coulomb criterion is used for the plastic displacement of the rigid block; (2) only downward movements are accounted for; (3) a translative sliding mechanism is assumed. Under such conditions, several expressions have been proposed for predicting permanent displacements of slopes during seismic events (Ambresys and Menu, 1988; Luzi and Pergalani 2000; Romeo 2000; Jibson 2007, among the others). These formulations have been provided by researchers for different ranges of seismic magnitudes, and for indexes describing the seismic action, such as peak ground acceleration, peak ground velocity, Arias Intensity, and damage potential. With respect to the resistant properties of the rock units, the critical acceleration is the relevant strength variable in every expressions; it is a function of local slope, groundwater level, unit weight shear resistance of the surficial sediments, and

  10. New Method for Estimating Landslide Losses for Major Winter Storms in California.

    NASA Astrophysics Data System (ADS)

    Wills, C. J.; Perez, F. G.; Branum, D.

    2014-12-01

    We have developed a prototype system for estimating the economic costs of landslides due to winter storms in California. This system uses some of the basic concepts and estimates of the value of structures from the HAZUS program developed for FEMA. Using the only relatively complete landslide loss data set that we could obtain, data gathered by the City of Los Angeles in 1978, we have developed relations between landslide susceptibility and loss ratio for private property (represented as the value of wood frame structures from HAZUS). The landslide loss ratios estimated from the Los Angeles data are calibrated using more generalized data from the 1982 storms in the San Francisco Bay area to develop relationships that can be used to estimate loss for any value of 2-day or 30-day rainfall averaged over a county. The current estimates for major storms are long projections from very small data sets, subject to very large uncertainties, so provide a very rough estimate of the landslide damage to structures and infrastructure on hill slopes. More importantly, the system can be extended and improved with additional data and used to project landslide losses in future major winter storms. The key features of this system—the landslide susceptibility map, the relationship between susceptibility and loss ratio, and the calibration of estimates against losses in past storms—can all be improved with additional data. Most importantly, this study highlights the importance of comprehensive studies of landslide damage. Detailed surveys of landslide damage following future storms that include locations and amounts of damage for all landslides within an area are critical for building a well-calibrated system to project future landslide losses. Without an investment in post-storm landslide damage surveys, it will not be possible to improve estimates of the magnitude or distribution of landslide damage, which can range up to billions of dollars.

  11. Climate services for adapting landslide hazard prevention measures in the Vrancea Seismic Region

    NASA Astrophysics Data System (ADS)

    Micu, Dana; Balteanu, Dan; Jurchescu, Marta; Sima, Mihaela; Micu, Mihai

    2014-05-01

    The Vrancea Seismic Region is covering an area of about 8 000 km2 in the Romanian Curvature Carpathians and Subcarpathians and it is considered one of Europe's most intensely multi-hazard-affected areas. Due to its geomorphic traits (heterogeneous morphostructural units of flysch mountains and molasse hills and depressions), the area is strongly impacted by extreme hydro-meteorological events which are potentially enhancing the numerous damages inflicted to a dense network of human settlements. An a priori knowledge of future climate change is a useful climate service for local authorities to develop regional adapting strategies and adequate prevention/preparedness frameworks. This paper aims at integrating the results of the high-resolution climate projections over the 21st century (within the FP7 ECLISE project) into the regional landslide hazard assessment. The requirements of users (Civil Protection, Land management, local authorities) for this area refer to reliable and high-resolution spatial data on landslide and flood hazard for short and medium-term risk management strategies. An insight into the future behavior of climate variability in the Vrancea Seismic Region, based on future climate projections of three regional models, under three RCPs (2.6, 4.5, 8.6), suggests a clear warming, both annually and seasonally and a rather limited annual precipitation decrease, but with a strong change of seasonality. A landslide inventory of 2485 cases (shallow and medium seated earth, debris and rock slides and earth and debris flows) was obtained based on large scale geomorphological mapping and aerial photos support (GeoEye, DigitalGlobe; provided by GoogleEarth and BingMaps). The landslides are uniformly distributed across the area, being considered representative for the entire morphostructural environment. Landslide susceptibility map was obtained using multivariate statistical analysis (logistic regression), while a relative landslide hazard index was computed

  12. Comparison of Fuzzy-Based Models in Landslide Hazard Mapping

    NASA Astrophysics Data System (ADS)

    Mijani, N.; Neysani Samani, N.

    2017-09-01

    Landslide is one of the main geomorphic processes which effects on the development of prospect in mountainous areas and causes disastrous accidents. Landslide is an event which has different uncertain criteria such as altitude, slope, aspect, land use, vegetation density, precipitation, distance from the river and distance from the road network. This research aims to compare and evaluate different fuzzy-based models including Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), Fuzzy Gamma and Fuzzy-OR. The main contribution of this paper reveals to the comprehensive criteria causing landslide hazard considering their uncertainties and comparison of different fuzzy-based models. The quantify of evaluation process are calculated by Density Ratio (DR) and Quality Sum (QS). The proposed methodology implemented in Sari, one of the city of Iran which has faced multiple landslide accidents in recent years due to the particular environmental conditions. The achieved results of accuracy assessment based on the quantifier strated that Fuzzy-AHP model has higher accuracy compared to other two models in landslide hazard zonation. Accuracy of zoning obtained from Fuzzy-AHP model is respectively 0.92 and 0.45 based on method Precision (P) and QS indicators. Based on obtained landslide hazard maps, Fuzzy-AHP, Fuzzy Gamma and Fuzzy-OR respectively cover 13, 26 and 35 percent of the study area with a very high risk level. Based on these findings, fuzzy-AHP model has been selected as the most appropriate method of zoning landslide in the city of Sari and the Fuzzy-gamma method with a minor difference is in the second order.

  13. Uncertainty on shallow landslide hazard assessment: from field data to hazard mapping

    NASA Astrophysics Data System (ADS)

    Trefolini, Emanuele; Tolo, Silvia; Patelli, Eduardo; Broggi, Matteo; Disperati, Leonardo; Le Tuan, Hai

    2015-04-01

    empirical relations with geotechnical index properties. Site specific information was regionalized at map scale by (hard and fuzzy) clustering analysis taking into account spatial variables such as: geology, geomorphology and hillslope morphometric variables (longitudinal and transverse curvature, flow accumulation and slope), the latter derived by a DEM with 10 m cell size. In order to map shallow landslide hazard, Monte Carlo simulation was performed for some common physically based models available in literature (eg. SINMAP, SHALSTAB, TRIGRS). Furthermore, a new approach based on the use of Bayesian Network was proposed and validated. Different models, such as Intervals, Convex Models and Fuzzy Sets, were adopted for the modelling of input parameters. Finally, an accuracy assessment was carried out on the resulting maps and the propagation of uncertainty of input parameters into the final shallow landslide hazard estimation was estimated. The outcomes of the analysis are compared and discussed in term of discrepancy among map pixel values and related estimated error. The novelty of the proposed method is on estimation of the confidence of the shallow landslides hazard mapping at regional level. This allows i) to discriminate regions where hazard assessment is robust from areas where more data are necessary to increase the confidence level and ii) to assess the reliability of the procedure used for hazard assessment.

  14. Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework

    USGS Publications Warehouse

    Godt, J.W.; Baum, R.L.; Savage, W.Z.; Salciarini, D.; Schulz, W.H.; Harp, E.L.

    2008-01-01

    Application of transient deterministic shallow landslide models over broad regions for hazard and susceptibility assessments requires information on rainfall, topography and the distribution and properties of hillside materials. We survey techniques for generating the spatial and temporal input data for such models and present an example using a transient deterministic model that combines an analytic solution to assess the pore-pressure response to rainfall infiltration with an infinite-slope stability calculation. Pore-pressures and factors of safety are computed on a cell-by-cell basis and can be displayed or manipulated in a grid-based GIS. Input data are high-resolution (1.8??m) topographic information derived from LiDAR data and simple descriptions of initial pore-pressure distribution and boundary conditions for a study area north of Seattle, Washington. Rainfall information is taken from a previously defined empirical rainfall intensity-duration threshold and material strength and hydraulic properties were measured both in the field and laboratory. Results are tested by comparison with a shallow landslide inventory. Comparison of results with those from static infinite-slope stability analyses assuming fixed water-table heights shows that the spatial prediction of shallow landslide susceptibility is improved using the transient analyses; moreover, results can be depicted in terms of the rainfall intensity and duration known to trigger shallow landslides in the study area.

  15. An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

    NASA Technical Reports Server (NTRS)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2006-01-01

    Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

  16. An integrated approach of analytical network process and fuzzy based spatial decision making systems applied to landslide risk mapping

    NASA Astrophysics Data System (ADS)

    Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar

    2017-09-01

    Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km2, is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.

  17. Landslide hazard assessment : LIFE+IMAGINE project methodology and Liguria region use case

    NASA Astrophysics Data System (ADS)

    Spizzichino, Daniele; Campo, Valentina; Congi, Maria Pia; Cipolloni, Carlo; Delmonaco, Giuseppe; Guerrieri, Luca; Iadanza, Carla; Leoni, Gabriele; Trigila, Alessandro

    2015-04-01

    Scope of the work is to present a methodology developed for analysis of potential impacts in areas prone to landslide hazard in the framework of the EC project LIFE+IMAGINE. The project aims to implement a web services-based infrastructure addressed to environmental analysis, that integrates, in its own architecture, specifications and results from INSPIRE, SEIS and GMES. Existing web services has been customized to provide functionalities for supporting environmental integrated management. The implemented infrastructure has been applied to landslide risk scenarios, developed in selected pilot areas, aiming at: i) application of standard procedures to implement a landslide risk analysis; ii) definition of a procedure for assessment of potential environmental impacts, based on a set of indicators to estimate the different exposed elements with their specific vulnerability in the pilot area. The landslide pilot and related scenario are focused at providing a simplified Landslide Risk Assessment (LRA) through: 1) a landslide inventory derived from available historical and recent databases and maps; 2) landslide susceptibility and hazard maps; 3) assessment of exposure and vulnerability on selected typologies of elements at risk; 4) implementation of a landslide risk scenario for different sets of exposed elements 5) development of a use case; 6) definition of guidelines, best practices and production of thematic maps. The LRA has been implemented in Liguria region, Italy, in two different catchment areas located in the Cinque Terre National Park, characterized by a high landslide susceptibility and low resilience. The landslide risk impact analysis has been calibrated taking into account the socio-economic damage caused by landslides triggered by the October 2011 meteorological event. During this event, over 600 landslides were triggered in the selected pilot area. Most of landslides affected the diffuse system of anthropogenic terraces and caused the direct

  18. Shallow landslide prediction and analysis with risk assessment using a spatial model in the coastal region in the state of São Paulo, Brazil

    NASA Astrophysics Data System (ADS)

    Camarinha, P. I. M.; Canavesi, V.; Alvalá, R. C. S.

    2013-10-01

    In Brazil, most of the disasters involving landslide occur in coastal regions, with population density concentrated on steep slopes. Thus, different approaches have been used to evaluate the landslide risk, although the greatest difficulty is related to the scarcity of spatial data with good quality. In this context, four cities located on the southeast coast of Brazil - Santos, Cubatão, Caraguatatuba and Ubatuba - in a region with the rough reliefs of the Serra do Mar and with a history of natural disasters were evaluated. Spatial prediction by fuzzy gamma technique was used for the landslide susceptibility mapping, considering environmental variables from data and software in the public domain. To validate the susceptibility mapping results, it was overlapped with risk sectors provided by the Geological Survey of Brazil (CPRM). A positive correlation was observed between the classes most susceptible and the location of these sectors. The results were also analyzed from the categorization of risk levels provided by CPRM. To compare the approach with other studies using landslide-scar maps, correlated indexes were evaluated, which also showed satisfactory results, thus indicating that the methodology presented is appropriate for risk assessment in urban areas and can be replicated to municipalities that do not have risk areas mapped.

  19. Potentiality of SENTINEL-1 for landslide detection: first results in the Molise Region (Italy)

    NASA Astrophysics Data System (ADS)

    Barra, Anna; Monserrat, Oriol; Mazzanti, Paolo; Esposito, Carlo; Crosetto, Michele; Scarascia Mugnozza, Gabriele

    2016-04-01

    A detailed inventory map, including information on landslide activity, is one of the most important input to landslide susceptibility and hazard analyses. The contribution of satellite SAR Interferometry in landslide risk mitigation is well-known within the scientific community. In fact, many encouraging results have been obtained, principally, in areas characterized by high coherence of the images (e.g. due to rock lithology or urban environment setting). In terms of coherence, the expected increased capabilities of Sentinel-1 for landslide mapping and monitoring are connected to both wavelength (55.5 mm) and short temporal baseline (12 days). The latter one is expected to be a key feature for increasing coherence and for defining monitoring and updating plans. With the aim of assessing these potentialities, we processed a set of 14 Sentinel-1 SLC images, acquired during a temporal span of 7 months, over the Molise region (Southern Italy), a critical area geologically susceptible to landslides. Even though Molise is mostly covered by crops and forested areas (63% and 35% respectively), that means a non-optimal coherence condition for SAR interferometry, promising results have been obtained. This has been achieved by integrating differential interferometric SAR techniques (12-days interferograms and time series) with GIS multilayer analysis (optical, geological, geomorphological, etc.). Specifically, analyzing a single burst of a Sentinel-1 frame (approximately 1875 km2), 62 landslides have been detected, thus allowing to improve the pre-existing inventory maps both in terms of landslide boundaries and state of activity. The results of our ongoing research show that Sentinel-1 can give a significant improvement in terms of exploitation of SAR data for landslide mapping and monitoring. As a matter of fact, by analyzing longer periods, it is expected to achieve a better understanding of landslide behavior and its relationship with triggering factors. This will be key

  20. Development of a globally applicable model for near real-time prediction of seismically induced landslides

    USGS Publications Warehouse

    Nowicki, M. Anna; Wald, David J.; Hamburger, Michael W.; Hearne, Mike; Thompson, Eric M.

    2014-01-01

    Substantial effort has been invested to understand where seismically induced landslides may occur in the future, as they are a costly and frequently fatal threat in mountainous regions. The goal of this work is to develop a statistical model for estimating the spatial distribution of landslides in near real-time around the globe for use in conjunction with the U.S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system. This model uses standardized outputs of ground shaking from the USGS ShakeMap Atlas 2.0 to develop an empirical landslide probability model, combining shaking estimates with broadly available landslide susceptibility proxies, i.e., topographic slope, surface geology, and climate parameters. We focus on four earthquakes for which digitally mapped landslide inventories and well-constrainedShakeMaps are available. The resulting database is used to build a predictive model of the probability of landslide occurrence. The landslide database includes the Guatemala (1976), Northridge (1994), Chi-Chi (1999), and Wenchuan (2008) earthquakes. Performance of the regression model is assessed using statistical goodness-of-fit metrics and a qualitative review to determine which combination of the proxies provides both the optimum prediction of landslide-affected areas and minimizes the false alarms in non-landslide zones. Combined with near real-time ShakeMaps, these models can be used to make generalized predictions of whether or not landslides are likely to occur (and if so, where) for earthquakes around the globe, and eventually to inform loss estimates within the framework of the PAGER system.

  1. The inner structure of landslides and landslide-prone slopes in south German cuesta landscapes assessed by geophysical, geomorphological and sedimentological approaches

    NASA Astrophysics Data System (ADS)

    Schwindt, Daniel; Sandmeier, Christine; Büdel, Christian; Jäger, Daniel; Wilde, Martina; Terhorst, Birgit

    2016-04-01

    Investigations on landslide activity in the cuesta landscape of Germany, usually characterized by an interbedding of morphologically hard (e.g. sand-/limestones) and soft (clay) sedimentary rocks are relatively sparse. However, spring 2013 has once again revealed a high susceptibility of the slopes in the Franconian and Swabian Alb to mass movements, when enduring rainfalls initiated numerous landslides causing considerable damage to settlements and infrastructure. Many aspects like the spatial distribution of landslides, triggering factors, and process dynamics - especially with view on the reactivation of landslides - require intensive investigations to allow for assessment of the landslide vulnerability and the development of reliable early-warning systems. Aim of the study is to achieve a deeper insight into the triggering factors and the process dynamics of landslides in the cuesta landscape with special regard on landslide proneness of slopes and the potential reactivation of old landslides. A multi-methodological approach was conducted based on geophysical investigations (seismic refraction tomography - SRT, electrical resistivity tomography - ERT), geomorphological mapping, morphometric GIS-based analysis, core soundings and substrate mapping. Study sites are located in the Swabian Alb (southwestern Germany) in the Jurassic escarpment where where Oxfordian marls and limestones superimpose Callovian clays, as well as in the northeastern Franconian Alb, within the escarpment of the so called Rhätolias with with red claystones of the late Norian (Feuerletten formation) below interbedding layers of sand- and claystones of the Rhaetian (Upper Triassic) and Hettangian ( Lower Jurassic). The investigated landslides strongly differ with respect to their age, from young landslides originated in spring 2013 to ancient landslides. Investigations reveal a distinct diversity of landslide types composed of a complex combination of processes. The applied methods allow

  2. Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness

    NASA Astrophysics Data System (ADS)

    Kirschbaum, Dalia; Stanley, Thomas

    2018-03-01

    Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past 7 days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a "nowcast" is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8% to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open-source framework that can be adapted to other spatial and temporal scales based on data availability.

  3. Operational early warning of shallow landslides in Norway: Evaluation of landslide forecasts and associated challenges

    NASA Astrophysics Data System (ADS)

    Dahl, Mads-Peter; Colleuille, Hervé; Boje, Søren; Sund, Monica; Krøgli, Ingeborg; Devoli, Graziella

    2015-04-01

    The Norwegian Water Resources and Energy Directorate (NVE) runs a national early warning system (EWS) for shallow landslides in Norway. Slope failures included in the EWS are debris slides, debris flows, debris avalanches and slush flows. The EWS has been operational on national scale since 2013 and consists of (a) quantitative landslide thresholds and daily hydro-meteorological prognosis; (b) daily qualitative expert evaluation of prognosis / additional data in decision to determine warning levels; (c) publication of warning levels through various custom build internet platforms. The effectiveness of an EWS depends on both the quality of forecasts being issued, and the communication of forecasts to the public. In this analysis a preliminary evaluation of landslide forecasts from the Norwegian EWS within the period 2012-2014 is presented. Criteria for categorizing forecasts as correct, missed events or false alarms are discussed and concrete examples of forecasts falling into the latter two categories are presented. The evaluation show a rate of correct forecasts exceeding 90%. However correct forecast categorization is sometimes difficult, particularly due to poorly documented landslide events. Several challenges has to be met in the process of further lowering rates of missed events of false alarms in the EWS. Among others these include better implementation of susceptibility maps in landslide forecasting, more detailed regionalization of hydro-meteorological landslide thresholds, improved prognosis on precipitation, snowmelt and soil water content as well as the build-up of more experience among the people performing landslide forecasting.

  4. Rainfall Induced Landslides in Puerto Rico (Invited)

    NASA Astrophysics Data System (ADS)

    Lepore, C.; Kamal, S.; Arnone, E.; Noto, V.; Shanahan, P.; Bras, R. L.

    2009-12-01

    Landslides are a major geologic hazard in the United States, typically triggered by rainfall, earthquakes, volcanoes and human activity. Rainfall-induced landslides are the most common type in the island of Puerto Rico, with one or two large events per year. We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model capable of simulating landslides, tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. .Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides, which is used to predict the dynamic susceptibility of the basin to landslides.

  5. Airborne geophysical mapping as an innovative methodology for landslide investigation: evaluation of results from the Gschliefgraben landslide, Austria

    NASA Astrophysics Data System (ADS)

    Supper, R.; Baroň, I.; Ottowitz, D.; Motschka, K.; Gruber, S.; Winkler, E.; Jochum, B.; Römer, A.

    2013-05-01

    In September 2009, a complex airborne geophysical survey was performed in the large landslide affected area of the Gschliefgraben valley, Upper Austria, in order to evaluate the usability of this method for landslide detection and mapping. An evaluation of the results, including different remote sensing and ground based methods, proved that airborne geophysics, especially the airborne electromagnetic method, has a high potential for landslide investigation. This is due to its sensitivity to fluid and clay content and porosity, which are parameters showing characteristic values in landslide prone structures. Resistivity distributions in different depth levels as well as depth-slices along selected profiles are presented and compared with ground geoelectrical profiles for the test area of Gschliefgraben. Further interesting results can be derived from the radiometric survey, whereas the naturally occurring radioisotopes 40K and 232Th, as well as the man-made nuclide 137Cs have been considered. While the content of potassium and thorium in the shallow subsurface layer is expressively related to the lithological composition, the distribution of caesium is mainly determined by mass wasting processes.

  6. Airborne geophysical mapping as an innovative methodology for landslide investigation: evaluation of results from the Gschliefgraben landslide, Austria

    NASA Astrophysics Data System (ADS)

    Supper, R.; Baroň, I.; Ottowitz, D.; Motschka, K.; Gruber, S.; Winkler, E.; Jochum, B.; Römer, A.

    2013-12-01

    In September 2009, a complex airborne geophysical survey was performed in the large landslide affected area of the Gschliefgraben valley, Upper Austria, in order to evaluate the applicability of this method for landslide detection and mapping. An evaluation of the results, including different remote-sensing and ground-based methods, proved that airborne geophysics, especially the airborne electromagnetic method, has a high potential for landslide investigation. This is due to its sensitivity to fluid and clay content and porosity, which are parameters showing characteristic values in landslide prone structures. Resistivity distributions in different depth levels as well as depth slices along selected profiles are presented and compared with ground geoelectrical profiles for the test area of Gschliefgraben. Further interesting results can be derived from the radiometric survey, whereas the naturally occurring radioisotopes 40K and 232Th, as well as the man-made nuclide 137Cs have been considered. While the content of potassium and thorium in the shallow subsurface layer is expressively related to the lithological composition, the distribution of caesium is mainly determined by mass wasting processes.

  7. Future Forest Cover Change Scenarios with Implications for Landslide Risk: An Example from Buzau Subcarpathians, Romania

    NASA Astrophysics Data System (ADS)

    Malek, Žiga; Boerboom, Luc; Glade, Thomas

    2015-11-01

    This study focuses on future forest cover change in Buzau Subcarpathians, a landslide prone region in Romania. Past and current trends suggest that the area might expect a future increase in deforestation. We developed spatially explicit scenarios until 2040 to analyze the spatial pattern of future forest cover change and potential changes to landslide risk. First, we generated transition probability maps using the weights of evidence method, followed by a cellular automata allocation model. We performed expert interviews, to develop two future forest management scenarios. The Alternative scenario (ALT) was defined by 67 % more deforestation than the Business as Usual scenario (BAU). We integrated the simulated scenarios with a landslide susceptibility map. In both scenarios, most of deforestation was projected in areas where landslides are less likely to occur. Still, 483 (ALT) and 276 (BAU) ha of deforestation were projected on areas with a high-landslide occurrence likelihood. Thus, deforestation could lead to a local-scale increase in landslide risk, in particular near or adjacent to forestry roads. The parallel process of near 10 % forest expansion until 2040 was projected to occur mostly on areas with high-landslide susceptibility. On a regional scale, forest expansion could so result in improved slope stability. We modeled two additional scenarios with an implemented landslide risk policy, excluding high-risk zones. The reduction of deforestation on high-risk areas was achieved without a drastic decrease in the accessibility of the areas. Together with forest expansion, it could therefore be used as a risk reduction strategy.

  8. Future Forest Cover Change Scenarios with Implications for Landslide Risk: An Example from Buzau Subcarpathians, Romania.

    PubMed

    Malek, Žiga; Boerboom, Luc; Glade, Thomas

    2015-11-01

    This study focuses on future forest cover change in Buzau Subcarpathians, a landslide prone region in Romania. Past and current trends suggest that the area might expect a future increase in deforestation. We developed spatially explicit scenarios until 2040 to analyze the spatial pattern of future forest cover change and potential changes to landslide risk. First, we generated transition probability maps using the weights of evidence method, followed by a cellular automata allocation model. We performed expert interviews, to develop two future forest management scenarios. The Alternative scenario (ALT) was defined by 67% more deforestation than the Business as Usual scenario (BAU). We integrated the simulated scenarios with a landslide susceptibility map. In both scenarios, most of deforestation was projected in areas where landslides are less likely to occur. Still, 483 (ALT) and 276 (BAU) ha of deforestation were projected on areas with a high-landslide occurrence likelihood. Thus, deforestation could lead to a local-scale increase in landslide risk, in particular near or adjacent to forestry roads. The parallel process of near 10% forest expansion until 2040 was projected to occur mostly on areas with high-landslide susceptibility. On a regional scale, forest expansion could so result in improved slope stability. We modeled two additional scenarios with an implemented landslide risk policy, excluding high-risk zones. The reduction of deforestation on high-risk areas was achieved without a drastic decrease in the accessibility of the areas. Together with forest expansion, it could therefore be used as a risk reduction strategy.

  9. Landslide Hazard Map of The Upper Tiber River Basin, Central Italy

    NASA Astrophysics Data System (ADS)

    Cardinali, M.; Carrara, A.; Guzzetti, F.; Reichenbach, P.

    For the Upper Tiber River basin, which extends over 4000 km2 in Central Italy, a landslide hazard map was derived from a statistical model based on a mix of morpho- logical, lithological, structural and land use data. All these data were obtained from the analysis of different sets of aerial photographs, ranging in scale from 1:33,000 to 1:13,000, systematic field surveys and bibliographical information. Rock types were grouped in 37 units on the basis of the hard vs. soft rock percentage, as as- certained from photo-geological interpretation and field surveys. During the photo- interpretation, the spatial relations between bedding plane attitude and slope aspect were also systematically determined. The landslide inventory map recognised 17,600 slope-failures that cover nearly 12.5% of the basin area. Landslides, which are mainly slide flow slide earth-flow and compound or complex movements, were classified and mapped as shallow or deep seated. A DTM, with a grid resolution of 25x25 m, was derived from digitised contour lines of base topographic maps, 1:25,000.in scale. The basin was then automatically partitioned into nearly 16,000 main slope-units through a specifically-designed software module that, starting from a high quality DTM gen- erates fully connected and complementary drainage and divide networks and a wide spectrum of morphometric parameters. Main slope-units were then subdivided accord- ing to the major rock types cropping out in the basin generating over 28,700 hydro- morphological-lithological terrain-units. Using the presence/absence of landslide in each terrain unit, as the grouping variable, a stepwise discriminant function was ap- plied to the terrain units. of the 50 variables entered into the discriminant function, 15 are lithological, 15 morphological, 11 express the structural setting or bedding plane attitude, 7 refer to land use and the last 2 reflect local climatic conditions. The model proved to be capable of correctly classifying as

  10. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

    USGS Publications Warehouse

    Ohlmacher, G.C.; Davis, J.C.

    2003-01-01

    Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

  11. Multi scale modelling of landslide hazard and risk assessment in data scarce area - a case study on Dhalai District, Tripura, India

    NASA Astrophysics Data System (ADS)

    Ghosh, Kapil; De, Sunil Kumar

    2017-04-01

    Successful landslide management plans and policy depends on in-depth knowledge about the hazard and associated risk. Thus, the present research is intended to present an integrated approach involving uses of geospatial technologies for landslide hazard and risk assessment at different scales (site specific to regional level). The landslide hazard map at regional scale (district level) is prepared by using weight-rating based method. To analyze landslide manifestation in the Dhalai district of Tripura different causative factor maps (lithology, road buffer, slope, relative relief, rainfall, fault buffer, landuse/landcover and drainage density) are derived. The analysis revealed that the geological structure and human interference have more influence than other considered factors on the landslide occurrences. The landslide susceptibility zonation map shows that about 1.64 and 16.68% of the total study area is falling under very high and high susceptibility zones respectively. The landslide risk assessment at district level is generated by integrating hazard scouring and resource damage potential scouring (fuzzy membership values) maps. The values of landslide risk matrix are varying within the range of 0.001 to 0.18 and the risk assessment map shows that only 0.45% (10.80 km2) of the district is under very high risk zone, whereas, about 50% pixels of existing road section are under very high to high level of landslide risk. The major part (94.06%) of the district is under very low to low risk zone. Landslide hazard and risk assessment at site specific level have been carried out through intensive field investigation in which it is found that the Ambassa landslide is located within 150 m buffer zone of fault line. Variation of geo-electrical resistivity (2.2Ωm to 31.4Ωm) indicates the complex geological character in this area. Based on the obtained geo-technical result which helps to identify the degree of risk to the existing resource, it is appropriate to

  12. Performance evaluation of the national early warning system for shallow landslides in Norway

    NASA Astrophysics Data System (ADS)

    Dahl, Mads-Peter; Piciullo, Luca; Devoli, Graziella; Colleuille, Hervé; Calvello, Michele

    2017-04-01

    As a consequence of the increased number of rainfall-and snowmelt-induced landslides (debris flows, debris slides, debris avalanches and slush flows) occurring in Norway, a national landslide early warning system (EWS) has been developed for monitoring and forecasting the hydro-meteorological conditions potentially necessary of triggering slope failures. The system, operational since 2013, is managed by the Norwegian Water Resources and Energy Directorate (NVE) and has been designed in cooperation with the Norwegian Public Road Administration (SVV), the Norwegian National Rail Administration (JBV) and the Norwegian Meteorological Institute (MET). Decision-making in the EWS is based upon hazard threshold levels, hydro-meteorological and real-time landslide observations as well as landslide inventory and susceptibility maps. Hazard threshold levels have been obtained through statistical analyses of historical landslides and modelled hydro-meteorological parameters. Daily hydro-meteorological conditions such as rainfall, snowmelt, runoff, soil saturation, groundwater level and frost depth have been derived from a distributed version of the hydrological HBV-model. Two different landslide susceptibility maps are used as supportive data in deciding daily warning levels. Daily alerts are issued throughout the country considering variable warning zones. Warnings are issued once per day for the following 3 days with an update possibility later during the day according to the information gathered by the monitoring variables. The performance of the EWS has been evaluated applying the EDuMaP method. In particular, the performance of warnings issued in Western Norway, in the period 2013-2014 has been evaluated using two different landslide datasets. The best performance is obtained for the smallest and more accurate dataset. Different performance results may be observed as a function of changing the landslide density criterion, Lden(k), (i.e., thresholds considered to

  13. Climate change induced lanslide hazard mapping over Greece- A case study in Pelion Mountain (SE Thessaly, Central Greece)

    NASA Astrophysics Data System (ADS)

    Angelitsa, Varvara; Loupasakis, Constantinos; Anagnwstopoulou, Christina

    2015-04-01

    Landslides, as a major type of geological hazard, represent one of the natural events that occur most frequently worldwide after hydro-meteorological events. Landslides occur when the stability of a slope changes due to a number of factors, such as the steep terrain and prolonged precipitation. Identification of landslides and compilation of landslide susceptibility, hazard and risk maps are very important issues for the public authorities providing substantial information regarding, the strategic planning and management of the land-use. Although landslides cannot be predicted accurately, many attempts have been made to compile these maps. Important factors for the the compilation of reliable maps are the quality and the amount of available data and the selection of the best method for the analysis. Numerous studies and publications providing landslide susceptibility,hazard and risk maps, for different regions of Greece, have completed up to now. Their common characteristic is that they are static, taking into account parameters like geology, mean annual precipitaion, slope, aspect, distance from roads, faults and drainage network, soil capability, land use etc., without introducing the dimension of time. The current study focuses on the Pelion Mountain, which is located at the southeastern part of Thessaly in Central Greece; aiming to compile "dynamic" susceptibility and hazard maps depending on climate changes. For this purpose, past and future precipipation data from regional climate models (RCMs) datasets are introduced as input parameters for the compilation of "dynamic" landslide hazard maps. Moreover, land motion mapping data produced by Persistent Scatterer Interferometry (PSI) are used for the validation of the landslide occurrence during the period from June 1992 to December 2003 and as a result for the calibration of the mapping procedure. The PSI data can be applied at a regional scale as support for land motion mapping and at local scale for the

  14. Inventory of landslides triggered by the 1994 Northridge, California earthquake

    USGS Publications Warehouse

    Harp, Edwin L.; Jibson, Randall W.

    1995-01-01

    The 17 January 1994 Northridge, California, earthquake (M=6.7) triggered more than 11,000 landslides over an area of about 10,000 km?. Most of the landslides were concentrated in a 1,000-km? area that includes the Santa Susana Mountains and the mountains north of the Santa Clara River valley. We mapped landslides triggered by the earthquake in the field and from 1:60,000-scale aerial photography provided by the U.S. Air Force and taken the morning of the earthquake; these were subsequently digitized and plotted in a GIS-based format, as shown on the accompanying maps (which also are accessible via Internet). Most of the triggered landslides were shallow (1-5 m), highly disrupted falls and slides in weakly cemented Tertiary to Pleistocene clastic sediment. Average volumes of these types of landslides were less than 1,000 m?, but many had volumes exceeding 100,000 m?. Many of the larger disrupted slides traveled more than 50 m, and a few moved as far as 200 m from the bases of steep parent slopes. Deeper ( >5 m) rotational slumps and block slides numbered in the hundreds, a few of which exceeded 100,000 m? in volume. The largest triggered landslide was a block slide having a volume of 8X10E06 m?. Triggered landslides damaged or destroyed dozens of homes, blocked roads, and damaged oil-field infrastructure. Analysis of landslide distribution with respect to variations in (1) landslide susceptibility and (2) strong shaking recorded by hundreds of instruments will form the basis of a seismic landslide hazard analysis of the Los Angeles area.

