Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Target-specific digital soil mapping supporting terroir mapping in Tokaj Wine Region, Hungary

NASA Astrophysics Data System (ADS)

Takács, Katalin; Szabó, József; Laborczi, Annamária; Szatmári, Gábor; László, Péter; Koós, Sándor; Bakacsi, Zsófia; Pásztor, László

2016-04-01

Tokaj Wine Region - located in Northeast-Hungary, at Hegyalja, in Tokaj Mountains - is a historical region for botrityzed dessert wine making. Very recently the sustainable quality wine production in the region was targeted, which requires detailed and "terroir-based approach" characterization of viticultural land and the survey of the state of vineyards. Terroir is a homogeneous area that relates to both environmental and cultural factors, that influence the grape and wine quality. Soil plays dominant role determining the viticultural potential and terroir delineation. According to viticultural experts the most relevant soil properties are drainage, water holding capacity, soil depth and pH. Not all of these soil characteristics can be directly measured, therefore the synthesis of observed soil properties is needed to satisfy the requirements of terroir mapping. The sampling strategy was designed to be representative to the combinations of basic environmental parameters (slope, aspect and geology) which determine the main soil properties of the vineyards. Field survey was carried out in two steps. At first soil samples were collected from 200 sites to obtain a general view about the pedology of the area. In the second stage further 650 samples were collected and the sampling strategy was designed based on spatial annealing technique taking into consideration the results of the preliminary survey and the local characteristics of vineyards. The data collection regarded soil type, soil depth, parent material, rate of erosion, organic matter content and further physical and chemical soil properties which support the inference of the proper soil parameters. In the framework of the recent project 33 primary and secondary soil property, soil class and soil function maps were compiled. A set of the resulting maps supports to meet the demands of the Hungarian standard viticultural potential assessment, while the majority of the maps is intended to be applied for terroir delineation. The spatial extension was performed by two, different methods which are widely applied in digital soil mapping. Regression kriging was used for creating continuous soil property maps, category type soil maps were compiled by classification trees method. Accuracy assessment was also provided for all of the soil map products. Our poster will present the summary of the project workflow - the design of sampling strategy, field survey, digital soil mapping process - and some examples of the resulting soil property maps indicating their applicability in terroir delineation. Acknowledgement: The authors are grateful to the Tokaj Kereskedöház Ltd. which has been supporting the project for the survey of the state of vineyards. Digital soil mapping was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

The Dokuchaev hypothesis as a basis for predictive digital soil mapping (on the 125th anniversary of its publication)

NASA Astrophysics Data System (ADS)

Florinsky, I. V.

2012-04-01

Predictive digital soil mapping is widely used in soil science. Its objective is the prediction of the spatial distribution of soil taxonomic units and quantitative soil properties via the analysis of spatially distributed quantitative characteristics of soil-forming factors. Western pedometrists stress the scientific priority and principal importance of Hans Jenny's book (1941) for the emergence and development of predictive soil mapping. In this paper, we demonstrate that Vasily Dokuchaev explicitly defined the central idea and statement of the problem of contemporary predictive soil mapping in the year 1886. Then, we reconstruct the history of the soil formation equation from 1899 to 1941. We argue that Jenny adopted the soil formation equation from Sergey Zakharov, who published it in a well-known fundamental textbook in 1927. It is encouraging that this issue was clarified in 2011, the anniversary year for publications of Dokuchaev and Jenny.

The use of crop rotation for mapping soil organic content in farmland

NASA Astrophysics Data System (ADS)

Yang, Lin; Song, Min; Zhu, A.-Xing; Qin, Chengzhi

2017-04-01

Most of the current digital soil mapping uses natural environmental covariates. However, human activities have significantly impacted the development of soil properties since half a century, and therefore become an important factor affecting soil spatial variability. Many researches have done field experiments to show how soil properties are impacted and changed by human activities, however, spatial variation data of human activities as environmental covariates have been rarely used in digital soil mapping. In this paper, we took crop rotation as an example of agricultural activities, and explored its effectiveness in characterizing and mapping the spatial variability of soil. The cultivated area of Xuanzhou city and Langxi County in Anhui Province was chosen as the study area. Three main crop rotations,including double-rice, wheat-rice,and oilseed rape-cotton were observed through field investigation in 2010. The spatial distribution of the three crop rotations in the study area was obtained by multi-phase remote sensing image interpretation using a supervised classification method. One-way analysis of variance (ANOVA) for topsoil organic content in the three crop rotation groups was performed. Factor importance of seven natural environmental covariates, crop rotation, Land use and NDVI were generated by variable importance criterion of Random Forest. Different combinations of environmental covariates were selected according to the importance rankings of environmental covariates for predicting SOC using Random Forest and Soil Landscape Inference Model (SOLIM). A cross validation was generated to evaluated the mapping accuracies. The results showed that there were siginificant differences of topsoil organic content among the three crop rotation groups. The crop rotation is more important than parent material, land use or NDVI according to the importance ranking calculated by Random Forest. In addition, crop rotation improved the mapping accuracy, especially for the flat clutivated area. This study demonstrates the usefulness of human activities in digital soil mapping and thus indicates the necessity for human activity factors in digital soil mapping studies.

A guide for the use of digital elevation model data for making soil surveys

USGS Publications Warehouse

Klingebiel, A.A.; Horvath, Emil H.; Reybold, William U.; Moore, D.G.; Fosnight, E.A.; Loveland, Thomas R.

1988-01-01

The intent of this publication is twofold: (1) to serve as a user guide for soil scientists and others interested in learning about the value and use of digital elevation model (DEM) data in making soil surveys and (2) to provide documentation of the Soil Landscape Analysis Project (SLAP). This publication provides a step-by-step guide on how digital slope-class maps are adjusted to topographic maps and orthophotoquads to obtain accurate slope-class maps, and how these derivative maps can be used as a base for soil survey premaps. In addition, guidance is given on the use of aspect-class maps and other resource data in making pre-maps. The value and use of tabular summaries are discussed. Examples of the use of DEM products by the authors and by selected field soil scientists are also given. Additional information on SLAP procedures may be obtained from USDA, Soil Conservation Service, Soil Survey Division, P.O. Box 2890, Washington, D.C. 20013, and from references (Horvath and others, 1987; Horvath and others, 1983; Klingebiel and others, 1987; and Young, 1987) listed in this publication. The slope and aspect products and the procedures for using these products have evolved during 5 years of cooperative research with the USDA, Soil Conservation Service and Forest Service, and the USDI, Bureau of Land Management.

Neighborhood size of training data influences soil map disaggregation

USDA-ARS?s Scientific Manuscript database

Soil class mapping relies on the ability of sample locations to represent portions of the landscape with similar soil types; however, most digital soil mapping (DSM) approaches intersect sample locations with one raster pixel per covariate layer regardless of pixel size. This approach does not take ...

Digital soils survey map of the Patagonia Mountains, Arizona

USGS Publications Warehouse

Norman, Laura; Wissler, Craig; Guertin, D. Phillip; Gray, Floyd

2002-01-01

The ‘Soil Survey of Santa Cruz and Parts of Cochise and Pima Counties, Arizona,' a product of the USDA’s Soil Conservation Service and the Forest Service in cooperation with the Arizona Agricultural Experiment Station, released in 1979, was created according to the site conditions in 1971, when soil scientists identified soils types on aerial photographs. The scale at which these maps were published is 1:20,000. These soil maps were automated for incorporation into the hydrologic modeling within a GIS. The aerial photos onto which the soils units were drawn had not been orthoganalized, and contained distortion. A total of 15 maps composed the study area. These maps were scanned into TIFF format using an 8-bit black and white drum scanner at 100 dpi. The images were imported into ERDAS IMAGINE and the white borders were removed through subset decollaring processes. Five CD-ROM’s containing Digital Orthophoto Quarter Quads (DOQQ’s) were used to register and rectify the scanned soils maps. Polygonal data was then attributed according to the datasets.

DOSoReMI.hu: collection of countrywide DSM products partly according to GSM.net specifications, partly driven by specific user demands

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Illés, Gábor; Bakacsi, Zsófia; Szabó, József

2017-04-01

Due to former soil surveys and mapping activities significant amount of soil information has accumulated in Hungary. In traditional soil mapping the creation of a new map was troublesome and laborious. As a consequence, robust maps were elaborated and rather the demands were fitted to the available map products. Until recently spatial soil information demands have been serviced with the available datasets either in their actual form or after certain specific and often enforced, thematic and spatial inference. Considerable imperfection may occur in the accuracy and reliability of the map products, since there might be significant discrepancies between the available data and the expected information. The DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project was started intentionally for the renewal of the national soil spatial infrastructure in Hungary. During our activities we have significantly extended the potential, how soil information requirements could be satisfied. Soil property, soil type as well as functional soil maps were targeted. The set of the applied digital soil mapping techniques has been gradually broadened incorporating and eventually integrating geostatistical, data mining and GIS tools. Soil property maps have been compiled partly according to GSM.net specifications, partly by slightly or more strictly changing some of their predefined parameters (depth intervals, pixel size, property etc.) according to the specific demands on the final products. The elaborated primary maps were further processed, since even DOSoReMI.hu intended to take steps for the regionalization of higher level soil information (processes, functions, and services) involving crop models in the spatial modelling. The framework of DOSoReMI.hu also provides opportunity for the elaboration of goal specific soil maps, with the prescription of the parameters (thematic, resolution, accuracy, reliability etc.) characterizing the map product. As a result, unique digital soil map products (in a more general meaning) were elaborated regionalizing specific soil (related) features, which were never mapped before, even nationally with high ( 1 ha) spatial resolution. Based upon the collected experiences, the full range of GSM.net products were also targeted. The web publishing of the results was also elaborated creating a proper WMS environment. Our paper will present the resulted national maps furthermore some conclusions drawn from the experiences.] Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA) under Grant K105167 and AGRARKLÍMA.2 VKSZ_12-1-2013-0034.