  15. Multi-scale landslide hazard assessment: Advances in global and regional methodologies

    NASA Astrophysics Data System (ADS)

    Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Hong, Yang

    2010-05-01

    The increasing availability of remotely sensed surface data and precipitation provides a unique opportunity to explore how smaller-scale landslide susceptibility and hazard assessment methodologies may be applicable at larger spatial scales. This research first considers an emerging satellite-based global algorithm framework, which evaluates how the landslide susceptibility and satellite derived rainfall estimates can forecast potential landslide conditions. An analysis of this algorithm using a newly developed global landslide inventory catalog suggests that forecasting errors are geographically variable due to improper weighting of surface observables, resolution of the current susceptibility map, and limitations in the availability of landslide inventory data. These methodological and data limitation issues can be more thoroughly assessed at the regional level, where available higher resolution landslide inventories can be applied to empirically derive relationships between surface variables and landslide occurrence. The regional empirical model shows improvement over the global framework in advancing near real-time landslide forecasting efforts; however, there are many uncertainties and assumptions surrounding such a methodology that decreases the functionality and utility of this system. This research seeks to improve upon this initial concept by exploring the potential opportunities and methodological structure needed to advance larger-scale landslide hazard forecasting and make it more of an operational reality. Sensitivity analysis of the surface and rainfall parameters in the preliminary algorithm indicates that surface data resolution and the interdependency of variables must be more appropriately quantified at local and regional scales. Additionally, integrating available surface parameters must be approached in a more theoretical, physically-based manner to better represent the physical processes underlying slope instability and landslide initiation

  16. Landslide inventory map as a tool for landscape planning and management in Buzau Land Geopark

    NASA Astrophysics Data System (ADS)

    Tatu, Mihai; Niculae, Lucica; Popa, Răzvan-Gabriel

    2015-04-01

    Buzău Land is an aspiring Geopark in Romania, located in the mountainous region of the southern part of the Carpathian Bend Area. From a geologic point of view, the East Carpathians represent a segment of the Alpine - Carpathian orogene, and they are composed of numerous tectonic units put up throughout the Mesozoic and Cenozoic orogenesis. They represent a result of two compressional phases, (1) during Late Cretaceous and (2) during Early and Middle Miocene that were responsible for thrusting of internal units onto external units. The latter cover tectonically the Foredeep folded deposits. Landslides are one of the most widespread and dangerous natural hazards in this region, disrupting access routes and damaging property and habitats at least twice per year, in the rainy seasons. This hazard induces deep changes in the landscape and has serious economic consequences related to the damaging of infrastructure and isolation of localities. The proximity to the Vrancea seismogenic zone increases the risk of landslide triggering. A first step in observing the space and time tendency and amplitude of landslides, in order to distinguish the main vulnerabilities and estimate the risk, is to produce an inventory map. We shall present a landslide inventory map for the Buzău Land territory (~1036 km2), which is the primary base of information for further discussions regarding this phenomenon and an essential tool in observing the development of mass-wasting processes and in landscape planning. The inventory map is in accordance with the recommendations of the IAEG Commission on Landslides and other Mass-Movement, applied across the EU. Based on this work, we can already draw some remarks: - The Geopark territory mostly covers two major tectonic units of the East Carpathians: the external nappes and the folded foredeep; areas with landslide potential are common, but by far the highest landslide frequency is observed in the foredeep. This is related to the soft, argillaceous

  17. Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US

    USDA-ARS?s Scientific Manuscript database

    As soil moisture increases, slope stability decreases. Remotely sensed soil moisture data can provide routine updates of slope conditions necessary for landslide predictions. For regional scale landslide investigations, only remote sensing methods have the spatial and temporal resolution required to...

  18. Methodologies for the assessment of earthquake-triggered landslides hazard. A comparison of Logistic Regression and Artificial Neural Network models.

    NASA Astrophysics Data System (ADS)

    García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.

    2009-04-01

    location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone with an adjustment of 95.1 % for ANN model and 89.4% for LR model. In addition, we make a comparative analysis of both techniques using the Receiver Operating Characteristic (ROC) curve, a graphical plot of the sensitivity vs. (1 - specificity) for a binary classifier system in function of its discrimination threshold, and calculating the Area Under the ROC (AUROC) value for each model. Finally, the previous models are used for the developing a new probabilistic landslide hazard map for future events. They are obtained combining the expected triggering factor (calculated earthquake ground motion) for a return period of 475 years with the susceptibility map.

  19. Large-scale mapping of landslides in the epicentral area Loma Prieta earthquake of October 17, 1989, Santa Cruz County

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Spittler, T.E.; Sydnor, R.H.; Manson, M.W.

    1990-01-01

    The Loma Prieta earthquake of October 17, 1989 triggered landslides throughout the Santa Cruz Mountains in central California. The California Department of Conservation, Division of Mines and Geology (DMG) responded to a request for assistance from the County of Santa Cruz, Office of Emergency Services to evaluate the geologic hazard from major reactivated large landslides. DMG prepared a set of geologic maps showing the landslide features that resulted from the October 17 earthquake. The principal purpose of large-scale mapping of these landslides is: (1) to provide county officials with regional landslide information that can be used for timely recovery ofmore » damaged areas; (2) to identify disturbed ground which is potentially vulnerable to landslide movement during winter rains; (3) to provide county planning officials with timely geologic information that will be used for effective land-use decisions; (4) to document regional landslide features that may not otherwise be available for individual site reconstruction permits and for future development.« less

  20. Quantify landslide exposure in areas with limited hazard information

    NASA Astrophysics Data System (ADS)

    Pellicani, R.; Spilotro, G.; Van Westen, C. J.

    2012-04-01

    In Daunia region, located in the North-western part of Apulia (Southern Italy), landslides are the main source of damage to properties in the urban centers of the area, involving especially transportation system and the foundation stability of buildings. In the last 50 years, the growing demand for physical development of these unstable minor hillside and mountain centers has produced a very rapid expansion of built-up areas, often with poor planning of urban and territorial infrastructures, and invasion of the agricultural soil. Because of the expansion of the built-up towards not safe areas, human activities such as deforestation or excavation of slopes for road cuts and building sites, etc., have become important triggers for landslide occurrence. In the study area, the probability of occurrence of landslides is very difficult to predict, as well as the expected magnitude of events, due to the limited data availability on past landslide activity. Because the main limitations concern the availability of temporal data on landslides and triggering events (frequency), run-out distance and landslide magnitude, it was not possible to produce a reliable landslide hazard map and, consequently, a risk map. Given these limitations in data availability and details, a qualitative exposure map has been produced and combined with a landslide susceptibility map, both generated using a spatial multi-criteria evaluation (SMCE) procedure in a GIS system, for obtaining the qualitative landslide risk map. The qualitative analysis has been provided the spatial distribution of the exposure level in the study area; this information could be used in a preliminary stage of regional planning. In order to have a better definition of the risk level in the Daunia territory, the quantification of the economic losses at municipal level was carried out. For transforming these information on economic consequences into landslide risk quantification, it was necessary to assume the temporal

  1. Bird conservation would complement landslide prevention in the Central Andes of Colombia.

    PubMed

    Ocampo-Peñuela, Natalia; Pimm, Stuart L

    2015-01-01

    Conservation and restoration priorities often focus on separate ecosystem problems. Inspired by the November 11th (2011) landslide event near Manizales, and the current poor results of Colombia's Article 111 of Law 99 of 1993 as a conservation measure in this country, we set out to prioritize conservation and restoration areas where landslide prevention would complement bird conservation in the Central Andes. This area is one of the most biodiverse places on Earth, but also one of the most threatened. Using the case of the Rio Blanco Reserve, near Manizales, we identified areas for conservation where endemic and small-range bird diversity was high, and where landslide risk was also high. We further prioritized restoration areas by overlapping these conservation priorities with a forest cover map. Restoring forests in bare areas of high landslide risk and important bird diversity yields benefits for both biodiversity and people. We developed a simple landslide susceptibility model using slope, forest cover, aspect, and stream proximity. Using publicly available bird range maps, refined by elevation, we mapped concentrations of endemic and small-range bird species. We identified 1.54 km(2) of potential restoration areas in the Rio Blanco Reserve, and 886 km(2) in the Central Andes region. By prioritizing these areas, we facilitate the application of Article 111 which requires local and regional governments to invest in land purchases for the conservation of watersheds.

  2. Analysis of national and regional landslide inventories in Europe

    NASA Astrophysics Data System (ADS)

    Hervás, J.; Van Den Eeckhaut, M.

    2012-04-01

    A landslide inventory can be defined as a detailed register of the distribution and characteristics of past landslides in an area. Today most landslide inventories have the form of digital databases including landslide distribution maps and associated alphanumeric information for each landslide. While landslide inventories are of the utmost importance for land use planning and risk management through the generation of landslide zonation (susceptibility, hazard and risk) maps, landslide databases are thought to greatly differ from one country to another and often also within the same country. This hampers the generation of comparable, harmonised landslide zonation maps at national and continental scales, which is needed for policy and decision making at EU level as regarded for instance in the INSPIRE Directive and the Thematic Strategy for Soil Protection. In order to have a clear understanding of the landslide inventories available in Europe and their potential to produce landslide zonation maps as well as to draw recommendations to improve harmonisation and interoperability between landslide databases, we have surveyed 37 countries. In total, information has been collected and analysed for 24 national databases in 22 countries (Albania, Andorra, Austria, Bosnia and Herzegovina, Bulgaria, Czech Republic, Former Yugoslav Republic of Macedonia, France, Greece, Hungary, Iceland, Ireland, Italy, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland and UK) and 22 regional databases in 10 countries. At the moment, over 633,000 landslides are recorded in national databases, representing on average less than 50% of the estimated landslides occurred in these countries. The sample of regional databases included over 103,000 landslides, with an estimated completeness substantially higher than that of national databases, as more attention can be paid for data collection over smaller regions. Yet, both for national and regional coverage, the data collection

  3. A combined geomorphological and geophysical approach to characterising relict landslide hazard on the Jurassic Escarpments of Great Britain

    NASA Astrophysics Data System (ADS)

    Boon, David P.; Chambers, Jonathan E.; Hobbs, Peter R. N.; Kirkham, Mathew; Merritt, Andrew J.; Dashwood, Claire; Pennington, Catherine; Wilby, Philip R.

    2015-11-01

    The Jurassic Escarpment in the North York Moors in Northern Britain has a high density of deep-seated relict landslides but their regional hazard is poorly understood due to a lack of detailed case studies. Investigation of a typical relict landslide at Great Fryup Dale suggests that the crop of the Whitby Mudstone Formation is highly susceptible to landslide hazards. The mudstone lithologies along the Escarpment form large multiple rotational failures which break down at an accelerated rate during wetter climates and degrade into extensive frontal mudflows. Geomorphological mapping, high resolution LiDAR imagery, boreholes, and geophysical ERT surveys are deployed in a combined approach to delimit internal architecture of the landslide. Cross-sections developed from these data indicate that the main movement displaced a bedrock volume of c. 1 × 107 m3 with a maximum depth of rupture of c. 50 m. The mode of failure is strongly controlled by lithology, bedding, joint pattern, and rate of lateral unloading. Dating of buried peats using the AMS method suggests that the 10 m thick frontal mudflow complex was last active in the Late Holocene, after c. 2270 ± 30 calendar years BP. Geomorphic mapping and dating work indicates that the landslide is dormant, but slope stability modelling suggests that the slope is less stable than previously assumed; implying that this and other similar landslides in Britain may become more susceptible to reactivation or extension during future wetter climatic phases. This study shows the value of a multi-technique approach for landslide hazard assessment and to enhance national landslide inventories.

  4. Quantification of Urban Environment's Role in Slope Stability for Landslide Events.

    NASA Astrophysics Data System (ADS)

    Bozzolan, E.; Holcombe, E.; Wagener, T.; Pianosi, F.

    2017-12-01

    The combination of a rapid and unplanned urban development with a likely future climate change could significantly affect landslide occurrences in the humid tropics, where rainfall events of high intensity and duration are the dominant trigger for landslide risk. The attention of current landslide hazard studies is largely focussed on natural slope processes based on combinations of environmental factors, excluding the role of urbanisation on slope stability. This project aims to understand the relative influence of urbanisation features on local slope stability and to translate the findings to a wider region. Individual slopes are firstly analysed with the software CHASM, a physically based model which combines soil hydrology and slope stability assessment. Instead of relying on existing records, generally lacking for landslides, ranges of plausible preparatory (such as slope, cohesion, friction angles), triggering (rainfall) and aggravating factors (deforestation, house density and water network) are defined and possible combinations of these factors are created by sampling from those ranges. The influence of urban features on site hydrology and stability mechanisms are evaluated and then implemented in denser urban contexts, characteristic of unplanned settlements. The results of CHASMS can be transferred to regional maps in order to identify the areas belonging to the triggering combinations of factors previously found. In this way, areas susceptible to landslides can be detected not only in terms of natural factors but also in relation to the degree of urbanisation. Realistic scenarios can be extrapolated from the areas considered and then analysed again with CHASM. This permits to adapt (and improve) the initial variability ranges of the factors, creating a general-specific cycle able to identify the landslide susceptibility regions and outline a hazard map. Once the triggers are understood, possible consequences can be assessed and mitigation strategies can

  5. Storm-Induced Slope Failure Susceptibility Mapping

    DOT National Transportation Integrated Search

    2018-01-01

    A pilot study was conducted to characterize and map the areas susceptible to slope failure using state-wide available data. The objective was to determine whether it would be possible to provide slope-failure susceptibility mapping that could be used...

  6. Mapping gullies, dunes, lava fields, and landslides via surface roughness

    NASA Astrophysics Data System (ADS)

    Korzeniowska, Karolina; Pfeifer, Norbert; Landtwing, Stephan

    2018-01-01

    Gully erosion is a widespread and significant process involved in soil and land degradation. Mapping gullies helps to quantify past, and anticipate future, soil losses. Digital terrain models offer promising data for automatically detecting and mapping gullies especially in vegetated areas, although methods vary widely measures of local terrain roughness are the most varied and debated among these methods. Rarely do studies test the performance of roughness metrics for mapping gullies, limiting their applicability to small training areas. To this end, we systematically explored how local terrain roughness derived from high-resolution Light Detection And Ranging (LiDAR) data can aid in the unsupervised detection of gullies over a large area. We also tested expanding this method for other landforms diagnostic of similarly abrupt land-surface changes, including lava fields, dunes, and landslides, as well as investigating the influence of different roughness thresholds, resolutions of kernels, and input data resolution, and comparing our method with previously published roughness algorithms. Our results show that total curvature is a suitable metric for recognising analysed gullies and lava fields from LiDAR data, with comparable success to that of more sophisticated roughness metrics. Tested dunes or landslides remain difficult to distinguish from the surrounding landscape, partly because they are not easily defined in terms of their topographic signature.

  7. Mapping Shallow Landslide Slope Inestability at Large Scales Using Remote Sensing and GIS

    NASA Astrophysics Data System (ADS)

    Avalon Cullen, C.; Kashuk, S.; Temimi, M.; Suhili, R.; Khanbilvardi, R.

    2015-12-01

    Rainfall induced landslides are one of the most frequent hazards on slanted terrains. They lead to great economic losses and fatalities worldwide. Most factors inducing shallow landslides are local and can only be mapped with high levels of uncertainty at larger scales. This work presents an attempt to determine slope instability at large scales. Buffer and threshold techniques are used to downscale areas and minimize uncertainties. Four static parameters (slope angle, soil type, land cover and elevation) for 261 shallow rainfall-induced landslides in the continental United States are examined. ASTER GDEM is used as bases for topographical characterization of slope and buffer analysis. Slope angle threshold assessment at the 50, 75, 95, 98, and 99 percentiles is tested locally. Further analysis of each threshold in relation to other parameters is investigated in a logistic regression environment for the continental U.S. It is determined that lower than 95-percentile thresholds under-estimate slope angles. Best regression fit can be achieved when utilizing the 99-threshold slope angle. This model predicts the highest number of cases correctly at 87.0% accuracy. A one-unit rise in the 99-threshold range increases landslide likelihood by 11.8%. The logistic regression model is carried over to ArcGIS where all variables are processed based on their corresponding coefficients. A regional slope instability map for the continental United States is created and analyzed against the available landslide records and their spatial distributions. It is expected that future inclusion of dynamic parameters like precipitation and other proxies like soil moisture into the model will further improve accuracy.

  8. Assessment of the predisposing factors for shallow landslides activation in terraced areas: the case of the Rupinaro catchment, Liguria (northwestern Italy).

    NASA Astrophysics Data System (ADS)

    Cignetti, Martina; Godone, Danilo; Giordan, Daniele

    2017-04-01

    The shallow landslides occurrence is strongly correlated with climatic conditions and environmental settings. In the Liguria region (northwestern Italy), the landscape presents an ancient human intervention represented by terraces and, in the last century, by a general overbuilding, both in the few flat areas and in the steep slope hinterland. From the twentieth century, the progressive abandonment of agriculture generated a lack of maintenance of terraced areas, which associated to the urban and the road net development, supported the slope susceptibility to instability. This makes the assessment of the predisposing factors for shallow landslides a multidisciplinary task, combining natural and man-made issues. In this work, we try to define all the main predisposing factors of the Rupinaro catchment (southeast Liguria). We operate starting from a high-resolution Digital Terrain Model (DTM) supplied by an airborne LiDAR survey carried out after the autumn 2014 rainfall events. From this DTM, we mapped a total amount of 96 landslides in the study area. Then, we implemented a classification methodology based on a simple parametric score. In GIS environment we overlaid several layers: i) lithological and hydrogeological map, ii) slope iii) aspect, iv) the land use information, available by the CORINE land cover, and iv) the presence of terraces. Each spatial data was than reclassified according a numerical code. The sum, by raster math, of these factors provided an overall score raster for the entire basin. This method allows the characterization of the entire watershed, gathering all the predisposing factors for the shallow landslides activation. A categorization of the landslides area mapped from the DTM and stored in a vector layer has been made. In particular, we estimated the most frequent code within each landslide polygon, obtaining a representative data of the most influential factors that triggered shallow landslides. The results showed the prevalent

  9. Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

    NASA Technical Reports Server (NTRS)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

    Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

  10. Plan curvature and landslide probability in regions dominated by earth flows and earth slides

    USGS Publications Warehouse

    Ohlmacher, G.C.

    2007-01-01

    Damaging landslides in the Appalachian Plateau and scattered regions within the Midcontinent of North America highlight the need for landslide-hazard mapping and a better understanding of the geomorphic development of landslide terrains. The Plateau and Midcontinent have the necessary ingredients for landslides including sufficient relief, steep slope gradients, Pennsylvanian and Permian cyclothems that weather into fine-grained soils containing considerable clay, and adequate precipitation. One commonly used parameter in landslide-hazard analysis that is in need of further investigation is plan curvature. Plan curvature is the curvature of the hillside in a horizontal plane or the curvature of the contours on a topographic map. Hillsides can be subdivided into regions of concave outward plan curvature called hollows, convex outward plan curvature called noses, and straight contours called planar regions. Statistical analysis of plan-curvature and landslide datasets indicate that hillsides with planar plan curvature have the highest probability for landslides in regions dominated by earth flows and earth slides in clayey soils (CH and CL). The probability of landslides decreases as the hillsides become more concave or convex. Hollows have a slightly higher probability for landslides than noses. In hollows landslide material converges into the narrow region at the base of the slope. The convergence combined with the cohesive nature of fine-grained soils creates a buttressing effect that slows soil movement and increases the stability of the hillside within the hollow. Statistical approaches that attempt to determine landslide hazard need to account for the complex relationship between plan curvature, type of landslide, and landslide susceptibility. ?? 2007 Elsevier B.V. All rights reserved.

  11. Landslide prediction system in Slovenia (Masprem)

    NASA Astrophysics Data System (ADS)

    Šinigoj, Jasna; Jemec Auflič, Mateja; Krivic, Matija

    2017-04-01

    The landslide prediction system MASPREM has been developed in 2013 to (1) predict rainfall induced landslides on national and local level and (2) inform Civil Protection agency and inhabitants of an increased probability of landslide occurrences. A landslide prediction system on national level integrates three major components: (1) a landslide susceptibility map; (2) landslide triggering rainfall threshold values and (3) precipitation forecasting model's (i.e., ALADIN, INCA). Landslide prediction is also calculated on a local level, including exposure maps of inhabitants, buildings and different types of infrastructure to potential landslide occurrence at a scale of 1: 25,000 for 14 selected municipalities. MASPREM system runs in a 12 hour cycling mode, for 24 hours ahead. The results of the probability of landslide models are classified into five classes, with values ranging from one to five; where class one represents areas with a negligible landslide probability and class five areas with a very high landslide probability. It is a fully automated system based on open source software (PostgreSQL) and web applications for displaying results (Java, GDAL). When precipitation forecasting models are transferred to the GeoZS server the conversion process to raster data starts, stores data in a PostgreSQL database and performs the calculation. Based on final results, the WMS service that is responsible for the distribution of data through the service for download and review of results in a web application is created. In the period, from September 2013 to August 2016, MASPREM gave an alert about the probability of landslide occurrences in 84 cases. While the system has potential to become operational in use after the validation phase, there are also limitations related to the input data that should not be neglected: spatial resolution of the ALADIN model, the incomplete landslide inventory that is important for the validation, defining how many days of antecedent rainfall

  12. The susceptibility analysis of landslides induced by earthquake in Aso volcanic area, Japan, scoping the prediction

    NASA Astrophysics Data System (ADS)

    Kubota, Tetsuya; Takeda, Tsuyoshi

    2017-04-01

    Kumamoto earthquake on April 16th 2016 in Kumamoto prefecture, Kyushu Island, Japan with intense seismic scale of M7.3 (maximum acceleration = 1316 gal in Aso volcanic region) yielded countless instances of landslide and debris flow that induced serious damages and causalities in the area, especially in the Aso volcanic mountain range. Hence, field investigation and numerical slope stability analysis were conducted to delve into the characteristics or the prediction factors of the landslides induced by this earthquake. For the numerical analysis, Finite Element Method (FEM) and CSSDP (Critical Slip Surface analysis by Dynamic Programming theory based on limit equilibrium method) were applied to the landslide slopes with seismic acceleration observed. These numerical analysis methods can automatically detect the landslide slip surface which has minimum Fs (factor of safety). The various results and the information obtained through this investigation and analysis were integrated to predict the landslide susceptible slopes in volcanic area induced by earthquakes and rainfalls of their aftermath, considering geologic-geomorphologic features, geo-technical characteristics of the landslides and vegetation effects on the slope stability. Based on the FEM or CSSDP results, the landslides occurred in this earthquake at the mild gradient slope on the ridge have the safety factor of slope Fs=2.20 approximately (without rainfall nor earthquake, and Fs>=1.0 corresponds to stable slope without landslide) and 1.78 2.10 (with the most severe rainfall in the past) while they have approximately Fs=0.40 with the seismic forces in this earthquake (horizontal direction 818 gal, vertical direction -320 gal respectively, observed in the earthquake). It insists that only in case of earthquakes the landslide in volcanic sediment apt to occur at the mild gradient slopes as well as on the ridges with convex cross section. Consequently, the following results are obtained. 1) At volcanic

  13. Bird conservation would complement landslide prevention in the Central Andes of Colombia

    PubMed Central

    Ocampo-Peñuela, Natalia

    2015-01-01

    Conservation and restoration priorities often focus on separate ecosystem problems. Inspired by the November 11th (2011) landslide event near Manizales, and the current poor results of Colombia’s Article 111 of Law 99 of 1993 as a conservation measure in this country, we set out to prioritize conservation and restoration areas where landslide prevention would complement bird conservation in the Central Andes. This area is one of the most biodiverse places on Earth, but also one of the most threatened. Using the case of the Rio Blanco Reserve, near Manizales, we identified areas for conservation where endemic and small-range bird diversity was high, and where landslide risk was also high. We further prioritized restoration areas by overlapping these conservation priorities with a forest cover map. Restoring forests in bare areas of high landslide risk and important bird diversity yields benefits for both biodiversity and people. We developed a simple landslide susceptibility model using slope, forest cover, aspect, and stream proximity. Using publicly available bird range maps, refined by elevation, we mapped concentrations of endemic and small-range bird species. We identified 1.54 km2 of potential restoration areas in the Rio Blanco Reserve, and 886 km2 in the Central Andes region. By prioritizing these areas, we facilitate the application of Article 111 which requires local and regional governments to invest in land purchases for the conservation of watersheds. PMID:25737819

  14. Slope Stability Analysis for Shallow Landslides using TRIGRS: A Case Study for Sta. Cruz, Zambales, Philippines

    NASA Astrophysics Data System (ADS)

    Mendoza, J. P. A.

    2016-12-01

    The Philippines, being located in the circum-Pacific, bounded by multiple subduction zones, open seas and ocean, is one of the most hazard-prone countries in the world (Benson, 1997). This widespread recurrence of natural hazards in the country requires much attention for disaster management (Aurelio, 2006). On the average, 21 typhoons enter the Philippine area of responsibility annually with 6-9 making a landfall. Several rainfall-induced landslide events are reported annually particularly during and after the inundation of major typhoons which imposes hazards to communities and causes destruction of properties due to the moving mass and possible flash floods it may induce. Shallow landslides are the most commonly observed failure involving soil-mantled slopes and are considered major geohazards, often causing property damage and other economic loss. Hence numerous studies on landslide susceptibility including numerical models based on infinite slope equation are used in order to identify slopes prone to occurrences of shallow landslides. The study aims to determine the relationships between the slope and elevation to the factor of safety for laterite-mantled topography by incorporating precipitation values in the determination of landslide susceptibility. Using a DEM, flow direction map and slope map of the Sta Cruz (Zambales, Philippines), the FORTRAN based program TRIGRS, was used to generate the values for the factors of safety in the study area. Overlays with a generated slope map and elevation map were used to determine relationships of the mentioned factors and the factors of safety. A slope in a topography mantled with lateritic soil will fail at a slope angle higher than 20 degrees. Generally, the factor of safety decreases as the slope angle increases; this increases the probability and risk of slope failure. Elevation has no bearing on the computation for the factor of safety. The factor of safety is heavily dependent on the slope angle. The value of

  15. Landslide hazard assessment: recent trends and techniques.

    PubMed

    Pardeshi, Sudhakar D; Autade, Sumant E; Pardeshi, Suchitra S

    2013-01-01

    Landslide hazard assessment is an important step towards landslide hazard and risk management. There are several methods of Landslide Hazard Zonation (LHZ) viz. heuristic, semi quantitative, quantitative, probabilistic and multi-criteria decision making process. However, no one method is accepted universally for effective assessment of landslide hazards. In recent years, several attempts have been made to apply different methods of LHZ and to compare results in order to find the best suited model. This paper presents the review of researches on landslide hazard mapping published in recent years. The advanced multivariate techniques are proved to be effective in spatial prediction of landslides with high degree of accuracy. Physical process based models also perform well in LHZ mapping even in the areas with poor database. Multi-criteria decision making approach also play significant role in determining relative importance of landslide causative factors in slope instability process. Remote Sensing and Geographical Information System (GIS) are powerful tools to assess landslide hazards and are being used extensively in landslide researches since last decade. Aerial photographs and high resolution satellite data are useful in detection, mapping and monitoring landslide processes. GIS based LHZ models helps not only to map and monitor landslides but also to predict future slope failures. The advancements in Geo-spatial technologies have opened the doors for detailed and accurate assessment of landslide hazards.

  16. Quantitative Susceptibility Mapping after Sports-Related Concussion.

    PubMed

    Koch, K M; Meier, T B; Karr, R; Nencka, A S; Muftuler, L T; McCrea, M

    2018-06-07

    Quantitative susceptibility mapping using MR imaging can assess changes in brain tissue structure and composition. This report presents preliminary results demonstrating changes in tissue magnetic susceptibility after sports-related concussion. Longitudinal quantitative susceptibility mapping metrics were produced from imaging data acquired from cohorts of concussed and control football athletes. One hundred thirty-six quantitative susceptibility mapping datasets were analyzed across 3 separate visits (24 hours after injury, 8 days postinjury, and 6 months postinjury). Longitudinal quantitative susceptibility mapping group analyses were performed on stability-thresholded brain tissue compartments and selected subregions. Clinical concussion metrics were also measured longitudinally in both cohorts and compared with the measured quantitative susceptibility mapping. Statistically significant increases in white matter susceptibility were identified in the concussed athlete group during the acute (24 hour) and subacute (day 8) period. These effects were most prominent at the 8-day visit but recovered and showed no significant difference from controls at the 6-month visit. The subcortical gray matter showed no statistically significant group differences. Observed susceptibility changes after concussion appeared to outlast self-reported clinical recovery metrics at a group level. At an individual subject level, susceptibility increases within the white matter showed statistically significant correlations with return-to-play durations. The results of this preliminary investigation suggest that sports-related concussion can induce physiologic changes to brain tissue that can be detected using MR imaging-based magnetic susceptibility estimates. In group analyses, the observed tissue changes appear to persist beyond those detected on clinical outcome assessments and were associated with return-to-play duration after sports-related concussion. © 2018 by American Journal of

  17. Ethical questions in landslide management and risk reduction in Norway

    NASA Astrophysics Data System (ADS)

    Taurisano, A.; Lyche, E.; Thakur, V.; Wiig, T.; Øvrelid, K.; Devoli, G.

    2012-04-01

    The loss of lives caused by landslides in Norway is smaller than in other countries due to the low population density in exposed areas. However, annual economic losses from damage to properties and infrastructures are vast. Yet nationally coordinated efforts to manage and reduce landslide and snow avalanche risk are a recent challenge, having started only in the last decade. Since 2009, this has been a task of the Norwegian Water Resources and Energy Directorate (NVE) under the Ministry of Petroleum and Energy. Ongoing work includes collection of landslide data, production of susceptibility and hazard maps, planning of mitigation measures along with monitoring and early warning systems, assistance to areal planning, providing expertise in emergencies and disseminating information to the public. These activities are realized in collaboration with the Norwegian Geological Survey (NGU), the Meteorological Institute, the Road and Railway authorities, universities and private consultant companies. As the total need for risk mitigating initiatives is by far larger than the annual budget, priority assessment is crucial. This brings about a number of ethical questions. 1. Susceptibility maps have been produced for the whole country and provide a first indication of areas with potential landslide or snow avalanche hazard, i.e. areas where special attention and expert assessments are needed before development. Areas where no potential hazard is shown can in practice be developed without further studies, which call for relatively conservative susceptibility maps. However, conservative maps are problematic as they too often increase both cost and duration of building projects beyond the reasonable. 2. Areas where hazard maps or risk mitigation initiatives will be funded are chosen by means of cost-benefits analyses which are often uncertain. How to estimate the benefits if the real probability for damage can only be judged on a very subjective level but not really calculated

  18. Comparison of landslide hazard and risk assessment practices in Europe

    NASA Astrophysics Data System (ADS)

    Corominas, J.; Mavrouli, O.

    2012-04-01

    An overview is made of the landslide hazard and risk assessment practices that are officially promoted or applied in Europe by administration offices, geological surveys, and decision makers (recommendations, regulations and codes). The reported countries are: Andorra, Austria, France, Italy (selected river basins), Romania, Spain (Catalonia), Switzerland and United Kingdom. The objective here was to compare the different practices for hazard and risk evaluation with respect to the official policies, the methodologies used (qualitative and quantitative), the provided outputs and their contents, and the terminology and map symbols used. The main observations made are illustrated with examples and the possibility of harmonization of the policies and the application of common practices to bridge the existing gaps is discussed. Some of the conclusions reached include the following: zoning maps are legally binding for public administrators and land owners only in some cases and generally when referring to site-specific or local scales rather than regional or national ones; so far, information is mainly provided on landslide susceptibility and hazard and risk assessment is performed only in a few countries; there is a variation in the use of scales between countries; the classification criteria for landslide types and mechanisms present large diversity even within the same country (in some cases no landslide mechanisms are specified while in others there is an exhaustive list); the techniques to obtain input data for the landslide inventory and susceptibility maps vary from basic to sophisticated, resulting in various levels of data quality and quantity; the procedures followed for hazard and risk assessment include analytical procedures supported by computer simulation, weighted-indicators, expert judgment and field survey-based, or a combination of all; there is an important variation between hazard and risk matrices with respect to the used parameters, the thresholds

  19. Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

    NASA Technical Reports Server (NTRS)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

    Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

  20. Hazard analysis in active landslide areas in the State of Veracruz, Mexico

    NASA Astrophysics Data System (ADS)

    Wilde, Martina; Morales Barrera, Wendy V.; Rodriguez Elizarrarás, Sergio R.; Solleiro Rebolledo, Elizabeth; Sedov, Sergey; Terhorst, Birgit

    2016-04-01

    The year 2013 was characterized by strong storms and hurricanes like the Hurricanes Barbara and Ingrid and the tropical storms Barry and Fernand, which occurred between June and November affecting especially the coastal regions of Mexico. First of all, the State of Veracruz experienced a series of intense rainfalls and as consequences of these events over 780 landslides were registered. More than 45000 people suffered from evacuations. Located on the coast of the Gulf of Mexico, Veracruz has a wide range of altitude differences. The area with the highest elevations reaches from 5675 m.a.s.l. (Pico de Orizaba, the highest mountain of Mexico) to approximately 3000 m.a.s.l. and is characterized by steep slopes and V-shaped valleys. The mountains are part of the Sierra Madre Oriental and the Trans-Mexican Volcanic Belt. Plateaus and rounded hills are typical for the intermediate zones (3000 - 500 m.a.s.l.). The lowest zone (from 500 m.a.s.l. to sea level) is defined by moderate slopes, large rivers and coastal plain areas. The geology shows a variety and complexity of sedimentary and volcanic rocks. The sedimentary formations comprise claystones, siltstones, sandstones and calcareous rocks. Plateaus of basalts and andesites and deposits of ignimbrites are representative for this area. Even though Veracruz is a region highly endangered by landslides, currently there are no susceptibility maps or any other relevant information with high spatial resolution. Because of the lack of high definite information about the landslide hazards in this area, detailed investigations about the conditions (geology, geomorphology, thresholds, etc.) are indispensable. A doctoral grant from the German Academic Exchange Service (DAAD) allowed to carry out investigations in areas affected by large landslides in the year 2013. The selected study sites comprise damaged infrastructures and settlements. With a multi-methodological and interdisciplinary approach different processes and types of

  1. The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

    NASA Astrophysics Data System (ADS)

    Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

    2016-04-01

    Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to

  2. Large-area landslide susceptibility with optimized slope-units

    NASA Astrophysics Data System (ADS)

    Alvioli, Massimiliano; Marchesini, Ivan; Reichenbach, Paola; Rossi, Mauro; Ardizzone, Francesca; Fiorucci, Federica; Guzzetti, Fausto

    2017-04-01

    A Slope-Unit (SU) is a type of morphological terrain unit bounded by drainage and divide lines that maximize the within-unit homogeneity and the between-unit heterogeneity across distinct physical and geographical boundaries [1]. Compared to other terrain subdivisions, SU are morphological terrain unit well related to the natural (i.e., geological, geomorphological, hydrological) processes that shape and characterize natural slopes. This makes SU easily recognizable in the field or in topographic base maps, and well suited for environmental and geomorphological analysis, in particular for landslide susceptibility (LS) modelling. An optimal subdivision of an area into a set of SU depends on multiple factors: size and complexity of the study area, quality and resolution of the available terrain elevation data, purpose of the terrain subdivision, scale and resolution of the phenomena for which SU are delineated. We use the recently developed r.slopeunits software [2,3] for the automatic, parametric delineation of SU within the open source GRASS GIS based on terrain elevation data and a small number of user-defined parameters. The software provides subdivisions consisting of SU with different shapes and sizes, as a function of the input parameters. In this work, we describe a procedure for the optimal selection of the user parameters through the production of a large number of realizations of the LS model. We tested the software and the optimization procedure in a 2,000 km2 area in Umbria, Central Italy. For LS zonation we adopt a logistic regression model implemented in an well-known software [4,5], using about 50 independent variables. To select the optimal SU partition for LS zonation, we want to define a metric which is able to quantify simultaneously: (i) slope-unit internal homogeneity (ii) slope-unit external heterogeneity (iii) landslide susceptibility model performance. To this end, we define a comprehensive objective function S, as the product of three

  3. Computed inverse resonance imaging for magnetic susceptibility map reconstruction.

    PubMed

    Chen, Zikuan; Calhoun, Vince

    2012-01-01

    This article reports a computed inverse magnetic resonance imaging (CIMRI) model for reconstructing the magnetic susceptibility source from MRI data using a 2-step computational approach. The forward T2*-weighted MRI (T2*MRI) process is broken down into 2 steps: (1) from magnetic susceptibility source to field map establishment via magnetization in the main field and (2) from field map to MR image formation by intravoxel dephasing average. The proposed CIMRI model includes 2 inverse steps to reverse the T2*MRI procedure: field map calculation from MR-phase image and susceptibility source calculation from the field map. The inverse step from field map to susceptibility map is a 3-dimensional ill-posed deconvolution problem, which can be solved with 3 kinds of approaches: the Tikhonov-regularized matrix inverse, inverse filtering with a truncated filter, and total variation (TV) iteration. By numerical simulation, we validate the CIMRI model by comparing the reconstructed susceptibility maps for a predefined susceptibility source. Numerical simulations of CIMRI show that the split Bregman TV iteration solver can reconstruct the susceptibility map from an MR-phase image with high fidelity (spatial correlation ≈ 0.99). The split Bregman TV iteration solver includes noise reduction, edge preservation, and image energy conservation. For applications to brain susceptibility reconstruction, it is important to calibrate the TV iteration program by selecting suitable values of the regularization parameter. The proposed CIMRI model can reconstruct the magnetic susceptibility source of T2*MRI by 2 computational steps: calculating the field map from the phase image and reconstructing the susceptibility map from the field map. The crux of CIMRI lies in an ill-posed 3-dimensional deconvolution problem, which can be effectively solved by the split Bregman TV iteration algorithm.

  4. Digital inventory of landslides and related deposits in Honduras triggered by Hurricane Mitch

    USGS Publications Warehouse

    Harp, Edwin L.; Hagaman, Kirk W.; Held, Matthew D.; McKenna, Jonathan P.

    2002-01-01

    by local contractors. Through the use of digital elevation models derived from 1:50,000-scale topographic maps and geologic maps, landslide susceptibility maps will be derived to aid land-use planning and relocation efforts.

  5. Specific Signature of Seismic Shaking in Landslide Inventories: Case of the Chichi Earthquake

    NASA Astrophysics Data System (ADS)

    Meunier, P.; Rault, C.; Marc, O.; Hovius, N.

    2017-12-01

    The 1999 Chichi earthquake triggered 10 000 landslides in its epicentral area. In addition to coseismic landsliding, directly induced by the shaking, the hillslopes response extended to several years after the main shock, during which landslide susceptibility remained higher than during the pre-seismic period. We attribute this elevated rate to weakening effects caused by the shaking. The characteristics of the coseismic landslide catalogues (clustering,slope and azimuth distribution) bears the signature of the seismic triggering. Extended landslide mapping (1994-2004) allows to track changes in these signatures in order to better interpret them. We present a summary of the change of these signatures through time and space. At the scale of the epicentral area, we show that coseismic landslide clustering did clearly occur along the fault where the shaking is strong. In 3 sub-catchments of the Choshui river, a finer analysis of the landslide time series reveals a mixed signature of both geology and shaking. Pre-quake rain-induced landslides preferentially occurred down slope and along the bedding planes while coseismic landslides locate higher in the landscape, on slopes strongly affected by site effects. However, during the post seismic period, the signature of the shaking is not present while landslide rate remains high, suggesting that weakening effects seemed homogeneously distributed in the landscape.

  6. Specific signature of seismic shaking in landslide catalogues: Case of the Chichi earthquake

    NASA Astrophysics Data System (ADS)

    Meunier, Patrick; Rault, Claire; Marc, Odin; Hovius, Niels

    2017-04-01

    The 1999 Chichi earthquake triggered 10 000 landslides in its epicentral area. In addition to coseismic landsliding, directly induced by the shaking, the hillslopes response extended to several years after the main shock, during which landslide susceptibility remained higher than during the pre-seismic period. We attribute this elevated rate to weakening effects caused by the shaking. The characteristics of the coseismic landslide catalogues (clustering, slope and azimuth distribution) bears the signature of the seismic triggering. Extended landslide mapping (1994-2004) allows to track changes in these signatures in order to better interpret them. We present a summary of the change of these signatures through time and space. At the scale of the epicentral area, we show that coseismic landslide clustering did clearly occur along the fault where the shaking is strong. In 3 sub-catchments of the Choshui river, a finer analysis of the landslide time series reveals a mixed signature of both geology and shaking. Pre-quake rain-induced landslides preferentially occurred down slope and along the bedding planes while coseismic landslides locate higher in the landscape, on slopes strongly affected by site effects. However, during the post seismic period, the signature of the shaking is not present while landslide rate remains high, suggesting that weakening effects seemed homogeneously distributed in the landscape.

  7. Highlighting landslides and other geomorphological features using sediment connectivity maps

    NASA Astrophysics Data System (ADS)

    Bossi, Giulia; Crema, Stefano; Cavalli, Marco; Marcato, Gianluca; Pasuto, Alessandro

    2016-04-01

    Landslide identification is usually made through interpreting geomorphological features in the field or with remote sensing imagery. In recent years, airborne laser scanning (LiDAR) has enhanced the potentiality of geomorphological investigations by providing a detailed and diffuse representation of the land surface. The development of algorithms for geomorphological analysis based on LiDAR derived high-resolution Digital Terrain Models (DTMs) is increasing. Among them, the sediment connectivity index (IC) has been used to quantify sediment dynamics in alpine catchments. In this work, maps of the sediment connectivity index are used for detecting geomorphological features and processes not exclusively related to water-laden processes or debris flows. The test area is located in the upper Passer Valley in South Tyrol (Italy). Here a 4 km2 Deep-seated Gravitational Slope Deformation (DGSD) with several secondary phenomena has been studied for years. The connectivity index was applied to a well-known study area in order to evaluate its effectiveness as an interpretative layer to assist geomorphological analysis. Results were cross checked with evidence previously identified by means of in situ investigations, photointerpretation and monitoring data. IC was applied to a 2.5 m LiDAR derived DTM using two different scenarios in order to test their effectiveness: i) IC derived on the hydrologically correct DTM; ii) IC derived on the original DTM. In the resulting maps a cluster of low-connectivity areas appears as the deformation of the DGSD induce a convexity in the central part of the phenomenon. The double crests, product of the sagging of the landslide, are extremely evident since in those areas the flow directions diverge from the general drainage pattern, which is directed towards the valley river. In the crown area a rock-slab that shows clear evidence of incumbent detachment is clearly highlighted since the maps emphasize the presence of traction trenches and

  8. Mapping Landslides in Lunar Impact Craters Using Chebyshev Polynomials and Dem's

    NASA Astrophysics Data System (ADS)

    Yordanov, V.; Scaioni, M.; Brunetti, M. T.; Melis, M. T.; Zinzi, A.; Giommi, P.

    2016-06-01

    Geological slope failure processes have been observed on the Moon surface for decades, nevertheless a detailed and exhaustive lunar landslide inventory has not been produced yet. For a preliminary survey, WAC images and DEM maps from LROC at 100 m/pixels have been exploited in combination with the criteria applied by Brunetti et al. (2015) to detect the landslides. These criteria are based on the visual analysis of optical images to recognize mass wasting features. In the literature, Chebyshev polynomials have been applied to interpolate crater cross-sections in order to obtain a parametric characterization useful for classification into different morphological shapes. Here a new implementation of Chebyshev polynomial approximation is proposed, taking into account some statistical testing of the results obtained during Least-squares estimation. The presence of landslides in lunar craters is then investigated by analyzing the absolute values off odd coefficients of estimated Chebyshev polynomials. A case study on the Cassini A crater has demonstrated the key-points of the proposed methodology and outlined the required future development to carry out.

  9. The landslide hazard in the San Francisco Bay region

    USGS Publications Warehouse

    Brabb, E.E.

    1977-01-01

    Development in hilly or mountainous terrain has resulted in much landslide damage. Areas susceptible to landsliding can be recognized. Practices for minimizing landslides are presented. ?? 1977 D. Reidel Publishing Company.

  10. Landslide risk impact management and web services for improving resilience: the LIFE+IMAGINE project approach

    NASA Astrophysics Data System (ADS)

    Congi, Maria Pia; Campo, Valentina; Cipolloni, Carlo; Delmonaco, Giuseppe; Guerrieri, Luca; Iadanza, Carla; Spizzichino, Daniele; Trigila, Alessandro

    2014-05-01

    The increasing damage caused by natural disasters in the last decades points out the need for interoperable added-value services to support environmental safety and human protection, by reducing vulnerability of exposed elements as well as improving the resilience of the involved communities. For this reason, to provide access to harmonized and customized data is only one of several steps towards delivering adequate support to risk assessment, reduction and management. Scope of the present work is to illustrate a methodology under development for analysis of potential impacts in areas prone to landslide hazard in the framework of the EC project LIFE+IMAGINE. The project aims to implement an infrastructure based on web services for environmental analysis, that integrates in its own architecture specifications and results from INSPIRE, SEIS and GMES. Existing web services will be customized during the project to provide functionalities for supporting the environmental integrated management. The implemented infrastructure will be applied to landslide risk scenarios, to be developed in selected pilot areas, aiming at: i) application of standard procedures to implement a landslide risk analysis; ii) definition of a procedure for assessment of potential environmental impacts, based on a set of indicators to estimate the different exposed elements with their specific vulnerability in the pilot area. More in detail, the landslide pilot will be aimed at providing a landslide risk scenario through the implementation and analysis of: 1) a landslide inventory from available historical databases and maps; 2) landslide susceptibility and hazard maps; 3) assessment of exposure and vulnerability on selected typologies of elements at risk; 4) implementation of a landslide risk scenario for different sets of exposed elements (e.g. population, road network, residential area, cultural heritage). The pilot will be implemented in Liguria, Italy, in two different catchment areas located

  11. Slope, Scarp and Sea Cliff Instability Susceptibility Mapping for Planning Regulations in Almada County, Portugal

    NASA Astrophysics Data System (ADS)

    Marques, Fernando; Queiroz, Sónia; Gouveia, Luís; Vasconcelos, Manuel

    2017-12-01

    In Portugal, the modifications introduced in 2008 and 2012 in the National Ecological Reserve law (REN) included the mandatory study of slope instability, including slopes, natural scarps, and sea cliffs, at municipal or regional scale, with the purpose of avoiding the use of hazardous zones with buildings and other structures. The law also indicates specific methods to perform these studies, with different approaches for slope instability, natural scarps and sea cliffs. The methods used to produce the maps required by REN law, with modifications and improvements to the law specified methods, were applied to the 71 km2 territory of Almada County, and included: 1) Slope instability mapping using the statistically based Information Value method validated with the landslide inventory using ROC curves, which provided an AAC=0.964, with the higher susceptibility zones which cover at least 80% of the landslides of the inventory to be included in REN map. The map was object of a generalization process to overcome the inconveniences of the use of a pixel based approach. 2) Natural scarp mapping including setback areas near the top, defined according to the law and setback areas near the toe defined by the application of the shadow angle calibrated with the major rockfalls which occurred in the study area; 3) Sea cliffs mapping including two levels of setback zones near the top, and one setback zone at the cliffs toe, which were based on systematic inventories of cliff failures occurred between 1947 and 2010 in a large scale regional littoral monitoring project. In the paper are described the methods used and the results obtained in this study, which correspond to the final maps of areas to include in REN. The results obtained in this study may be considered as an example of good practice of the municipal authorities in terms of solid, technical and scientifically supported regulation definitions, hazard prevention and safe and sustainable land use management.

  12. Assessing landslide susceptibility, hazards and sediment yield in the Río El Estado watershed, Pico de Orizaba volcano, Mexico

    NASA Astrophysics Data System (ADS)

    Legorreta Paulin, G.; Bursik, M. I.; Lugo Hubp, J.; Aceves Quesada, J. F.

    2014-12-01

    Orizaba, and may prove useful in the assessment of landslide susceptibility and hazard in volcanic terrains.

  13. Map and description of the active part of the Slumgullion Landslide, Hinsdale County, Colorado

    USGS Publications Warehouse

    Fleming, R.W.; Baum, Rex L.; Giardino, Marco

    1999-01-01

    This text accompanies a map of many of the features on the active part of the Slumgullion landslide, Hinsdale County, Colo. Long-term movement creates and destroys a variety of structural features on the surface of the landslide including faults, fractures, and folds, as well as basins and ridges. The Slumgullion landslide consists of a large volume of inactive landslide deposits and a much smaller volume that is actively moving within the deposits of the older landslide. Previously, collapse of the south side of the scarp on Mesa Seco produced materials that blocked the Lake Fork of the Gunnison River and created Lake San Cristobal. The current landslide activity was triggered by a collapse, which apparently extended the preexisting headscarp toward the north. The loading induced by the deposition of the collapsed materials reactivated some of the older landslide deposits. Displacement rates in the active part of the landslide range from about 0.2 m/yr at the uppermost fractures to a maximum of 7.4 m/yr in the narrowest part of the landslide. From this maximum rate, displacement rate declines to 2 or less m/yr at the toe. The interplay between different displacement rates, varying width, and curving boundaries gives rise to the structures within the landslide. For purposes of description, the landslide has been divided into seven zones: head, zone of stretching, the hopper and neck, zone of pull-apart basins, pond deposits and emergent toe, zone of shortening and spreading, and active toe. Each zone has its characteristic kinematic expression that provides information on the internal deformation of the landslide. In general, the upper part of the landslide is characterized by features such as normal faults and tension cracks associated with stretching. The lowermost part of the landslide is characterized by thrust faults and other features associated with shortening. In between, features are a result of widening, bending, or narrowing of the landslide. Also, in

  14. Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications

    PubMed Central

    Liu, Chunlei; Wei, Hongjiang; Gong, Nan-Jie; Cronin, Matthew; Dibb, Russel; Decker, Kyle

    2016-01-01

    Quantitative susceptibility mapping (QSM) is a recently developed MRI technique for quantifying the spatial distribution of magnetic susceptibility within biological tissues. It first uses the frequency shift in the MRI signal to map the magnetic field profile within the tissue. The resulting field map is then used to determine the spatial distribution of the underlying magnetic susceptibility by solving an inverse problem. The solution is achieved by deconvolving the field map with a dipole field, under the assumption that the magnetic field is a result of the superposition of the dipole fields generated by all voxels and that each voxel has its unique magnetic susceptibility. QSM provides improved contrast to noise ratio for certain tissues and structures compared to its magnitude counterpart. More importantly, magnetic susceptibility is a direct reflection of the molecular composition and cellular architecture of the tissue. Consequently, by quantifying magnetic susceptibility, QSM is becoming a quantitative imaging approach for characterizing normal and pathological tissue properties. This article reviews the mechanism generating susceptibility contrast within tissues and some associated applications. PMID:26844301

  15. Geological Investigation and analysis in response to Earthquake Induced Landslide in West Sumatra

    NASA Astrophysics Data System (ADS)

    Karnawati, D.; Wilopo, W.; Salahudin, S.; Sudarno, I.; Burton, P.

    2009-12-01

    Substantial socio-economical loss occurred in response to the September 30. 2009 West Sumatra Earthquake with magnitude of 7.6. Damage of houses and engineered structures mostly occurred at the low land of alluvium sediments due to the ground amplification, whilst at the high land of mountain slopes several villages were buried by massive debris of rocks and soils. It was recorded that 1115 people died due to this disasters. Series of geological investigation was carried out by Geological Engineering Department of Gadjah Mada University, with the purpose to support the rehabilitation program. Based on this preliminary investigation it was identified that most of the house and engineered structural damages at the alluvial deposits mainly due to by the poor quality of such houses and engineered structures, which poorly resist the ground amplification, instead of due to the control of geological conditions. On the other hand, the existence and distribution of structural geology (faults and joints) at the mountaineous regions are significant in controlling the distribution of landslides, with the types of rock falls, debris flows and debris falls. Despite the landslide susceptibility mapping conducted by Geological Survey of Indonesia, more detailed investigation is required to be carried out in the region surrounding Maninjau Lake, in order to provide safer places for village relocation. Accordingly Gadjah Mada University in collaboration with the local university (Andalas University) as well as with the local Government of Agam Regency and the Geological Survey of Indonesia, serve the mission for conducting rather more detailed geological and landslide investigation. It is also crucial that the investigation (survey and mapping) on the social perception and expectation of local people living in this landslide susceptible area should also be carried out, to support the mitigation effort of any future potential earthquake induced landslides.

  16. Database Organisation in a Web-Enabled Free and Open-Source Software (foss) Environment for Spatio-Temporal Landslide Modelling

    NASA Astrophysics Data System (ADS)

    Das, I.; Oberai, K.; Sarathi Roy, P.

    2012-07-01

    Landslides exhibit themselves in different mass movement processes and are considered among the most complex natural hazards occurring on the earth surface. Making landslide database available online via WWW (World Wide Web) promotes the spreading and reaching out of the landslide information to all the stakeholders. The aim of this research is to present a comprehensive database for generating landslide hazard scenario with the help of available historic records of landslides and geo-environmental factors and make them available over the Web using geospatial Free & Open Source Software (FOSS). FOSS reduces the cost of the project drastically as proprietary software's are very costly. Landslide data generated for the period 1982 to 2009 were compiled along the national highway road corridor in Indian Himalayas. All the geo-environmental datasets along with the landslide susceptibility map were served through WEBGIS client interface. Open source University of Minnesota (UMN) mapserver was used as GIS server software for developing web enabled landslide geospatial database. PHP/Mapscript server-side application serve as a front-end application and PostgreSQL with PostGIS extension serve as a backend application for the web enabled landslide spatio-temporal databases. This dynamic virtual visualization process through a web platform brings an insight into the understanding of the landslides and the resulting damage closer to the affected people and user community. The landslide susceptibility dataset is also made available as an Open Geospatial Consortium (OGC) Web Feature Service (WFS) which can be accessed through any OGC compliant open source or proprietary GIS Software.

  17. Logistic Regression for Seismically Induced Landslide Predictions: Using Uniform Hazard and Geophysical Layers as Predictor Variables

    NASA Astrophysics Data System (ADS)

    Nowicki, M. A.; Hearne, M.; Thompson, E.; Wald, D. J.

    2012-12-01

    Seismically induced landslides present a costly and often fatal threats in many mountainous regions. Substantial effort has been invested to understand where seismically induced landslides may occur in the future. Both slope-stability methods and, more recently, statistical approaches to the problem are described throughout the literature. Though some regional efforts have succeeded, no uniformly agreed-upon method is available for predicting the likelihood and spatial extent of seismically induced landslides. For use in the U. S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system, we would like to routinely make such estimates, in near-real time, around the globe. Here we use the recently produced USGS ShakeMap Atlas of historic earthquakes to develop an empirical landslide probability model. We focus on recent events, yet include any digitally-mapped landslide inventories for which well-constrained ShakeMaps are also available. We combine these uniform estimates of the input shaking (e.g., peak acceleration and velocity) with broadly available susceptibility proxies, such as topographic slope and surface geology. The resulting database is used to build a predictive model of the probability of landslide occurrence with logistic regression. The landslide database includes observations from the Northridge, California (1994); Wenchuan, China (2008); ChiChi, Taiwan (1999); and Chuetsu, Japan (2004) earthquakes; we also provide ShakeMaps for moderate-sized events without landslide for proper model testing and training. The performance of the regression model is assessed with both statistical goodness-of-fit metrics and a qualitative review of whether or not the model is able to capture the spatial extent of landslides for each event. Part of our goal is to determine which variables can be employed based on globally-available data or proxies, and whether or not modeling results from one region are transferrable to

  18. Impacts of Landuse Management and Climate Change on Landslides Susceptibility over the Olympic Peninsula of Washington State

    NASA Astrophysics Data System (ADS)

    Barik, M. G.; Adam, J. C.

    2009-12-01

    The commercial forests on the western side of the Olympic Mountains in Washington State are a region of steep slopes and high annual rainfall (2500-6000 mm/year) and are therefore highly susceptible to landslides. Potential climatic change (more intense and frequent winter storms) may exacerbate landslide susceptibility unless forest management practices are changed. As this area is a critical habitat for numerous organisms, including salmon, this may result in potentially severe consequences to riparian habitat due to increased sediment loads. Therefore, there is a need to investigate potential forest management plans to promote the economic viability of timber extraction while protecting the natural habitat, particularly in riparian areas. The objective of this study is to predict the long term effects of forest management decisions under projected climate change on slope stability. We applied the physically-based Distributed Hydrology Soil Vegetation Model (DHSVM) with its sediment module to simulate mass wasting and sediment delivery under different vegetation and climate scenarios. Sub-basins were selected and classified according to elevation, slope, land cover and soil type. Various land management practices (such as clear-cutting in riparian areas, logging under short rotations, varying amount of timbers left intact in riparian areas) were applied to each of the selected sub-basins. DHSVM was used to simulate landslide volume, frequency, and sediment loads for each of the land cover applications under various future climate scenarios. We comment on the suitability of various harvesting techniques for different parts of the forest to minimize landslide-induced sediment loading to streams in an altered climate. This approach can be developed as a decision making tool that can be used by forest managers to make long-term planning decisions.

  19. ­­­­High-Resolution Mapping of Kick`em Jenny Submarine Volcano and Associated Landslides

    NASA Astrophysics Data System (ADS)

    Ruchala, T. L.; Carey, S.; Hart, L.; Chen, M.; Scott, C.; Tominaga, M.; Dondin, F. J. Y.; Fujii, M.

    2016-02-01

    To understand the physical and geological processes that drive the volcanism and control the morphology of Kick`em Jenny (KEJ) volcano, the only active submarine volcano in the in the Lesser Antilles volcanic arc, we conducted near-source, high-resolution mapping of KEJ and its subsurface using the Remotely Operated Vehicle (ROV) Hercules during cruise NA054 of the E/V Nautilus (Sept.-Oct. 2014). Shipboard bathymetric data (EM302 system) and slope analysis maps were used to decipher the detailed seafloor morphology surrounding KEJ. Multiple generations of submarine landslides and canyons were observed, suggesting the area has been hosting dynamic sediment transport systems at multiple scales over time. Some of them might have been associated by past eruptions. Clear contacts between partially lithified carbonate sediments and volcanic formations were identified from ROV videos at the middle of the landslide slope face. Detailed observations of facies on these exposures provide constraints on the time intervals between landslide events along the western slope of KEJ. ROV video imagery also identified outcrops of columnar basalts located in the middle of the landslide deposits. These are similar in appearance to those observed in the KEJ crater during previous ROV dives, indicating a possible travel distance of volcanic materials from the crater region along landslide path. High-resolution photo mosaics, bathymetry, and magnetic data acquired by ROV Hercules were used to investigate geological processes and the possible volcanic source of landslide material within the KEJ crater. Mapping in the northwestern part of the crater floor revealed distinctive regions, including (i) microbial mats, (ii) active hydrothermal vent sites; (iii) landforms curved by channelized bottom current where seafloor is outcropped; and (iv) coarse scree the distribution of which may correlate with the distance from the crater rim. Near-bottom magnetic profiles show coherent magnetic

  20. Landslide hazard prediction in the North-Eastern Apennines (Italy)

    NASA Astrophysics Data System (ADS)

    Disperati, L.; Guastaldi, E.; Rindinella, A.

    2003-04-01

    In order to assess the landslide hazard nearby the Pergola city (in the Northern-Eastern Apennines, Italy) a ground survey at a scale of 1:10,000 was performed for an extent of about 370 km^2 (Carmignani, 2001), and a GIS of landslides was built. Following statistical analysis allows to assess the correlation among landslide occurrences and causal factors related to the detachment zone (lithology, engineering geology, elevation, slope, aspect, bedding as related with slope face -RBS- and land use). Consequently, considering the morphological, lithological and anthropic characters of current slides, it was agreed to locate possible future landslides in those area actually stable but characterised by similar conditions. Because of that, a geostatistical analysis was performed. Comparing for every landslide the occurence of either single or combined causal factor, the analysis was carried out in grid format. The spatial analysis of the GIS data layers allowed building the unique condition regions (Chung et al., 1995) and creating statistical data on causal factors in relation of landslides. Afterwards, for every region the susceptibility to development of new occurrences (favourability mapping) was calculated by utilising the certainty factor (CF; Chung &Fabbri, 1993). For landslides where crown was identified, the main scarp was considered as occurrence; a buffer around the highest point of landslide was built for all the others (Disperati et al., 2002). Such procedure was applied both for slides (175 occurrences) and flows (464 occurrences). Furthermore, by the application of the procedure to causal factors and their combination, additional information regarding susceptibility to development of new occurrences was calculated. The selection of the most suitable factors combination can be done through the results accuracy assessment in relation of time and/or space (Chung, 1999), by utilising two different hazard information layers, respectively computed from a

  1. Assessment of physical vulnerability of buildings and analysis of landslide risk at the municipal scale - application to the Loures municipality, Portugal

    NASA Astrophysics Data System (ADS)

    Guillard-Gonçalves, C.; Zêzere, J. L.; Pereira, S.; Garcia, R. A. C.

    2015-09-01

    This study offers a semi-quantitative assessment of the physical vulnerability of buildings to landslides in the Loures municipality, as well as an analysis of the landslide risk computed as the product of the vulnerability by the economic value of the buildings and by the landslide hazard. The physical vulnerability assessment, which was based on a questionnaire sent to a pool of Portuguese and European researchers, and the assessment of the subjectivity of their answers are innovative contributions of this work. The generalization of the vulnerability to the smallest statistical subsection was validated by changing the map unit and applying the vulnerability to all the buildings of a test site (approximately 800 buildings), which were inventoried during fieldwork. The economic value of the buildings of the Loures municipality was calculated using an adaptation of the Portuguese Tax Services formula. The hazard was assessed by combining the susceptibility of the slopes, the spatio-temporal probability and the frequency-magnitude relationship of the landslide. Finally, the risk was mapped for different landslide magnitudes and different spatio-temporal probabilities. The highest landslide risk was found for the landslide with a depth of 3 m in the landslide body, and a height of 1m in the landslide foot.

  2. Assessing population exposure for landslide risk analysis using dasymetric cartography

    NASA Astrophysics Data System (ADS)

    Garcia, Ricardo A. C.; Oliveira, Sérgio C.; Zêzere, José L.

    2016-12-01

    Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost-benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment.

  3. Determination of important topographic factors for landslide mapping analysis using MLP network.

    PubMed

    Alkhasawneh, Mutasem Sh; Ngah, Umi Kalthum; Tay, Lea Tien; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

    2013-01-01

    Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.

  4. Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network

    PubMed Central

    Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

    2013-01-01

    Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors. PMID:24453846

  5. Landslides of Palestinian Region

    NASA Astrophysics Data System (ADS)

    Alwahsh, H.

    2013-12-01

    Natural disasters are extreme sudden events caused by environmental and natural actors that take away the lives of many thousands of people each year and damage large amount of properties. They strike anywhere on earth, often without any warning. A risk maps of natural disaster are very useful to identify the places that might be adversely affected in the event of natural disaster. The earthquakes are one of natural disaster that have the greatest hazards and will cause loss of life and properties due to damaging the structures of building, dams, bridges. In addition, it will affect local geology and soil conditions. The site effects play an important role in earthquake risk because of its amplification or damping simulation. Another parameter in developing risk map is landslide, which is also one of the most important topics in site effect hazards. Palestine region has been suffering landslide hazards because of the topographical and geological conditions of this region. Most Palestine consists of mountainous area, which has great steep slopes and the type of soil is mainly grayish to yellowish silty clay (Marl Soil). Due to the above mentioned factors many landslides have been occurred from Negev south to the northern borders of Palestine. An example of huge and destruction landslide in a Palestine authority is the landslide in the White Mountain area in the city of Nablus, which occurred in 1997. The geotechnical and geophysical investigation as well as slope stability analysis should be considered in making landslide maps that are necessary to develop risk levels of the natural disaster. Landslides occurred in slopes that are created naturally or by human beings. Failure of soil mass occurs, and hence landslide of soil mass happen due to sliding of soil mass along a plane or curved surface. In general, the slopes become unstable when the shear stresses (driving force) generated in the soil mass exceed the available shearing resistance on the rupture surface

  6. Map showing recent and historic landslide activity on coastal bluffs of Puget Sound between Shilshole Bay and Everett, Washington

    USGS Publications Warehouse

    Baum, R.L.; Harp, E.L.; Hultman, W.A.

    2000-01-01

    Many landslides occurred on the coastal bluffs between Seattle and Everett, Washington during the winters of 1996 and 1997. Shallow earth slides and debris flows were the most common, but a few deep-seated rotational earth slides also occurred. The landslides caused significant property damage and interfered with rail traffic; future landslides in the area pose significant hazards to property and public safety. Field observations indicate that ground-water seepage, runoff concentration, and dumping at the tops of the bluffs all contributed to instability of the bluffs. Most landslides in the study area occurred in colluvium, residuum, and landslide deposits derived from the Vashon Drift, particularly the advance outwash. In the northern part of the area, colluvium derived from the Pleistocene Whidbey Formation was also involved in shallow landslides. Comparison of recent activity with historic records in the southern part of the map area indicates that landslides tend to occur in many of the same areas as previous landslides.

  7. Toward accelerating landslide mapping with interactive machine learning techniques

    NASA Astrophysics Data System (ADS)

    Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

    2013-04-01

    Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also

  8. Brain Injury Lesion Imaging Using Preconditioned Quantitative Susceptibility Mapping without Skull Stripping.

    PubMed

    Soman, S; Liu, Z; Kim, G; Nemec, U; Holdsworth, S J; Main, K; Lee, B; Kolakowsky-Hayner, S; Selim, M; Furst, A J; Massaband, P; Yesavage, J; Adamson, M M; Spincemallie, P; Moseley, M; Wang, Y

    2018-04-01

    Identifying cerebral microhemorrhage burden can aid in the diagnosis and management of traumatic brain injury, stroke, hypertension, and cerebral amyloid angiopathy. MR imaging susceptibility-based methods are more sensitive than CT for detecting cerebral microhemorrhage, but methods other than quantitative susceptibility mapping provide results that vary with field strength and TE, require additional phase maps to distinguish blood from calcification, and depict cerebral microhemorrhages as bloom artifacts. Quantitative susceptibility mapping provides universal quantification of tissue magnetic property without these constraints but traditionally requires a mask generated by skull-stripping, which can pose challenges at tissue interphases. We evaluated the preconditioned quantitative susceptibility mapping MR imaging method, which does not require skull-stripping, for improved depiction of brain parenchyma and pathology. Fifty-six subjects underwent brain MR imaging with a 3D multiecho gradient recalled echo acquisition. Mask-based quantitative susceptibility mapping images were created using a commonly used mask-based quantitative susceptibility mapping method, and preconditioned quantitative susceptibility images were made using precondition-based total field inversion. All images were reviewed by a neuroradiologist and a radiology resident. Ten subjects (18%), all with traumatic brain injury, demonstrated blood products on 3D gradient recalled echo imaging. All lesions were visible on preconditioned quantitative susceptibility mapping, while 6 were not visible on mask-based quantitative susceptibility mapping. Thirty-one subjects (55%) demonstrated brain parenchyma and/or lesions that were visible on preconditioned quantitative susceptibility mapping but not on mask-based quantitative susceptibility mapping. Six subjects (11%) demonstrated pons artifacts on preconditioned quantitative susceptibility mapping and mask-based quantitative susceptibility mapping

  9. Regional Landslide Mapping Aided by Automated Classification of SqueeSAR™ Time Series (Northern Apennines, Italy)

    NASA Astrophysics Data System (ADS)

    Iannacone, J.; Berti, M.; Allievi, J.; Del Conte, S.; Corsini, A.

    2013-12-01

    Space borne InSAR has proven to be very valuable for landslides detection. In particular, extremely slow landslides (Cruden and Varnes, 1996) can be now clearly identified, thanks to the millimetric precision reached by recent multi-interferometric algorithms. The typical approach in radar interpretation for landslides mapping is based on average annual velocity of the deformation which is calculated over the entire times series. The Hotspot and Cluster Analysis (Lu et al., 2012) and the PSI-based matrix approach (Cigna et al., 2013) are examples of landslides mapping techniques based on average annual velocities. However, slope movements can be affected by non-linear deformation trends, (i.e. reactivation of dormant landslides, deceleration due to natural or man-made slope stabilization, seasonal activity, etc). Therefore, analyzing deformation time series is crucial in order to fully characterize slope dynamics. While this is relatively simple to be carried out manually when dealing with small dataset, the time series analysis over regional scale dataset requires automated classification procedures. Berti et al. (2013) developed an automatic procedure for the analysis of InSAR time series based on a sequence of statistical tests. The analysis allows to classify the time series into six distinctive target trends (0=uncorrelated; 1=linear; 2=quadratic; 3=bilinear; 4=discontinuous without constant velocity; 5=discontinuous with change in velocity) which are likely to represent different slope processes. The analysis also provides a series of descriptive parameters which can be used to characterize the temporal changes of ground motion. All the classification algorithms were integrated into a Graphical User Interface called PSTime. We investigated an area of about 2000 km2 in the Northern Apennines of Italy by using SqueeSAR™ algorithm (Ferretti et al., 2011). Two Radarsat-1 data stack, comprising of 112 scenes in descending orbit and 124 scenes in ascending orbit

  10. Application of Time Series Insar Technique for Deformation Monitoring of Large-Scale Landslides in Mountainous Areas of Western China

    NASA Astrophysics Data System (ADS)

    Qu, T.; Lu, P.; Liu, C.; Wan, H.

    2016-06-01

    Western China is very susceptible to landslide hazards. As a result, landslide detection and early warning are of great importance. This work employs the SBAS (Small Baseline Subset) InSAR Technique for detection and monitoring of large-scale landslides that occurred in Li County, Sichuan Province, Western China. The time series INSAR is performed using descending scenes acquired from TerraSAR-X StripMap mode since 2014 to get the spatial distribution of surface displacements of this giant landslide. The time series results identify the distinct deformation zone on the landslide body with a rate of up to 150mm/yr. The deformation acquired by SBAS technique is validated by inclinometers from diverse boreholes of in-situ monitoring. The integration of InSAR time series displacements and ground-based monitoring data helps to provide reliable data support for the forecasting and monitoring of largescale landslide.