Elaboration of a framework for the compilation of countrywide, digital maps for the satisfaction of recent demands on spatial, soil related information in Hungary

NASA Astrophysics Data System (ADS)

Pásztor, László; Dobos, Endre; Szabó, József; Bakacsi, Zsófia; Laborczi, Annamária

2013-04-01

There is a heap of evidences that demands on soil related information have been significant worldwide and it is still increasing. Soil maps were typically used for long time to satisfy these demands. By the spread of GI technology, spatial soil information systems (SSIS) and digital soil mapping (DSM) took the role of traditional soil maps. Due to the relatively high costs of data collection, new conventional soil surveys and inventories are getting less and less frequent, which fact valorises legacy soil information and the systems which are serving the their digitally processed version. The existing data contain a wealth of information that can be exploited by proper methodology. Not only the degree of current needs for soil information has changed but also its nature. Traditionally the agricultural functions of soils were focussed on, which was also reflected in the methodology of data collection and mapping. Recently the multifunctionality of soils is getting to gain more and more ground; consequently information related to additional functions of soils becomes identically important. The new types of information requirements however cannot be fulfilled generally with new data collections at least not on such a level as it was done in the frame of traditional soil surveys. Soil monitoring systems have been established for the collection of recent information on the various elements of the DPSIR (Driving Forces-Pressures-State-Impacts-Responses) framework, but the primary goal of these systems has not been mapping by all means. And definitely this is the case concerning the two recently working Hungarian soil monitoring systems. In Hungary, presently soil data requirements are fulfilled with the recently available datasets either by their direct usage or after certain specific and generally fortuitous, thematic and/or spatial inference. Due to the more and more frequently emerging discrepancies between the available and the expected data, there might be notable imperfection as for the accuracy and reliability of the delivered products. Since, similarly to the great majority of the world, large-scale, comprehensive new surveys cannot be expected in the near future, the actually available legacy data should be relied on. With a recently started project we would like to significantly extend the potential, how countrywide soil information requirements could be satisfied. In the frame of our project we plan the execution of spatial and thematic data mining of significant amount of soil related information available in the form of legacy soil data as well as digital databases and spatial soil information systems. In the course of the analyses we will lean on auxiliary, spatial data themes related to environmental elements. Based on the established relationships we will convert and integrate the specific data sets for the regionalization of the various, derived soil parameters. By the aid of GIS and geostatistical tools we will carry out the spatial extension of certain pedological variables featuring the (including degradation) state, processes or functions of soils. We plan to compile digital soil maps which fulfil optimally the national and international demands from points of view of thematic, spatial and temporal accuracy. The targeted spatial resolution of the proposed countrywide, digital, thematic soil property and function maps is at least 1:50.000 (approx. 50-100 meter raster). Our stressful objective is the definite solution of the regionalization of the information collected in the frame of two recent, contemporary, national, systematic soil data collection (not designed for mapping purpose) on the recent state of soils, in order to produce countrywide maps for the spatial inventory of certain soil properties, processes and functions with sufficient accuracy and reliability.

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Comparing the performance of various digital soil mapping approaches to map physical soil properties

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Pásztor, László

2015-04-01

Spatial information on physical soil properties is intensely expected, in order to support environmental related and land use management decisions. One of the most widely used properties to characterize soils physically is particle size distribution (PSD), which determines soil water management and cultivability. According to their size, different particles can be categorized as clay, silt, or sand. The size intervals are defined by national or international textural classification systems. The relative percentage of sand, silt, and clay in the soil constitutes textural classes, which are also specified miscellaneously in various national and/or specialty systems. The most commonly used is the classification system of the United States Department of Agriculture (USDA). Soil texture information is essential input data in meteorological, hydrological and agricultural prediction modelling. Although Hungary has a great deal of legacy soil maps and other relevant soil information, it often occurs, that maps do not exist on a certain characteristic with the required thematic and/or spatial representation. The recent developments in digital soil mapping (DSM), however, provide wide opportunities for the elaboration of object specific soil maps (OSSM) with predefined parameters (resolution, accuracy, reliability etc.). Due to the simultaneous richness of available Hungarian legacy soil data, spatial inference methods and auxiliary environmental information, there is a high versatility of possible approaches for the compilation of a given soil map. This suggests the opportunity of optimization. For the creation of an OSSM one might intend to identify the optimum set of soil data, method and auxiliary co-variables optimized for the resources (data costs, computation requirements etc.). We started comprehensive analysis of the effects of the various DSM components on the accuracy of the output maps on pilot areas. The aim of this study is to compare and evaluate different digital soil mapping methods and sets of ancillary variables for producing the most accurate spatial prediction of texture classes in a given area of interest. Both legacy and recently collected data on PSD were used as reference information. The predictor variable data set consisted of digital elevation model and its derivatives, lithology, land use maps as well as various bands and indices of satellite images. Two conceptionally different approaches can be applied in the mapping process. Textural classification can be realized after particle size data were spatially extended by proper geostatistical method. Alternatively, the textural classification is carried out first, followed by the spatial extension through suitable data mining method. According to the first approach, maps of sand, silt and clay percentage have been computed through regression kriging (RK). Since the three maps are compositional (their sum must be 100%), we applied Additive Log-Ratio (alr) transformation, instead of kriging them independently. Finally, the texture class map has been compiled according to the USDA categories from the three maps. Different combinations of reference and training soil data and auxiliary covariables resulted several different maps. On the basis of the other way, the PSD were classified firstly into the USDA categories, then the texture class maps were compiled directly by data mining methods (classification trees and random forests). The various results were compared to each other as well as to the RK maps. The performance of the different methods and data sets has been examined by testing the accuracy of the geostatistically computed and the directly classified results to assess the most predictive and accurate method. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Peculiarities of changes in the soil cover of landscapes adjacent to a megalopolis

NASA Astrophysics Data System (ADS)

Lazareva, Margarita; Aparin, Boris; Sukhacheva, Elena

2017-04-01

The progressive growth of cities has a significant impact on the soil cover of territories adjacent to the same. Megalopolises are centers of anthropogenic impact on the soils. Generally, forms and intensity of the urban impact on the soil cover weaken with increasing distance from the city's boundaries. In this respect, ample opportunities for the analysis of urban impact on the adjacent territories are provided by the study of the soil cover in the Leningrad Region (the LR). Saint Petersburg is a major European megalopolis, which is the administrative center of the LR. The time period of Saint Petersburg's impact on the environment does not exceed 300 years, which allows us to identify very clearly the character and areas of its impact on the soil cover. Over the past decades, there have been significant changes in the soils and the soil cover of the LR. In a large territory, there appeared new anthropogenic soils and soil cover organization forms, having no natural analogues, with a dramatic increase in the surface area of degraded soils. To access the current state of soil cover, to identify the role of anthropogenic factors of changes in this state; to carry out land reclamation, remediation and rehabilitation measures; to perform land cadastral valuation etc., we need an information resource containing data on the current state of soils and soil cover in the LR, the key element of which should be a map. We carried out mapping and created a 1:200 000 digital soil map (DSM) for the LR's territories. Diagnostics of soil contours were performed using traditionally drawn-up (paper) maps of soils and soil-formation factors; satellite images (Google, Yandex); data of remote sensing (Spot 5, Landsat 7,8); digital maps of main soil-formation factors (topographical ones, etc.). The digital soil map of the LR has been created in the geographic information system - QGIS. The map clarifies the contours of natural soils and soil combinations, and shows, for the first time, the contours of: - non-soil formations; - soils of the initial soil formation; - soils of agricultural lands within their existing boundaries; - soils and soil combinations that are specific for human settlements and horticultural land plots; - fallow lands; - anthropogenically disturbed soils. During the analysis of the created digital medium-scale soil map, we identified some changes in the soil cover of the territories adjacent to Saint Petersburg. Virtually in all the landscapes, we found a large number of soil cover structures, the components of which, along with natural soils, are anthropogenically disturbed soils, anthropogenic soils and non-soil formations. We revealed that the human impact on the soil cover is manifested within the range that varies from insignificant changes in soil parameters to radical transformations of the soil profile, complete destruction of soil and "creation" of new soil forms and soil cover organization forms. We have developed a typology of anthropogenically changed and anthropogenically created soil cover structures, taking into consideration the types of the economic impact on and the quality of environmental functions performed by the soils.

Ecological effects of the Hayman Fire - Part 3: Soil properties, erosion, and implications for rehabilitation and aquatic ecosystems

Treesearch

Jan E. Cipra; Eugene F. Kelly; Lee MacDonald; John Norman

2003-01-01

This team was asked to address three questions regarding soil properties, erosion and sedimentation, and how aquatic and terrestrial ecosystems have responded or could respond to various land management options. We have used soil survey maps, burn severity maps, and digital elevation model (DEM) maps as primary map data. We used our own field measurements and...

Using a spatial and tabular database to generate statistics from terrain and spectral data for soil surveys

USGS Publications Warehouse

Horvath , E.A.; Fosnight, E.A.; Klingebiel, A.A.; Moore, D.G.; Stone, J.E.; Reybold, W.U.; Petersen, G.W.

1987-01-01

A methodology has been developed to create a spatial database by referencing digital elevation, Landsat multispectral scanner data, and digitized soil premap delineations of a number of adjacent 7.5-min quadrangle areas to a 30-m Universal Transverse Mercator projection. Slope and aspect transformations are calculated from elevation data and grouped according to field office specifications. An unsupervised classification is performed on a brightness and greenness transformation of the spectral data. The resulting spectral, slope, and aspect maps of each of the 7.5-min quadrangle areas are then plotted and submitted to the field office to be incorporated into the soil premapping stages of a soil survey. A tabular database is created from spatial data by generating descriptive statistics for each data layer within each soil premap delineation. The tabular data base is then entered into a data base management system to be accessed by the field office personnel during the soil survey and to be used for subsequent resource management decisions.Large amounts of data are collected and archived during resource inventories for public land management. Often these data are stored as stacks of maps or folders in a file system in someone's office, with the maps in a variety of formats, scales, and with various standards of accuracy depending on their purpose. This system of information storage and retrieval is cumbersome at best when several categories of information are needed simultaneously for analysis or as input to resource management models. Computers now provide the resource scientist with the opportunity to design increasingly complex models that require even more categories of resource-related information, thus compounding the problem.Recently there has been much emphasis on the use of geographic information systems (GIS) as an alternative method for map data archives and as a resource management tool. Considerable effort has been devoted to the generation of tabular databases, such as the U.S. Department of Agriculture's SCS/S015 (Soil Survey Staff, 1983), to archive the large amounts of information that are collected in conjunction with mapping of natural resources in an easily retrievable manner.During the past 4 years the U.S. Geological Survey's EROS Data Center, in a cooperative effort with the Bureau of Land Management (BLM) and the Soil Conservation Service (SCS), developed a procedure that uses spatial and tabular databases to generate elevation, slope, aspect, and spectral map products that can be used during soil premapping. The procedure results in tabular data, residing in a database management system, that are indexed to the final soil delineations and help quantify soil map unit composition.The procedure was developed and tested on soil surveys on over 600 000 ha in Wyoming, Nevada, and Idaho. A transfer of technology from the EROS Data Center to the BLM will enable the Denver BLM Service Center to use this procedure in soil survey operations on BLM lands. Also underway is a cooperative effort between the EROS Data Center and SCS to define and evaluate maps that can be produced as derivatives of digital elevation data for 7.5-min quadrangle areas, such as those used during the premapping stage of the soil surveys mentioned above, the idea being to make such products routinely available.The procedure emphasizes the applications of digital elevation and spectral data to order-three soil surveys on rangelands, and will:Incorporate digital terrain and spectral data into a spatial database for soil surveys.Provide hardcopy products (that can be generated from digital elevation model and spectral data) that are useful during the soil pre-mapping process.Incorporate soil premaps into a spatial database that can be accessed during the soil survey process along with terrain and spectral data.Summarize useful quantitative information for soil mapping and for making interpretations for resource management.