  11. Expert opinion on landslide susceptibility elicted by probabilistic inversion from scenario rankings

    NASA Astrophysics Data System (ADS)

    Lee, Katy; Dashwood, Claire; Lark, Murray

    2016-04-01

    For many natural hazards the opinion of experts, with experience in assessing susceptibility under different circumstances, is a valuable source of information on which to base risk assessments. This is particularly important where incomplete process understanding, and limited data, limit the scope to predict susceptibility by mechanistic or statistical modelling. The expert has a tacit model of a system, based on their understanding of processes and their field experience. This model may vary in quality, depending on the experience of the expert. There is considerable interest in how one may elicit expert understanding by a process which is transparent and robust, to provide a basis for decision support. One approach is to provide experts with a set of scenarios, and then to ask them to rank small overlapping subsets of these with respect to susceptibility. Methods of probabilistic inversion have been used to compute susceptibility scores for each scenario, implicit in the expert ranking. It is also possible to model these scores as functions of measurable properties of the scenarios. This approach has been used to assess susceptibility of animal populations to invasive diseases, to assess risk to vulnerable marine environments and to assess the risk in hypothetical novel technologies for food production. We will present the results of a study in which a group of geologists with varying degrees of expertise in assessing landslide hazards were asked to rank sets of hypothetical simplified scenarios with respect to land slide susceptibility. We examine the consistency of their rankings and the importance of different properties of the scenarios in the tacit susceptibility model that their rankings implied. Our results suggest that this is a promising approach to the problem of how experts can communicate their tacit model of uncertain systems to those who want to make use of their expertise.

  12. Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge.

    PubMed

    Langkammer, Christian; Schweser, Ferdinand; Shmueli, Karin; Kames, Christian; Li, Xu; Guo, Li; Milovic, Carlos; Kim, Jinsuh; Wei, Hongjiang; Bredies, Kristian; Buch, Sagar; Guo, Yihao; Liu, Zhe; Meineke, Jakob; Rauscher, Alexander; Marques, José P; Bilgic, Berkin

    2018-03-01

    The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully. Gradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions. Twenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance. Because QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria. Magn Reson Med 79:1661-1673, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  13. Fostering the uptake of satellite Earth Observation data for landslide hazard understanding: the CEOS Landslide Pilot

    NASA Astrophysics Data System (ADS)

    Kirschbaum, Dalia; Malet, Jean-Philippe; Roessner, Sigrid

    2017-04-01

    Landslides occur around the world, on every continent, and play an important role in the evolution of landscapes. They also represent a serious hazard in many areas of the world. Despite their importance, it has been estimated that past landslide and landslide potential maps cover less than 1% of the slopes in these landmasses. Systematic information on the type, abundance, and distribution of existing landslides is lacking. Even in countries where landslide information is abundant (e.g. Italy), the vast majority of landslides caused by meteorological (intense or prolonged rainfall, rapid snowmelt) or geophysical (earthquake) triggers go undetected. This paucity of knowledge has consequences on the design of effective remedial and mitigation measures. Systematic use of Earth observation (EO) data and technologies can contribute effectively to detect, map, and monitor landslides, and landslide prone hillsides, in different physiographic and climatic regions. The CEOS (Committee on Earth Observation Satellites) Working Group on Disasters has recently launched a Landslide Pilot (period 2017-2019) with the aim to demonstrate the effective exploitation of satellite EO across the full cycle of landslide disaster risk management, including preparedness, response, and recovery at global, regional, and local scales, with a distinct multi-hazard focus on cascading impacts and risks. The Landslide Pilot is focusing efforts on three objectives: 1. Establish effective practices for merging different Earth Observation data (e.g. optical and radar) to better monitor and map landslide activity over time and space. 2. Demonstrate how landslide products, models, and services can support disaster risk management for multi-hazard and cascading landslide events. 3. Engage and partner with data brokers and end users to understand requirements and user expectations and get feedback through the activities described in objectives 1-2. The Landslide Pilot was endorsed in April 2016 and work

  14. Land Cover Mapping using GEOBIA to Estimate Loss of Salacca zalacca Trees in Landslide Area of Clapar, Madukara District of Banjarnegara

    NASA Astrophysics Data System (ADS)

    Permata, Anggi; Juniansah, Anwar; Nurcahyati, Eka; Dimas Afrizal, Mousafi; Adnan Shafry Untoro, Muhammad; Arifatha, Na'ima; Ramadhani Yudha Adiwijaya, Raden; Farda, Nur Mohammad

    2016-11-01

    Landslide is an unpredictable natural disaster which commonly happens in highslope area. Aerial photography in small format is one of acquisition method that can reach and obtain high resolution spatial data faster than other methods, and provide data such as orthomosaic and Digital Surface Model (DSM). The study area contained landslide area in Clapar, Madukara District of Banjarnegara. Aerial photographs of landslide area provided advantage in objects visibility. Object's characters such as shape, size, and texture were clearly seen, therefore GEOBIA (Geography Object Based Image Analysis) was compatible as method for classifying land cover in study area. Dissimilar with PPA (PerPixel Analyst) method that used spectral information as base object detection, GEOBIA could use spatial elements as classification basis to establish a land cover map with better accuracy. GEOBIA method used classification hierarchy to divide post disaster land cover into three main objects: vegetation, landslide/soil, and building. Those three were required to obtain more detailed information that can be used in estimating loss caused by landslide and establishing land cover map in landslide area. Estimating loss in landslide area related to damage in Salak (Salacca zalacca) plantations. This estimation towards quantity of Salak tree that were drifted away by landslide was calculated in assumption that every tree damaged by landslide had same age and production class with other tree that weren't damaged. Loss calculation was done by approximating quantity of damaged trees in landslide area with data of trees around area that were acquired from GEOBIA classification method.

  15. Comparison between monitored and modeled pore water pressure and safety factor in a slope susceptible to shallow landslides

    NASA Astrophysics Data System (ADS)

    Bordoni, Massimiliano; Meisina, Claudia; Zizioli, Davide; Valentino, Roberto; Bittelli, Marco; Chersich, Silvia

    2014-05-01

    Shallow landslides can be defined as slope movements affecting superficial deposits of small thicknesses which are usually triggered due to extreme rainfall events, also very concentrated in time. Shallow landslides are hazardous phenomena: in particular, if they happen close to urbanized areas they could cause significant damages to cultivations, structures, infrastructures and, sometimes, human losses. The triggering mechanism of rainfall-induced shallow landslides is strictly linked with the hydrological and mechanical responses of usually unsaturated soils to rainfall events. For this reason, it is fundamental knowing the intrinsic hydro-mechanical properties of the soils in order to assess both susceptibility and hazard of shallow landslide and to develop early-warning systems at large scale. The hydrological data collected by a 20 months monitoring on a slope susceptible to shallow landslides in an area of the North -Eastern Oltrepo Pavese (Northern Apennines, Italy) were used to identify the hydrological behaviors of the investigated soils towards rainfall events. Field conditions under different rainfall trends have also been modeled by using both hydrological and physically-based stability models for the evaluation of the slope safety factor . The main objectives of this research are: (a) to compare the field measured pore water pressures at different depths with results of hydrological models, in order to evaluate the efficiency of the tested models and to determine how precipitations affect pore pressure development; (b) to compare the time trends of the safety factor that have been obtained by applying different stability models; (c) to evaluate, through a sensitivity analysis, the effects of soil hydrological properties on modeling pore water pressure and safety factor. The test site slope where field measurements were acquired is representative of other sites in Northern Apennines affected by shallow landslides and is characterized by medium

  16. Usefulness of quantitative susceptibility mapping for the diagnosis of Parkinson disease.

    PubMed

    Murakami, Y; Kakeda, S; Watanabe, K; Ueda, I; Ogasawara, A; Moriya, J; Ide, S; Futatsuya, K; Sato, T; Okada, K; Uozumi, T; Tsuji, S; Liu, T; Wang, Y; Korogi, Y

    2015-06-01

    Quantitative susceptibility mapping allows overcoming several nonlocal restrictions of susceptibility-weighted and phase imaging and enables quantification of magnetic susceptibility. We compared the diagnostic accuracy of quantitative susceptibility mapping and R2* (1/T2*) mapping to discriminate between patients with Parkinson disease and controls. For 21 patients with Parkinson disease and 21 age- and sex-matched controls, 2 radiologists measured the quantitative susceptibility mapping values and R2* values in 6 brain structures (the thalamus, putamen, caudate nucleus, pallidum, substantia nigra, and red nucleus). The quantitative susceptibility mapping values and R2* values of the substantia nigra were significantly higher in patients with Parkinson disease (P < .01); measurements in other brain regions did not differ significantly between patients and controls. For the discrimination of patients with Parkinson disease from controls, receiver operating characteristic analysis suggested that the optimal cutoff values for the substantia nigra, based on the Youden Index, were >0.210 for quantitative susceptibility mapping and >28.8 for R2*. The sensitivity, specificity, and accuracy of quantitative susceptibility mapping were 90% (19 of 21), 86% (18 of 21), and 88% (37 of 42), respectively; for R2* mapping, they were 81% (17 of 21), 52% (11 of 21), and 67% (28 of 42). Pair-wise comparisons showed that the areas under the receiver operating characteristic curves were significantly larger for quantitative susceptibility mapping than for R2* mapping (0.91 versus 0.69, P < .05). Quantitative susceptibility mapping showed higher diagnostic performance than R2* mapping for the discrimination between patients with Parkinson disease and controls. © 2015 by American Journal of Neuroradiology.

  17. Temporal and spatial distribution of landslides in the Redwood Creek Basin, Northern California

    USGS Publications Warehouse

    Madej, Mary Ann; Medley, C. Nicholas; Patterson, Glenn; Parker, Melanie J.

    2011-01-01

    Mass movement processes are a dominant means of supplying sediment to mountainous rivers of north coastal California, but the episodic nature of landslides represents a challenge to interpreting patterns of slope instability. This study compares two major landslide events occurring in 1964-1975 and in 1997 in the Redwood Creek basin in north coastal California. In 1997, a moderate-intensity, long-duration storm with high antecedent precipitation triggered 317 landslides with areas greater than 400 m2 in the 720-km2 Redwood Creek basin. The intensity-duration threshold for landslide initiation in 1997 was consistent with previously published values. Aerial photographs (1:6,000 scale) taken a few months after the 1997 storm facilitated the mapping of shallow debris slides, debris flows, and bank failures. The magnitude and location of the 1997 landslides were compared to the distributions of landslides generated by larger floods in 1964, 1972, and 1975. The volume of landslide material produced by the 1997 storm was an order of magnitude less than that generated in the earlier period. During both periods, inner gorge hillslopes produced many landslides, but the relative contribution of tributary basins to overall landslide production differed. Slope stability models can help identify areas susceptible to failure. The 22 percent of the watershed area classified as moderately to highly unstable by the SHALSTAB slope stability model included locations that generated almost 90 percent of the landslide volume during the 1997 storm.

  18. An integrated approach coupling physically based models and probabilistic method to assess quantitatively landslide susceptibility at different scale: application to different geomorphological environments

    NASA Astrophysics Data System (ADS)

    Vandromme, Rosalie; Thiéry, Yannick; Sedan, Olivier; Bernardie, Séverine

    2016-04-01

    probability to obtain a safety factor below 1 represents the probability of occurrence of a landslide for a given triggering event. The dispersion of the distribution gives the uncertainty of the result. Finally, a map is created, displaying a probability of occurrence for each computing cell of the studied area. In order to take into account the land-uses change, a complementary module integrating the vegetation effects on soil properties has been recently developed. Last years, the model has been applied at different scales for different geomorphological environments: (i) at regional scale (1:50,000-1:25,000) in French West Indies and French Polynesian islands (ii) at local scale (i.e.1:10,000) for two complex mountainous areas; (iii) at the site-specific scale (1:2,000) for one landslide. For each study the 3D geotechnical model has been adapted. The different studies have allowed : (i) to discuss the different factors included in the model especially the initial 3D geotechnical models; (ii) to precise the location of probable failure following different hydrological scenarii; (iii) to test the effects of climatic change and land-use on slopes for two cases. In that way, future changes in temperature, precipitation and vegetation cover can be analyzed, permitting to address the impacts of global change on landslides. Finally, results show that it is possible to obtain reliable information about future slope failures at different scale of work for different scenarii with an integrated approach. The final information about landslide susceptibility (i.e. probability of failure) can be integrated in landslide hazard assessment and could be an essential information source for future land planning. As it has been performed in the ANR Project SAMCO (Society Adaptation for coping with Mountain risks in a global change COntext), this analysis constitutes a first step in the chain for risk assessment for different climate and economical development scenarios, to evaluate the

  19. Inundation Mapping and Hazard Assessment of Tectonic and Landslide Tsunamis in Southeast Alaska

    NASA Astrophysics Data System (ADS)

    Suleimani, E.; Nicolsky, D.; Koehler, R. D., III

    2014-12-01

    The Alaska Earthquake Center conducts tsunami inundation mapping for coastal communities in Alaska, and is currently focused on the southeastern region and communities of Yakutat, Elfin Cove, Gustavus and Hoonah. This activity provides local emergency officials with tsunami hazard assessment, planning, and mitigation tools. At-risk communities are distributed along several segments of the Alaska coastline, each having a unique seismic history and potential tsunami hazard. Thus, a critical component of our project is accurate identification and characterization of potential tectonic and landslide tsunami sources. The primary tectonic element of Southeast Alaska is the Fairweather - Queen Charlotte fault system, which has ruptured in 5 large strike-slip earthquakes in the past 100 years. The 1958 "Lituya Bay" earthquake triggered a large landslide into Lituya Bay that generated a 540-m-high wave. The M7.7 Haida Gwaii earthquake of October 28, 2012 occurred along the same fault, but was associated with dominantly vertical motion, generating a local tsunami. Communities in Southeast Alaska are also vulnerable to hazards related to locally generated waves, due to proximity of communities to landslide-prone fjords and frequent earthquakes. The primary mechanisms for local tsunami generation are failure of steep rock slopes due to relaxation of internal stresses after deglaciation, and failure of thick unconsolidated sediments accumulated on underwater delta fronts at river mouths. We numerically model potential tsunami waves and inundation extent that may result from future hypothetical far- and near-field earthquakes and landslides. We perform simulations for each source scenario using the Alaska Tsunami Model, which is validated through a set of analytical benchmarks and tested against laboratory and field data. Results of numerical modeling combined with historical observations are compiled on inundation maps and used for site-specific tsunami hazard assessment by

  20. Uncertainty evaluation of a regional real-time system for rain-induced landslides

    NASA Astrophysics Data System (ADS)

    Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

    2015-04-01

    A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

  1. Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

    NASA Astrophysics Data System (ADS)

    Oliveira, Sérgio C.; Zêzere, José L.; Lajas, Sara; Melo, Raquel

    2017-07-01

    Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km2) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

  2. Modelling of Rainfall Induced Landslides in Puerto Rico

    NASA Astrophysics Data System (ADS)

    Lepore, C.; Arnone, E.; Sivandran, G.; Noto, L. V.; Bras, R. L.

    2010-12-01

    We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model, Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator with VEGetation Generator for Interactive Evolution (tRIBS-VEGGIE), tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico and validated against in-situ measurements. A slope-failure module has been added to tRIBS-VEGGIE’s framework, after analyzing several failure criterions to identify the most suitable for our application; the module is used to predict the location and timing of landsliding events. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides.

  3. Regional landslide-hazard assessment for Seattle, Washington, USA

    USGS Publications Warehouse

    Baum, R.L.; Coe, J.A.; Godt, J.W.; Harp, E.L.; Reid, M.E.; Savage, W.Z.; Schulz, W.H.; Brien, D.L.; Chleborad, A.F.; McKenna, J.P.; Michael, J.A.

    2005-01-01

    Landslides are a widespread, frequent, and costly hazard in Seattle and the Puget Sound area of Washington State, USA. Shallow earth slides triggered by heavy rainfall are the most common type of landslide in the area; many transform into debris flows and cause significant property damage or disrupt transportation. Large rotational and translational slides, though less common, also cause serious property damage. The hundreds of landslides that occurred during the winters of 1995-96 and 1996-97 stimulated renewed interest by Puget Sound communities in identifying landslide-prone areas and taking actions to reduce future landslide losses. Informal partnerships between the U.S. Geological Survey (USGS), the City of Seattle, and private consultants are focusing on the problem of identifying and mapping areas of landslide hazard as well as characterizing temporal aspects of the hazard. We have developed GIS-based methods to map the probability of landslide occurrence as well as empirical rainfall thresholds and physically based methods to forecast times of landslide occurrence. Our methods for mapping landslide hazard zones began with field studies and physically based models to assess relative slope stability, including the effects of material properties, seasonal groundwater levels, and rainfall infiltration. We have analyzed the correlation between historic landslide occurrence and relative slope stability to map the degree of landslide hazard. The City of Seattle is using results of the USGS studies in storm preparedness planning for emergency access and response, planning for development or redevelopment of hillsides, and municipal facility planning and prioritization. Methods we have developed could be applied elsewhere to suit local needs and available data.

  4. Towards a National Hazard Map of Landslides: Juan de Grijalva, Chiapas, and Mitlatongo, Oaxaca, two catastrophic landslides on southeastern of Mexico

    NASA Astrophysics Data System (ADS)

    Dominguez-M, L.; Castañeda, A.; Ramirez, A.; González, A. E.

    2013-05-01

    One of the most catastrophic events, with economical losses and deaths, in Mexico and Latin America, is the landslide event. The Juan de Grijalva landslide, which blocked one of the largest rivers in the Chiapas state of Mexico, on November 4, 2007, is considered one of the greatest that have occurred in the world in the last 100 years (Dominguez, 2008) and it could be the one with the largest economic impact in the history of Mexico. This landslide occurred four days after a period of very heavy rains that caused, in the peak of the emergency, flooding in almost 62% of the area of the state of Tabasco (CENAPRED, 2009) and is also one of the most serious disasters that were faced by the Mexican government in the past 10 years. The Juan de Grijalva landslide mobilized the entire government apparatus and required an investment of just over 0.1 billions of US Dollars (CENAPRED, 2009) for the rehabilitation of the river runway and additional works in order to prevent further damages if another landslide occurs in the vicinity. A similar case of interest for Mexican researchers and specialists in earth sciences is the big landslide occurred in the communities of Santa Cruz Mitlatongo, municipality of Magdalena Jaltepec, and Santiago Mitlatongo, municipality of Nochixtlan, both in the state of Oaxaca (Dominguez, 2011). This landslide has dimensions of just over 2,500 m long and 900 m wide, and it remains active from September 2011. Since then, the landslide has moved just over 230 m in length and has destroyed about 850 houses. Given the geological and geotechnical characteristics of these landslides and the economic and social impact caused, the National Center for Disaster Prevention (CENAPRED) has initiated a research project in order to learn the main factors (constraints and triggers) that influenced both landslides. In relation with the National Hazard Landslide Map, developed by CENAPRED, these events are an important task of the National Inventory of Landslides

  5. Landslides in the western Columbia Gorge, Skamania County, Washington

    USGS Publications Warehouse

    Pierson, Thomas C.; Evarts, Russell C.; Bard, Joseph A.

    2016-11-04

    SummaryRecent light detection and ranging (lidar) imagery has allowed us to identify and map a large number of previously unrecognized landslides, or slides, in heavily forested terrain in the western Columbia Gorge, Skamania County, Washington, and it has revealed that the few previously recognized areas of instability are actually composites of multiple smaller landslides. The high resolution of the imagery further reveals that landslides in the map area have complex movement histories and span a wide range of relative ages. Movement histories are inferred from relative landslide locations and crosscutting relations of surface features. Estimated age ranges are based on (1) limited absolute dating; (2) relative fineness of landscape surface textures, calibrated by comparison with surfaces of currently active and dated landslides as interpreted from interferometric synthetic aperture radar (InSAR), global positioning system (GPS), and historical records; (3) sharpness and steepness of larger-scale surface morphologic features, calibrated by comparison with similar dated features in other regions; (4) degree of surface erosion; and (5) evidence of erosion or deposition by late Pleistocene (15–22 ka) Missoula floods at or below 200 m altitude. The relative age categories are recent (0 to ~1,000 years old), intermediate-age (~1,000 to ~15,000 years old), and old (>~15,000 years old). Within the 221.5 km2 map area, we identified 215 discrete landslides, covering 140.9 km2 (64 percent of the map area). At least 12 of the recent landslides are currently moving or have moved within the last two decades. Mapping for this study expanded the area of previously recognized unstable terrain by 56 percent. Landslide geometries suggest that more than half (62 percent) of these slope failures are translational landslides or composite landslides with translational elements, with failure occurring along gently sloping bedding planes in zones of deeply weathered, locally clay rich

  6. Computed inverse MRI for magnetic susceptibility map reconstruction

    PubMed Central

    Chen, Zikuan; Calhoun, Vince

    2015-01-01

    Objective This paper reports on a computed inverse magnetic resonance imaging (CIMRI) model for reconstructing the magnetic susceptibility source from MRI data using a two-step computational approach. Methods The forward T2*-weighted MRI (T2*MRI) process is decomposed into two steps: 1) from magnetic susceptibility source to fieldmap establishment via magnetization in a main field, and 2) from fieldmap to MR image formation by intravoxel dephasing average. The proposed CIMRI model includes two inverse steps to reverse the T2*MRI procedure: fieldmap calculation from MR phase image and susceptibility source calculation from the fieldmap. The inverse step from fieldmap to susceptibility map is a 3D ill-posed deconvolution problem, which can be solved by three kinds of approaches: Tikhonov-regularized matrix inverse, inverse filtering with a truncated filter, and total variation (TV) iteration. By numerical simulation, we validate the CIMRI model by comparing the reconstructed susceptibility maps for a predefined susceptibility source. Results Numerical simulations of CIMRI show that the split Bregman TV iteration solver can reconstruct the susceptibility map from a MR phase image with high fidelity (spatial correlation≈0.99). The split Bregman TV iteration solver includes noise reduction, edge preservation, and image energy conservation. For applications to brain susceptibility reconstruction, it is important to calibrate the TV iteration program by selecting suitable values of the regularization parameter. Conclusions The proposed CIMRI model can reconstruct the magnetic susceptibility source of T2*MRI by two computational steps: calculating the fieldmap from the phase image and reconstructing the susceptibility map from the fieldmap. The crux of CIMRI lies in an ill-posed 3D deconvolution problem, which can be effectively solved by the split Bregman TV iteration algorithm. PMID:22446372

  7. Maps Showing Locations of Damaging Landslides Caused by El Nino Rainstorms, Winter Season 1997-98, San Francisco Bay Region, California

    USGS Publications Warehouse

    Godt, Jonathan W.

    1999-01-01

    Heavy rainfall associated with a strong El Nino caused over $150 million in landslide damage in the 10-county San Francisco Bay region during the winter and spring of 1998. Reports of landsliding began in early January 1998 and continued throughout the winter and spring. On February 9, President Clinton declared all 10 counties eligible for Federal Emergency Management Agency (FEMA) disaster assistance. In April and May of 1998, personnel from the U.S. Geological Survey (USGS) conducted a field reconnaissance in the area to provide a general overview of landslide damage resulting from the 1997-98 sequence of El Nino-related storms. Seven scientists from the USGS Landslide Hazards Program based in Reston, Virginia; Golden, Colorado; and Menlo Park, California; and five scientists from the USGS Geologic Mapping Program?s San Francisco Bay Mapping Team based in Menlo Park, California, cooperated in the landslide-damage assessments. The assessments were done for 10 counties in the Bay area: Alameda, Contra Costa, Marin, Napa, San Francisco, Santa Clara, Santa Cruz, San Mateo, Solano, and Sonoma. USGS Maps in this series include: MF-2325-A (Napa County), MF-2325-B (Alameda County), MF-2325-C (Marin County), MF-2325-D (Santa Cruz County), MF-2325-E (Contra Costa County), MF-2325-F (Sonoma County), MF-2325-G (San Francisco City and County), MF-2325-H (San Mateo County), MF-2325-I (Solano County), MF-2325-J (Santa Clara County). In addition to USGS scientists providing data from the field evaluation, each of the counties, many consultants, and others cooperated fully in providing the landslide-damage information compiled here.

  8. Probabilistic assessment of precipitation-triggered landslides using historical records of landslide occurence, Seattle, Washington

    USGS Publications Warehouse

    Coe, J.A.; Michael, J.A.; Crovelli, R.A.; Savage, W.Z.; Laprade, W.T.; Nashem, W.D.

    2004-01-01

    Ninety years of historical landslide records were used as input to the Poisson and binomial probability models. Results from these models show that, for precipitation-triggered landslides, approximately 9 percent of the area of Seattle has annual exceedance probabilities of 1 percent or greater. Application of the Poisson model for estimating the future occurrence of individual landslides results in a worst-case scenario map, with a maximum annual exceedance probability of 25 percent on a hillslope near Duwamish Head in West Seattle. Application of the binomial model for estimating the future occurrence of a year with one or more landslides results in a map with a maximum annual exceedance probability of 17 percent (also near Duwamish Head). Slope and geology both play a role in localizing the occurrence of landslides in Seattle. A positive correlation exists between slope and mean exceedance probability, with probability tending to increase as slope increases. Sixty-four percent of all historical landslide locations are within 150 m (500 ft, horizontal distance) of the Esperance Sand/Lawton Clay contact, but within this zone, no positive or negative correlation exists between exceedance probability and distance to the contact.

  9. Landslide and flood hazard assessment in urban areas of Levoča region (Eastern Slovakia)

    NASA Astrophysics Data System (ADS)

    Magulova, Barbora; Caporali, Enrica; Bednarik, Martin

    2010-05-01

    The case study presents the use of statistical methods and analysis tools, for hazard assessment of "urbanization units", implemented in a Geographic Information Systems (GIS) environment. As a case study, the Levoča region (Slovakia) is selected. The region, with a total area of about 351 km2, is widely affected by landslides and floods. The problem, for small urbanization areas, is nowadays particularly significant from the socio-economic point of view. It is considered, presently, also an increasing problem, mainly because of climate change and more frequent extreme rainfall events. The geo-hazards are evaluated using a multivariate analysis. The landslide hazard assessment is based on the comparison and subsequent statistical elaboration of territorial dependence among different input factors influencing the instability of the slopes. Particularly, five factors influencing slope stability are evaluated, i.e. lithology, slope aspect, slope angle, hypsographic level and present land use. As a result a new landslide susceptibility map is compiled and different zones of stable, dormant and non-stable areas are defined. For flood hazard map a detailed digital elevation model is created. A compose index of flood hazard is derived from topography, land cover and pedology related data. To estimate flood discharge, time series of stream flow and precipitation measurements are used. The assessment results are prognostic maps of landslide hazard and flood hazard, which presents the optimal base for urbanization planning.

  10. Landslide Susceptibility Assessment in the Central Part of Republic of Moldova

    NASA Astrophysics Data System (ADS)

    Ercanoglu, Murat; Boboc, Nicolae; Sirodoev, Igor; Ahmet Temiz, F.; Sirodoev, Ghenadi

    2010-05-01

    There has been an increasing interest in natural hazard assessments within the scientific community, particularly in the last two decades. In other respect, there is also a dramatically rising trend in the number of natural hazards. Growing population and expansion of settlements and lifelines over hazardous areas have largely increased the impact of natural disasters both in industrialized and developing countries. Furthermore, natural disasters such as earthquakes, landslides, floods have dramatic effects on human life, infrastructures, environment, and so on. Landslides, one of the most destructive natural hazards, constitute a major geological hazard throughout the world, like in Turkey and Moldova. There are a lot of regions affected by landslides in Turkey (particularly the West, Middle and East Black Sea Region) and Moldova (e.g.: area between Nisporeni, Calarasi, Balti, Western Rezina District, Codri Hills in Central Moldova etc.), and consequences of landslides are of great importance in the two countries. In the last 50 years' period, only the economic loss due to landslides in Turkey is estimated about 5 billion , and 12.5 % of the whole settlement areas, including big and populated cities, are facing landslide threat. Similar to Turkey, there are about 16000 areas affected by landslides in Moldova. In February-March, 1998 the intensity of landslides in the central part of Moldova, including Chisinau, considerably increased. In total, 357 private households involving 1400 people were affected, 214 houses were destroyed, and 137 were damaged. The total national damage accounted for 44.3 million Lei. At present on Moldavian territory, there are more than 17000 landslides of various types. These landslides are mostly located within Central Moldavian heights, one of the most complicated geomorphologic structure and territory's fragmentation. Among major landslide triggering factors, in addition to natural ones, one should also consider the anthropogenic

  11. Map showing recent (1997-98 El Nino) and historical landslides, Crow Creek and vicinity, Alameda and Contra Costa Counties, California

    USGS Publications Warehouse

    Coe, Jeffrey A.; Godt, Jonathan; Tachker, Pierre

    2004-01-01

    This report documents the spatial distribution of 3,800 landslides caused by 1997-98 El Ni?o winter rainfall in the vicinity of Crow Creek in Alameda and Contra Costa Counties, California. The report also documents 558 historical (pre-1997-98) landslides. Landslides were mapped from 1:12,000-scale aerial photographs and classified as either debris flows or slides. Slides include rotational and translational slides, earth flows, and complex slope movements. Debris flows and slides from the 1997-98 winter modified 1 percent of the surface of the 148.6 km2 study area. Debris flows were scattered throughout the area, regardless of the type of underlying bedrock geology. Slides, however, were concentrated in a soft sandstone, conglomerate, and clayey group of rock units. Digital map files accompany the report.

  12. Landslides Identification Using Airborne Laser Scanning Data Derived Topographic Terrain Attributes and Support Vector Machine Classification

    NASA Astrophysics Data System (ADS)

    Pawłuszek, Kamila; Borkowski, Andrzej

    2016-06-01

    Since the availability of high-resolution Airborne Laser Scanning (ALS) data, substantial progress in geomorphological research, especially in landslide analysis, has been carried out. First and second order derivatives of Digital Terrain Model (DTM) have become a popular and powerful tool in landslide inventory mapping. Nevertheless, an automatic landslide mapping based on sophisticated classifiers including Support Vector Machine (SVM), Artificial Neural Network or Random Forests is often computationally time consuming. The objective of this research is to deeply explore topographic information provided by ALS data and overcome computational time limitation. For this reason, an extended set of topographic features and the Principal Component Analysis (PCA) were used to reduce redundant information. The proposed novel approach was tested on a susceptible area affected by more than 50 landslides located on Rożnów Lake in Carpathian Mountains, Poland. The initial seven PCA components with 90% of the total variability in the original topographic attributes were used for SVM classification. Comparing results with landslide inventory map, the average user's accuracy (UA), producer's accuracy (PA), and overall accuracy (OA) were calculated for two models according to the classification results. Thereby, for the PCA-feature-reduced model UA, PA, and OA were found to be 72%, 76%, and 72%, respectively. Similarly, UA, PA, and OA in the non-reduced original topographic model, was 74%, 77% and 74%, respectively. Using the initial seven PCA components instead of the twenty original topographic attributes does not significantly change identification accuracy but reduce computational time.

  13. Quantitative Susceptibility Mapping in Parkinson's Disease.

    PubMed

    Langkammer, Christian; Pirpamer, Lukas; Seiler, Stephan; Deistung, Andreas; Schweser, Ferdinand; Franthal, Sebastian; Homayoon, Nina; Katschnig-Winter, Petra; Koegl-Wallner, Mariella; Pendl, Tamara; Stoegerer, Eva Maria; Wenzel, Karoline; Fazekas, Franz; Ropele, Stefan; Reichenbach, Jürgen Rainer; Schmidt, Reinhold; Schwingenschuh, Petra

    2016-01-01

    Quantitative susceptibility mapping (QSM) and R2* relaxation rate mapping have demonstrated increased iron deposition in the substantia nigra of patients with idiopathic Parkinson's disease (PD). However, the findings in other subcortical deep gray matter nuclei are converse and the sensitivity of QSM and R2* for morphological changes and their relation to clinical measures of disease severity has so far been investigated only sparsely. The local ethics committee approved this study and all subjects gave written informed consent. 66 patients with idiopathic Parkinson's disease and 58 control subjects underwent quantitative MRI at 3T. Susceptibility and R2* maps were reconstructed from a spoiled multi-echo 3D gradient echo sequence. Mean susceptibilities and R2* rates were measured in subcortical deep gray matter nuclei and compared between patients with PD and controls as well as related to clinical variables. Compared to control subjects, patients with PD had increased R2* values in the substantia nigra. QSM also showed higher susceptibilities in patients with PD in substantia nigra, in the nucleus ruber, thalamus, and globus pallidus. Magnetic susceptibility of several of these structures was correlated with the levodopa-equivalent daily dose (LEDD) and clinical markers of motor and non-motor disease severity (total MDS-UPDRS, MDS-UPDRS-I and II). Disease severity as assessed by the Hoehn & Yahr scale was correlated with magnetic susceptibility in the substantia nigra. The established finding of higher R2* rates in the substantia nigra was extended by QSM showing superior sensitivity for PD-related tissue changes in nigrostriatal dopaminergic pathways. QSM additionally reflected the levodopa-dosage and disease severity. These results suggest a more widespread pathologic involvement and QSM as a novel means for its investigation, more sensitive than current MRI techniques.

  14. The variability of root cohesion as an influence on shallow landslide susceptibility in the Oregon Coast Range

    USGS Publications Warehouse

    Schmidt, K.M.; Roering, J.J.; Stock, J.D.; Dietrich, W.E.; Montgomery, D.R.; Schaub, T.

    2001-01-01

    Decades of quantitative measurement indicate that roots can mechanically reinforce shallow soils in forested landscapes. Forests, however, have variations in vegetation species and age which can dominate the local stability of landslide-initiation sites. To assess the influence of this variability on root cohesion we examined scarps of landslides triggered during large storms in February and November of 1996 in the Oregon Coast Range and hand-dug soil pits on stable ground. At 41 sites we estimated the cohesive reinforcement to soil due to roots by determining the tensile strength, species, depth, orientation, relative health, and the density of roots ???1 mm in diameter within a measured soil area. We found that median lateral root cohesion ranges from 6.8-23.2 kPa in industrial forests with significant understory and deciduous vegetation to 25.6-94.3 kPa in natural forests dominated by coniferous vegetation. Lateral root cohesion in clearcuts is uniformly ???10 kPa. Some 100-year-old industrial forests have species compositions, lateral root cohesion, and root diameters that more closely resemble 10-year-old clearcuts than natural forests. As such, the influence of root cohesion variability on landslide susceptibility cannot be determined solely from broad age classifications or extrapolated from the presence of one species of vegetation. Furthermore, the anthropogenic disturbance legacy modifies root cohesion for at least a century and should be considered when comparing contemporary landslide rates from industrial forests with geologic background rates.