Turning soil survey data into digital soil maps in the Energy Region Eger Research Model Area

NASA Astrophysics Data System (ADS)

Pásztor, László; Dobos, Anna; Kürti, Lívia; Takács, Katalin; Laborczi, Annamária

2015-04-01

Agria-Innoregion Knowledge Centre of the Eszterházy Károly College has carried out targeted basic researches in the field of renewable energy sources and climate change in the framework of TÁMOP-4.2.2.A-11/1/KONV project. The project has covered certain issues, which require the specific knowledge of the soil cover; for example: (i) investigation of quantitative and qualitative characteristics of natural and landscape resources; (ii) determination of local amount and characteristics of renewable energy sources; (iii) natural/environmental risk analysis by surveying the risk factors. The Energy Region Eger Research Model Area consists of 23 villages and is located in North-Hungary, at the Western part of Bükkalja. Bükkalja is a pediment surface with erosional valleys and dense river network. The diverse morphology of this area results diversity in soil types and soil properties as well. There was large-scale (1:10,000 and 1:25,000 scale) soil mappings in this area in the 1960's and 1970's which provided soil maps, but with reduced spatial coverage and not with fully functional thematics. To achive the recent tasks (like planning suitable/optimal land-use system, estimating biomass production and development of agricultural and ecomonic systems in terms of sustainable regional development) new survey was planned and carried out by the staff of the College. To map the soils in the study area 10 to 22 soil profiles were uncovered per settlement in 2013 and 2014. Field work was carried out according to the FAO Guidelines for Soil Description and WRB soil classification system was used for naming soils. According to the general goal of soil mapping the survey data had to be spatially extended to regionalize the collected thematic local knowledge related to soil cover. Firstly three thematic maps were compiled by digital soil mapping methods: thickness of topsoil, genetic soil type and rate of surface erosion. High resolution digital elevation model, Earth observation imagery, geology and land cover maps were used as spatial ancillary environmental variables related to soil forming processes. Regression kriging (RK) has been used for the spatial inference of quantitative data (thickness of topsoil); classification and regression trees (CART) were applied for the spatial inference of category type information (genetic soil type and rate of surface erosion) with the aid of the available and properly preprocessed auxiliary co-variables. The applied spatial resolution was 25 meters. The deduced digital soil maps hopefully will significantly promote to plan sustainable economic model in the region which can provide protection and regeneration of local natural conditions and potentials for local inhabitants for a long time. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and TÁMOP-4.2.2.A-11/1/KONV project.

Application of Remote Sensing Data to Improve the Water and Soil Resource Management of Rwanda

NASA Astrophysics Data System (ADS)

Csorba, Ádám; Bukombe, Benjamin; Naramabuye, Francois Xavier; Szegi, Tamás; Vekerdy, Zoltán; Michéli, Erika

2017-04-01

The Rwandan agriculture strongly relies in the dry seasons on the water stored in artificial reservoirs of various sizes for irrigation purposes. Furthermore, the success of irrigation depends on a wide range of soil properties which directly affect the moisture regime of the growing medium. By integrating remote sensing and auxiliary data the objectives of our study are to monitor the water level fluctuation in the reservoirs, estimate the volume of water available for irrigation and to combine this information with soil property maps to support the decision making for sustainable irrigation water management in a study area in Southern Rwanda. For water level and volume estimation a series of Sentinel-1 (product type: GRD, acquisition mode: IW, polarizations HH and VH) data were obtained covering the study area and spanning over a period of two years. To map the extent of water bodies the Radar-Based Water Body Mapping module of the Water Observation and Information System (WOIS) was used. High-resolution optical data (Sentinel-2) were used for validation in cloud-free periods. To estimate the volume changes in the reservoirs, we combined the information derived from the water body mapping procedure and digital elevation models. For sustainable irrigation water management, digital soil property maps were developed by the application of wide range of environmental covariates related to soil forming factors. To develop covariates which represent the land use a time series analysis of the 2 years of Sentinel-1 data was performed. As auxiliary soil data, the ISRIC-WISE harmonized soil profile database was used. The developed digital soil mapping approach is integrated into a new WOIS workflow.

Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects.

PubMed

Moulatlet, Gabriel Massaine; Zuquim, Gabriela; Figueiredo, Fernando Oliveira Gouvêa; Lehtonen, Samuli; Emilio, Thaise; Ruokolainen, Kalle; Tuomisto, Hanna

2017-10-01

Amazonia combines semi-continental size with difficult access, so both current ranges of species and their ability to cope with environmental change have to be inferred from sparse field data. Although efficient techniques for modeling species distributions on the basis of a small number of species occurrences exist, their success depends on the availability of relevant environmental data layers. Soil data are important in this context, because soil properties have been found to determine plant occurrence patterns in Amazonian lowlands at all spatial scales. Here we evaluate the potential for this purpose of three digital soil maps that are freely available online: SOTERLAC, HWSD, and SoilGrids. We first tested how well they reflect local soil cation concentration as documented with 1,500 widely distributed soil samples. We found that measured soil cation concentration differed by up to two orders of magnitude between sites mapped into the same soil class. The best map-based predictor of local soil cation concentration was obtained with a regression model combining soil classes from HWSD with cation exchange capacity (CEC) from SoilGrids. Next, we evaluated to what degree the known edaphic affinities of thirteen plant species (as documented with field data from 1,200 of the soil sample sites) can be inferred from the soil maps. The species segregated clearly along the soil cation concentration gradient in the field, but only partially along the model-estimated cation concentration gradient, and hardly at all along the mapped CEC gradient. The main problems reducing the predictive ability of the soil maps were insufficient spatial resolution and/or georeferencing errors combined with thematic inaccuracy and absence of the most relevant edaphic variables. Addressing these problems would provide better models of the edaphic environment for ecological studies in Amazonia.

Application of digital soil mapping in Argentina: An example using apparent soil electrical conductivity

NASA Astrophysics Data System (ADS)

Domenech, Marisa; Castro Franco, Mauricio; Costa, Jose Luis; Aparicio, Virginia

2017-04-01

Apparent soil electrical conductivity (ECa) has been used to capture soil data in several Argentinean Pampas locations. The aim of this study was to generate digital soil mapping on the basis of understanding the relation among ECa and soil properties in three farming fields of the southeast Buenos Aires province. We carried out a geostatistical analysis using ECa data obtained at two depths 0-30cm (ECa_30cm) and 0-90cm (ECa_90cm). Then, two zones derived from ECa measurements were delimited in each field. A soil-sampling scheme was applied in each zone using two depths: 0-30cm and 30-90cm. Texture, Organic Matter Content (OMC), cation-exchange capacity (CEC), pH, saturated paste electrical conductivity (ECe) and effective depth were analyzed. The relation between zones and soil properties were studied using nested factor ANOVA. Our results indicated that clay content and effective depth showed significant differences among ECa_30 zones in all fields. In Argentine Pampas, the presence of petrocalcic horizons limits the effective soil depth at field scale. These horizons vary in depth, structure, hardness and carbonates content. In addition, they influence the spatial pattern of clay content. The relation among other physical and chemical soil properties was not consistent. Two soil unit maps were delimited in each field. These results might support irrigation management due to clay content and effective depth would be controlling soil water storage. Our findings highlight the high accuracy use of soil sensors in developing digital soil mapping at field scale, irrigation management zones, precision agriculture and hydrological modeling in Pampas region conditions.

How to feed environmental studies with soil information to address SDG 'Zero hunger'

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2017-04-01

As pledged by UN Sustainable Development Goal (SDG) 2, there should be zero hunger, food security, improved food nutrition and sustainable agriculture by 2030. Environmental studies are essential to reach SDG 2. Soils play a crucial role, especially in addressing 'Zero hunger'. This study aims to discuss the connection between the supply and demand of soil data for environmental studies and how this connection can be improved illustrating different methods. As many studies are resource constrained, the options to collect new soil data are limited. Therefore, it is essential to use existing soil information, auxiliary data and collected field data efficiently. Existing soil data are criticised in literature as i) being dominantly qualitative, ii) being often outdated, iii) being not spatially exhaustive, iv) being only available at general scales, v) being inconsistent, and vi) lacking quality assessments. Additional field data can help to overcome some of these problems. Outdated maps can, for example, be improved by collecting additional soil data in areas where changes in soil properties are expected. Existing soil data can also provide insight in the expected soil variability and, as such, these data can be used for the design of sampling schemes. Existing soil data are also crucial input for studies on digital soil mapping because they give information on parent material and the relative age of soils. Digital soil mapping is commonly applied as an efficient method to quantitatively predict the spatial variation of soil properties. However, the efficiency of digital soil mapping may increase if we look at functional soil properties (e.g. nutrient availability, available water capacity) for the soil profile that vary in a two-dimensional space rather than at basic soil properties of individual soil layers (e.g. texture, organic matter content, nitrogen content) that vary in a three-dimensional space. Digital soil mapping techniques are based on statistical relations between soil properties and environmental variables. However, in some cases a more mechanistic approach, based on pedological knowledge, might be more convincing to predict soil properties. This study showed that the soil science community is able to provide the required soil information for environmental studies. However, there is not a single solution that provides the required soil data. Case studies are needed to prove that certain methods meet the data requirements, whereafter these case studies function as a lighthouse to other studies. We illustrate data availability and methodological innovations for a case study in Kenya, where the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) aims to contribute to SDG 2.

Digital mapping of soil properties in Zala County, Hungary for the support of county-level spatial planning and land management

NASA Astrophysics Data System (ADS)

Pásztor, László; Laborczi, Annamária; Szatmári, Gábor; Fodor, Nándor; Bakacsi, Zsófia; Szabó, József; Illés, Gábor

2014-05-01

The main objective of the DOSoReMI.hu (Digital, Optimized, Soil Related Maps and Information in Hungary) project is to significantly extend the potential, how demands on spatial soil related information could be satisfied in Hungary. Although a great amount of soil information is available due to former mappings and surveys, there are more and more frequently emerging discrepancies between the available and the expected data. The gaps are planned to be filled with optimized DSM products heavily based on legacy soil data, which still represent a valuable treasure of soil information at the present time. Impact assessment of the forecasted climate change and the analysis of the possibilities of the adaptation in the agriculture and forestry can be supported by scenario based land management modelling, whose results can be incorporated in spatial planning. This framework requires adequate, preferably timely and spatially detailed knowledge of the soil cover. For the satisfaction of these demands in Zala County (one of the nineteen counties of Hungary), the soil conditions of the agricultural areas were digitally mapped based on the most detailed, available recent and legacy soil data. The agri-environmental conditions were characterized according to the 1:10,000 scale genetic soil mapping methodology and the category system applied in the Hungarian soil-agricultural chemistry practice. The factors constraining the fertility of soils were featured according to the biophysical criteria system elaborated for the delimitation of naturally handicapped areas in the EU. Production related soil functions were regionalized incorporating agro-meteorological modelling. The appropriate derivatives of a 20m digital elevation model were used in the analysis. Multitemporal MODIS products were selected from the period of 2009-2011 representing different parts of the growing season and years with various climatic conditions. Additionally two climatic data layers, the 1:100.000 Geological Map of Hungary and the map of groundwater depth were used as auxiliary environmental covariables. Various soil related information were mapped in three distinct sets: (i) basic soil properties determining agri-environmental conditions (soil type according to the Hungarian genetic classification, rootable depth, sand and clay content for the 1st and 2nd soil layers, pH, OM and carbonate content for the plough layer); (ii) biophysical criteria of natural handicaps defined by common European system and (iii) agro-meteorologically modelled yield values for different crops, meteorological and management scenarios. The applied method(s) for the spatial inference of specific themes was/were suitably selected: regression and classification trees for categorical data, indicator kriging for probabilistic management of criterion information; and typically regression kriging for quantitative data. Our paper will present the mapping processes themselves, the resulted maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and by the European Union with the co-financing of the European Social Fund (TÁMOP-4.2.2.A-11/1/KONV-2012-0013.).