  15. Analysis of Submarine Landslides and Canyons along the U.S. Atlantic Margin Using Extended Continental Shelf Mapping Data

    NASA Astrophysics Data System (ADS)

    Chaytor, J. D.; Brothers, D. S.; Ten Brink, U. S.; Hoy, S. K.; Baxter, C.; Andrews, B.

    2013-12-01

    U.S. Geological Survey (USGS) studies of the U.S. Atlantic continental slope and rise aim to understand the: 1) the role of submarine landslides in tsunami generation, and 2) the linkages between margin morphology and sedimentary processes, particularly in and around submarine canyon systems. Data from U.S. Extended Continental Shelf (ECS) and numerous subsequent mapping surveys have facilitated the identification and characterization of submarine landslides and related features in fine detail over an unprecedented spatial extent. Ongoing analysis of USGS collected piston cores, sub-bottom and multichannel seismic (MCS) reflection profiles, and an extensive suite of legacy MCS data from two landslides, the Southern New England landslide zone and the Currituck Landslide, suggest that the most recent major landslide events are pre-Holocene, but that failures were complex and most likely multi-phase, at times resulting in extensive overlapping debris deposits. Piston core records plus visual observations of the seafloor from recent TowCam deployments and NOAA Ship Okeanos Explorer ROV dives reveal ongoing development of colluvial wedge-style debris aprons at the base of scarps within these landslides, showing that these regions continue to evolve long after the initial failure events. Multibeam bathymetry data and MCS profiles along the upper slope reveal evidence for vertical fluid migration and possible seabed gas expulsion. These observations underscore the need to reevaluate the sources of pore fluid overpressure in slope sediments and their role in landslide generation. ECS and more recent multibeam mapping have provided the opportunity to investigate the full extent of submarine canyon morphology and evolution from Cape Hatteras up to the US-Canadian EEZ, which has led to better understanding of the important role of antecedent margin physiography on their development. Six submarine canyon systems along the margin (Veatch, Hydrographer, Hudson, Wilmington

  16. Rapid mapping of landslide disaster using UAV- photogrammetry

    NASA Astrophysics Data System (ADS)

    Cahyono, A. B.; Zayd, R. A.

    2018-03-01

    Unmanned Aerial Vehicle (UAV) systems offered many advantages in several mapping applications such as slope mapping, geohazard studies, etc. This study utilizes UAV system for landslide disaster occurred in Jombang Regency, East Java. This study concentrates on type of rotor-wing UAV, that is because rotor wing units are stable and able to capture images easily. Aerial photograph were acquired in the form of strips which followed the procedure of acquiring aerial photograph where taken 60 photos. Secondary data of ground control points using GPS Geodetic and check points established using Total Station technique was used. The digital camera was calibrated using close range photogrammetric software and the recovered camera calibration parameters were then used in the processing of digital images. All the aerial photographs were processed using digital photogrammetric software and the output in the form of orthophoto was produced. The final result shows a 1: 1500 scale orthophoto map from the data processing with SfM algorithm with GSD accuracy of 3.45 cm. And the calculated volume of contour line delineation of 10527.03 m3. The result is significantly different from the result of terrestrial methode equal to 964.67 m3 or 8.4% of the difference of both.

  17. Multiple Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California

    USGS Publications Warehouse

    Pike, Richard J.; Graymer, Russell W.

    2008-01-01

    With the exception of Los Angeles, perhaps no urban area in the United States is more at risk from landsliding, triggered by either precipitation or earthquake, than the San Francisco Bay region of northern California. By January each year, seasonal winter storms usually bring moisture levels of San Francisco Bay region hillsides to the point of saturation, after which additional heavy rainfall may induce landslides of various types and levels of severity. In addition, movement at any time along one of several active faults in the area may generate an earthquake large enough to trigger landslides. The danger to life and property rises each year as local populations continue to expand and more hillsides are graded for development of residential housing and its supporting infrastructure. The chapters in the text consist of: *Introduction by Russell W. Graymer *Chapter 1 Rainfall Thresholds for Landslide Activity, San Francisco Bay Region, Northern California by Raymond C. Wilson *Chapter 2 Susceptibility to Deep-Seated Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike and Steven Sobieszczyk *Chapter 3 Susceptibility to Shallow Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Kevin M. Schmidt and Steven Sobieszczyk *Chapter 4 Landslide Hazard Modeled for the Cities of Oakland, Piedmont, and Berkeley, Northern California, from a M=7.1 Scenario Earthquake on the Hayward Fault Zone by Scott B. Miles and David K. Keefer *Chapter 5 Synthesis of Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike The plates consist of: *Plate 1 Susceptibility to Deep-Seated Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike, Russell W. Graymer, Sebastian Roberts, Naomi B. Kalman, and Steven Sobieszczyk *Plate 2 Susceptibility to Shallow Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Kevin M. Schmidt and Steven

  18. Geospatial Approach on Landslide Hazard Zonation Mapping Using Multicriteria Decision Analysis: A Study on Coonoor and Ooty, Part of Kallar Watershed, The Nilgiris, Tamil Nadu

    NASA Astrophysics Data System (ADS)

    Rahamana, S. Abdul; Aruchamy, S.; Jegankumar, R.

    2014-12-01

    Landslides are one of the critical natural phenomena that frequently lead to serious problems in hilly area, resulting to loss of human life and property, as well as causing severe damage to natural resources. The local geology with high degree of slope coupled with high intensity of rainfall along with unplanned human activities of the study area causes many landslides in this region. The present study area is more attracted by tourist throughout the year, so this area must be considered for preventive measures. Geospatial based Multicriteria decision analysis (MCDA) technique is increasingly used for landslide vulnerability and hazard zonation mapping. It enables the integration of different data layers with different levels of uncertainty. In this present study, it is used analytic hierarchy process (AHP) method to prepare landslide hazard zones of the Coonoor and Ooty, part of Kallar watershed, The Nilgiris, Tamil Nadu. The study was carried out using remote sensing data, field surveys and geographic information system (GIS) tools. The ten factors that influence landslide occurrence, such as elevation, slope aspect, slope angle, drainage density, lineament density, soil, precipitation, land use/land cover (LULC), distance from road and NDVI were considered. These factors layers were extracted from the various related spatial data's. These factors were evaluated, and then, the individual factor weight and class weight were assigned to each of the related factors. The Landslide Hazard Zone Index (LHZI) was calculated using Multicriteria decision analysis (MCDA) the technique based on the assigned weight and the rating is given by the Analytical Hierarchy Process (AHP) method. The final cumulative map of the study area was categorized into four hazard zones and classified as zone I to IV. There are 3.56% of the area comes under the hazard zone IV fallowed by 48.19% of the area comes under zone III, 43.63 % of the area in zone II and 4.61% of the area comes hazard

  19. Analysis of the effects of geological and geomorphological factors on earthquake triggered landslides using artificial neural networks (ANN)

    NASA Astrophysics Data System (ADS)

    Kawabata, D.; Bandibas, J.

    2007-12-01

    The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic and geologic features, rock types and vegetative cover are important base factors of landslide occurrence. However, determining the relationship between these factors and landslide occurrence is very difficult using conventional mathematical analysis. The use of an advanced computing technique for this kind of analysis is very important. Artificial neural network (ANN) has recently been included in the list of analytical tools for a wide range of applications in the natural sciences research fields. One of the advantages of using ANN for pattern recognition is that it can handle data at any measurement scale ranging from nominal, ordinal to linear and ratio, and any form of data distribution (Wang et al., 1995). In addition, it can easily handle qualitative variables making it widely used in integrated analysis of spatial data from multiple sources for predicting and classification. This study focuses on the definition of the relationship between geological factors and landslide occurrence using artificial neural networks. The study also focuses on the effect of the DTMs (e.g. ASTER DTM, ALSM, digitized from paper map and digital photogrammetric measurement data). The main aim of the study is to generate landslide susceptibility index map using the defined relationship using ANN. Landslide data in the Chuetsu region were used in this research. The 2004 earthquake triggered many landslides in the region. The initial results of the study showed that ANN is more accurate in defining the relationship between geological and geomorphological factors and landslide occurrence. It also determined the best combination of geological and geomorphological factors that is directly related to landslide occurrence.

  20. Quantitative susceptibility mapping of human brain at 3T: a multisite reproducibility study.

    PubMed

    Lin, P-Y; Chao, T-C; Wu, M-L

    2015-03-01

    Quantitative susceptibility mapping of the human brain has demonstrated strong potential in examining iron deposition, which may help in investigating possible brain pathology. This study assesses the reproducibility of quantitative susceptibility mapping across different imaging sites. In this study, the susceptibility values of 5 regions of interest in the human brain were measured on 9 healthy subjects following calibration by using phantom experiments. Each of the subjects was imaged 5 times on 1 scanner with the same procedure repeated on 3 different 3T systems so that both within-site and cross-site quantitative susceptibility mapping precision levels could be assessed. Two quantitative susceptibility mapping algorithms, similar in principle, one by using iterative regularization (iterative quantitative susceptibility mapping) and the other with analytic optimal solutions (deterministic quantitative susceptibility mapping), were implemented, and their performances were compared. Results show that while deterministic quantitative susceptibility mapping had nearly 700 times faster computation speed, residual streaking artifacts seem to be more prominent compared with iterative quantitative susceptibility mapping. With quantitative susceptibility mapping, the putamen, globus pallidus, and caudate nucleus showed smaller imprecision on the order of 0.005 ppm, whereas the red nucleus and substantia nigra, closer to the skull base, had a somewhat larger imprecision of approximately 0.01 ppm. Cross-site errors were not significantly larger than within-site errors. Possible sources of estimation errors are discussed. The reproducibility of quantitative susceptibility mapping in the human brain in vivo is regionally dependent, and the precision levels achieved with quantitative susceptibility mapping should allow longitudinal and multisite studies such as aging-related changes in brain tissue magnetic susceptibility. © 2015 by American Journal of Neuroradiology.

  1. Subsurface geological modeling using GIS and remote sensing data: a case study from Platanos landslide, Western Greece

    NASA Astrophysics Data System (ADS)

    Kavoura, K.; Kordouli, M.; Nikolakopoulos, K.; Elias, P.; Sykioti, O.; Tsagaris, V.; Drakatos, G.; Rondoyanni, Th.; Tsiambaos, G.; Sabatakakis, N.; Anastasopoulos, V.

    2014-08-01

    Landslide phenomena constitute a major geological hazard in Greece and especially in the western part of the country as a result of anthropogenic activities, growing urbanization and uncontrolled land - use. More frequent triggering events and increased susceptibility of the ground surface to instabilities as consequence of climate change impacts (continued deforestation mainly due to the devastating forest wildfires and extreme meteorological events) have also increased the landslide risk. The studied landslide occurrence named "Platanos" has been selected within the framework of "Landslide Vulnerability Model - LAVMO" project that aims at creating a persistently updated electronic platform assessing risks related with landslides. It is a coastal area situated between Korinthos and Patras at the northwestern part of the elongated graben of the Corinth Gulf. The paper presents the combined use of geological-geotechnical insitu data, remote sensing data and GIS techniques for the evaluation of a subsurface geological model. High accuracy Digital Surface Model (DSM), airphotos mosaic and satellite data, with a spatial resolution of 0.5m were used for an othophoto base map compilation of the study area. Geological - geotechnical data obtained from exploratory boreholes were digitized and implemented in a GIS platform with engineering geological maps for a three - dimensional subsurface model evaluation. This model is provided for being combined with inclinometer measurements for sliding surface location through the instability zone.

  2. Undersea landslides: Extent and significance in the Pacific Ocean, an update

    USGS Publications Warehouse

    Lee, H.J.

    2005-01-01

    Submarine landslides are known to occur disproportionately in a limited number of environments including fjords, deltas, canyons, volcanic islands and the open continental slope. An evaluation of the progress that has been made in understanding Pacific Ocean submarine landslides over the last 15 years shows that mapping technologies have improved greatly, allowing a better interpretation of landslide features. Some features previously identified as landslides are being reinterpreted by some as sediment waves. Previously underappreciated environments for landslides such as deep-sea trenches are being recognized and lava deltas are being found to be landslide prone. Landslides are also being recognized much more commonly as a potential source of tsunamis. Landslides that have produced tsunamis in the past are being mapped and in some cases modeled. The flow characteristics of turbidity currents produced by landslides in canyon heads have recently been monitored and the source of these failures has been identified using repeated multibeam mapping. Finally, some landslide deposits are being dated as part of assessing risk to coastal cities from landslide-tsunamis. European Geosciences Union ?? 2005 Author(s). This work is licensed under a Creative Commons License.

  3. Active machine learning for rapid landslide inventory mapping with VHR satellite images (Invited)

    NASA Astrophysics Data System (ADS)

    Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

    2013-12-01

    VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern

  4. Investigating landslides caused by earthquakes - A historical review

    USGS Publications Warehouse

    Keefer, D.K.

    2002-01-01

    Post-earthquake field investigations of landslide occurrence have provided a basis for understanding, evaluating, and mapping the hazard and risk associated with earthquake-induced landslides. This paper traces the historical development of knowledge derived from these investigations. Before 1783, historical accounts of the occurrence of landslides in earthquake are typically so incomplete and vague that conclusions based on these accounts are of limited usefulness. For example, the number of landslides triggered by a given event is almost always greatly underestimated. The first formal, scientific post-earthquake investigation that included systematic documentation of the landslides was undertaken in the Calabria region of Italy after the 1783 earthquake swarm. From then until the mid-twentieth century, the best information on earthquake-induced landslides came from a succession of post-earthquake investigations largely carried out by formal commissions that undertook extensive ground-based field studies. Beginning in the mid-twentieth century, when the use of aerial photography became widespread, comprehensive inventories of landslide occurrence have been made for several earthquakes in the United States, Peru, Guatemala, Italy, El Salvador, Japan, and Taiwan. Techniques have also been developed for performing "retrospective" analyses years or decades after an earthquake that attempt to reconstruct the distribution of landslides triggered by the event. The additional use of Geographic Information System (GIS) processing and digital mapping since about 1989 has greatly facilitated the level of analysis that can applied to mapped distributions of landslides. Beginning in 1984, synthesis of worldwide and national data on earthquake-induced landslides have defined their general characteristics and relations between their occurrence and various geologic and seismic parameters. However, the number of comprehensive post-earthquake studies of landslides is still

  5. Investigating Landslides Caused by Earthquakes A Historical Review

    NASA Astrophysics Data System (ADS)

    Keefer, David K.

    Post-earthquake field investigations of landslide occurrence have provided a basis for understanding, evaluating, and mapping the hazard and risk associated withearthquake-induced landslides. This paper traces thehistorical development of knowledge derived from these investigations. Before 1783, historical accounts of the occurrence of landslides in earthquakes are typically so incomplete and vague that conclusions based on these accounts are of limited usefulness. For example, the number of landslides triggered by a given event is almost always greatly underestimated. The first formal, scientific post-earthquake investigation that included systematic documentation of the landslides was undertaken in the Calabria region of Italy after the 1783 earthquake swarm. From then until the mid-twentieth century, the best information on earthquake-induced landslides came from a succession ofpost-earthquake investigations largely carried out by formal commissions that undertook extensive ground-based field studies. Beginning in the mid-twentieth century, when the use of aerial photography became widespread, comprehensive inventories of landslide occurrence have been made for several earthquakes in the United States, Peru, Guatemala, Italy, El Salvador, Japan, and Taiwan. Techniques have also been developed for performing ``retrospective'' analyses years or decades after an earthquake that attempt to reconstruct the distribution of landslides triggered by the event. The additional use of Geographic Information System (GIS) processing and digital mapping since about 1989 has greatly facilitated the level of analysis that can applied to mapped distributions of landslides. Beginning in 1984, syntheses of worldwide and national data on earthquake-induced landslides have defined their general characteristics and relations between their occurrence and various geologic and seismic parameters. However, the number of comprehensive post-earthquake studies of landslides is still

  6. Large landslides associated with a diapiric fold in Canelles Reservoir (Spanish Pyrenees): Detailed geological-geomorphological mapping, trenching and electrical resistivity imaging

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Francisco; Linares, Rogelio; Roqué, Carles; Zarroca, Mario; Carbonel, Domingo; Rosell, Joan; Gutiérrez, Mateo

    2015-07-01

    Detailed geomorphological-geological mapping in Canelles Reservoir, the Spanish Pyrenees, reveals the presence of several large landslides overlooked in previous cartographic works. One of the slope movements, designated as the Canelles landslide, corresponds to a 40 × 106 m3 translational landslide reactivated in 2006 by a severe decline in the reservoir water level. The geomorphic features mapped in the upper part of the Canelles landslide, including surface ruptures corroborated by electrical resistivity imaging and trenching, indicate multiple displacement episodes previous to the 2006 human-induced event. Consistently, the stratigraphic and structural relationships observed in a trench record at least two displacement events older and larger in magnitude than the 2006 reactivation. The oldest recorded event occurred in the 6th to 7th Centuries and the second in 1262-1679 yr AD. This latter episode might be correlative to the 1373 Ribagorza earthquake (Mw 6.2), which caused the reactivation of a landslide and the consequent destruction of a village in the adjacent valley. The available data indicate that over more than one millennium the kinematics of the landslide has been characterised by discrete small-displacement episodes. These data, together with the available literature on rapid rockslides, do not concur with the acceleration predicted by modelling in a previous investigation, which foresees a speed of 16 m s- 1 despite the low average dip of the sliding surface (9-10°). This case study illustrates that the trenching technique may provide valuable practical information on the past behaviour of landslides, covering a much broader time span than instrumental and historical records.

  7. A nation-wide system for landslide mapping and risk management in Italy: The second Not-ordinary Plan of Environmental Remote Sensing

    NASA Astrophysics Data System (ADS)

    Di Martire, D.; Paci, M.; Confuorto, P.; Costabile, S.; Guastaferro, F.; Verta, A.; Calcaterra, D.

    2017-12-01

    Landslides are frequent events that may cause human casualties and injuries as well as damage to urban and man-made structures, with extensive loss of economic resources. For this reason, landslide mapping is a primary tool for hazard and risk assessment. Italian Ministry of Environment, thanks to great availability and functionality of Synthetic Aperture Radar (SAR) data promoted the Not-ordinary Plan of Environmental Remote Sensing (Piano Straordinario di Telerilevamento Ambientale, PST-A in Italian) in 2008, as to constitute a national database of active or potential instability phenomena affecting the Italian territory, based on the exploitation of interferometric products (ERS and ENVISAT). In this paper, the PST-A-3 is described. A procedure based on the integration of engineering-geological approaches and SAR interferometry data belonging to COSMO-SkyMed constellation (100 frames 40 × 40 km) has been here implemented over 7,400 km2 of the Italian territory. First, landslides have been mapped by field geologists, defining type and state of activity. Simultaneously to field surveys, remote sensing data have been analyzed as to detect areas with considerable displacement registered by the satellite. Both products have been overlaid, also quantifying the coincidence between the events reported according to the two detection methodologies and subtracting those landslide not recordable by the satellite, finally obtaining an updated landslide inventory map with 4,522 newly detected phenomena. Therefore, PST-A-3 proves to be a valuable system for local authorities, in order to provide a contribution to risk management but also for the forecasting of landslide events, as testified by two case studies selected. Thanks to the PST-A experience, the use of such strategy to other countries could represent a valid contribution to land management at worldwide scale.

  8. Semi-automated extraction of landslides in Taiwan based on SPOT imagery and DEMs

    NASA Astrophysics Data System (ADS)

    Eisank, Clemens; Hölbling, Daniel; Friedl, Barbara; Chen, Yi-Chin; Chang, Kang-Tsung

    2014-05-01

    The vast availability and improved quality of optical satellite data and digital elevation models (DEMs), as well as the need for complete and up-to-date landslide inventories at various spatial scales have fostered the development of semi-automated landslide recognition systems. Among the tested approaches for designing such systems, object-based image analysis (OBIA) stepped out to be a highly promising methodology. OBIA offers a flexible, spatially enabled framework for effective landslide mapping. Most object-based landslide mapping systems, however, have been tailored to specific, mainly small-scale study areas or even to single landslides only. Even though reported mapping accuracies tend to be higher than for pixel-based approaches, accuracy values are still relatively low and depend on the particular study. There is still room to improve the applicability and objectivity of object-based landslide mapping systems. The presented study aims at developing a knowledge-based landslide mapping system implemented in an OBIA environment, i.e. Trimble eCognition. In comparison to previous knowledge-based approaches, the classification of segmentation-derived multi-scale image objects relies on digital landslide signatures. These signatures hold the common operational knowledge on digital landslide mapping, as reported by 25 Taiwanese landslide experts during personal semi-structured interviews. Specifically, the signatures include information on commonly used data layers, spectral and spatial features, and feature thresholds. The signatures guide the selection and implementation of mapping rules that were finally encoded in Cognition Network Language (CNL). Multi-scale image segmentation is optimized by using the improved Estimation of Scale Parameter (ESP) tool. The approach described above is developed and tested for mapping landslides in a sub-region of the Baichi catchment in Northern Taiwan based on SPOT imagery and a high-resolution DEM. An object

  9. Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition

    PubMed Central

    Li, Wei; Wu, Bing; Liu, Chunlei

    2011-01-01

    Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter microarchitectures. PMID:21224002

  10. Real-time landslide warning during heavy rainfall

    USGS Publications Warehouse

    Keefer, D.K.; Wilson, R.C.; Mark, R.K.; Brabb, E.E.; Brown, W. M.; Ellen, S.D.; Harp, E.L.; Wieczorek, G.F.; Alger, C.S.; Zatkin, R.S.

    1987-01-01

    A real-time system for issuing warnings of landslides during major storms is being developed for the San Francisco Bay region, California. The system is based on empirical and theoretical relations between rainfall and landslide initiation, geologic determination of areas susceptible to landslides, real-time monitoring of a regional network of telemetering rain gages, and National Weather Service precipitation forecasts. This system was used to issue warnings during the storms of 12 to 21 February 1986, which produced 800 millimeters of rainfall in the region. Although analysis after the storms suggests that modifications and additional developments are needed, the system successfully predicted the times of major landslide events. It could be used as a prototype for systems in other landslide-prone regions.

  11. [Fine mapping of complex disease susceptibility loci].

    PubMed

    Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

    2014-01-01

    Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

  12. Effects of white matter microstructure on phase and susceptibility maps.

    PubMed

    Wharton, Samuel; Bowtell, Richard

    2015-03-01

    To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contributions. © 2014 Wiley Periodicals, Inc.

  13. Assessing population exposure for landslide risk analysis using dasymetric cartography

    NASA Astrophysics Data System (ADS)

    Garcia, Ricardo A. C.; Oliveira, Sergio C.; Zezere, Jose L.

    2015-04-01

    Exposed Population is a major topic that needs to be taken into account in a full landslide risk analysis. Usually, risk analysis is based on an accounting of inhabitants number or inhabitants density, applied over statistical or administrative terrain units, such as NUTS or parishes. However, this kind of approach may skew the obtained results underestimating the importance of population, mainly in territorial units with predominance of rural occupation. Furthermore, the landslide susceptibility scores calculated for each terrain unit are frequently more detailed and accurate than the location of the exposed population inside each territorial unit based on Census data. These drawbacks are not the ideal setting when landslide risk analysis is performed for urban management and emergency planning. Dasymetric cartography, which uses a parameter or set of parameters to restrict the spatial distribution of a particular phenomenon, is a methodology that may help to enhance the resolution of Census data and therefore to give a more realistic representation of the population distribution. Therefore, this work aims to map and to compare the population distribution based on a traditional approach (population per administrative terrain units) and based on dasymetric cartography (population by building). The study is developed in the Region North of Lisbon using 2011 population data and following three main steps: i) the landslide susceptibility assessment based on statistical models independently validated; ii) the evaluation of population distribution (absolute and density) for different administrative territorial units (Parishes and BGRI - the basic statistical unit in the Portuguese Census); and iii) the dasymetric population's cartography based on building areal weighting. Preliminary results show that in sparsely populated administrative units, population density differs more than two times depending on the application of the traditional approach or the dasymetric

  14. The impact of landslides on urban areas and infrastructure in Italy

    NASA Astrophysics Data System (ADS)

    Trigila, Alessandro; Spizzichino, Daniele; Iadanza, Carla

    2010-05-01

    Landslide risk in Italy is particularly high since in addition to the geological, geomorphological, seismic and structural settings which render it susceptible to frequent and widespread landslide phenomena, the Italian territory is also densely populated and highly urbanized. In terms of landslide hazard, 485,004 landslides occurred between A.D. 1116 and 2006 within Italy, with a landslide area of 20,721 km2 equal to 6.9% of the national territory. 5,708 municipal districts are affected by landslides (70.5% of the total), of which 2,940 with extremely high levels of criticality due to landslides affecting urban centres. This data emerges from the IFFI Project (Italian Landslide Inventory) which, set up by ISPRA - Institute for Environmental Protection and Research/Geological Survey of Italy and the Regions and self-governing Provinces, identifies landslide phenomena across Italy in accordance with standardized methods of data collection, recording and mapping. With regard to exposure and vulnerability, urban areas in Italy account for 17,929 km2, equal to 5.9% of the national territory. In the past 50 years, urban areas in Italy underwent a dramatic increase, whose surface has more than doubled. Often building areas did not benefit from any form of proper land use planning and management or detailed landslide hazard assessment. Moreover unauthorized building has reached levels as high as 60% in regions of Southern Italy. This study assesses the incidence of landslide phenomena and their impacts within urban areas of Italian provincial capitals in terms of number of landslides, surface area and type of movement. The people exposed to landslide risk at national level and critical points along highways, railways and road network has been also estimated. Landslides have been classified in two main categories: rapid and slow movements. The rapid phenomena are strictly correlated to the people safety, while the slow ones concern mainly losses and usability of buildings

  15. Landslide vulnerability criteria: a case study from Umbria, central Italy.

    PubMed

    Galli, Mirco; Guzzetti, Fausto

    2007-10-01

    Little is known about the vulnerability to landslides, despite landslides causing frequent and widespread damage to the population and the built-up environment in many areas of the world. Lack of information about vulnerability to landslides limits our ability to determine landslide risk. This paper provides information on the vulnerability of buildings and roads to landslides in Umbria, central Italy. Information on 103 landslides of the slide and slide-earth flow types that have resulted in damage to buildings and roads at 90 sites in Umbria is used to establish dependencies between the area of the landslide and the vulnerability to landslides. The dependencies obtained are applied in the hills surrounding the town of Collazzone, in central Umbria, an area for which a detailed landslide inventory map is available. By exploiting the landslide inventory and the established vulnerability curves, the geographical distribution of the vulnerability to landslides is mapped and statistics of the expected damage are calculated. Reliability and limits of the vulnerability thresholds and of the obtained vulnerability assessment are discussed.

  16. Investigating Earthquake-induced Landslides­a Historical Review

    NASA Astrophysics Data System (ADS)

    Keefer, D. K.; Geological Survey, Us; Park, Menlo; Usa, Ca

    Although earthquake-induced landslides have been described in documents for more than 3700 years, accounts from earthquakes before the late eighteenth century are incomplete concerning landslide numbers and vague concerning landslide character- istics. They are thus typically misleading concerning the true abundance of landslides and range of landslide characteristics. Beginning with studies of the 1783 Calabria, Italy earthquake, more complete and precise data concerning the occurrence of land- slides in earthquakes have become available. The historical development of knowl- edge concerning landslides triggered by earthquakes can be divided into several peri- ods. The first period, from 1783 until the first application of aerial photography, was characterized by ground-based studies of earthquake effects, typically carried out by formal scientific commissions. These formal studies typically identified a large, but not necessarily comprehensive, sampling of localities where landslides had occurred. In some, but not all cases, landslide characteristics were also described in enough de- tail that the general range of landslide characteristics could begin to be determined. More recently, some nineteenth to mid-twentieth century earthquakes have been stud- ied using retrospective analyses, in which the landslide occurrences associated with the event are inferred years to decades later, using contemporary accounts, mapping from aerial photographs, statistical studies, and (or) geotechnical analyses. The first use of aerial photographs to map earthquake effects immediately after the event prob- ably occurred in 1948. Since that time, the use of aerial photography has greatly facil- itated the compilation of post-earthquake landslide inventories, although because of the limitations of aerial photography, ground-based field studies continue to be cru- cial in preparing accurate and comprehensive landslide maps. Beginning with a small California earthquake in 1957

  17. Integrating the effects of forest cover on slope stability in a deterministic landslide susceptibility model (TRIGRS 2.0)

    NASA Astrophysics Data System (ADS)

    Zieher, T.; Rutzinger, M.; Bremer, M.; Meissl, G.; Geitner, C.

    2014-12-01

    The potentially stabilizing effects of forest cover in respect of slope stability have been the subject of many studies in the recent past. Hence, the effects of trees are also considered in many deterministic landslide susceptibility models. TRIGRS 2.0 (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability; USGS) is a dynamic, physically-based model designed to estimate shallow landslide susceptibility in space and time. In the original version the effects of forest cover are not considered. As for further studies in Vorarlberg (Austria) TRIGRS 2.0 is intended to be applied in selected catchments that are densely forested, the effects of trees on slope stability were implemented in the model. Besides hydrological impacts such as interception or transpiration by tree canopies and stems, root cohesion directly influences the stability of slopes especially in case of shallow landslides while the additional weight superimposed by trees is of minor relevance. Detailed data on tree positions and further attributes such as tree height and diameter at breast height were derived throughout the study area (52 km²) from high-resolution airborne laser scanning data. Different scenarios were computed for spruce (Picea abies) in the study area. Root cohesion was estimated area-wide based on published correlations between root reinforcement and distance to tree stems depending on the stem diameter at breast height. In order to account for decreasing root cohesion with depth an exponential distribution was assumed and implemented in the model. Preliminary modelling results show that forest cover can have positive effects on slope stability yet strongly depending on tree age and stand structure. This work has been conducted within C3S-ISLS, which is funded by the Austrian Climate and Energy Fund, 5th ACRP Program.

  18. Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in the Brain

    PubMed Central

    Liu, Chunlei; Li, Wei; Tong, Karen A.; Yeom, Kristen W.; Kuzminski, Samuel

    2015-01-01

    Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique that enhances image contrast by using the susceptibility differences between tissues. It is created by combining both magnitude and phase in the gradient echo data. SWI is sensitive to both paramagnetic and diamagnetic substances which generate different phase shift in MRI data. SWI images can be displayed as a minimum intensity projection that provides high resolution delineation of the cerebral venous architecture, a feature that is not available in other MRI techniques. As such, SWI has been widely applied to diagnose various venous abnormalities. SWI is especially sensitive to deoxygenated blood and intracranial mineral deposition and, for that reason, has been applied to image various pathologies including intracranial hemorrhage, traumatic brain injury, stroke, neoplasm, and multiple sclerosis. SWI, however, does not provide quantitative measures of magnetic susceptibility. This limitation is currently being addressed with the development of quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI). While QSM treats susceptibility as isotropic, STI treats susceptibility as generally anisotropic characterized by a tensor quantity. This article reviews the basic principles of SWI, its clinical and research applications, the mechanisms governing brain susceptibility properties, and its practical implementation, with a focus on brain imaging. PMID:25270052

  19. Effects of White Matter Microstructure on Phase and Susceptibility Maps

    PubMed Central

    Wharton, Samuel; Bowtell, Richard

    2015-01-01

    Purpose To investigate the effects on quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI) of the frequency variation produced by the microstructure of white matter (WM). Methods The frequency offsets in a WM tissue sample that are not explained by the effect of bulk isotropic or anisotropic magnetic susceptibility, but rather result from the local microstructure, were characterized for the first time. QSM and STI were then applied to simulated frequency maps that were calculated using a digitized whole-brain, WM model formed from anatomical and diffusion tensor imaging data acquired from a volunteer. In this model, the magnitudes of the frequency contributions due to anisotropy and microstructure were derived from the results of the tissue experiments. Results The simulations suggest that the frequency contribution of microstructure is much larger than that due to bulk effects of anisotropic magnetic susceptibility. In QSM, the microstructure contribution introduced artificial WM heterogeneity. For the STI processing, the microstructure contribution caused the susceptibility anisotropy to be significantly overestimated. Conclusion Microstructure-related phase offsets in WM yield artifacts in the calculated susceptibility maps. If susceptibility mapping is to become a robust MRI technique, further research should be carried out to reduce the confounding effects of microstructure-related frequency contributions. Magn Reson Med 73:1258–1269, 2015. © 2014 Wiley Periodicals, Inc. PMID:24619643

  20. Landslides Induced by 2015 Gorkha Earthquake and Their Continuous Evolution Post 2015 and 2016-Monsoon

    NASA Astrophysics Data System (ADS)

    Spear, B.; Haritashya, U. K.; Kargel, J. S.

    2017-12-01

    Gorkha Nepal has been a hot bed of landslide activity since the 7.8 magnitude earthquake that occurred on April 25th 2015. Even though previous studies have mapped and analyzed the landslides that were directly related to the earthquake, this research maps and analyzes the landslides that occurred during monsoon or after monsoon season in 2015 and 2016. Specifically, our objectives included monitoring post-earthquake landslide evolution and reactivation. We also observed landslides which occurred in the steep side slopes of various small rivers and threatened to block the flow of river. Consequently, we used Landsat, Sentinel, ASTER and images available at Google Earth Engine to locate, map, and analyze these landslides. Our preliminary result indicates 5,270 landslides, however 957 of these landslides occurred significantly after the earthquake. Of the 957 landslides, 508 of them occurred during the monsoon season of 2015 and 48 in the 2016 monsoon season. As well as locating and mapping these landslides, we were able to identify that there were 22 landslides blocking rivers and 24 were reactivated. Our result and landslide density maps clearly identifies zones that are prone to landslides. For example, the steepest areas, such as the Helambu or Langtang region, have a very high concentration of landslides since the earthquake. Furthermore, landslides with the largest area were often nearby each other in very steep regions. This research can be used to determine which areas in the Gorkha Nepal region are safe to use and which areas are high risk.

  1. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis

    NASA Astrophysics Data System (ADS)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  2. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    PubMed

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  3. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    PubMed Central

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  4. A GRASS GIS Semi-Stochastic Model for Evaluating the Probability of Landslides Impacting Road Networks in Collazzone, Central Italy

    NASA Astrophysics Data System (ADS)

    Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.