Large-extent digital soil mapping approaches for total soil depth

NASA Astrophysics Data System (ADS)

Mulder, Titia; Lacoste, Marine; Saby, Nicolas P. A.; Arrouays, Dominique

2015-04-01

Total soil depth (SDt) plays a key role in supporting various ecosystem services and properties, including plant growth, water availability and carbon stocks. Therefore, predictive mapping of SDt has been included as one of the deliverables within the GlobalSoilMap project. In this work SDt was predicted for France following the directions of GlobalSoilMap, which requires modelling at 90m resolution. This first method, further referred to as DM, consisted of modelling the deterministic trend in SDt using data mining, followed by a bias correction and ordinary kriging of the residuals. Considering the total surface area of France, being about 540K km2, employed methods may need to be able dealing with large data sets. Therefore, a second method, multi-resolution kriging (MrK) for large datasets, was implemented. This method consisted of modelling the deterministic trend by a linear model, followed by interpolation of the residuals. For the two methods, the general trend was assumed to be explained by the biotic and abiotic environmental conditions, as described by the Soil-Landscape paradigm. The mapping accuracy was evaluated by an internal validation and its concordance with previous soil maps. In addition, the prediction interval for DM and the confidence interval for MrK were determined. Finally, the opportunities and limitations of both approaches were evaluated. The results showed consistency in mapped spatial patterns and a good prediction of the mean values. DM was better capable in predicting extreme values due to the bias correction. Also, DM was more powerful in capturing the deterministic trend than the linear model of the MrK approach. However, MrK was found to be more straightforward and flexible in delivering spatial explicit uncertainty measures. The validation indicated that DM was more accurate than MrK. Improvements for DM may be expected by predicting soil depth classes. MrK shows potential for modelling beyond the country level, at high resolution. Large-extent digital soil mapping approaches for SDt may be improved by (1) taking into account SDt observations which are censored and (2) using high-resolution biotic and abiotic environmental data. The latter may improve modelling the soil-landscape interactions influencing soil pedogenesis. Concluding, this work provided a robust and reproducible method (DM) for high-resolution soil property modelling, in accordance with the GlobalSoilMap requirements and an efficient alternative for large-extent digital soil mapping (MrK).

Introduction to the special section ‘Applications of electromagnetic induction to digital soil mapping’

USDA-ARS?s Scientific Manuscript database

Use of electromagnetic induction (EMI) instruments has increased as a tool to map soils because it provides a means of locating suitable sampling sites that provide the basis for mapping the spatial variability of various soil properties either directly or indirectly measured with EMI, including sa...

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

NASA Astrophysics Data System (ADS)

Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.

2017-01-01

Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.

Integrated terrain mapping with digital Landsat images in Queensland, Australia

USGS Publications Warehouse

Robinove, Charles Joseph

1979-01-01

Mapping with Landsat images usually is done by selecting single types of features, such as soils, vegetation, or rocks, and creating visually interpreted or digitally classified maps of each feature. Individual maps can then be overlaid on or combined with other maps to characterize the terrain. Integrated terrain mapping combines several terrain features into each map unit which, in many cases, is more directly related to uses of the land and to methods of land management than the single features alone. Terrain brightness, as measured by the multispectral scanners in Landsat 1 and 2, represents an integration of reflectance from the terrain features within the scanner's instantaneous field of view and is therefore more correlatable with integrated terrain units than with differentiated ones, such as rocks, soils, and vegetation. A test of the feasibilty of the technique of mapping integrated terrain units was conducted in a part of southwestern Queensland, Australia, in cooperation with scientists of the Queensland Department of Primary Industries. The primary purpose was to test the use of digital classification techniques to create a 'land systems map' usable for grazing land management. A recently published map of 'land systems' in the area (made by aerial photograph interpretation and ground surveys), which are integrated terrain units composed of vegetation, soil, topography, and geomorphic features, was used as a basis for comparison with digitally classified Landsat multispectral images. The land systems, in turn, each have a specific grazing capacity for cattle (expressed in beasts per km 2 ) which is estimated following analysis of both research results and property carrying capacities. Landsat images, in computer-compatible tape form, were first contrast-stretched to increase their visual interpretability, and digitally classified by the parallelepiped method into distinct spectral classes to determine their correspondence to the land systems classes and to areally smaller, but readily recognizable, 'land units.' Many land systems appeared as distinct spectral classes or as acceptably homogeneous combinations of several spectral classes. The digitally classified map corresponded to the general geographic patterns of many of the land systems. Statistical correlation of the digitally classified map and the published map was not possible because the published map showed only land systems whereas the digitally classified map showed some land units as well as systems. The general correspondence of spectral classes to the integrated terrain units means that the digital mapping of the units may precede fieldwork and act as a guide to field sampling and detailed terrain unit description as well as measuring of the location, area, and extent of each unit. Extension of the Landsat mapping and classification technique to other arid and semi-arid regions of the world may be feasible.

The methods of geomorphometry and digital soil mapping for assessing spatial variability in the properties of agrogray soils on a slope

NASA Astrophysics Data System (ADS)

Gopp, N. V.; Nechaeva, T. V.; Savenkov, O. A.; Smirnova, N. V.; Smirnov, V. V.

2017-01-01

The relationships between the morphometric parameters (MPs) of topography calculated on the basis of digital elevation model (ASTER GDEM, 30 m) and the properties of the plow layer of agrogray soils on a slope were analyzed. The contribution of MPs to the spatial variability of the soil moisture reached 42%; to the content of physical clay (<0.01 mm particles), 59%; to the humus content, 46%; to the total nitrogen content, 31%; to the content of nitrate nitrogen, 28%; to the content of mobile phosphorus, 40%; to the content of exchangeable potassium, 45%; to the content of exchangeable calcium, 67%; to the content of exchangeable magnesium, 40%; and to the soil pH, 42%. A comparative analysis of the plow layer within the eluvial and transitional parts of the slope was performed with the use of geomorphometric methods and digital soil mapping. The regression analysis showed statistically significant correlations between the properties of the plow layer and the MPs describing surface runoff, geometric forms of surface, and the soil temperature regime.

A GIS based method for soil mapping in Sardinia, Italy: a geomatic approach.

PubMed

Vacca, A; Loddo, S; Melis, M T; Funedda, A; Puddu, R; Verona, M; Fanni, S; Fantola, F; Madrau, S; Marrone, V A; Serra, G; Tore, C; Manca, D; Pasci, S; Puddu, M R; Schirru, P

2014-06-01

A new project was recently initiated for the realization of the "Land Unit and Soil Capability Map of Sardinia" at a scale of 1:50,000 to support land use planning. In this study, we outline the general structure of the project and the methods used in the activities that have been thus far conducted. A GIS approach was used. We used the soil-landscape paradigm for the prediction of soil classes and their spatial distribution or the prediction of soil properties based on landscape features. The work is divided into two main phases. In the first phase, the available digital data on land cover, geology and topography were processed and classified according to their influence on weathering processes and soil properties. The methods used in the interpretation are based on consolidated and generalized knowledge about the influence of geology, topography and land cover on soil properties. The existing soil data (areal and point data) were collected, reviewed, validated and standardized according to international and national guidelines. Point data considered to be usable were input into a specific database created for the project. Using expert interpretation, all digital data were merged to produce a first draft of the Land Unit Map. During the second phase, this map will be implemented with the existing soil data and verified in the field if also needed with new soil data collection, and the final Land Unit Map will be produced. The Land Unit and Soil Capability Map will be produced by classifying the land units using a reference matching table of land capability classes created for this project. Copyright © 2013 Elsevier Ltd. All rights reserved.

Urban cover mapping using digital, high-resolution aerial imagery

Treesearch

Soojeong Myeong; David J. Nowak; Paul F. Hopkins; Robert H. Brock

2003-01-01

High-spatial resolution digital color-infrared aerial imagery of Syracuse, NY was analyzed to test methods for developing land cover classifications for an urban area. Five cover types were mapped: tree/shrub, grass/herbaceous, bare soil, water and impervious surface. Challenges in high-spatial resolution imagery such as shadow effect and similarity in spectral...

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation.

PubMed

Keyes, S D; Gillard, F; Soper, N; Mavrogordato, M N; Sinclair, I; Roose, T

2016-06-14

The mechanical impedance of soils inhibits the growth of plant roots, often being the most significant physical limitation to root system development. Non-invasive imaging techniques have recently been used to investigate the development of root system architecture over time, but the relationship with soil deformation is usually neglected. Correlative mapping approaches parameterised using 2D and 3D image data have recently gained prominence for quantifying physical deformation in composite materials including fibre-reinforced polymers and trabecular bone. Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) are computational techniques which use the inherent material texture of surfaces and volumes, captured using imaging techniques, to map full-field deformation components in samples during physical loading. Here we develop an experimental assay and methodology for four-dimensional, in vivo X-ray Computed Tomography (XCT) and apply a Digital Volume Correlation (DVC) approach to the data to quantify deformation. The method is validated for a field-derived soil under conditions of uniaxial compression, and a calibration study is used to quantify thresholds of displacement and strain measurement. The validated and calibrated approach is then demonstrated for an in vivo test case in which an extending maize root in field-derived soil was imaged hourly using XCT over a growth period of 19h. This allowed full-field soil deformation data and 3D root tip dynamics to be quantified in parallel for the first time. This fusion of methods paves the way for comparative studies of contrasting soils and plant genotypes, improving our understanding of the fundamental mechanical processes which influence root system development. Copyright © 2016 Elsevier Ltd. All rights reserved.