    2013-04-01

    During a landslide triggering event, the tens to thousands of landslides resulting from the trigger (e.g., earthquake, heavy rainfall) may block a number of sections of the road network, posing a risk to rescue efforts, logistics and accessibility to a region. Here, we present initial results from a semi-stochastic model we are developing to evaluate the probability of landslides intersecting a road network and the network-accessibility implications of this across a region. This was performed in the open source GRASS GIS software, where we took 'model' landslides and dropped them on a 79 km2 test area region in Collazzone, Umbria, Central Italy, with a given road network (major and minor roads, 404 km in length) and already determined landslide susceptibilities. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m.2 The number of landslide areas selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. 79 landslide areas chosen randomly for each iteration. Landslides were then 'dropped' over the region semi-stochastically: (i) random points were generated across the study region; (ii) based on the landslide susceptibility map, points were accepted/rejected based on the probability of a landslide occurring at that location. After a point was accepted, it was assigned a landslide area (AL) and length to width ratio. Landslide intersections with roads were then assessed and indices such as the location, number and size of road blockage recorded. The GRASS-GIS model was performed 1000 times in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event of 1 landslide km-2 over a 79 km2 region with 404 km of road, the number of road blockages

  5. Quantitative Susceptibility Mapping of the Midbrain in Parkinson’s Disease

    PubMed Central

    Du, Guangwei; Liu, Tian; Lewis, Mechelle M.; Kong, Lan; Wang, Yi; Connor, James; Mailman, Richard B.; Huang, Xuemei

    2017-01-01

    Background Parkinson’s disease (PD) is marked pathologically by dopamine neuron loss and iron overload in the substantia nigra pars compacta. Midbrain iron content is reported to be increased in PD based on magnetic resonance imaging (MRI) R2* changes. Because quantitative susceptibility mapping is a novel MRI approach to measure iron content, we compared it with R2* for assessing midbrain changes in PD. Methods Quantitative susceptibility mapping and R2* maps were obtained from 47 PD patients and 47 healthy controls. Midbrain susceptibility and R2* values were analyzed by using both voxel-based and region-of-interest approaches in normalized space, and analyzed along with clinical data, including disease duration, Unified Parkinson’s Disease Rating Scale (UPDRS) I, II, and III sub-scores, and levodopa-equivalent daily dosage. All studies were done while PD patients were “on drug.” Results Compared with controls, PD patients showed significantly increased susceptibility values in both right (cluster size = 106 mm3) and left (164 mm3) midbrain, located ventrolateral to the red nucleus that corresponded to the substantia nigra pars compacta. Susceptibility values in this region were correlated significantly with disease duration, UPDRS II, and levodopa-equivalent daily dosage. Conversely, R2* was increased significantly only in a much smaller region (62 mm3) of the left lateral substantia nigra pars compacta and was not significantly correlated with clinical parameters. Conclusion The use of quantitative susceptibility mapping demonstrated marked nigral changes that correlated with clinical PD status more sensitively than R2*. These data suggest that quantitative susceptibility mapping may be a superior imaging biomarker to R2* for estimating brain iron levels in PD. PMID:26362242

  6. Exploitation of the Intermittent SBAS (ISBAS) algorithm with COSMO-SkyMed data for landslide inventory mapping in north-western Sicily, Italy

    NASA Astrophysics Data System (ADS)

    Novellino, A.; Cigna, F.; Sowter, A.; Ramondini, M.; Calcaterra, D.

    2017-03-01

    A large scale study of landslide processes was undertaken by coupling conventional geomorphological field surveys with aerial photographs along with an advanced Interferometric Synthetic Aperture Radar (InSAR) analysis of ground instability in north-western Sicily. COSMO-SkyMed satellite images for the period between 2008 and 2011 were processed using the Intermittent Small BAseline Subset (ISBAS) technique, recently developed at the Department of Civil Engineering of the University of Nottingham. The use of ISBAS allowed the derivation of ground surface displacements across non-urbanized areas, thus overcoming one of the main limitations of conventional interferometric techniques. ISBAS provides ground motion information not only for urban but also for rural, woodland, grassland and agricultural terrains, which cover > 60% of north-western Sicily, thereby improving by 40 times in some cases, the slope instability investigation capabilities of InSAR methods. ISBAS ground motion data enabled the updating of the landslide inventory for the areas of Piana degli Albanesi and Marineo (over 130 km2), which encompass a number of active, dormant and inactive landslides according to the pre-existing landslide inventory maps produced through aerial photo-interpretation and local field checks. An average of ∼ 7000 ISBAS pixels km- 2 allowed the detection of small displacements in regions difficult to access. In particular, 226 landslides - mainly slides, flows and creep and four badlands were identified, comprising a total area of 25.3 km2. When compared to the previous landslide inventory maps, 84 phenomena were confirmed, 67 new events were detected and 79 previously mapped events were re-assessed, modifying their typology, boundary and/or state of activity. Because the InSAR method used here is designed to measure slow rates of velocity and therefore may not detect fast-moving, events such as falls and topples, the results for Piana degli Albanesi and Marineo demonstrate

  7. A Cascading Storm-Flood-Landslide Guidance System: Development and Application in China

    NASA Astrophysics Data System (ADS)

    Zeng, Ziyue; Tang, Guoqiang; Long, Di; Ma, Meihong; Hong, Yang

    2016-04-01

    than other parts, while the northeast of Yunnan are most susceptible to floods and landslides, which agrees with the distribution of observed flood and landslide events. Moreover, risks for the multi-hazards were classified into four categories. Results show a strong correlation between the distributions of flash flood prone and landslide-prone regions and also highlight the counties with high risk of storms (e.g., Funing and Malipo), flash floods (e.g., Gongshan and Yanjing) and landslides (e.g., Zhaotong and Luxi). Compared to other approaches, the Cascading Storm-Flood-Landslide Guidance System uses a straightforward yet useful indicator-based weighted linear combination method and could be a useful prototype in mapping characteristics of storm-triggered hazards for users at different administrative levels (e.g., catchment, town, county, province and even nation) in China.

  8. Landslide incidence in the North of Portugal: Analysis of a historical landslide database based on press releases and technical reports

    NASA Astrophysics Data System (ADS)

    Pereira, Susana; Zêzere, José Luís; Quaresma, Ivânia Daniela; Bateira, Carlos

    2014-06-01

    This work presents and explores the Northern Portugal Landslide Database (NPLD) for the period 1900-2010. NPLD was compiled from press releases (regional and local newspapers) and technical reports (reports by civil protection authorities and academic works); it includes 628 landslides, corresponding to 5.7 landslides per year on average. Although 50% of landslides occurred in the last 35 years of the series, the temporal distribution of landslides does not show any regular increase with time. The relationship between annual precipitation and landslide occurrence shows that reported landslides tend to be more frequent in wetter years. Moreover, landslides occur mostly in the wettest months of the year (December, January and February), which reflects the importance of rainfall in triggering slope instability. Most landslides cause damage that affects people and/or structures; 69.4% of the landslides in Northern Portugal caused 136 fatalities, 173 injured and left 460 persons homeless. More than half of the total landslides (321 landslides) led to railway or motorway closures and 49 landslides destroyed 126 buildings. The NPLD is compared with a landslide database for the whole of Portugal constructed from a single daily national newspaper covering the same reference period. It will be demonstrated that the regional and local newspapers are more effective than the national newspaper in reporting damaging landslides in the North of Portugal. Like other documentary-based landslide inventories, the NPLD does not accurately report non-damaging landslides. Therefore, NPLD was found unsuitable to validate municipal-scale landslide susceptibility models derived from detailed geomorphology-based landslide inventories.

  9. Riding the storm--landslide danger in the San Francisco Bay Area

    USGS Publications Warehouse

    Adams, Karen

    2007-01-01

    Movie Synopsis: --A catastrophic 1982 rainstorm triggered 18,000 landslides in the Bay Area, claiming 25 lives and causing $66 million in property damage. --The combination of steep slopes, weak rocks, and intense winter storms make Bay Area uplands an ideal setting for landslides. --Landslides include both swift, potentially deadly debris flows and slower, but destructive deepseated slides. --Learn what USGS scientists have discovered about landslide dynamics and which slopes are most susceptible to sliding. --Hear the devastating stories of Bay Area residents affected by landslides and learn to recognize the danger signs.

  10. Landslides and engineering geology of the Seattle, Washington, area

    USGS Publications Warehouse

    Baum, Rex L.; Godt, Jonathan W.; Highland, Lynn M.

    2008-01-01

    This volume brings together case studies and summary papers describing the application of state-of-the-art engineering geologic methods to landslide hazard analysis for the Seattle, Washington, area. An introductory chapter provides a thorough description of the Quaternary and bedrock geology of Seattle. Nine additional chapters review the history of landslide mapping in Seattle, present case studies of individual landslides, describe the results of spatial assessments of landslide hazard, discuss hydrologic controls on landsliding, and outline an early warning system for rainfall-induced landslides.

  11. Landslides caused by the M 7.6 Tecomán, Mexico earthquake of January 21, 2003

    USGS Publications Warehouse

    Keefer, David K.; Wartman, Joseph; Navarro, Ochoa C.; Rodriguez-Marek, Adrian; Wieczorek, Gerald F.

    2006-01-01

    In contrast to the coastal cordilleras, the volcanic rocks to the north were more susceptible to the occurrence of seismically triggered landslides. The greatest number and concentrations of landslides occurred there, and the landslides were larger than those in the coastal cordilleras, even though this volcanic terrain was farther from the earthquake source. Here, stretches of river bluffs several hundred meters long had been stripped of vegetation and surficial material by coalescing landslides, and several days after the main shock, thousands of small rock falls were still occurring each day, indicating an ongoing hazard. The high susceptibility of volcanic materials to earthquake-generated landslides conforms to findings in other recent earthquakes.

  12. Earthquake induced landslide hazard: a multidisciplinary field observatory in the Marmara SUPERSITE

    NASA Astrophysics Data System (ADS)

    Bigarré, Pascal

    2014-05-01

    , that shows an important slump mass facing the Istanbul coastline. A multidisciplinary research program based on pre-existing studies has been designed with objectives and tasks linked to constrain and tackle progressively some challenging issues related to data integration, modeling, monitoring and mapping technologies. Concerning the on-shore area, this program includes the refined analysis of the seismic site response, the permanent multi-parameter ground monitoring of a representative unstable slope as well as the in-depth slope stability analysis based on the stress-strain dynamic numerical modelling approach. Hyperspectral and Dinsar imagery technologies are also deployed to complete inventory and observational information. The development of a dynamic GIS tool featuring capabilities to integrate and process very different types of data, and up-date susceptibility maps based on near to real-time rainfall-seismic shaking input, is currently undertaken. Moreover, the research is gaining high profit of a vast drilling program undertaken by the Istanbul Metropolitan Area, aiming to yield a detailed geological and geotechnical characterization of the slopes. Also included in the objectives is to test a landslide early warning system. As regards the selected off-shore area, high resolution geophysical marine surveys are being conducted to complete its geomorphological description to help in mapping possible incipient mass movements. This is especially expected to provide better-constrained input for both laboratory testing and numerical modeling of tsunami scenarios thank to a unique lab-scale tsunami channel.

  13. An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

    NASA Astrophysics Data System (ADS)

    Gorsevski, Pece V.; Jankowski, Piotr

    2010-08-01

    The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

  14. Assessment of the landslide and flood risks in São Paulo City, Brazil

    NASA Astrophysics Data System (ADS)

    Vieira, Bianca; Listo, Fabrízio

    2010-05-01

    landslides, debris and remnants of buildings. The drainage systems are precarious and there is runoff on the surface and sewage pipes on soil surface. Some houses were built without keeping safe distance from the top and bottom of the slope, increasing landslide risk. Others were built very close to the stream. There are cracks in the houses and walls and trees inclined by mass movements and riverbank erosion. In general, the urban occupation, after deforesting, characterized by land fragmentation and by settlements without urban infrastructure, occurred in the terrain less favorable to the occupation, where a natural susceptibility to landslides and flood processes exists. Thus, we believe that this mapping can help the identification of the active processes (landslides and floods) and the assessment of risk areas. Therefore, these maps can be used by public administration on identifying areas more appropriate to urban occupation.

  15. Landslide databases for applied landslide impact research: the example of the landslide database for the Federal Republic of Germany

    NASA Astrophysics Data System (ADS)

    Damm, Bodo; Klose, Martin

    2014-05-01

    This contribution presents an initiative to develop a national landslide database for the Federal Republic of Germany. It highlights structure and contents of the landslide database and outlines its major data sources and the strategy of information retrieval. Furthermore, the contribution exemplifies the database potentials in applied landslide impact research, including statistics of landslide damage, repair, and mitigation. The landslide database offers due to systematic regional data compilation a differentiated data pool of more than 5,000 data sets and over 13,000 single data files. It dates back to 1137 AD and covers landslide sites throughout Germany. In seven main data blocks, the landslide database stores besides information on landslide types, dimensions, and processes, additional data on soil and bedrock properties, geomorphometry, and climatic or other major triggering events. A peculiarity of this landslide database is its storage of data sets on land use effects, damage impacts, hazard mitigation, and landslide costs. Compilation of landslide data is based on a two-tier strategy of data collection. The first step of information retrieval includes systematic web content mining and exploration of online archives of emergency agencies, fire and police departments, and news organizations. Using web and RSS feeds and soon also a focused web crawler, this enables effective nationwide data collection for recent landslides. On the basis of this information, in-depth data mining is performed to deepen and diversify the data pool in key landslide areas. This enables to gather detailed landslide information from, amongst others, agency records, geotechnical reports, climate statistics, maps, and satellite imagery. Landslide data is extracted from these information sources using a mix of methods, including statistical techniques, imagery analysis, and qualitative text interpretation. The landslide database is currently migrated to a spatial database system

  16. Emergency response to landslide using GNSS measurements and UAV

    NASA Astrophysics Data System (ADS)

    Nikolakopoulos, Konstantinos G.; Koukouvelas, Ioannis K.

    2017-10-01

    Landslide monitoring can be performed using many different methods: Classical geotechnical measurements like inclinometer, topographical survey measurements with total stations or GNSS sensors and photogrammetric techniques using airphotos or high resolution satellite images. However all these methods are expensive or difficult to be developed immediately after the landslide triggering. In contrast airborne technology and especially the use of Unmanned Aerial Vehicles (UAVs) make response to landslide disaster easier as UAVs can be launched quickly in dangerous terrains and send data about the sliding areas to responders on the ground either as RGB images or as videos. In addition, the emergency response to landslide is critical for the further monitoring. For proper displacement identification all the above mentioned monitoring methods need a high resolution and a very accurate representation of the relief. The ideal solution for the accurate and quick mapping of a landslide is the combined use of UAV's photogrammetry and GNSS measurements. UAVs have started their development as expensive toys but they currently became a very valuable tool in large scale mapping of sliding areas. The purpose of this work is to demonstrate an effective solution for the initial landslide mapping immediately after the occurrence of the phenomenon and the possibility of the periodical assessment of the landslide. Three different landslide cases from Greece are presented in the current study. All three landslides have different characteristics: occurred in different geomorphologic environments, triggered by different causes and had different geologic bedrock. In all three cases we performed detailed GNSS measurements of the landslide area, we generated orthophotos as well as Digital Surface Models (DSMs) at an accuracy of less than +/-10 cm. Slide direction and velocity, mass balances as well as protection and mitigation measurements can be derived from the application of the UAVs

  17. Hematocrit Measurement with R2* and Quantitative Susceptibility Mapping in Postmortem Brain.

    PubMed

    Walsh, A J; Sun, H; Emery, D J; Wilman, A H

    2018-05-24

    Noninvasive venous oxygenation quantification with MR imaging will improve the neurophysiologic investigation and the understanding of the pathophysiology in neurologic diseases. Available MR imaging methods are limited by sensitivity to flow and often require assumptions of the hematocrit level. In situ postmortem imaging enables evaluation of methods in a fully deoxygenated environment without flow artifacts, allowing direct calculation of hematocrit. This study compares 2 venous oxygenation quantification methods in in situ postmortem subjects. Transverse relaxation (R2*) mapping and quantitative susceptibility mapping were performed on a whole-body 4.7T MR imaging system. Intravenous measurements in major draining intracranial veins were compared between the 2 methods in 3 postmortem subjects. The quantitative susceptibility mapping technique was also applied in 10 healthy control subjects and compared with reference venous oxygenation values. In 2 early postmortem subjects, R2* mapping and quantitative susceptibility mapping measurements within intracranial veins had a significant and strong correlation ( R 2 = 0.805, P = .004 and R 2 = 0.836, P = .02). Higher R2* and susceptibility values were consistently demonstrated within gravitationally dependent venous segments during the early postmortem period. Hematocrit ranged from 0.102 to 0.580 in postmortem subjects, with R2* and susceptibility as large as 291 seconds -1 and 1.75 ppm, respectively. Measurements of R2* and quantitative susceptibility mapping within large intracranial draining veins have a high correlation in early postmortem subjects. This study supports the use of quantitative susceptibility mapping for evaluation of in vivo venous oxygenation and postmortem hematocrit concentrations. © 2018 by American Journal of Neuroradiology.

  18. Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

    NASA Astrophysics Data System (ADS)

    Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

    2011-12-01

    The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting

  19. Mapping spatial patterns of people's risk perception of landslides

    NASA Astrophysics Data System (ADS)

    Kofler, Christian; Pedoth, Lydia; Elzbieta Stawinoga, Agnieszka; Schneiderbauer, Stefan

    2016-04-01

    The resilience of communities against natural hazards is largely influenced by how the individuals perceive risk. A good understanding of people's risk perception, awareness and hazard knowledge is crucial for developing and improving risk management and communication strategies between authorities and the affected population. A lot of research has been done in investigating the social aspects of risks to natural hazards by means of interviews or questionnaires. However, there is still a lack of research in the investigation of the influence of the spatial distance to a hazard event on peoples risk perception. While the spatial dimension of a natural hazard event is always assessed in works with a natural science approach, it is often neglected in works on social aspects of natural hazards. In the present study, we aimed to overcome these gaps by combining methods from different disciplines and assessing and mapping the spatial pattern of risk perception through multivariate statistical approaches based on empirical data from questionnaires. We will present results from a case study carried out in Badia, located in the Province of South Tyrol- Italy, where in December 2012 a landslide destroyed four residential buildings and led to the evacuation of 36 people. By means of questionnaires distributed to all adults living in the case study area we assessed people's risk perception and asked respondents to allocate their place of residence on a map of the case study area subdivided in 7 zones. Based on the data of the questionnaire results we developed a risk perception factor in order to express various assessed aspects linked to risk perception with one metric. We analyzed and mapped this factor according to the different zones reflecting the spatial distance to the event. Furthermore, a cluster analysis identified various risk behavior profiles within the population. We also investigated the spatial patterns of these risk profiles. We revealed that the residential

  20. A regional inventory of the landslide processes and the elements at risk on the Rift flanks west of Lake Kivu (DRC)

    NASA Astrophysics Data System (ADS)

    Maki Mateso, Jean-Claude; Monsieurs, Elise; Jacobs, Liesbet; Bagalwa Mateso, Luc; Fiama Bondo, Silvanos; Delvaux, Damien; Albino, Fabien; Kervyn, François; Dewitte, Olivier

    2016-04-01

    The Rift flanks west of Lake Kivu (DRC) are one of the Congolese regions most affected by fatal landslides. However, information on the distribution of these processes and their impact on society is still lacking. Here we present a first regional landslide inventory and the associated elements at risk. The inventory was conducted in an area of 5,700 km² in three administrative territories between the cities of Bukavu and Goma. The region is one of the most densely populated area of DRC with a density of up to 200 persons/km². The approach for the inventory relies on visual analysis of Google Earth imagery and a 5 m resolution DEM that we produced from TanDEM-X interferometry. Field validation was performed in target places accounting for 5% of the study area. More than 2,000 landslides were mapped and distinction was made between deep and shallow, and slide and flow processes. Average landslide area is 6 ha (max. = 430 ha). Geomorphological analysis of landslide distribution shows topographic, lithologic, climatic and seismic controls. For 600 randomly-selected landslides, elements at risk (house, road, cultivated land, river) were inventoried in the areas affected and potentially affected by the instabilities; 10% of the landslides are inhabited and 25% do not present any risk. Numerous landslides have caused direct and indirect damage in recent years. In some places, the impact of mining activities on slope stability can be important. Google Earth was the only way to locate the recent shallow failures triggered by known extreme rainfall events. This inventory is a first step towards the understanding of the landslide processes in the region. Further studies are needed to complete and validate the information, to better infer about the triggers, and to compute susceptibility and risk maps.

  1. Mapping the kinematics of the Blaubach landslide (Austria) using digital photogrammetry

    NASA Astrophysics Data System (ADS)

    Kaufmann, V.; Lieb, G. K.

    2003-04-01

    The Blaubach landslide (12°08'E, 47°12'N, northern margin of the Hohe Tauern range, Austria) is located in the upper part of the catchment area of the Blaubach torrent. The latter follows an important Eastern Alpine fault. The area of interest is built of tectonically fractured rock favoring fluvial erosion, debris flows, and other types of mass movements triggered by widespread deep reaching gravitational slope deformations. The Blaubach landslide is characterized by high surface movement and a front with several secondary slides, which are free of vegetation and provide high quantities of material to the torrent below. This natural hazard has induced the construction of protective measures such as retaining walls in the torrent bed since 1950. However, as of yet no numerical data have been available concerning the surface kinematics of the landslide, such as flow/creep velocity, surface height change, or volumetric change. The Austrian Forest Engineering Service of Torrent and Avalanche Control therefore launched a project related to these questions. One task was to reconstruct the morphodynamics of the landslide area using historical multi-temporal aerial photographs. Aerial photographs at various image scales between 1:9,300 and 1:45,800 of 11 different data acquisition periods between 1953 and 1999 were acquired from the Austrian Federal Office of Surveying and Mapping. The photographs were scanned using the UltraScan 5000 of Vexcel Imaging Austria in order to facilitate digital photogrammetry. A special software package ADVM (Automatic Displacement Vector Measurement), originally developed at the Institute of Geodesy for monitoring debris-covered glaciers and rock glaciers, was used to automatically derive three-dimensional displacement vectors, both area-wide and dense, based on advanced image matching techniques. The digital photogrammetric method applied is based on quasi-orthophotos. This approach supports the fusion of multi-temporal aerial photographs

  2. Validating the usability of an interactive Earth Observation based web service for landslide investigation

    NASA Astrophysics Data System (ADS)

    Albrecht, Florian; Weinke, Elisabeth; Eisank, Clemens; Vecchiotti, Filippo; Hölbling, Daniel; Friedl, Barbara; Kociu, Arben

    2017-04-01

    Regional authorities and infrastructure maintainers in almost all mountainous regions of the Earth need detailed and up-to-date landslide inventories for hazard and risk management. Landslide inventories usually are compiled through ground surveys and manual image interpretation following landslide triggering events. We developed a web service that uses Earth Observation (EO) data to support the mapping and monitoring tasks for improving the collection of landslide information. The planned validation of the EO-based web service does not only cover the analysis of the achievable landslide information quality but also the usability and user friendliness of the user interface. The underlying validation criteria are based on the user requirements and the defined tasks and aims in the work description of the FFG project Land@Slide (EO-based landslide mapping: from methodological developments to automated web-based information delivery). The service will be validated in collaboration with stakeholders, decision makers and experts. Users are requested to test the web service functionality and give feedback with a web-based questionnaire by following the subsequently described workflow. The users will operate the web-service via the responsive user interface and can extract landslide information from EO data. They compare it to reference data for quality assessment, for monitoring changes and for assessing landslide-affected infrastructure. An overview page lets the user explore a list of example projects with resulting landslide maps and mapping workflow descriptions. The example projects include mapped landslides in several test areas in Austria and Northern Italy. Landslides were extracted from high resolution (HR) and very high resolution (VHR) satellite imagery, such as Landsat, Sentinel-2, SPOT-5, WorldView-2/3 or Pléiades. The user can create his/her own project by selecting available satellite imagery or by uploading new data. Subsequently, a new landslide

  3. Map showing 1983 landslides in Utah

    USGS Publications Warehouse

    Brabb, Earl E.; Wieczorek, Gerald F.; Harp, Edwin L.

    1989-01-01

    The State of Utah sustained direct damages from landslides and flooding in excess of $400 million during approximately three months in the spring of 1983.  These disastrous events were declared national disaster areas (Anderson and others, 1985).

  4. Structural control of landslides. A regional approach based on a developed ArcGIS tool

    NASA Astrophysics Data System (ADS)

    Ilinca, Viorel; Sandric, Ionut; Chitu, Zenaida; Jurchescu, Marta

    2016-04-01

    The relationship between bedding planes and topographic slopes plays a major role in controlling landslide mechanisms. The catastrophic nature of many landslides around the Globe was proved to have a relevant structural background. This paper aims at analyzing the relationship between the spatial distribution of landslides and geological structure and lithology at a regional scale (1:50,000). Moreover, by automatizing a well known method to assess the influence of bedding planes on landslide occurence, this study further provides a GIS-based tool useful to speed up regional analyses, when study areas extend over hundreds or thousands of square kilometers. Three areas with different geological and geomorphological features and extents ranging from 70 to 179 km² were selected as case-studies. The sites are located in the Southern Carpathians, the Curvature and the Getic Subcarpathians of Romania. Computation of the topography - bedding plane relation required the following three phases: i) data acquisition, ii) developing a tool for an easy data processing and analysis and iii) testing the tool on the few selected sites having different geological and geomorphological settings. Three categories of spatial data were acquired: i) landslide inventory data; ii) detailed lithological data and iii) data related to geological structure (dip angle and dip direction point data). The landslide database was built based on interpretation of aerial images and field mapping during a more than 8 years long period. Lithology was extracted from geological maps at a 1:50,000 scale, while dip angle and dip direction data were obtained both from geological maps and direct measurements in the field meant to increase the level of detail. In order to rapidly identify the type of slope in relation to the geological structure (anaclinal, cataclinal and orthoclinal), a tool was developed which integrates a well-known index called TOBIA. This custom created GIS tool was developed using Python

  5. Landslide deposit boundaries for the Little North Santiam River Basin, Oregon

    USGS Publications Warehouse

    Sobieszczyk, Steven

    2010-01-01

    This layer is an inventory of existing landslides deposits in the Little North Santiam River Basin, Oregon (2009). Each landslide deposit shown on this map has been classified according to a number of specific characteristics identified at the time recorded in the GIS database. The classification scheme was developed by the Oregon Department of Geology and Mineral Industries (Burns and Madin, 2009). Several significant landslide characteristics recorded in the database are portrayed with symbology on this map. The specific characteristics shown for each landslide are the activity of landsliding, landslide features, deep or shallow failure, type of landslide movement, and confidence of landslide interpretation. These landslide characteristics are determined primarily on the basis of geomorphic features, or landforms, observed for each landslide. This work was completed as part of the Master's thesis "Turbidity Monitoring and LiDAR Imagery Indicate Landslides are Primary Source of Suspended-Sediment Load in the Little North Santiam River Basin, Oregon, Winter 2009-2010" by Steven Sobieszczyk, Portland State University and U.S. Geological Survey.Data layers in this geodatabase include: landslide deposit boundaries (Deposits); field-verfied location imagery (Photos); head scarp or scarp flanks (Scarp_Flanks); and secondary scarp features (Scarps).The geodatabase template was developed by the Oregon Department of Geology and Mineral Industries (Burns and Madin, 2009).

  6. Regional coseismic landslide hazard assessment without historical landslide inventories: A new approach

    NASA Astrophysics Data System (ADS)

    Kritikos, Theodosios; Robinson, Tom R.; Davies, Tim R. H.

    2015-04-01

    Currently, regional coseismic landslide hazard analyses require comprehensive historical landslide inventories as well as detailed geotechnical data. Consequently, such analyses have not been possible where these data are not available. A new approach is proposed herein to assess coseismic landslide hazard at regional scale for specific earthquake scenarios in areas without historical landslide inventories. The proposed model employs fuzzy logic and geographic information systems to establish relationships between causative factors and coseismic slope failures in regions with well-documented and substantially complete coseismic landslide inventories. These relationships are then utilized to estimate the relative probability of landslide occurrence in regions with neither historical landslide inventories nor detailed geotechnical data. Statistical analyses of inventories from the 1994 Northridge and 2008 Wenchuan earthquakes reveal that shaking intensity, topography, and distance from active faults and streams are the main controls on the spatial distribution of coseismic landslides. Average fuzzy memberships for each factor are developed and aggregated to model the relative coseismic landslide hazard for both earthquakes. The predictive capabilities of the models are assessed and show good-to-excellent model performance for both events. These memberships are then applied to the 1999 Chi-Chi earthquake, using only a digital elevation model, active fault map, and isoseismal data, replicating prediction of a future event in a region lacking historic inventories and/or geotechnical data. This similarly results in excellent model performance, demonstrating the model's predictive potential and confirming it can be meaningfully applied in regions where previous methods could not. For such regions, this method may enable a greater ability to analyze coseismic landslide hazard from specific earthquake scenarios, allowing for mitigation measures and emergency response plans

  7. Quantitative Susceptibility Mapping using Structural Feature based Collaborative Reconstruction (SFCR) in the Human Brain

    PubMed Central

    Cai, Congbo; Chen, Zhong; van Zijl, Peter C.M.

    2017-01-01

    The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l1 norm constraint and a voxel fidelity based l2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k-space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result. PMID:27019480

  8. Potential Landslide Early Detection Near Wenchuan by a Qualitatively Multi-Baseline Dinsar Method

    NASA Astrophysics Data System (ADS)

    Dai, K.; Chen, G.; Xu, Q.; Li, Z.; Qu, T.; Hu, L.; Lu, H.

    2018-04-01

    Early detection of landslides is important for disaster prevention, which was still very hard work with traditional surveying methods. Interferometric Synthetic Aperture Radar (InSAR) technology provided us the ability to monitor displacements along the slope with wide coverage and high accuracy. In this paper, we proposed a qualitatively multi-baseline DInSAR method to early detect and map the potential landslides. Two sections of China National Highway 317 and 213 were selected as study area. With this method 10 potential landslide areas were early detected and mapped in a quick and effective way. One of them (i.e. Shidaguan landslide) collapsed on August 2017, which was coincident with our results, suggesting that this method could become an effective way to acquire the landslide early detection map to assist the future disaster prevention work.

  9. Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey).

    PubMed

    Karsli, F; Atasoy, M; Yalcin, A; Reis, S; Demir, O; Gokceoglu, C

    2009-09-01

    Various natural hazards such as landslides, avalanches, floods and debris flows can result in enormous property damages and human casualties in Eastern Black Sea region of Turkey. Mountainous topographic character and high frequency of heavy rain are the main factors for landslide occurrence in Ardesen, Rize. For this reason, the main target of the present study is to evaluate the landslide hazards using a sequence of historical aerial photographs in Ardesen (Rize), Turkey, by Photogrammetry and Geographical Information System (GIS). Landslide locations in the study area were identified by interpretation of aerial photographs dated in 1973 and 2002, and by field surveys. In the study, the selected factors conditioning landslides are lithology, slope gradient, slope aspect, vegetation cover, land class, climate, rainfall and proximity to roads. These factors were considered as effective on the occurrence of landslides. The areas under landslide threat were analyzed and mapped considering the landslide conditioning factors. Some of the conditioning factors were investigated and estimated by employing visual interpretation of aerial photos and topographic data. The results showed that the slope, lithology, terrain roughness, proximity to roads, and the cover type played important roles on landslide occurrence. The results also showed that degree of landslides was affected by the number of houses constructed in the region. As a consequence, the method employed in the study provides important benefits for landslide hazard mitigation efforts, because a combination of both photogrammetric techniques and GIS is presented.

  10. The role of land use changes in the distribution of shallow landslides.

    PubMed

    Persichillo, Maria Giuseppina; Bordoni, Massimiliano; Meisina, Claudia

    2017-01-01

    The role of land use dynamics on shallow landslide susceptibility remains an unresolved problem. Thus, this work aims to assess the influence of land use changes on shallow landslide susceptibility. Three shallow landslide-prone areas that are representative of peculiar land use settings in the Oltrepò Pavese (North Apennines) are analysed: the Rio Frate, Versa and Alta Val Tidone catchments. These areas were affected by widespread land abandonment and modifications in agricultural practices from 1954 to 2012 and relevant shallow landslide phenomena in 2009, 2013 and 2014. A multi-temporal land use change analysis allows us to evaluate the degree of transformation in the three investigated areas and the influence of these changes on the susceptibility to shallow landslides. The results show that the three catchments were characterised by pronounced land abandonment and important changes in agricultural practices. In particular, abandoned cultivated lands that gradually recovered through natural grasses, shrubs and woods were identified as the land use change classes that were most prone to shallow landslides. Additionally, the negative qualities of the agricultural maintenance practices increased the surface water runoff and consequently intensified erosion processes and instability phenomena. Although the land use was identified as the most important predisposing factor in all the study areas, some cases existed in which the predisposition of certain areas to shallow landslides was influenced by the combined effect of land use changes and the geological conditions, as highlighted by the high susceptibility of slopes that are characterised by adverse local geological (thick soils derived from clayey-marly bedrocks) and geomorphological (slope angle higher than 25°) conditions. Thus, the achieved results are particularly useful to understand the best land conservation strategies to be adopted to reduce instability phenomena and the consequent economic losses in

  11. Assessing the Economic Cost of Landslide Damage in Low-Relief Regions: Case Study Evidence from the Flemish Ardennes (Belgium)

    NASA Astrophysics Data System (ADS)

    Vranken, L.; Van Turnhout, P.; Van Den Eeckhaut, M.; Vandekerckhove, L.; Vantilt, G.; Poesen, J.

    2012-04-01

    connecting two important Belgian cities has been built and within that one project, the cost to prevent damage to railroads augmented already to at least 4 567 822 €. The value of real estate located in regions affected by landslides decreased with 15% to 35%. All these damage costs were then used to made potential damage maps. Based on the inventory of landslides, frequency of landslides' re-activation and land use, we categorized regions that are affected by landslides according to their temporal probability of landslide re-activation. This allowed us to produce a (semi-) qualitative risk map for regions that were affected by landslides in the past. This paper shows that, though generally not spectacular, landsliding in low-relief regions susceptible to landslides is a slow but continuously operating process with considerable damage allowing one to identify several medium to high landslide risk zones. As such this study provides important information for government officials, especially those in charge of spatial planning and of town and environmental planning, as it clearly informs about the costs associated with certain land use types in landslide prone areas. This information can be particularly useful for regions in which increasing demand for building land pressures government officials and (local) political leaders to expand the built environment.