The History of Soil Mapping and Classification in Europe: The role of the European Commission

NASA Astrophysics Data System (ADS)

Montanarella, Luca

2014-05-01

Early systematic soil mapping in Europe dates back to the early times of soil science in the 19th Century and was developed at National scales mostly for taxation purposes. National soil classification systems emerged out of the various scientific communities active at that time in leading countries like Germany, Austria, France, Belgium, United Kingdom and many others. Different scientific communities were leading in the various countries, in some cases stemming from geological sciences, in others as a branch of agricultural sciences. Soil classification for the purpose of ranking soils for their capacity to be agriculturally productive emerged as the main priority, allowing in some countries for very detailed and accurate soil maps at 1:5,000 scale and larger. Detailed mapping was mainly driven by taxation purposes in the early times but evolved in several countries also as a planning and management tool for farms and local administrations. The need for pan-European soil mapping and classification efforts emerged only after World War II in the early 1950's under the auspices of FAO with the aim to compile a common European soil map as a contribution to the global soil mapping efforts of FAO at that time. These efforts evolved over the next decades, with the support of the European Commission, towards the establishment of a permanent network of National soil survey institutions (the European Soil Bureau Network). With the introduction of digital soil mapping technologies, the new European Soil Information System (EUSIS) was established, incorporating data at multiple scales for the EU member states and bordering countries. In more recent years, the formal establishment of the European Soil Data Centre (ESDAC) hosted by the European Commission, together with a formal legal framework for soil mapping and soil classification provided by the INSPIRE directive and the related standardization and harmonization efforts, has led to the operational development of advanced digital soil mapping techniques supporting the contribution of Europe to a common global soil information system under the coordination of the Global Soil Partnership (GSP) of FAO. Further information: http://eusoils.jrc.ec.europa.eu/ References: Mark G Kibblewhite, Ladislav Miko, Luca Montanarella, Legal frameworks for soil protection: current development and technical information requirements, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 573-577. Luca Montanarella, Ronald Vargas, Global governance of soil resources as a necessary condition for sustainable development, Current Opinion in Environmental Sustainability, Volume 4, Issue 5, November 2012, Pages 559-564.

Considering the spatial-scale factor when modelling sustainable land management.

NASA Astrophysics Data System (ADS)

Bouma, Johan

2015-04-01

Considering the spatial-scale factor when modelling sustainable land management. J.Bouma Em.prof. soil science, Wageningen University, Netherlands. Modelling soil-plant processes is a necessity when exploring future effects of climate change and innovative soil management on agricultural productivity. Soil data are needed to run models and traditional soil maps and the associated databases (based on various soil Taxonomies ), have widely been applied to provide such data obtained at "representative" points in the field. Pedotransferfunctions (PTF)are used to feed simulation models, statistically relating soil survey data ( obtained at a given point in the landscape) to physical parameters for simulation, thus providing a link with soil functionality. Soil science has a basic problem: their object of study is invisible. Only point data are obtained by augering or in pits. Only occasionally roadcuts provide a better view. Extrapolating point to area data is essential for all applications and presents a basic problem for soil science, because mapping units on soil maps, named for a given soil type,may also contain other soil types and quantitative information about the composition of soil map units is usually not available. For detailed work at farm level ( 1:5000-1:10000), an alternative procedure is proposed. Based on a geostatistical analysis, onsite soil observations are made in a grid pattern with spacings based on a geostatistical analysis. Multi-year simulations are made for each point of the functional properties that are relevant for the case being studied, such as the moisture supply capacity, nitrate leaching etc. under standardized boundary conditions to allow comparisons. Functional spatial units are derived next by aggregating functional point data. These units, which have successfully functioned as the basis for precision agriculture, do not necessarily correspond with Taxonomic units but when they do the Taxonomic names should be noted . At lower landscape and watershed scale ( 1:25.000 -1:50000) digital soil mapping can provide soil data for small grids that can be used for modeling, again through pedotransferfunctions. There is a risk, however, that digital mapping results in an isolated series of projects that don't increase the knowledge base on soil functionality, e.g.linking Taxonomic names ( such as soil series) to functionality, allowing predictions of soil behavior at new sites where certain soil series occur. We therefore suggest that aside from collecting 13 soil characteristics for each grid, as occurs in digital soil mapping, also the Taxonomic name of the representative soil in the grid is recorded. At spatial scales of 1:50000 and smaller, use of Taxonomic names becomes ever more attractive because at such small scales relations between soil types and landscape features become more pronounced. But in all cases, selection of procedures should not be science-based but based on the type of questions being asked including their level of generalization. These questions are quite different at the different spatial-scale levels and so should be the procedures.

Application of spatial pedotransfer functions to understand soil modulation of vegetation response to climate

USDA-ARS?s Scientific Manuscript database

A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high resolution spatial representation of soil physical and hydraulic properties. We present a novel approach to predict hydraulic soil parameters by combining digital soil mapping techniques with pedotransfer fun...

Studying of Forests Potentials for Introducing of Mediterranean Industrial Woody Species to Desertification Combating

NASA Astrophysics Data System (ADS)

Mahdavi Najafabadi, R.; Khajeddin, S. J.; Sofyanian, A. R.; Karimzadeh, H. R.; Rezaei, M.

2009-04-01

Most of arid and semiarid parts of the world suffer from great lack of forest land. Therefore taking a good care of these forest lands quantity and quality and control of renewable natural resources is very important. Zagroass forests are located in semiarid parts of Iran. The main purpose of this research is to determine the potential habitat of forest olive for Chaharmahal va Bakhtiary using GIS. This province has a total area of 1653300 hectars. The main steps of this project are as follows: collecting data and maps, digitizing topographic maps with scale of 1:25000, and developing maps of slope, elevation levels, aspect, climatic classification. Regretion analysis was performed on the climatic data and the gradian equations were developed with a high R2 value. Using these equations the following maps were developed. For the whole province: isothermal, isoheytal, abs. max isothermal, relative humidity relative humidity of dry months. Soil maps were also digitized and the information system suitable for this study was developed. Using this bank the following layers were made: land units, soil depth, two soil textures, EC, pH, CaCo3. The following layers were made using digitized data, land use hydraulic network, lake and marsh land. Considering ecological needs of olive and extracting them from all diferent layers using boolean method. The layers showing suitable locations for planting olive(olea europea) was made. One of these maps includes all types of soils suitable for planting olive and the other excludes silty clay loam soils which are not so suitable. The total area achived was 9500 hectars in the whole province and the area excluding silty clay loam soils was determined to be 900 hectars. Using RS information and GIS technology in these types of projects can increase accuracy specialy including some more layers is recommended.

Comparison of different landform classification methods for digital landform and soil mapping of the Iranian loess plateau

NASA Astrophysics Data System (ADS)

Hoffmeister, Dirk; Kramm, Tanja; Curdt, Constanze; Maleki, Sedigheh; Khormali, Farhad; Kehl, Martin

2016-04-01

The Iranian loess plateau is covered by loess deposits, up to 70 m thick. Tectonic uplift triggered deep erosion and valley incision into the loess and underlying marine deposits. Soil development strongly relates to the aspect of these incised slopes, because on northern slopes vegetation protects the soil surface against erosion and facilitates formation and preservation of a Cambisol, whereas on south-facing slopes soils were probably eroded and weakly developed Entisols formed. While the whole area is intensively stocked with sheep and goat, rain-fed cropping of winter wheat is practiced on the valley floors. Most time of the year, the soil surface is unprotected against rainfall, which is one of the factors promoting soil erosion and serious flooding. However, little information is available on soil distribution, plant cover and the geomorphological evolution of the plateau, as well as on potentials and problems in land use. Thus, digital landform and soil mapping is needed. As a requirement of digital landform and soil mapping, four different landform classification methods were compared and evaluated. These geomorphometric classifications were run on two different scales. On the whole area an ASTER GDEM and SRTM dataset (30 m pixel resolution) was used. Likewise, two high-resolution digital elevation models were derived from Pléiades satellite stereo-imagery (< 1m pixel resolution, 10 by 10 km). The high-resolution information of this dataset was aggregated to datasets of 5 and 10 m scale. The applied classification methods are the Geomorphons approach, an object-based image approach, the topographical position index and a mainly slope based approach. The accuracy of the classification was checked with a location related image dataset obtained in a field survey (n ~ 150) in September 2015. The accuracy of the DEMs was compared to measured DGPS trenches and map-based elevation data. The overall derived accuracy of the landform classification based on the high-resolution DEM with a resolution of 5 m is approximately 70% and on a 10 m resolution >58%. For the 30 m resolution datasets is the achieved accuracy approximately 40%, as several small scale features are not recognizable in this resolution. Thus, for an accurate differentiation between different important landform types, high-resolution datasets are necessary for this strongly shaped area. One major problem of this approach are the different classes derived by each method and the various class annotations. The result of this evaluation will be regarded for the derivation of landform and soil maps.

Digital Terroir Mapping in the Tokaj Historical Wine Region

NASA Astrophysics Data System (ADS)

Pásztor, László; Lukácsy, György; Szabó, József; László, Péter; Burai, Péter; Bakacsi, Zsófia; Koós, Sándor; Laborczi, Annamária; Takács, Katalin; Bekő, László

2015-04-01

Tokaj is a historical region for botritized dessert wine making, the famed Tokaji Wine Region has the distinction of being Europe's first classified wine region. Very recently the sustainable quality wine production in the region was targeted, which requires detailed and "terroir-based approach" characterization of viticultural land. Tokaj region consists of 27 villages, the total producing vineyard surface area is 5,500 hectares, and the total vineyard land exceeds 11,000 hectares. The Tokaj Kereskedőház Ltd. is the only state owned winery in Hungary. The company is integrating grapes for wine production from 1,100 hectares of vineyard, which consist of 3,500 parcels with average size of 0.3 hectares. In 2013 the Hungarian Government has decided to elaborate a sustainable quality wine production in the Tokaj region coordinated by the Tokaj Kereskedőház Ltd, the biggest wine producer. To achieve the target it is indispensable to assess the viticultural potential of the land. In 2013 the characterization of the vineyard land potential was started collecting detailed, up-to-date information on the main environmental factors (geology, geomorphology and soil) which comprise the terroir effect and combined with legacy data of climate. The Council of Wine Communities of Tokaj Region has decided to widen the survey for the whole wine region in the year 2014. The primary objective of our work was the execution of an appropriate terroir zoning, which was carried out by digital terroir mapping. As a start-up we adapted some concepts recently applied in French wine regions. The implementation was however carried out totally in spatial, digital environment. Four main sources of information have been used (i) airborne laser scanning, (ii) hyperspectral imaginary, (iii) digital soil maps compiled based on detailed soil survey and (iv) interpolated climatic data. Based on them pedoclimate, mesoclimate and soil water reservoir were spatially predicted. The operational spatial resolution was set to 25 meters as a compromise between the denser remotely sensed data and the resolution available by the spatial inference of the collected soil information by proper digital soil mapping techniques. Finally the plant available water content, the vigor potential and precocity (earliness) potential was calculated. Based on these three maps the optimal target of production (dessert wine, dry wine, sparkling wine) could be determined and the information could provide a basis for decisions made both prior to planting and during production. Acknowledgement: The authors are grateful to the Tokaj Kereskedőház Ltd. and to András Tombor, Head of the Supervisory Board of Tokaj Kereskedőház Ltd. who has been supporting the project for the survey of the state of vineyards. Digital soil mapping was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.