  12. Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington

    USGS Publications Warehouse

    Brien, Dianne L.; Reid, Mark E.

    2008-01-01

    In Seattle, Washington, deep-seated landslides on bluffs along Puget Sound have historically caused extensive damage to land and structures. These large failures are controlled by three-dimensional (3-D) variations in strength and pore-water pressures. We assess the slope stability of part of southwestern Seattle using a 3-D limit-equilibrium analysis coupled with a 3-D groundwater flow model. Our analyses use a high-resolution digital elevation model (DEM) combined with assignment of strength and hydraulic properties based on geologic units. The hydrogeology of the Seattle area consists of a layer of permeable glacial outwash sand that overlies less permeable glacial lacustrine silty clay. Using a 3-D groundwater model, MODFLOW-2000, we simulate a water table above the less permeable units and calibrate the model to observed conditions. The simulated pore-pressure distribution is then used in a 3-D slope-stability analysis, SCOOPS, to quantify the stability of the coastal bluffs. For wet winter conditions, our analyses predict that the least stable areas are steep hillslopes above Puget Sound, where pore pressures are elevated in the outwash sand. Groundwater flow converges in coastal reentrants, resulting in elevated pore pressures and destabilization of slopes. Regions predicted to be least stable include the areas in or adjacent to three mapped historically active deep-seated landslides. The results of our 3-D analyses differ significantly from a slope map or results from one-dimensional (1-D) analyses.

  13. Positive Contrast Visualization of Nitinol Devices using Susceptibility Gradient Mapping

    PubMed Central

    Vonken, Evert-jan P.A.; Schär, Michael; Stuber, Matthias

    2008-01-01

    MRI visualization of devices is traditionally based on the signal loss due to T2* effects originating from the local susceptibility differences. To visualize nitinol devices with positive contrast a recently introduced post processing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center of mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualization of a nitinol wire and two stents are shown for illustration. PMID:18727096

  14. A tool for the estimation of the distribution of landslide area in R

    NASA Astrophysics Data System (ADS)

    Rossi, M.; Cardinali, M.; Fiorucci, F.; Marchesini, I.; Mondini, A. C.; Santangelo, M.; Ghosh, S.; Riguer, D. E. L.; Lahousse, T.; Chang, K. T.; Guzzetti, F.

    2012-04-01

    We have developed a tool in R (the free software environment for statistical computing, http://www.r-project.org/) to estimate the probability density and the frequency density of landslide area. The tool implements parametric and non-parametric approaches to the estimation of the probability density and the frequency density of landslide area, including: (i) Histogram Density Estimation (HDE), (ii) Kernel Density Estimation (KDE), and (iii) Maximum Likelihood Estimation (MLE). The tool is available as a standard Open Geospatial Consortium (OGC) Web Processing Service (WPS), and is accessible through the web using different GIS software clients. We tested the tool to compare Double Pareto and Inverse Gamma models for the probability density of landslide area in different geological, morphological and climatological settings, and to compare landslides shown in inventory maps prepared using different mapping techniques, including (i) field mapping, (ii) visual interpretation of monoscopic and stereoscopic aerial photographs, (iii) visual interpretation of monoscopic and stereoscopic VHR satellite images and (iv) semi-automatic detection and mapping from VHR satellite images. Results show that both models are applicable in different geomorphological settings. In most cases the two models provided very similar results. Non-parametric estimation methods (i.e., HDE and KDE) provided reasonable results for all the tested landslide datasets. For some of the datasets, MLE failed to provide a result, for convergence problems. The two tested models (Double Pareto and Inverse Gamma) resulted in very similar results for large and very large datasets (> 150 samples). Differences in the modeling results were observed for small datasets affected by systematic biases. A distinct rollover was observed in all analyzed landslide datasets, except for a few datasets obtained from landslide inventories prepared through field mapping or by semi-automatic mapping from VHR satellite imagery

  15. Landslide kinematics and their potential controls from hourly to decadal timescales: Insights from integrating ground-based InSAR measurements with structural maps and long-term monitoring data

    NASA Astrophysics Data System (ADS)

    Schulz, William H.; Coe, Jeffrey A.; Ricci, Pier P.; Smoczyk, Gregory M.; Shurtleff, Brett L.; Panosky, Joanna

    2017-05-01

    Knowledge of kinematics is rudimentary for understanding landslide controls and is increasingly valuable with greater spatiotemporal coverage. However, characterizing landslide-wide kinematics is rare, especially at broadly ranging timescales. We used highly detailed kinematic data obtained using photogrammetry and field mapping during the 1980s and 1990s and our 4.3-day ground-based InSAR survey during 2010 to study kinematics of the large, persistently moving Slumgullion landslide. The landslide was segregated into 11 kinematic elements using the 1980s-1990s data and the InSAR survey revealed most of these elements within a few hours. Averages of InSAR-derived displacement point measures within each element agreed well with higher quality in situ observations; averaging was deemed necessary because adverse look angles for the radar coupled with tree cover on the landslide introduced error in the InSAR results. We found that the landslide moved during 2010 at about half its 1985-1990 speed, but slowing was most pronounced at the landslide head. Gradually decreased precipitation and increased temperature between the periods likely resulted in lower groundwater levels and consequent slowing of the landslide. We used GPS survey results and limit-equilibrium modeling to analyze changing stability of the landslide head from observed thinning and found that its stability increased between the two periods, which would result in its slowing, and the consequent slowing of the entire landslide. Additionally, InSAR results suggested movement of kinematic element boundaries in the head region and our field mapping verified that they moved and changed character, likely because of the long-term increasing head stability. On an hourly basis, InSAR results were near error bounds but suggested landslide acceleration in response to seemingly negligible rainfall. Pore-pressure diffusion modeling suggested that rainfall infiltration affected frictional strength only to shallow depths

  16. Landslide kinematics and their potential controls from hourly to decadal timescales: Insights from integrating ground-based InSAR measurements with structural maps and long-term monitoring data

    USGS Publications Warehouse

    Schulz, William; Coe, Jeffrey A.; Ricci, P.P; Smoczyk, Gregory M.; Shurtleff, Brett L; Panosky, J

    2017-01-01

    Knowledge of kinematics is rudimentary for understanding landslide controls and is increasingly valuable with greater spatiotemporal coverage. However, characterizing landslide-wide kinematics is rare, especially at broadly ranging timescales. We used highly detailed kinematic data obtained using photogrammetry and field mapping during the 1980s and 1990s and our 4.3-day ground-based InSAR survey during 2010 to study kinematics of the large, persistently moving Slumgullion landslide. The landslide was segregated into 11 kinematic elements using the 1980s–1990s data and the InSAR survey revealed most of these elements within a few hours. Averages of InSAR-derived displacement point measures within each element agreed well with higher quality in situ observations; averaging was deemed necessary because adverse look angles for the radar coupled with tree cover on the landslide introduced error in the InSAR results. We found that the landslide moved during 2010 at about half its 1985–1990 speed, but slowing was most pronounced at the landslide head. Gradually decreased precipitation and increased temperature between the periods likely resulted in lower groundwater levels and consequent slowing of the landslide. We used GPS survey results and limit-equilibrium modeling to analyze changing stability of the landslide head from observed thinning and found that its stability increased between the two periods, which would result in its slowing, and the consequent slowing of the entire landslide. Additionally, InSAR results suggested movement of kinematic element boundaries in the head region and our field mapping verified that they moved and changed character, likely because of the long-term increasing head stability. On an hourly basis, InSAR results were near error bounds but suggested landslide acceleration in response to seemingly negligible rainfall. Pore-pressure diffusion modeling suggested that rainfall infiltration affected frictional strength only to shallow

  17. Using Logistic Regression and Random Forests multivariate statistical methods for landslide spatial probability assessment in North-Est Sicily, Italy

    NASA Astrophysics Data System (ADS)

    Trigila, Alessandro; Iadanza, Carla; Esposito, Carlo; Scarascia-Mugnozza, Gabriele

    2015-04-01

    North-East Sicily is strongly exposed to shallow landslide events. On October, 1st 2009 a severe rainstorm (225.5 mm of cumulative rainfall in 9 hours) caused flash floods and more than 1000 landslides, which struck several small villages as Giampilieri, Altolia, Molino, Pezzolo, Scaletta Zanclea, Itala, with 31 fatalities, 6 missing persons and damage to buildings and transportation infrastructures. Landslides, mainly consisting in earth and debris translational slides evolving into debris flows, triggered on steep slopes involving colluvium and regolith materials which cover the underlying metamorphic bedrock of Peloritani Mountains. In this area catchments are small (about 10 square kilometres), elongated, with steep slopes, low order streams, short time of concentration, and discharge directly into the sea. In the past, landslides occurred at Altolia in 1613 and 2000, at Molino in 1750, 1805 and 2000, at Giampilieri in 1791, 1918, 1929, 1932, 2000 and on October 25, 2007. The aim of this work is to define susceptibility models for shallow landslides using multivariate statistical analyses in the Giampilieri area (25 square kilometres). A detailed landslide inventory map has been produced, as the first step, through field surveys coupled with the observation of high resolution aerial colour orthophoto taken immediately after the event. 1,490 initiation zones have been identified; most of them have planimetric dimensions ranging between tens to few hundreds of square metres. The spatial hazard assessment has been focused on the detachment areas. Susceptibility models, performed in a GIS environment, took into account several parameters. The morphometric and hydrologic parameters has been derived from a detailed LiDAR 1×1 m. Square grid cells of 4×4 m were adopted as mapping units, on the basis of the area-frequency distribution of the detachment zones, and the optimal representation of the local morphometric conditions (e.g. slope angle, plan curvature). A

  18. Research on the evolution model and deformation mechanisms of Baishuihe landslide based on analyzing geologic process of slope

    NASA Astrophysics Data System (ADS)

    Zhang, S.; Tang, H.; Cai, Y.; Tan, Q.

    2016-12-01

    The landslide is a result of both inner and exterior geologic agents, and inner ones always have significant influences on the susceptibility of geologic bodies to the exterior ones. However, current researches focus more on impacts of exterior factors, such as precipitation and reservoir water, than that of geologic process. Baishuihe landslide, located on the south bank of Yangtze River and 56km upstream from the Three Gorges Project, was taken as the study subject with the in-situ investigation and exploration carried out for the first step. After the spatial analysis using the 3D model of topography built by ArcGIS (Fig.1), geologic characteristics of the slope that lies in a certain range near the Baishuihe landslide on the same bank were investigated for further insights into geologic process of the slope, with help of the geological map and structure outline map. Baishuihe landslide developed on the north limb of Baifuping anticline, a dip slope on the southwest margin of Zigui basin. The eastern and western boundaries are both ridges and in the middle a distinct slide depression is in process of deforming. Evolutionary process of Baishuihe landslide includes three steps below. 1) Emergence of Baifuping anticline leaded to interbedded dislocation, tension cracks and joint fractures in bedrocks. 2) Weathering continuously weakened strength of soft interlayers in the Shazhenxi Formation (T3s). 3) Rock slide caused by neotectonics happened on a large scale along the weak layers and joint planes, forming initial Baishuihe landslide. Although the landslide has undergone reconstruction for a long time, it could still be divided clearly into two parts, namely a) the rock landslide at the back half (south) and b) the debris landslide at the front half (north). a) The deformation mechanism for the rock landslide is believed to be deterioration in strength of weak bedding planes due to precipitation and free face caused by human activities or river incision. b

  19. Complex landslides in the Trans-Mexican Volcanic Belt - a case study in the State of Veracruz

    NASA Astrophysics Data System (ADS)

    Wilde, M.; Terhorst, B.; Schwindt, D.; Rodriguez Elizarrarás, S. R.; Morales Barrera, W. V.; Bücker, M.; Flores Orozco, A.; García García, E.; Pita de la Paz, C.

    2017-12-01

    The State of Veracruz (Mexico) is a region which is highly affected by landslides, therefore detailed studies on triggering factors and process dynamics of landslides are required. Profound insights are essential for further hazard assessments and compilation of susceptibility maps. Exemplary landslide sites were investigated in order to determine characteristic features of specific regions. In the Chiconquiaco Mountain Range numerous damaging landslide events occurred in the year of 2013 and our case study corresponds to a deep-seated landslide originating from this slide-intensive year. The main scientific aspects are placed on the reconstruction of the landslides geometry and its process dynamics. Therefore, surface and subsurface analysis form the base of a multimethodological approach. In order to perform surface analysis, aerial photographs were collected by an unmanned aerial vehicle (UAV) aiming at the generation of a 3D model with the Structure from Motion (SfM) work routine. Ground control points (GCP) were used to ensure the geometric accuracy of the model. The obtained DEM of the 2013 slide mass as well as an elevation model representing the topographic situation before the event (year 2011) were used to detect surface changes. The data enabled determination of the most affected areas as well as areas characterized by secondary movements. Furthermore, the volume of the slide mass could be calculated. Geophysical methods, as electrical resistivity tomography (ERT) as well as seismic refraction tomography (SRT), were applied for subsurface analysis. Differences in subsurface composition, respectively density, allowed for separation of the slide mass and the underlying unit. Most relevant for our studies is the detection of an earlier landslide leading to the assumption that the 2013 landslide event corresponds to a reactivation process. This multimethodological approach enables a far-reaching visualization of complex landslides and strongly supports the

  20. Connectivity of earthquake-triggered landslides with the fluvial network: Implications for landslide sediment transport after the 2008 Wenchuan earthquake

    NASA Astrophysics Data System (ADS)

    Li, Gen; West, A. Joshua; Densmore, Alexander L.; Hammond, Douglas E.; Jin, Zhangdong; Zhang, Fei; Wang, Jin; Hilton, Robert G.

    2016-04-01

    Evaluating the influence of earthquakes on erosion, landscape evolution, and sediment-related hazards requires understanding fluvial transport of material liberated in earthquake-triggered landslides. The location of landslides relative to river channels is expected to play an important role in postearthquake sediment dynamics. In this study, we assess the position of landslides triggered by the Mw 7.9 Wenchuan earthquake, aiming to understand the relationship between landslides and the fluvial network of the steep Longmen Shan mountain range. Combining a landslide inventory map and geomorphic analysis, we quantify landslide-channel connectivity in terms of the number of landslides, landslide area, and landslide volume estimated from scaling relationships. We observe a strong spatial variability in landslide-channel connectivity, with volumetric connectivity (ξ) ranging from ~20% to ~90% for different catchments. This variability is linked to topographic effects that set local channel densities, seismic effects (including seismogenic faulting) that regulate landslide size, and substrate effects that may influence both channelization and landslide size. Altogether, we estimate that the volume of landslides connected to channels comprises 43 + 9/-7% of the total coseismic landslide volume. Following the Wenchuan earthquake, fine-grained (<~0.25 mm) suspended sediment yield across the Longmen Shan catchments is positively correlated to catchment-wide landslide density, but this correlation is statistically indistinguishable whether or not connectivity is considered. The weaker-than-expected influence of connectivity on suspended sediment yield may be related to mobilization of fine-grained landslide material that resides in hillslope domains, i.e., not directly connected to river channels. In contrast, transport of the coarser fraction (which makes up >90% of the total landslide volume) may be more significantly affected by landslide locations.

  1. Object-based landslide detection in different geographic regions

    NASA Astrophysics Data System (ADS)

    Friedl, Barbara; Hölbling, Daniel; Eisank, Clemens; Blaschke, Thomas

    2015-04-01

    Landslides occur in almost all mountainous regions of the world and rank among the most severe natural hazards. In the last decade - according to the world disaster report 2014 published by the International Federation of Red Cross and Red Crescent Societies (IRFC) - more than 9.000 people were killed by mass movements, more than 3.2 million people were affected and the total amount of disaster estimated damage accounts to more than 1.700 million US dollars. The application of remote sensing data for mapping landslides can contribute to post-disaster reconstruction or hazard mitigation, either by providing rapid information about the spatial distribution and location of landslides in the aftermath of triggering events or by creating and updating landslide inventories. This is especially valid for remote and inaccessible areas, where information on landslides is often lacking. However, reliable methods are needed for extracting timely and relevant information about landslides from remote sensing data. In recent years, novel methods such as object-based image analysis (OBIA) have been successfully employed for semi-automated landslide mapping. Several studies revealed that OBIA frequently outperforms pixel-based approaches, as a range of image object properties (spectral, spatial, morphometric, contextual) can be exploited during the analysis. However, object-based methods are often tailored to specific study areas, and thus, the transferability to regions with different geological settings, is often limited. The present case study evaluates the transferability and applicability of an OBIA approach for landslide detection in two distinct regions, i.e. the island of Taiwan and Austria. In Taiwan, sub-areas in the Baichi catchment in the North and in the Huaguoshan catchment in the southern-central part of the island are selected; in Austria, landslide-affected sites in the Upper Salzach catchment in the federal state of Salzburg are investigated. For both regions

  2. Mining Input Data for Multivariate Probabilistic Modeling of Rainfall-Induced Landslide Hazard in the Lake ATITLÁN Watershed in Guatemala

    NASA Astrophysics Data System (ADS)

    Cobin, P. F.; Oommen, T.; Gierke, J. S.

    2013-12-01

    The Lake Atitlán watershed is home to approximately 200,000 people and is located in the western highlands of Guatemala. Steep slopes, highly susceptible to landslides during the rainy season, characterize the region. Typically these landslides occur during high-intensity precipitation events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. Different datasets of landslide and non-landslide points across the watershed were used to compare model success at a small scale and regional scale. This study used data from multiple attributes: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The open source software Weka was used for the data mining. Several attribute selection methods were applied to the data to predetermine the potential landslide causative influence. Different multivariate algorithms were then evaluated for their ability to predict landslide occurrence. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The attribute combinations of the most successful models were compared to the attribute evaluator results. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points for the regions selected in the watershed. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

  3. Contour Connection Method for automated identification and classification of landslide deposits

    NASA Astrophysics Data System (ADS)

    Leshchinsky, Ben A.; Olsen, Michael J.; Tanyu, Burak F.

    2015-01-01

    Landslides are a common hazard worldwide that result in major economic, environmental and social impacts. Despite their devastating effects, inventorying existing landslides, often the regions at highest risk of reoccurrence, is challenging, time-consuming, and expensive. Current landslide mapping techniques include field inventorying, photogrammetric approaches, and use of bare-earth (BE) lidar digital terrain models (DTMs) to highlight regions of instability. However, many techniques do not have sufficient resolution, detail, and accuracy for mapping across landscape scale with the exception of using BE DTMs, which can reveal the landscape beneath vegetation and other obstructions, highlighting landslide features, including scarps, deposits, fans and more. Current approaches to landslide inventorying with lidar to create BE DTMs include manual digitizing, statistical or machine learning approaches, and use of alternate sensors (e.g., hyperspectral imaging) with lidar. This paper outlines a novel algorithm to automatically and consistently detect landslide deposits on a landscape scale. The proposed method is named as the Contour Connection Method (CCM) and is primarily based on bare earth lidar data requiring minimal user input such as the landslide scarp and deposit gradients. The CCM algorithm functions by applying contours and nodes to a map, and using vectors connecting the nodes to evaluate gradient and associated landslide features based on the user defined input criteria. Furthermore, in addition to the detection capabilities, CCM also provides an opportunity to be potentially used to classify different landscape features. This is possible because each landslide feature has a distinct set of metadata - specifically, density of connection vectors on each contour - that provides a unique signature for each landslide. In this paper, demonstrations of using CCM are presented by applying the algorithm to the region surrounding the Oso landslide in Washington

  4. Developing a methodology for the national-scale assessment of rainfall-induced landslide hazard in a changing climate

    NASA Astrophysics Data System (ADS)

    Jurchescu, Marta; Micu, Dana; Sima, Mihaela; Bălteanu, Dan; Bojariu, Roxana; Dumitrescu, Alexandru; Dragotă, Carmen; Micu, Mihai; Senzaconi, Francisc

    2017-04-01

    Landslides together with earthquakes and floods represent the main natural hazards in Romania, causing major impacts to human activities. The RO-RISK (Disaster Risk Evaluation at a National Level) project is a flagship project aimed to strengthen risk prevention and management in Romania, by evaluating - among the specific risks in the country - landslide hazard and risk at a national level. Landslide hazard is defined as "the probability of occurrence within a specified period of time and within a given area of a landslide of a given magnitude" (Varnes 1984; Guzzetti et al. 1999). Nevertheless, most landslide ʿhazardʾ maps only consist in susceptibility (i.e. spatial probability) zonations without considering temporal or magnitude information on the hazard. This study proposes a methodology for the assessment of landslide hazard at the national scale on a scenario basis, while also considering changes in hazard patterns and levels under climate change conditions. A national landslide database consisting of more than 3,000 records has been analyzed against a meteorological observation dataset in order to assess the relationship between precipitation and landslides. Various extreme climate indices were computed in order to account for the different rainfall patterns able to prepare/trigger landslides (e.g. extreme levels of seasonal rainfall, 3-days rainfall or number of consecutive rainy days with different return periods). In order to derive national rainfall thresholds, i.e. valid for diverse climatic environments across the country, values in the parameter maps were rendered comparable by means of normalization with the mean annual precipitation and the rainy-day-normal. A hazard assessment builds on a frequency-magnitude relationship. In the current hazard scenario approach, frequency was kept constant for each single map, while the magnitude of the expected geomorphic event was modeled in relation to the distributed magnitude of the triggering factor. Given

  5. Does Geology Matter? Post-Hurricane Maria Landslide Distribution Across the Mountainous Regions of Puerto Rico, USA

    NASA Astrophysics Data System (ADS)

    Cerovski-Darriau, C.; Bessette-Kirton, E.; Schulz, W. H.; Kean, J. W.; Godt, J.; Coe, J. A.

    2017-12-01

    topographic relief, generated debris flows. More clay-rich units generated some deeper slumps or shallow flows. Correlations with the 1:100K geologic map revealed that 62% of the high-density areas occurred within granodiorite. Therefore, we hypothesize that when rainfall is not limiting, geology is a major control of landslide susceptibility.

  6. Extreme Precipitation and High-Impact Landslides

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

    2012-01-01

    It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing

  7. A new methodology for modeling of direct landslide costs for transportation infrastructures

    NASA Astrophysics Data System (ADS)

    Klose, Martin; Terhorst, Birgit

    2014-05-01

    The world's transportation infrastructure is at risk of landslides in many areas across the globe. A safe and affordable operation of traffic routes are the two main criteria for transportation planning in landslide-prone areas. The right balancing of these often conflicting priorities requires, amongst others, profound knowledge of the direct costs of landslide damage. These costs include capital investments for landslide repair and mitigation as well as operational expenditures for first response and maintenance works. This contribution presents a new methodology for ex post assessment of direct landslide costs for transportation infrastructures. The methodology includes tools to compile, model, and extrapolate landslide losses on different spatial scales over time. A landslide susceptibility model enables regional cost extrapolation by means of a cost figure obtained from local cost compilation for representative case study areas. On local level, cost survey is closely linked with cost modeling, a toolset for cost estimation based on landslide databases. Cost modeling uses Landslide Disaster Management Process Models (LDMMs) and cost modules to simulate and monetize cost factors for certain types of landslide damage. The landslide susceptibility model provides a regional exposure index and updates the cost figure to a cost index which describes the costs per km of traffic route at risk of landslides. Both indexes enable the regionalization of local landslide losses. The methodology is applied and tested in a cost assessment for highways in the Lower Saxon Uplands, NW Germany, in the period 1980 to 2010. The basis of this research is a regional subset of a landslide database for the Federal Republic of Germany. In the 7,000 km² large Lower Saxon Uplands, 77 km of highway are located in potential landslide hazard area. Annual average costs of 52k per km of highway at risk of landslides are identified as cost index for a local case study area in this region. The

  8. Regional analysis of distribution of pre and post 2015 Nepal Earthquake landslides

    NASA Astrophysics Data System (ADS)

    Valagussa, Andrea; Frattini, Paolo; Crosta, Giovanni; Valbuzzi, Elena

    2016-04-01

    A magnitude 7.8 earthquake struck Nepal on April 25, 2015. Three landslide inventories have been prepared in four districts: Dhading (1885 km2), Sindhupalchok (2488 km2), Rasuwa (1522 km2) and Nuwakot (1194 km2), that are located north of Kathmandu. These inventories extend 14 to 138 km SE from the epicenter of the main shock (April 25, 2015), 4.5 to 143 km NW from the epicenter of the main aftershock (May 12, 2015), and 34 to 136 km from the Main Frontal Thrust. The first inventory is a coseismic and post-seismic landslide inventory based on multi-temporal images (Google Earth, Google Crisis maps, Bing maps), and helicopter-based video. The second one is a pre-event shallow landslide inventory. In these two inventories the most abundant landslide types are: debris flows, shallow translational slides, and rockfalls. The third is a deep seated landslide inventory, in which the most represented landslide types are rock avalanches, slumps, rockslides and deep-seated gravitational slope deformations (DSGSD). All the landslides have been mapped as individual polygons. For the analysis we focus our attention on four districts: First we studied how the landslide frequency density changes as a function of topographic parameters (i.e. slope gradient, slope aspect, and elevation). The analyses have been based on the ASTER Global Digital Elevation Model (ASTER GDEM). For coseismic and post-seismic landslides we observed that the mean slope gradient at which the landslide occurs is higher with respect to the two other inventories (50° and 30/40° respectively). The slope aspect of coseismic and post-seismic landslides is also different, with a larger frequency of landslides towards SW, whereas in pre-event landslides the most common slope aspect is SE. This could be related to the direction of the seismic wave. At least the coseismic and post-seismic landslides occur, in mean, at an elevation lower than the pre-event landslides. We also analyzed the relationship between the

  9. Evaluation of Rainfall-induced Landslide Potential

    NASA Astrophysics Data System (ADS)

    Chen, Y. R.; Tsai, K. J.; Chen, J. W.; Chue, Y. S.; Lu, Y. C.; Lin, C. W.

    2016-12-01

    Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assessed rainfall-induced landslide potential and spatial distribution in some watersheds of Southern Taiwan to configure reasonable assessment process and methods for landslide potential. This study focused on the multi-year multi-phase heavy rainfall events after 2009 Typhoon Morakot and applied the analysis techniques for the classification of satellite images of research region before and after rainfall to obtain surface information and hazard log data. GIS and DEM were employed to obtain the ridge and water system and to explore characteristics of landslide distribution. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various hazard factors. Furthermore, the interaction between rainfall characteristic, slope disturbance and landslide mechanism was analyzed. The results of image classification show that the values of coefficient of agreement are at medium-high level. The agreement of landslide potential map is at around 80% level compared with historical disaster sites. The relations between landslide potential level, slope disturbance degree, and the ratio of number and area of landslide increment corresponding heavy rainfall events are positive. The ratio of landslide occurrence is proportional to the value of instability index. Moreover, for each rainfall event, the number and scale of secondary landslide sites are much more than those of new landslide sites. The greater the slope land disturbance, the more likely it is that the scale of secondary landslide become greater. The spatial distribution of landslide depends on the interaction of rainfall patterns, slope, and elevation of the research area.

  10. Comparison of the Structurally Controlled Landslides Numerical Model Results to the M 7.2 2013 Bohol Earthquake Co-seismic Landslides

    NASA Astrophysics Data System (ADS)

    Macario Galang, Jan Albert; Narod Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo

    2015-04-01

    The M 7.2 October 15, 2013 Bohol earthquake is the most destructive earthquake to hit the Philippines since 2012. The epicenter was located in Sagbayan municipality, central Bohol and was generated by a previously unmapped reverse fault called the "Inabanga Fault". Its name, taken after the barangay (village) where the fault is best exposed and was first seen. The earthquake resulted in 209 fatalities and over 57 billion USD worth of damages. The earthquake generated co-seismic landslides most of which were related to fault structures. Unlike rainfall induced landslides, the trigger for co-seismic landslides happen without warning. Preparedness against this type of landslide therefore, relies heavily on the identification of fracture-related unstable slopes. To mitigate the impacts of co-seismic landslide hazards, morpho-structural orientations or discontinuity sets were mapped in the field with the aid of a 2012 IFSAR Digital Terrain Model (DTM) with 5-meter pixel resolution and < 0.5 meter vertical accuracy. Coltop 3D software was then used to identify similar structures including measurement of their dip and dip directions. The chosen discontinuity sets were then keyed into Matterocking software to identify potential rock slide zones due to planar or wedged discontinuities. After identifying the structurally-controlled unstable slopes, the rock mass propagation extent of the possible rock slides was simulated using Conefall. The results were compared to a post-earthquake landslide inventory of 456 landslides. Out the total number of landslides identified from post-earthquake high-resolution imagery, 366 or 80% intersect the structural-controlled hazard areas of Bohol. The results show the potential of this method to identify co-seismic landslide hazard areas for disaster mitigation. Along with computer methods to simulate shallow landslides, and debris flow paths, located structurally-controlled unstable zones can be used to mark unsafe areas for settlement. The

  11. Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada

    NASA Astrophysics Data System (ADS)

    Blais-Stevens, A.; Behnia, P.

    2016-02-01

    This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC), by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect, surficial geology, plan curvature, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high-resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g. 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.

  12. Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada

    NASA Astrophysics Data System (ADS)

    Blais-Stevens, A.; Behnia, P.

    2015-05-01

    This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC) by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect (derived from a 5 m × 5 m DEM), surficial geology, permafrost distribution, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g., 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.

  13. Quantitative susceptibility mapping (QSM) of white matter multiple sclerosis lesions: interpreting positive susceptibility and the presence of iron

    PubMed Central

    Wisnieff, Cynthia; Ramanan, Sriram; Olesik, John; Gauthier, Susan; Wang, Yi; Pitt, David

    2014-01-01

    Purpose Within multiple sclerosis (MS) lesions iron is present in chronically activated microglia. Thus, iron detection with MRI might provide a biomarker for chronic inflammation within lesions. Here, we examine contributions of iron and myelin to magnetic susceptibility of lesions on quantitative susceptibility mapping (QSM). Methods Fixed MS brain tissue was assessed with MRI including gradient echo data, which was processed to generate field (phase), R2* and QSM. Five lesions were sectioned and evaluated by immunohistochemistry for presence of myelin, iron and microglia/macrophages. Two of the lesions had an elemental analysis for iron concentration mapping, and their phospholipid content was estimated from the difference in the iron and QSM data. Results Three of the five lesions had substantial iron deposition that was associated with microglia and positive susceptibility values. For the two lesions with elemental analysis, the QSM derived phospholipid content maps were consistent with myelin labeled histology. Conclusion Positive susceptibility values with respect to water indicate the presence of iron in MS lesions, though both demyelination and iron deposition contribute to QSM. PMID:25137340

  14. A combined field/remote sensing approach for characterizing landslide risk in coastal areas

    NASA Astrophysics Data System (ADS)

    Francioni, Mirko; Coggan, John; Eyre, Matthew; Stead, Doug

    2018-05-01

    Understanding the key factors controlling slope failure mechanisms in coastal areas is the first and most important step for analyzing, reconstructing and predicting the scale, location and extent of future instability in rocky coastlines. Different failure mechanisms may be possible depending on the influence of the engineering properties of the rock mass (including the fracture network), the persistence and type of discontinuity and the relative aspect or orientation of the coastline. Using a section of the North Coast of Cornwall, UK, as an example we present a multi-disciplinary approach for characterizing landslide risk associated with coastal instabilities in a blocky rock mass. Remotely captured terrestrial and aerial LiDAR and photogrammetric data were interrogated using Geographic Information System (GIS) techniques to provide a framework for subsequent analysis, interpretation and validation. The remote sensing mapping data was used to define the rock mass discontinuity network of the area and to differentiate between major and minor geological structures controlling the evolution of the North Coast of Cornwall. Kinematic instability maps generated from aerial LiDAR data using GIS techniques and results from structural and engineering geological surveys are presented. With this method, it was possible to highlight the types of kinematic failure mechanism that may generate coastal landslides and highlight areas that are more susceptible to instability or increased risk of future instability. Multi-temporal aerial LiDAR data and orthophotos were also studied using GIS techniques to locate recent landslide failures, validate the results obtained from the kinematic instability maps through site observations and provide improved understanding of the factors controlling the coastal geomorphology. The approach adopted is not only useful for academic research, but also for local authorities and consultancy's when assessing the likely risks of coastal instability.

  15. New Zealand's National Landslide Database

    NASA Astrophysics Data System (ADS)

    Rosser, B.; Dellow, S.; Haubrook, S.; Glassey, P.

    2016-12-01

    Since 1780, landslides have caused an average of about 3 deaths a year in New Zealand and have cost the economy an average of at least NZ$250M/a (0.1% GDP). To understand the risk posed by landslide hazards to society, a thorough knowledge of where, when and why different types of landslides occur is vital. The main objective for establishing the database was to provide a centralised national-scale, publically available database to collate landslide information that could be used for landslide hazard and risk assessment. Design of a national landslide database for New Zealand required consideration of both existing landslide data stored in a variety of digital formats, and future data, yet to be collected. Pre-existing databases were developed and populated with data reflecting the needs of the landslide or hazard project, and the database structures of the time. Bringing these data into a single unified database required a new structure capable of storing and delivering data at a variety of scales and accuracy and with different attributes. A "unified data model" was developed to enable the database to hold old and new landslide data irrespective of scale and method of capture. The database contains information on landslide locations and where available: 1) the timing of landslides and the events that may have triggered them; 2) the type of landslide movement; 3) the volume and area; 4) the source and debris tail; and 5) the impacts caused by the landslide. Information from a variety of sources including aerial photographs (and other remotely sensed data), field reconnaissance and media accounts has been collated and is presented for each landslide along with metadata describing the data sources and quality. There are currently nearly 19,000 landslide records in the database that include point locations, polygons of landslide source and deposit areas, and linear features. Several large datasets are awaiting upload which will bring the total number of landslides to

  16. Landslide Detection in the Carlyon Beach, WA Peninsula: Analysis Of High Resolution DEMs

    NASA Astrophysics Data System (ADS)

    Fayne, J.; Tran, C.; Mora, O. E.

    2017-12-01

    Landslides are geological events caused by slope instability and degradation, leading to the sliding of large masses of rock and soil down a mountain or hillside. These events are influenced by topography, geology, weather and human activity, and can cause extensive damage to the environment and infrastructure, such as the destruction of transportation networks, homes, and businesses. It is therefore imperative to detect early-warning signs of landslide hazards as a means of mitigation and disaster prevention. Traditional landslide surveillance consists of field mapping, but the process is expensive and time consuming. This study uses Light Detection and Ranging (LiDAR) derived Digital Elevation Models (DEMs) and k-means clustering and Gaussian Mixture Model (GMM) to analyze surface roughness and extract spatial features and patterns of landslides and landslide-prone areas. The methodology based on several feature extractors employs an unsupervised classifier on the Carlyon Beach Peninsula in the state of Washington to attempt to identify slide potential terrain. When compared with the independently compiled landslide inventory map, the proposed algorithm correctly classifies up to 87% of the terrain. These results suggest that the proposed methods and LiDAR-derived DEMs can provide important surface information and be used as efficient tools for digital terrain analysis to create accurate landslide maps.