NASA Astrophysics Data System (ADS)

Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele

2017-04-01

Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.

Mapping specific soil functions based on digital soil property maps

NASA Astrophysics Data System (ADS)

Pásztor, László; Fodor, Nándor; Farkas-Iványi, Kinga; Szabó, József; Bakacsi, Zsófia; Koós, Sándor

2016-04-01

Quantification of soil functions and services is a great challenge in itself even if the spatial relevance is supposed to be identified and regionalized. Proxies and indicators are widely used in ecosystem service mapping. Soil services could also be approximated by elementary soil features. One solution is the association of soil types with services as basic principle. Soil property maps however provide quantified spatial information, which could be utilized more versatilely for the spatial inference of soil functions and services. In the frame of the activities referred as "Digital, Optimized, Soil Related Maps and Information in Hungary" (DOSoReMI.hu) numerous soil property maps have been compiled so far with proper DSM techniques partly according to GSM.net specifications, partly by slightly or more strictly changing some of its predefined parameters (depth intervals, pixel size, property etc.). The elaborated maps have been further utilized, since even DOSoReMI.hu was intended to take steps toward the regionalization of higher level soil information (secondary properties, functions, services). In the meantime the recently started AGRAGIS project requested spatial soil related information in order to estimate agri-environmental related impacts of climate change and support the associated vulnerability assessment. One of the most vulnerable services of soils in the context of climate change is their provisioning service. In our work it was approximated by productivity, which was estimated by a sequential scenario based crop modelling. It took into consideration long term (50 years) time series of both measured and predicted climatic parameters as well as accounted for the potential differences in agricultural practice and crop production. The flexible parametrization and multiple results of modelling was then applied for the spatial assessment of sensitivity, vulnerability, exposure and adaptive capacity of soils in the context of the forecasted changes in climatic conditions in the Carpathian Basin. In addition to soil fertility, degradation risk due to N-leaching was also assessed by the model runs by taking into account the movement of nitrate in the profile during the simulated periods. Our paper will present the resulted national maps and some conclusions drawn from the experiences. Acknowledgement: Our work was supported by Iceland, Liechtenstein and Norway through the EEA Grants and the REC (Project No: EEA C12-12) and the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Use of LANDSAT data to define soil boundaries in Carroll County, Missouri

NASA Technical Reports Server (NTRS)

Davidson, S. E.

1981-01-01

Bands 4, 5 and 7 false color composite photographs were prepared using data from LANDSAT scenes acquired during April 1977 and April 1981 on computer compatible tapes, and these color composites were compared with band 7 black and white photographs prepared for the entire county. Delineations of soil boundaries at the soil association level were achieved using LANDSAT spectral reflectance data and slope maps for a portion of Carroll County, Missouri. Forty two spectral reflectance classes from April 1977 LANDSAT data were overlaid on digitized slope maps of nine USGS 7.5 minute series topographic quadrangle slope maps to achieve boundary delineations of the soil associations.

A statistical approach for validating eSOTER and digital soil maps in front of traditional soil maps

NASA Astrophysics Data System (ADS)

Bock, Michael; Baritz, Rainer; Köthe, Rüdiger; Melms, Stephan; Günther, Susann

2015-04-01

During the European research project eSOTER, three different Digital Soil Maps (DSM) were developed for the pilot area Chemnitz 1:250,000 (FP7 eSOTER project, grant agreement nr. 211578). The core task of the project was to revise the SOTER method for the interpretation of soil and terrain data. It was one of the working hypothesis that eSOTER does not only provide terrain data with typical soil profiles, but that the new products actually perform like a conceptual soil map. The three eSOTER maps for the pilot area considerably differed in spatial representation and content of soil classes. In this study we compare the three eSOTER maps against existing reconnaissance soil maps keeping in mind that traditional soil maps have many subjective issues and intended bias regarding the overestimation and emphasize of certain features. Hence, a true validation of the proper representation of modeled soil maps is hardly possible; rather a statistical comparison between modeled and empirical approaches is possible. If eSOTER data represent conceptual soil maps, then different eSOTER, DSM and conventional maps from various sources and different regions could be harmonized towards consistent new data sets for large areas including the whole European continent. One of the eSOTER maps has been developed closely to the traditional SOTER method: terrain classification data (derived from SRTM DEM) were combined with lithology data (re-interpreted geological map); the corresponding terrain units were then extended with soil information: a very dense regional soil profile data set was used to define soil mapping units based on a statistical grouping of terrain units. The second map is a pure DSM map using continuous terrain parameters instead of terrain classification; radiospectrometric data were used to supplement parent material information from geology maps. The classification method Random Forest was used. The third approach predicts soil diagnostic properties based on covariates similar to DSM practices; in addition, multi-temporal MODIS data were used; the resulting soil map is the product of these diagnostic layers producing a map of soil reference groups (classified according to WRB). Because the third approach was applied to a larger test area in central Europe, and compared to the first two approaches, has worked with coarser input data, comparability is only partly fulfilled. To evaluate the usability of the three eSOTER maps, and to make a comparison among them, traditional soil maps 1:200,000 and 1:50,000 were used as reference data sets. Three statistical methods were applied: (i) in a moving window the distribution of the soil classes of each DSM product was compared to that of the soil maps by calculating the corrected coefficient of contingency, (ii) the value of predictive power for each of the eSOTER maps was determined, and (iii) the degree of consistency was derived. The latter is based on a weighting of the match of occurring class combinations via expert knowledge and recalculating the proportions of map appearance with these weights. To re-check the validation results a field study by local soil experts was conducted. The results show clearly that the first eSOTER approach based on the terrain classification / reinterpreted parent material information has the greatest similarity with traditional soil maps. The spatial differentiation offered by such an approach is well suitable to serve as a conceptual soil map. Therefore, eSOTER can be a tool for soil mappers to generate conceptual soil maps in a faster and more consistent way. This conclusion is at least valid for overview scales such as 1.250,000.

Soil organic carbon content assessment in a heterogeneous landscape: comparison of digital soil mapping and visible and near Infrared spectroscopy approaches

NASA Astrophysics Data System (ADS)

Michot, Didier; Fouad, Youssef; Pascal, Pichelin; Viaud, Valérie; Soltani, Inès; Walter, Christian

2017-04-01

This study aims are: i) to assess SOC content distribution according to the global soil map (GSM) project recommendations in a heterogeneous landscape ; ii) to compare the prediction performance of digital soil mapping (DSM) and visible-near infrared (Vis-NIR) spectroscopy approaches. The study area of 140 ha, located at Plancoët, surrounds the unique mineral spring water of Brittany (Western France). It's a hillock characterized by a heterogeneous landscape mosaic with different types of forest, permanent pastures and wetlands along a small coastal river. We acquired two independent datasets: j) 50 points selected using a conditioned Latin hypercube sampling (cLHS); jj) 254 points corresponding to the GSM grid. Soil samples were collected in three layers (0-5, 20-25 and 40-50cm) for both sampling strategies. SOC content was only measured in cLHS soil samples, while Vis-NIR spectra were measured on all the collected samples. For the DSM approach, a machine-learning algorithm (Cubist) was applied on the cLHS calibration data to build rule-based models linking soil carbon content in the different layers with environmental covariates, derived from digital elevation model, geological variables, land use data and existing large scale soil maps. For the spectroscopy approach, we used two calibration datasets: k) the local cLHS ; kk) a subset selected from the regional spectral database of Brittany after a PCA with a hierarchical clustering analysis and spiked by local cLHS spectra. The PLS regression algorithm with "leave-one-out" cross validation was performed for both calibration datasets. SOC contents for the 3 layers of the GSM grid were predicted using the different approaches and were compared with each other. Their prediction performance was evaluated by the following parameters: R2, RMSE and RPD. Both approaches led to satisfactory predictions for SOC content with an advantage for the spectral approach, particularly as regards the pertinence of the variation range.

Topographic soil wetness index derived from combined Alaska-British Columbia datasets for the Gulf of Alaska region

NASA Astrophysics Data System (ADS)

D'Amore, D. V.; Biles, F. E.

2016-12-01

The flow of water is often highlighted as a priority in land management planning and assessments related to climate change. Improved measurement and modeling of soil moisture is required to develop predictive estimates for plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning in the face of climate change. Drainage indexes are commonly derived from GIS tools with digital elevation models. Soil moisture classes derived from these tools are useful digital proxies for ecosystem functions associated with the concentration of water on the landscape. We developed a spatially explicit topographically derived soil wetness index (TWI) across the perhumid coastal temperate rainforest (PCTR) of Alaska and British Columbia. Developing applicable drainage indexes in complex terrain and across broad areas required careful application of the appropriate DEM, caution with artifacts in GIS covers and mapping realistic zones of wetlands with the indicator. The large spatial extent of the model has facilitated the mapping of forest habitat and the development of water table depth mapping in the region. A key element of the TWI is the merging of elevation datasets across the US-Canada border where major rivers transect the international boundary. The unified TWI allows for seemless mapping across the international border and unified ecological applications. A python program combined with the unified DEM allows end users to quickly apply the TWI to all areas of the PCTR. This common platform can facilitate model comparison and improvements to local soil moisture conditions, generation of streamflow, and ecological site conditions. In this presentation we highlight the application of the TWI for mapping risk factors related to forest decline and the development of a regional water table depth map. Improved soil moisture maps are critical for deriving spatial models of changes in soil moisture for both plant growth and streamflow across future climate conditions.

Inventory and analysis of rangeland resources of the state land block on Parker Mountain, Utah

NASA Technical Reports Server (NTRS)

Jaynes, R. A. (Principal Investigator)

1983-01-01

High altitude color infrared (CIR) photography was interpreted to provide an 1:24,000 overlay to U.S.G.S. topographic maps. The inventory and analysis of rangeland resources was augmented by the digital analysis of LANDSAT MSS data. Available geology, soils, and precipitation maps were used to sort out areas of confusion on the CIR photography. The map overlay from photo interpretation was also prepared with reference to print maps developed from LANDSAT MSS data. The resulting map overlay has a high degree of interpretive and spatial accuracy. An unacceptable level of confusion between the several sagebrush types in the MSS mapping was largely corrected by introducing ancillary data. Boundaries from geology, soils, and precipitation maps, as well as field observations, were digitized and pixel classes were adjusted according to the location of pixels with particular spectral signatures with respect to such boundaries. The resulting map, with six major cover classes, has an overall accuracy of 89%. Overall accuracy was 74% when these six classes were expanded to 20 classes.