  17. Two models for evaluating landslide hazards

    USGS Publications Warehouse

    Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

    2006-01-01

    Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.

  18. Analysis of the 2003 Varunawat Landslide, Uttarkashi, India using Earth Observation data

    NASA Astrophysics Data System (ADS)

    Vinod Kumar, K.; Lakhera, R. C.; Martha, Tapas R.; Chatterjee, R. S.; Bhattacharya, A.

    2008-08-01

    Mass movements such as landslides in mountainous terrains are natural degradation processes and one of the most important landscape-building factors. Varunawat Parbat overlooking Uttarkashi town witnessed a series of landslides on 23 September 2003 and the debris slides and rock falls continued for 2 weeks. This landslide complex was triggered due to the incessant rainfall prior to the event, and its occurrence led to the blockage of the pilgrim route to Gangotri (source of the Ganges river) and evacuation of thousands of people to safer places. Though there was no loss of lives due to timely evacuation, heavy losses to the property were reported. High-resolution stereoscopic earth observation data were acquired after the incidence to study the landslide in detail with emphasis on the cause of the landslide and mode of failure. Areas along the road and below the Varunawat foothill region are mapped for landslide risk. It was found that the foothill region of the Varunawat Parbat was highly disturbed by man-made activities and houses are dangerously located below steep slopes. The potential zones for landslides along with the existing active and old landslides are mapped. These areas are critical and their treatment with priority is required in order to minimise further landslide occurrences.

  19. ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations

    USGS Publications Warehouse

    Cauzzi, Carlo; Fah, Donat; Wald, David J.; Clinton, John; Losey, Stephane; Wiemer, Stefan

    2018-01-01

    In Switzerland, nearly all historical Mw ~ 6 earthquakes have induced damaging landslides, rockslides and snow avalanches that, in some cases, also resulted in damage to infrastructure and loss of lives. We describe the customisation to Swiss conditions of a globally calibrated statistical approach originally developed to rapidly assess earthquake-induced landslide likelihoods worldwide. The probability of occurrence of such earthquake-induced effects is modelled through a set of geospatial susceptibility proxies and peak ground acceleration. The predictive model is tuned to capture the observations from past events and optimised for near-real-time estimates based on USGS-style ShakeMaps routinely produced by the Swiss Seismological Service. Our emphasis is on the use of high-resolution geospatial datasets along with additional local information on ground failure susceptibility. Even if calibrated on historic events with moderate magnitudes, the methodology presented in this paper yields sensible results also for low-magnitude recent events. The model is integrated in the Swiss ShakeMap framework. This study has a high practical relevance to many Swiss ShakeMap stakeholders, especially those managing lifeline systems, and to other global users interested in conducting a similar customisation for their region of interest.

  20. Rainfall thresholds for possible landslide occurrence in Italy

    NASA Astrophysics Data System (ADS)

    Peruccacci, Silvia; Brunetti, Maria Teresa; Gariano, Stefano Luigi; Melillo, Massimo; Rossi, Mauro; Guzzetti, Fausto

    2017-08-01

    The large physiographic variability and the abundance of landslide and rainfall data make Italy an ideal site to investigate variations in the rainfall conditions that can result in rainfall-induced landslides. We used landslide information obtained from multiple sources and rainfall data captured by 2228 rain gauges to build a catalogue of 2309 rainfall events with - mostly shallow - landslides in Italy between January 1996 and February 2014. For each rainfall event with landslides, we reconstructed the rainfall history that presumably caused the slope failure, and we determined the corresponding rainfall duration D (in hours) and cumulated event rainfall E (in mm). Adopting a power law threshold model, we determined cumulated event rainfall-rainfall duration (ED) thresholds, at 5% exceedance probability, and their uncertainty. We defined a new national threshold for Italy, and 26 regional thresholds for environmental subdivisions based on topography, lithology, land-use, land cover, climate, and meteorology, and we used the thresholds to study the variations of the rainfall conditions that can result in landslides in different environments, in Italy. We found that the national and the environmental thresholds cover a small part of the possible DE domain. The finding supports the use of empirical rainfall thresholds for landslide forecasting in Italy, but poses an empirical limitation to the possibility of defining thresholds for small geographical areas. We observed differences between some of the thresholds. With increasing mean annual precipitation (MAP), the thresholds become higher and steeper, indicating that more rainfall is needed to trigger landslides where the MAP is high than where it is low. This suggests that the landscape adjusts to the regional meteorological conditions. We also observed that the thresholds are higher for stronger rocks, and that forested areas require more rainfall than agricultural areas to initiate landslides. Finally, we

  1. Advancements in near real time mapping of earthquake and rainfall induced landslides in the Avcilar Peninsula, Marmara Region

    NASA Astrophysics Data System (ADS)

    Coccia, Stella

    2014-05-01

    Stella COCCIA (1), Fiona THEOLEYRE (1), Pascal BIGARRE(1) , Semih ERGINTAV(2), Oguz OZEL(3) and Serdar ÖZALAYBEY(4) (1) National Institute of Industrial Environment and Risks (INERIS) Nancy, France, (2) Kandilli Observatory and Earthquake Research Institute (KOERI), Istanbul, Turkey, (3) Istanbul University (IU), Istanbul, Turkey, (4) TUBITAK MAM, Istanbul, Turkey The European Project MARsite (http://marsite.eu/), started in 2012 and leaded by the KOERI, aims to improve seismic risk evaluation and preparedness to face the next dreadful large event expected for the next three decades. MARsite is thus expected to move a "step forward" the most advanced monitoring technologies, and offering promising open databases to the worldwide scientific community in the frame of other European environmental large-scale infrastructures, such as EPOS (http://www.epos-eu.org/ ). Among the 11 work packages (WP), the main aim of the WP6 is to study seismically-induced landslide hazard, by using and improving observing and monitoring systems in geological, hydrogeotechnical and seismic onshore and offshore areas. One of the WP6 specific study area is the Avcilar Peninsula, situated between Kucukcekmece and Buyukcekmece Lakes in the north-west of the region of Marmara. There, more than 400 landslides are located. According to geological and geotechnical investigations and studies, soil movements of this area are related to underground water and pore pressure changes, seismic forces arising after earthquakes and decreasing sliding strength in fissured and heavily consolidated clays. The WP6 includes various tasks and one of these works on a methodology to develop a dynamic system to create combined earthquake and rainfall induced landslides hazard maps at near real time and automatically. This innovative system could be used to improve the prevention strategy as well as in disaster management and relief operations. Base on literature review a dynamic GIS platform is used to combine

  2. Analysis of Environmental Vulnerability in The Landslide Areas (Case Study: Semarang Regency)

    NASA Astrophysics Data System (ADS)

    Hani'ah; Firdaus, H. S.; Nugraha, A. L.

    2017-12-01

    The Land conversion can increase the risk of landslide disaster in Semarang Regency caused by human activity. Remote sensing and geographic information system to be used in this study to mapping the landslide areas because satellite image data can represent the object on the earth surface in wide area coverage. Satellite image Landsat 8 is used to mapping land cover that processed by supervised classification method. The parameters to mapping landslide areas are based on land cover, rainfall, slope, geological factors and soil types. Semarang Regency have the minimum value of landslide is 1.6 and the maximum value is 4.3, which is dominated by landslide prone areas about 791.27 km2. The calculation of the environmental vulnerability index in the study area is based on Perka BNPB No. 2/2012. Accumulation score of environmental vulnerability index is moderate value, that means environment condition must be considered, such as vegetation as ground cover and many others aspects. The range of NDVI value shows that density level in conservation areas (0.030 - 0.844) and conservation forest (0.045 - 0.849), which rarely until high density level. The results of this study furthermore can be assessed to reduce disaster risks from landslide as an effort of disaster preventive.

  3. Comparison of Structurally Controlled Landslide Hazard Simulation to the Co-seismic Landslides Caused by the M 7.2 2013 Bohol Earthquake.

    NASA Astrophysics Data System (ADS)

    Galang, J. A. M. B.; Eco, R. C.; Lagmay, A. M. A.

    2014-12-01

    The M_w 7.2 October 15, 2013 Bohol earthquake is one of the more destructive earthquake to hit the Philippines in the 21st century. The epicenter was located in Sagbayan municipality, central Bohol and was generated by a previously unmapped reverse fault called the "Inabanga Fault". The earthquake resulted in 209 fatalities and over 57 million USD worth of damages. The earthquake generated co-seismic landslides most of which were related to fault structures. Unlike rainfall induced landslides, the trigger for co-seismic landslides happen without warning. Preparations for this type of landslides rely heavily on the identification of fracture-related slope instability. To mitigate the impacts of co-seismic landslide hazards, morpho-structural orientations of discontinuity sets were mapped using remote sensing techniques with the aid of a Digital Terrain Model (DTM) obtained in 2012. The DTM used is an IFSAR derived image with a 5-meter pixel resolution and approximately 0.5 meter vertical accuracy. Coltop 3D software was then used to identify similar structures including measurement of their dip and dip directions. The chosen discontinuity sets were then keyed into Matterocking software to identify potential rock slide zones due to planar or wedged discontinuities. After identifying the structurally-controlled unstable slopes, the rock mass propagation extent of the possible rock slides was simulated using Conefall. Separately, a manually derived landslide inventory has been performed using post-earthquake satellite images and LIDAR. The results were compared to the landslide inventory which identified at least 873 landslides. Out of the 873 landslides identified through the inventory, 786 or 90% intersect the simulated structural-controlled landslide hazard areas of Bohol. The results show the potential of this method to identify co-seismic landslide hazard areas for disaster mitigation. Along with computer methods to simulate shallow landslides, and debris flow

  4. Data management with a landslide inventory of the Franconian Alb (Germany) using a spatial database and GIS tools

    NASA Astrophysics Data System (ADS)

    Bemm, Stefan; Sandmeier, Christine; Wilde, Martina; Jaeger, Daniel; Schwindt, Daniel; Terhorst, Birgit

    2014-05-01

    ), informations on location, landslide types and causes, geomorphological positions, geometries, hazards and damages, as well as assessments related to the activity of landslides. Furthermore, there are stored spatial objects, which represent the components of a landslide, in particular the scarps and the accumulation areas. Besides, waterways, map sheets, contour lines, detailed infrastructure data, digital elevation models, aspect and slope data are included. Examples of spatial queries to the database are intersections of raster and vector data for calculating values for slope gradients or aspects of landslide areas and for creating multiple, overlaying sections for the comparison of slopes, as well as distances to the infrastructure or to the next receiving drainage. Furthermore, getting informations on landslide magnitudes, distribution and clustering, as well as potential correlations concerning geomorphological or geological conditions. The data management concept in this study can be implemented for any academic, public or private use, because it is independent from any obligatory licenses. The created spatial database offers a platform for interdisciplinary research and socio-economic questions, as well as for landslide susceptibility and hazard indication mapping. Obe, R.O., Hsu, L.S. 2011. PostGIS in action. - pp 492, Manning Publications, Stamford

  5. Insight From the Statistics of Nothing: Estimating Limits of Change Detection Using Inferred No-Change Areas in DEM Difference Maps and Application to Landslide Hazard Studies

    NASA Astrophysics Data System (ADS)

    Haneberg, W. C.

    2017-12-01

    Remote characterization of new landslides or areas of ongoing movement using differences in high resolution digital elevation models (DEMs) created through time, for example before and after major rains or earthquakes, is an attractive proposition. In the case of large catastrophic landslides, changes may be apparent enough that simple subtraction suffices. In other cases, statistical noise can obscure landslide signatures and place practical limits on detection. In ideal cases on land, GPS surveys of representative areas at the time of DEM creation can quantify the inherent errors. In less-than-ideal terrestrial cases and virtually all submarine cases, it may be impractical or impossible to independently estimate the DEM errors. Examining DEM difference statistics for areas reasonably inferred to have no change, however, can provide insight into the limits of detectability. Data from inferred no-change areas of airborne LiDAR DEM difference maps of the 2014 Oso, Washington landslide and landslide-prone colluvium slopes along the Ohio River valley in northern Kentucky, show that DEM difference maps can have non-zero mean and slope dependent error components consistent with published studies of DEM errors. Statistical thresholds derived from DEM difference error and slope data can help to distinguish between DEM differences that are likely real—and which may indicate landsliding—from those that are likely spurious or irrelevant. This presentation describes and compares two different approaches, one based upon a heuristic assumption about the proportion of the study area likely covered by new landslides and another based upon the amount of change necessary to ensure difference at a specified level of probability.

  6. National Map Data Base On Landslide Prerequisites In Clay and Silt Areas - Development of Prototype

    NASA Astrophysics Data System (ADS)

    Viberg, Leif

    Swedish geotechnical institute, SGI, has in co-operation with Swedish geologic survey, Lantmateriet (land surveying) and Swedish Rescue Service developed a theme database on landslide prerequisites in clay and silt areas. The work is carried out on commission of the Swedish government. A report with suggestions for production of the database has been delivered to the government. The database is a prototype, which has been tested in an area in northern Sweden. Recommended presentation map scale is about 1:50 000. Distribution of the database via Internet is discussed. The aim of the database is to use it as a modern planning tool in combination with other databases, e g databases on flooding prognoses. The main use is supposed to be in early planning stages, e g for new building and infrastructure development and for risk analyses. The database can also be used in more acute cases, e g for risk analyses and rescue operations in connection with flooding over large areas. Users are supposed to be municipal and county planners and rescue services, infrastructure planners, consultants and assurance companies. The database is constructed by combination of two existing databases: Elevation data and soil map data. The investigation area is divided into three zones with different stability criteria: 1. Clay and silt in sloping ground or adjoining water. 2. Clay and silt in flat ground. 3. Rock and other soils than clay and silt. The geometrical and soil criteria for the zones are specified in an algoritm, that will do the job to sort out the different zones. The algoritm is thereby using data from the elevation and soil databases. The investigation area is divided into cells (raster format) with 5 x 5 m side length. Different algoritms had to be developed before reasonable calculation time was reached. The theme may be presented on screen or as a map plot. A prototype map has been produced for the test area. A description is accompanying the map. The database is suggested

  7. Analysis Of Landslide Materials Spreading In Bendan Dhuwur Village Gajahmungkur Subdistrict Semarang City

    NASA Astrophysics Data System (ADS)

    Trisnawati, Devina; Najib; Kusuma, Istiqomah Ari; Husna, Anissa Fitratul

    2018-02-01

    Bendan Dhuwur is one of area in Semarang city, which continuously has landslide problem. This problem resulted in damage of some buildings and main road. Landslide materials/coluvial have been estimated lays on under those infrastructures and tend to move during rainy season. Therefore, it needs to understand the spread of coluvial to minimize the effect of landslide. Remote sensing method has been used to analyze multi temporal image for mapping landslide materials from different years recorded direction of creep and spread of coluvials. This method has been combined with surface and subsurface data from mapping and resistivity data. The analysis result on map which show that the coluvial material spreads on the south side, beneath the University of Tujuh Belas Agustus construction and Pawiyatan Luhur road. Its move to east leads to the Kaligarang river.

  8. Semi-quantitative assessment of the physical vulnerability of buildings for the landslide risk analysis. A case study in the Loures municipality, Lisbon district, Portugal

    NASA Astrophysics Data System (ADS)

    Guillard-Gonçalves, Clémence; Zêzere, José Luis; Pereira, Susana; Garcia, Ricardo

    2016-04-01

    The physical vulnerability of the buildings of Loures (a Portuguese municipality) to landslides was assessed, and the landslide risk was computed as the product of the landslide hazard by the vulnerability and the market economic value of the buildings. First, the hazard was assessed by combining the spatio-temporal probability and the frequency-magnitude relationship of the landslides, which was established by plotting the probability of a landslide area. The susceptibility of deep-seated and shallow landslides was assessed by a bi-variate statistical method and was mapped. The annual and multiannual spatio-temporal probabilities were estimated, providing a landslide hazard model. Then, an assessment of buildings vulnerability to landslides, based on an inquiry of a pool of landslide European experts, was developed and applied to the study area. The inquiry was based on nine magnitude scenarios and four structural building types. A sub-pool of the landslide experts who know the study area was extracted from the pool, and the variability of the answers coming from the pool and the sub-pool was assessed with standard deviation. Moreover, the average vulnerability of the basic geographic entities was compared by changing the map unit and applying the vulnerability to all the buildings of a test site (included in the study area), the inventory of which was listed on the field. Next, the market economic value of the buildings was calculated using an adaptation of the Portuguese Tax Services approach. Finally, the annual and multiannual landslide risk was computed for the nine landslide magnitude scenarios and different spatio-temporal probabilities by multiplying the potential loss (Vulnerability × Economic Value) by the hazard probability. As a rule, the vulnerability values given by the sub-pool of experts who know the study area are higher than those given by the European experts, namely for the high magnitude landslides. The obtained vulnerabilities vary from 0

  9. Monitoring landslide kinematics by multi-temporal radar interferometry - the Corvara landslide case study

    NASA Astrophysics Data System (ADS)

    Thiebes, Benni; Cuozzo, Giovanni; Callegari, Mattia; Schlögel, Romy; Mulas, Marco; Corsini, Alessandro; Mair, Volkmar

    2016-04-01

    Corvara landslide in the Italian Dolomites is slow-moving landslide on which extensive research activities have been carried out since the 1990ies, including sub-surface techniques (e.g. drillings, piezometers and inclinometers), surface methods (e.g. geomorphological mapping and GPS measurements), and remote sensing techniques (e.g. multi-temporal radar interferometry (MTI), and recently amplitude-based offset-tracking and UAV-based photogrammetry). The currently active volume of Corvara landslide has been estimated to be approximately 25 million m³ with shear surfaces at depths of 40 m. Displacement velocities greatly vary spatially and temporally, with only a few cm per year in the accumulation zone, and more than 20 m per year in the highly active source zone. Autumn rainfall and spring snow melt, as well as accumulation of snow during winter have been identified as the major displacement triggering and accelerating events. The ongoing landslide movements pose a threat to the municipality of Corvara, the national road 244, extensive ski resort infrastructure and a golf course. Over the last years, the focus for monitoring the Corvara landslide was put on MTI using 16 artificial corner reflectors and on permanent and periodic differential GPS measurements. This aimed for (1) assessing the ongoing displacements of an active and complex landslide, and (2) analysing the benefits and limitations of MTI for landslide monitoring from the perspective of geomorphologists but also for administrative end-user such as civil protection and Geological surveys. Here, we present the latest results of these analyses, and report on the potential of MTI and related investigations, as well as future fields of research.

  10. Landslides in everyday life: An interdisciplinary approach to understanding vulnerability in the Himalayas

    NASA Astrophysics Data System (ADS)

    Sudmeier-Rieux, K.; Breguet, A.; Dubois, J.; Jaboyedoff, M.

    2009-04-01

    Several thousand landslides were triggered by the Kashmir earthquake, scarring the hillside with cracks. Monsoon rains continue to trigger landslides, which have increased the exposure of populations because of lost agricultural lands, blocked roads and annual fatalities due to landslides. The great majority of these landslides are shallow and relatively small but greatly impacting the population. In this region, landslides were a factor before the earthquake, mainly due to road construction and gravel excavation, but the several thousand landslides triggered by the earthquake have completely overwhelmed the local population and authorities. In Eastern Nepal, the last large earthquake to hit this region occurred in 1988, also triggering numerous landslides and cracks. Here, landslides can be considered a more common phenomenon, yet coping capacities amount to local observations of landslide movement, subsequent abandonment of houses and land as they become too dangerous. We present a comparative case study from Kashmir, Pakistan and Eastern Nepal, highlighting an interdisciplinary approach to understanding the complex interactions between land use, landslides and vulnerability. Our approach sets out to understand underlying causes of the massive landslides triggered by the 2005 earthquake in Kashmir, Pakistan, and also the increasing number of landslides in Nepal. By approaching the issue of landslides from multiple angles (risk perceptions, land use, local coping capacities, geological assessment, risk mapping) and multiple research techniques (remote sensing, GIS, geological assessment, participatory mapping, focus groups) we are better able to create a more complete picture of the "hazardscape". We find that by combining participatory social science research with hazard mapping, we obtain a more complete understanding of underlying causes, coping strategies and possible mitigation options, placing natural hazards in the context of everyday life. This method is

  11. System designed for issuing landslide alerts in the San Francisco Bay area

    USGS Publications Warehouse

    Finley, D.

    1987-01-01

    A system for forecasting landslides during major storms has been developed for the San Francisco Bay area by the U.S Geological Survey and was successfully tested during heavy storms in the bay area during February 1986. Based on the forecasts provided by the USGS, the National Weather Service (NWS) included landslide warnings in its regular weather forecasts or in special weather statements transmitted to local radio and television stations and other news media. USGS scientists said the landslide forecasting and warning system for the San Francisco Bay area can be used as a prototype in developing similar systems for other parts of the Nation susceptible to landsliding. Studies show damage from landslides in the United States averages an estimated $1.5 billion per year. 

  12. Rainfall-triggered landslides, anthropogenic hazards, and mitigation strategies

    USGS Publications Warehouse

    Larsen, M.C.

    2008-01-01

    Rainfall-triggered landslides are part of a natural process of hillslope erosion that can result in catastrophic loss of life and extensive property damage in mountainous, densely populated areas. As global population expansion on or near steep hillslopes continues, the human and economic costs associated with landslides will increase. Landslide hazard mitigation strategies generally involve hazard assessment mapping, warning systems, control structures, and regional landslide planning and policy development. To be sustainable, hazard mitigation requires that management of natural resources is closely connected to local economic and social interests. A successful strategy is dependent on a combination of multi-disciplinary scientific and engineering approaches, and the political will to take action at the local community to national scale.

  13. Mapping Geohazards in the Churia Region of Nepal: An Application of Remote Sensing and Geographic Information Systems

    NASA Astrophysics Data System (ADS)

    Bannister, Terri

    The Churia region of Nepal is experiencing serious environmental degradation due to landslides, monsoon flooding, land use changes, and gravel excavation. The objectives of this study were to quantify the temporal change of landslides as related to changes in land use/deforestation/urbanization, to quantify the temporal change and extent of river inundation in the Terai, to quantify the extent to which stone quarrying exacerbates the degradation process, and to generate a landslide hazard risk map. Gravel extraction and precipitation data, along with field work and geospatial methods, were used to map degradation by focusing on the centrally located districts of Bara, Rautahat, and Makwanpur. Landsat land use classifications were conducted on imagery from 1976, 1988, 1999, and 2015. A modified Normalized Difference Mid-Infrared (NDMIDIR) algorithm was created by incorporating slope, elevation, and land use types to identify landslide scars. A GIS model using weighted landslide variables derived from remote sensing and GIS methods to predict landslide susceptibility was created. These variables include hydrology, settlement, lithology, geology, precipitation, infrastructure, elevation, slope, aspect, land use, and previous landslides. Gravel excavation in 2007/2008 was nearly 700% higher than in 2001/2002. The Normalized Difference Vegetation Index (NDVI) results showed that the study area is losing 1.03% forest cover annually; in 1977, there was 70% forest cover, but only 32% forest cover remained in 2016. The accuracy assessment of the 2015 Landsat 8 land use classification was 79%. NDMIDIR results showed that from 1988 to 2016, the total area representing landslide scars increased from 7.26km2 to 8.73 km2. The weighted variable GIS model output map indicated that 70% of the Siwalik zone and southern Lesser Himalayan zone in the three study districts have significant risk of landslides. Landslides and flooding from heavy monsoon rain, deforestation to develop

  14. Debris-flow initiation from large, slow-moving landslides

    USGS Publications Warehouse

    Reid, M.E.; Brien, D.L.; LaHusen, R.G.; Roering, J.J.; de la Fuente, J.; Ellen, S.D.; ,

    2003-01-01

    In some mountainous terrain, debris flows preferentially initiate from the toes and margins of larger, deeper, slower-moving landslides. During the wet winter of 1997, we began real-time monitoring of the large, active Cleveland Corral landslide complex in California, USA. When the main slide is actively moving, small, shallow, first-time slides on the toe and margins mobilize into debris flows and travel down adjacent gullies. We monitored the acceleration of one such failure; changes in velocity provided precursory indications of rapid failure. Three factors appear to aid the initiation of debris flows at this site: 1) locally steepened ground created by dynamic landslide movement, 2) elevated pore-water pressures and abundant soil moisture, and 3) locally cracked and dilated materials. This association between debris flows and large landslides can be widespread in some terrain. Detailed photographic mapping in two watersheds of northwestern California illustrates that the areal density of debris-flow source landsliding is about 3 to 7 times greater in steep geomorphically fresher landslide deposits than in steep ground outside landslide deposits. ?? 2003 Millpress.

  15. Morphometric analysis of landslide in the Mountain Region of the State of Rio de Janeiro in Brazi: the case study of D'anta's watershed

    NASA Astrophysics Data System (ADS)

    Carvalho Araújo, João Paulo; da Silva, Lúcia Maria; Avear, Marcello; Dourado, Francisco; Ferreira Fernandes, Nelson

    2013-04-01

    Mass movements are recurrent phenomena in the whole Mountain Region of the State of Rio de Janeiro in Brazil. These events actively participate in the relief evolution and are also responsible for many damages and loss of human lives. The triggering of these events depends on the natural environment and the preparatory and immediate action of the physical, biotic and human agents responsible for these processes. This work is based on the hypothesis in which the topographical conditions have a major effect on the spatial distribution of translational landslides caused by decreased of the internal resistance of the material mobilized. Therefore, the purpose of this study is to identify the topographical conditions favorable to landslide triggering based on morphometric analysis in a pilot watershed - D'antás watershed - located in the mountainous region of the State of Rio de Janeiro. The indices include the topographic wetness index (TWI), contributing area, slope angle and elevation and were derived from 5-m grid digital terrain model, computed on a Geographic Information System (GIS). The maps produced allowed the analysis of topographic influence on the landslides distribution from the indices of frequency classes (F), concentration of scars (CC) and potential of landslide (PL). The landscape sectors that are more likely to be affected by landslides were the ones where the elevation ranges from 1070m - 1187m, slope angle between 40.95° and 47.77°, contributing area between (log10) 1.32 m² - 1.95 m² and topographic wetness index between 7.11 to 9.59. This work provides important information which may help in the decision-making process, using fewer data and indices of easy application. Finally, the results obtained will subsidize of a landslide susceptibility map through the implementation of the conditional probability method aimed at predicting and mitigating of the damage caused by landslides.

  16. Prototyping an Early-warning System for Rainfall-triggered Landslides on a Regional Scale Using a Physically-based Model and Remote Sensing Datasets

    NASA Astrophysics Data System (ADS)

    Liao, Z.; Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.; Sassa, K.; Karnawati, D.; Fathani, F.

    2010-12-01

    Recent advancements in the availability of remotely sensed datasets provide an opportunity to advance the predictability of rainfall-triggered landslides at larger spatial scales. An early-warning system based on a physical landslide model and remote sensing information is used to simulate the dynamical response of the soil water content to the spatiotemporal variability of rainfall in complex terrain. The system utilizes geomorphologic datasets including a 30-meter ASTER DEM, a 1-km downscaled FAO soil map, and satellite-based Tropical Rainfall Measuring Mission (TRMM) precipitation. The applied physical model SLIDE (SLope-Infiltration-Distributed Equilibrium) defines a direct relationship between a factor of safety and the rainfall depth on an infinite slope. This prototype model is applied to a case study in Honduras during Hurricane Mitch in 1998 and a secondary case of typhoon-induced shallow landslides over Java Island, Indonesia. In Honduras, two study areas were selected which cover approximately 1,200 square kilometers and where a high density of shallow landslides occurred. The results were quantitatively evaluated using landslide inventory data compiled by the United States Geological Survey (USGS) following Hurricane Mitch, and show a good agreement between the modeling results and observations. The success rate for accurately estimating slope failure locations reached as high as 78% and 75%, while the error indices were 35% and 49%, respectively for each of the two selected study areas. Advantages and limitations of this application are discussed with respect to future assessment and challenges of performing a slope-stability estimation using coarse data at 1200 square kilometers. In Indonesia, the system has been applied over the whole Java Island. The prototyped early-warning system has been enhanced by integration of a susceptibility mapping and a precipitation forecasting model (i.e. Weather Research Forecast). The performance has been evaluated

  17. Combining heuristic and statistical techniques in landslide hazard assessments

    NASA Astrophysics Data System (ADS)

    Cepeda, Jose; Schwendtner, Barbara; Quan, Byron; Nadim, Farrokh; Diaz, Manuel; Molina, Giovanni

    2014-05-01

    As a contribution to the Global Assessment Report 2013 - GAR2013, coordinated by the United Nations International Strategy for Disaster Reduction - UNISDR, a drill-down exercise for landslide hazard assessment was carried out by entering the results of both heuristic and statistical techniques into a new but simple combination rule. The data available for this evaluation included landslide inventories, both historical and event-based. In addition to the application of a heuristic method used in the previous editions of GAR, the availability of inventories motivated the use of statistical methods. The heuristic technique is largely based on the Mora & Vahrson method, which estimates hazard as the product of susceptibility and triggering factors, where classes are weighted based on expert judgment and experience. Two statistical methods were also applied: the landslide index method, which estimates weights of the classes for the susceptibility and triggering factors based on the evidence provided by the density of landslides in each class of the factors; and the weights of evidence method, which extends the previous technique to include both positive and negative evidence of landslide occurrence in the estimation of weights for the classes. One key aspect during the hazard evaluation was the decision on the methodology to be chosen for the final assessment. Instead of opting for a single methodology, it was decided to combine the results of the three implemented techniques using a combination rule based on a normalization of the results of each method. The hazard evaluation was performed for both earthquake- and rainfall-induced landslides. The country chosen for the drill-down exercise was El Salvador. The results indicate that highest hazard levels are concentrated along the central volcanic chain and at the centre of the northern mountains.

  18. Landslide Distribution, Damage and Land Use Interactions During the 2004 Chuetsu Earthquake

    NASA Astrophysics Data System (ADS)

    Sidle, R. C.; Trandafir, A. C.; Kamai, T.

    2005-05-01

    A series of earthquakes struck Niigata Prefecture, Japan, on 23 October 2004 killing about 40 people and injuring about 3000. These earthquakes were characterized by a shallow focal depth (13 km) that generated strong levels of ground motion, resulting in extensive damage and thousands of landslides throughout the region. Most landslides on natural slopes occurred in the regional geological structure consisting of sandy siltstone and thin-bedded alternations of sandstone and siltstone. Earthquakes exacerbate such potential instabilities by the ground motion induced and the enhancement of pore water pressure in wet regoliths. The three strongest earthquakes occurred within a period of less than 40 minutes, and had sequential magnitudes (JMA) of 6.8, 6.3, and 6.5. The highest density of landslides (12/km2) was mapped within a 2.9 km radius of the M6.5 epicenter near Yamakoshi village; about 4 times higher density compared to the other epicenters located to the east and west. This higher density may be a consequence of the cumulative shaking effects associated with the two earlier earthquakes of M6.8 and 6.5, in addition to the topographic and geologic factors controlling the stability of the region. Roads, residential fills, agricultural terraces on hillslopes, and other earthworks increased the susceptibility of sites to slope failure. Numerous earthquake-induced failures in terraces and adjacent hillslopes around rice paddy fields occurred near Yamakoshi village. A housing development in Nagaoka city constructed on an old earthflow suffered from severe damage to fill slopes during the earthquake. Nearly saturated conditions in these deep fills together with poor drainage systems contributed to the landslide damages. Clearly, land use activities in rural and urban areas exacerbated the extent of earthquake-triggered landslides.

  19. Landslides from the February 4, 1976, Guatemala earthquake

    USGS Publications Warehouse

    Harp, Edwin L.; Wilson, Raymond C.; Wieczorek, Gerald F.

    1981-01-01

    The M (Richter magnitude) = 7.5 Guatemala earthquake of February 4, 1976, generated more than 10,000 landslides throughout an area of approximately 16,000 km2. These landslides caused hundreds of fatalities as well as extensive property damage. Landslides disrupted both highways and the railroad system and thus severely hindered early rescue efforts. In Guatemala City, extensive property damage and loss of life were due to ground failure beneath dwellings built too close to the edges of steeply incised canyons. We have recorded the distribution of landslides from this earthquake by mapping individual slides at a scale of 1:50,000 for most of the landslide-affected area, using high-altitude aerial photography. The highest density of landslides was in the highlands west of Guatemala City. The predominant types of earthquake-triggered landslides were rock falls and debris slides of less than 15,000 m3 volume; in addition to these smaller landslides, 11 large landslides had volumes of more than 100,000 m3. Several of these large landslides posed special hazards to people and property from lakes impounded by the landslide debris and from the ensuing floods that occurred upon breaching and rapid erosion of the debris. The regional landslide distribution was observed to depend on five major factors: (1) seismic intensity; (2) lithology: 90 percent of all landslides were within Pleistocene pumice deposits; (3) slope steepness; (4) topographic amplification of seismic ground motion; and (5) regional fractures. The presence of preearthquake landslides had no apparent effect on the landslide distribution, and landslide concentration in the Guatemala City area does not correlate with local seismic-intensity data. The landslide concentration, examined at this scale, appears to be governed mainly by lithologic differences within the pumice deposits, preexisting fractures, and amplification of ground motion by topography-all factors related to site conditions.

  20. Rainfall-induced landslide vulnerability Assessment in urban area reflecting Urban structure and building characteristics

    NASA Astrophysics Data System (ADS)

    Park, C.; Cho, M.; Lee, D.

    2017-12-01

    Landslide vulnerability assessment methodology of urban area is proposed with urban structure and building charateristics which can consider total damage cost of climate impacts. We used probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by slope stability analysis and Monte Carlo simulations. And We combined debris flows with considering spatial movements under topographical condition and built environmental condition. Urban vulnerability of landslide is assessed by two categories: physical demages and urban structure aspect. Physical vulnerability is related to buildings, road, other ubran infra. Urban structure vulnerability is considered a function of the socio-economic factors, trigger factor of secondary damage, and preparedness level of the local government. An index-based model is developed to evaluate the life and indirect damage under landslide as well as the resilience ability against disasters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. The general trend found in this study indicates that the higher population density areas under a weaker fiscal condition that are located at the downstream of mountainous areas are more vulnerable than the areas in opposite conditions.