Semi-automated landform classification for hazard mapping of soil liquefaction by earthquake

NASA Astrophysics Data System (ADS)

Nakano, Takayuki

2018-05-01

Soil liquefaction damages were caused by huge earthquake in Japan, and the similar damages are concerned in near future huge earthquake. On the other hand, a preparation of soil liquefaction risk map (soil liquefaction hazard map) is impeded by the difficulty of evaluation of soil liquefaction risk. Generally, relative soil liquefaction risk should be able to be evaluated from landform classification data by using experimental rule based on the relationship between extent of soil liquefaction damage and landform classification items associated with past earthquake. Therefore, I rearranged the relationship between landform classification items and soil liquefaction risk intelligibly in order to enable the evaluation of soil liquefaction risk based on landform classification data appropriately and efficiently. And I developed a new method of generating landform classification data of 50-m grid size from existing landform classification data of 250-m grid size by using digital elevation model (DEM) data and multi-band satellite image data in order to evaluate soil liquefaction risk in detail spatially. It is expected that the products of this study contribute to efficient producing of soil liquefaction hazard map by local government.

Integrating depth functions and hyper-scale terrain analysis for 3D soil organic carbon modeling in agricultural fields at regional scale

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, L.; van Wesemael, B.; Stevens, A.; Doetterl, S.; Van Oost, K.; Behrens, T.; Schmidt, K.

2012-04-01

Soil Organic Carbon (SOC) represents a key component in the global C cycle and has an important influence on the global CO2 fluxes between terrestrial biosphere and atmosphere. In the context of agricultural landscapes, SOC inventories are important since soil management practices have a strong influence on CO2 fluxes and SOC stocks. However, there is lack of accurate and cost-effective methods for producing high spatial resolution of SOC information. In this respect, our work is focused on the development of a three dimensional modeling approach for SOC monitoring in agricultural fields. The study area comprises ~420 km2 and includes 4 of the 5 agro-geological regions of the Grand-Duchy of Luxembourg. The soil dataset consist of 172 profiles (1033 samples) which were not sampled specifically for this study. This dataset is a combination of profile samples collected in previous soil surveys and soil profiles sampled for other research purposes. The proposed strategy comprises two main steps. In the first step the SOC distribution within each profile (vertical distribution) is modeled. Depth functions for are fitted in order to summarize the information content in the profile. By using these functions the SOC can be interpolated at any depth within the profiles. The second step involves the use of contextual terrain (ConMap) features (Behrens et al., 2010). These features are based on the differences in elevation between a given point location in the landscape and its circular neighbourhoods at a given set of different radius. One of the main advantages of this approach is that it allows the integration of several spatial scales (eg. local and regional) for soil spatial analysis. In this work the ConMap features are derived from a digital elevation model of the area and are used as predictors for spatial modeling of the parameters of the depth functions fitted in the previous step. In this poster we present some preliminary results in which we analyze: i. The use of different depth functions, ii. The use of different machine learning approaches for modeling the parameters of the fitted depth functions using the ConMap features and iii. The influence of different spatial scales on the SOC profile distribution variability. Keywords: 3D modeling, Digital soil mapping, Depth functions, Terrain analysis. Reference Behrens, T., K. Schmidt, K., Zhu, A.X. Scholten, T. 2010. The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science, v. 61, p.133-143.

Earth Observation and Geospatial techniques for Soil Salinity and Land Capability Assessment over Sundarban Bay of Bengal Coast, India

NASA Astrophysics Data System (ADS)

Das, Sumanta; Choudhury, Malini Roy; Das, Subhasish; Nagarajan, M.

2016-12-01

To guarantee food security and job creation of small scale farmers to commercial farmers, unproductive farms in the South 24 PGS, West Bengal need land reform program to be restructured and evaluated for agricultural productivity. This study established a potential role of remote sensing and GIS for identification and mapping of salinity zone and spatial planning of agricultural land over the Basanti and Gosaba Islands(808.314sq. km) of South 24 PGS. District of West Bengal. The primary data i.e. soil pH, Electrical Conductivity (EC) and Sodium Absorption ratio (SAR) were obtained from soil samples of various GCP (Ground Control Points) locations collected at 50 mts. intervals by handheld GPS from 0-100 cm depths. The secondary information is acquired from the remotely sensed satellite data (LANDSAT ETM+) in different time scale and digital elevation model. The collected field samples were tested in the laboratory and were validated with Remote Sensing based digital indices analysisover the temporal satellite data to assess the potential changes due to over salinization. Soil physical properties such as texture, structure, depth and drainage condition is stored as attributes in a geographical soil database and linked with the soil map units. The thematic maps are integrated with climatic and terrain conditions of the area to produce land capability maps for paddy. Finally, The weighted overlay analysis was performed to assign theweights according to the importance of parameters taken into account for salineareaidentification and mapping to segregate higher, moderate, lower salinity zonesover the study area.

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Digital modelling of landscape and soil in a mountainous region: A neuro-fuzzy approach

NASA Astrophysics Data System (ADS)

Viloria, Jesús A.; Viloria-Botello, Alvaro; Pineda, María Corina; Valera, Angel

2016-01-01

Research on genetic relationships between soil and landforms has largely improved soil mapping. Recent technological advances have created innovative methods for modelling the spatial soil variation from digital elevation models (DEMs) and remote sensors. This generates new opportunities for the application of geomorphology to soil mapping. This study applied a method based on artificial neural networks and fuzzy clustering to recognize digital classes of land surfaces in a mountainous area in north-central Venezuela. The spatial variation of the fuzzy memberships exposed the areas where each class predominates, while the class centres helped to recognize the topographic attributes and vegetation cover of each class. The obtained classes of terrain revealed the structure of the land surface, which showed regional differences in climate, vegetation, and topography and landscape stability. The land-surface classes were subdivided on the basis of the geological substratum to produce landscape classes that additionally considered the influence of soil parent material. These classes were used as a framework for soil sampling. A redundancy analysis confirmed that changes of landscape classes explained the variation in soil properties (p = 0.01), and a Kruskal-Wallis test showed significant differences (p = 0.01) in clay, hydraulic conductivity, soil organic carbon, base saturation, and exchangeable Ca and Mg between classes. Thus, the produced landscape classes correspond to three-dimensional bodies that differ in soil conditions. Some changes of land-surface classes coincide with abrupt boundaries in the landscape, such as ridges and thalwegs. However, as the model is continuous, it disclosed the remaining variation between those boundaries.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

PubMed Central

Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources. PMID:28114334

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

PubMed

Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.

Map of Nasca Geoglyphs

NASA Astrophysics Data System (ADS)

Hanzalová, K.; Pavelka, K.

2013-07-01

The Czech Technical University in Prague in the cooperation with the University of Applied Sciences in Dresden (Germany) work on the Nasca Project. The cooperation started in 2004 and much work has been done since then. All work is connected with Nasca lines in southern Peru. The Nasca project started in 1995 and its main target is documentation and conservation of the Nasca lines. Most of the project results are presented as WebGIS application via Internet. In the face of the impending destruction of the soil drawings, it is possible to preserve this world cultural heritage for the posterity at least in a digital form. Creating of Nasca lines map is very useful. The map is in a digital form and it is also available as a paper map. The map contains planimetric component of the map, map lettering and altimetry. Thematic folder in this map is a vector layer of the geoglyphs in Nasca/Peru. Basis for planimetry are georeferenced satellite images, altimetry is created from digital elevation model. This map was created in ArcGis software.

Lunar mineral feedstocks from rocks and soils: X-ray digital imaging in resource evaluation

NASA Technical Reports Server (NTRS)

Chambers, John G.; Patchen, Allan; Taylor, Lawrence A.; Higgins, Stefan J.; Mckay, David S.

1994-01-01

The rocks and soils of the Moon provide raw materials essential to the successful establishment of a lunar base. Efficient exploitation of these resources requires accurate characterization of mineral abundances, sizes/shapes, and association of 'ore' and 'gangue' phases, as well as the technology to generate high-yield/high-grade feedstocks. Only recently have x-ray mapping and digital imaging techniques been applied to lunar resource evaluation. The topics covered include inherent differences between lunar basalts and soils and quantitative comparison of rock-derived and soil-derived ilmenite concentrates. It is concluded that x-ray digital-imaging characterization of lunar raw materials provides a quantitative comparison that is unattainable by traditional petrographic techniques. These data are necessary for accurately determining mineral distributions of soil and crushed rock material. Application of these techniques will provide an important link to choosing the best raw material for mineral beneficiation.

Irrigation salinity hazard assessment and risk mapping in the lower Macintyre Valley, Australia.

PubMed

Huang, Jingyi; Prochazka, Melissa J; Triantafilis, John

2016-05-01

In the Murray-Darling Basin of Australia, secondary soil salinization occurs due to excessive deep drainage and the presence of shallow saline water tables. In order to understand the cause and best management, soil and vadose zone information is necessary. This type of information has been generated in the Toobeah district but owing to the state border an inconsistent methodology was used. This has led to much confusion from stakeholders who are unable to understand the ambiguity of the results in terms of final overall risk of salinization. In this research, a digital soil mapping method that employs various ancillary data is presented. Firstly, an electromagnetic induction survey using a Geonics EM34 and EM38 was used to characterise soil and vadose zone stratigraphy. From the apparent electrical conductivity (ECa) collected, soil sampling locations were selected and with laboratory analysis carried out to determine average (2-12m) clay and EC of a saturated soil-paste extract (ECe). EM34 ECa, land surface parameters derived from a digital elevation model and measured soil data were used to establish multiple linear regression models, which allowed for mapping of various hazard factors, including clay and ECe. EM38 ECa data were calibrated to deep drainage obtained from Salt and Leaching Fraction (SaLF) modelling of soil data. Expert knowledge and indicator kriging were used to determine critical values where the salinity hazard factors were likely to contribute to a shallow saline water table (i.e., clay ≤35%; ECe>2.5dS/m, and deep drainage >100mm/year). This information was combined to produce an overall salinity risk map for the Toobeah district using indicator kriging. The risk map shows potential salinization areas and where detailed information is required and where targeted research can be conducted to monitor soil conditions and water table heights and determine best management strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

Distribution of soil organic carbon in the conterminous United States

USGS Publications Warehouse

Bliss, Norman B.; Waltman, Sharon; West, Larry T.; Neale, Anne; Mehaffey, Megan; Hartemink, Alfred E.; McSweeney, Kevin M.

2014-01-01

The U.S. Soil Survey Geographic (SSURGO) database provides detailed soil mapping for most of the conterminous United States (CONUS). These data have been used to formulate estimates of soil carbon stocks, and have been useful for environmental models, including plant productivity models, hydrologic models, and ecological models for studies of greenhouse gas exchange. The data were compiled by the U.S. Department of Agriculture Natural Resources Conservation Service (NRCS) from 1:24,000-scale or 1:12,000-scale maps. It was found that the total soil organic carbon stock in CONUS to 1 m depth is 57 Pg C and for the total profile is 73 Pg C, as estimated from SSURGO with data gaps filled from the 1:250,000-scale Digital General Soil Map. We explore the non-linear distribution of soil carbon on the landscape and with depth in the soil, and the implications for sampling strategies that result from the observed soil carbon variability.

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning. [Oregon

NASA Technical Reports Server (NTRS)

Simonson, G. H. (Principal Investigator); Paine, D. P.; Lawrence, R. D.; Pyott, W. T.; Herzog, J. H.; Murray, R. J.; Norgren, J. A.; Cornwell, J. A.; Rogers, R. A.

1973-01-01

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is nearly complete on 1:250,000 scale enlargements of ERTS-1 imagery. Maps of geology, landforms, soils and vegetation-land use are being interpreted to show limitations, suitabilities and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS-1 imagery has shown a number of features not previously mapped in Oregon. A timber inventory of Ochoco National Forest has been made. Inventory of forest clear-cutting practices has been successfully demonstrated with ERTS-1 color composites. Soil tonal differences in fallow fields shown on ERTS-1 correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic materials classes has been successful in separation of most major classes around Newberry Cauldera, Mt. Washington and Big Summit Prairie. Computer routines are available for correction of scanner data variations; and for matching scales and coordinates between digital and photographic imagery. Methods of Diazo film color printing of computer classifications and elevation-slope perspective plots with computer are being developed.

Bolivian satellite technology program on ERTS natural resources

NASA Technical Reports Server (NTRS)

Brockmann, H. C. (Principal Investigator); Bartoluccic C., L.; Hoffer, R. M.; Levandowski, D. W.; Ugarte, I.; Valenzuela, R. R.; Urena E., M.; Oros, R.

1977-01-01

The author has identified the following significant results. Application of digital classification for mapping land use permitted the separation of units at more specific levels in less time. A correct classification of data in the computer has a positive effect on the accuracy of the final products. Land use unit comparison with types of soils as represented by the colors of the coded map showed a class relation. Soil types in relation to land cover and land use demonstrated that vegetation was a positive factor in soils classification. Groupings of image resolution elements (pixels) permit studies of land use at different levels, thereby forming parameters for the classification of soils.

Towards quantitative usage of EMI-data for Digital Soil Mapping

NASA Astrophysics Data System (ADS)

Nüsch, A.-K.; Wunderlich, T.; Kathage, S.; Werban, U.; Dietrich, P.

2009-04-01

As formulated in the Thematic Strategy for Soil Protection prepared by the European Commission soil degradation is a serious problem in Europe. The degradation is driven or exacerbated by human activity and has a direct impact on water and air quality, biodiversity, climate and human life-quality. High-resolution soil property maps are one major prerequisite for the specific protection of soil function and restoration of degraded soils as well as sustainable land use, water and environmental management. However, the currently available techniques for (digital) soil mapping still have deficiencies in terms of reliability and precision, the feasibility of investigation of large areas (e.g. catchments and landscapes) and the assessment of soil degradation threats at this scale. The focus of the iSOIL (Interactions between soil related science - Linking geophysics, soil science and digital soil mapping) project is on improving fast and reliable mapping of soil properties, soil functions and soil degradation threats. This requires the improvement as well as integration of geophysical and spectroscopic measurement techniques in combination with advanced soil sampling approaches, pedometrical and pedophysical approaches. Many commercially available geophysical sensors and equipment (EMI, DC, gamma-spectroscopy, magnetics) are ready to use for measurements of different parameters. Data collection with individual sensors is well developed and numerously described. However comparability of data of different sensor types as well as reproducibility of data is not self-evident. In particular handling of sensors has to be carried out accurately, e.g. consistent calibration. Soil parameters will be derived from geophysical properties to create comprehensive soil maps. Therefore one prerequisite is the comparison of different geophysical properties not only qualitative but also quantitative. At least reproducibility is one of the most important conditions for monitoring tasks. The first parameter we focussed on is apparent electrical conductivity (ECa). It is an important geophysical properity in soil science since soil parameters (water content, etc.) can be deduced. Nowadays mobile geophysical platforms allow to survey large areas comprehensively in a short time period. These platforms have been equipped with EM38DD (Geonics) and Profiler EMP-400 (GSSI) - two different types of electromagnetic induction (EMI) instruments - within first iSOIL field campaign. While EM38DD measures in horizontal and vertical mode at the same time, Profiler measures three frequencies simultaneously and magnetic susceptibility additionally. Coil separation of the instruments is nearly the same, so penetration depth is similar. On the other hand, frequencies are arbitrary at Profiler but fixed at EM38DD. These differences in penetration depth have to taken into account. By our measurement we tested the comparability of the data to show differences between instruments of the same type (EM38DD-EM38DD) using different settings, and different types (EM38DD-Profiler). Moreover both sensors work in continuous as well in discontinuous mode. The results show that quality of data is comparable, but the quantities are varying. This has to be considered for further interpretations and monitoring. In the next steps we have to determine how to convert relative data into absolute data since ECa data from different locations are not comparable to each other in a quantitative way. In the talk we will give an introduction in the application of EMI for soil monitoring, followed by an overview about comparability and reproducibility of data.

Exploring the potential offered by legacy soil databases for ecosystem services mapping of Central African soils

NASA Astrophysics Data System (ADS)

Verdoodt, Ann; Baert, Geert; Van Ranst, Eric

2014-05-01

Central African soil resources are characterised by a large variability, ranging from stony, shallow or sandy soils with poor life-sustaining capabilities to highly weathered soils that recycle and support large amounts of biomass. Socio-economic drivers within this largely rural region foster inappropriate land use and management, threaten soil quality and finally culminate into a declining soil productivity and increasing food insecurity. For the development of sustainable land use strategies targeting development planning and natural hazard mitigation, decision makers often rely on legacy soil maps and soil profile databases. Recent development cooperation financed projects led to the design of soil information systems for Rwanda, D.R. Congo, and (ongoing) Burundi. A major challenge is to exploit these existing soil databases and convert them into soil inference systems through an optimal combination of digital soil mapping techniques, land evaluation tools, and biogeochemical models. This presentation aims at (1) highlighting some key characteristics of typical Central African soils, (2) assessing the positional, geographic and semantic quality of the soil information systems, and (3) revealing its potential impacts on the use of these datasets for thematic mapping of soil ecosystem services (e.g. organic carbon storage, pH buffering capacity). Soil map quality is assessed considering positional and semantic quality, as well as geographic completeness. Descriptive statistics, decision tree classification and linear regression techniques are used to mine the soil profile databases. Geo-matching as well as class-matching approaches are considered when developing thematic maps. Variability in inherent as well as dynamic soil properties within the soil taxonomic units is highlighted. It is hypothesized that within-unit variation in soil properties highly affects the use and interpretation of thematic maps for ecosystem services mapping. Results will mainly be based on analyses done in Rwanda, but can be complemented with ongoing research results or prospects for Burundi.

Microcopying wildland maps for distribution and scanner digitizing

Treesearch

Elliot L Amidon; Joyce E. Dye

1976-01-01

Maps for wildland resource inventory and managament purposes typically show vegetation types, soils, and other areal information. For field work, maps must be large-scale. For safekeeping and compact storage, however, they can be reduced onto film, ready to be enlarged on demand by office viewers. By meeting certain simple requirements, film images are potential input...

Digital mapping of soil properties in Canadian managed forests at 250 m of resolution using the k-nearest neighbor method

NASA Astrophysics Data System (ADS)

Mansuy, N. R.; Paré, D.; Thiffault, E.

2015-12-01

Large-scale mapping of soil properties is increasingly important for environmental resource management. Whileforested areas play critical environmental roles at local and global scales, forest soil maps are typically at lowresolution.The objective of this study was to generate continuous national maps of selected soil variables (C, N andsoil texture) for the Canadian managed forest landbase at 250 m resolution. We produced these maps using thekNN method with a training dataset of 538 ground-plots fromthe National Forest Inventory (NFI) across Canada,and 18 environmental predictor variables. The best predictor variables were selected (7 topographic and 5 climaticvariables) using the Least Absolute Shrinkage and Selection Operator method. On average, for all soil variables,topographic predictors explained 37% of the total variance versus 64% for the climatic predictors. Therelative root mean square error (RMSE%) calculated with the leave-one-out cross-validation method gave valuesranging between 22% and 99%, depending on the soil variables tested. RMSE values b 40% can be considered agood imputation in light of the low density of points used in this study. The study demonstrates strong capabilitiesfor mapping forest soil properties at 250m resolution, compared with the current Soil Landscape of CanadaSystem, which is largely oriented towards the agricultural landbase. The methodology used here can potentiallycontribute to the national and international need for spatially explicit soil information in resource managementscience.

High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia.

PubMed

Wang, Bin; Waters, Cathy; Orgill, Susan; Gray, Jonathan; Cowie, Annette; Clark, Anthony; Liu, De Li

2018-07-15

Efficient and effective modelling methods to assess soil organic carbon (SOC) stock are central in understanding the global carbon cycle and informing related land management decisions. However, mapping SOC stocks in semi-arid rangelands is challenging due to the lack of data and poor spatial coverage. The use of remote sensing data to provide an indirect measurement of SOC to inform digital soil mapping has the potential to provide more reliable and cost-effective estimates of SOC compared with field-based, direct measurement. Despite this potential, the role of remote sensing data in improving the knowledge of soil information in semi-arid rangelands has not been fully explored. This study firstly investigated the use of high spatial resolution satellite data (seasonal fractional cover data; SFC) together with elevation, lithology, climatic data and observed soil data to map the spatial distribution of SOC at two soil depths (0-5cm and 0-30cm) in semi-arid rangelands of eastern Australia. Overall, model performance statistics showed that random forest (RF) and boosted regression trees (BRT) models performed better than support vector machine (SVM). The models obtained moderate results with R 2 of 0.32 for SOC stock at 0-5cm and 0.44 at 0-30cm, RMSE of 3.51MgCha -1 at 0-5cm and 9.16MgCha -1 at 0-30cm without considering SFC covariates. In contrast, by including SFC, the model accuracy for predicting SOC stock improved by 7.4-12.7% at 0-5cm, and by 2.8-5.9% at 0-30cm, highlighting the importance of including SFC to enhance the performance of the three modelling techniques. Furthermore, our models produced a more accurate and higher resolution digital SOC stock map compared with other available mapping products for the region. The data and high-resolution maps from this study can be used for future soil carbon assessment and monitoring. Copyright © 2018 Elsevier B.V. All rights reserved.

The use of LANDSAT digital data and computer-implemented techniques for an agricultural application

NASA Technical Reports Server (NTRS)

Joyce, A. T.; Griffin, R. H., II

1978-01-01

Agricultural applications procedures are described for use of LANDSAT digital data and other digitalized data (e.g., soils). The results of having followed these procedures are shown in production estimates for cotton and soybeans in Washington County, Mississippi. Examples of output products in both line printer and map formats are included, and a product adequacy assessment is made.

Digital version of the European Atlas of natural radiation.

PubMed

Cinelli, Giorgia; Tollefsen, Tore; Bossew, Peter; Gruber, Valeria; Bogucarskis, Konstantins; De Felice, Luca; De Cort, Marc

2018-02-26

The European Atlas of Natural Radiation is a collection of maps displaying the levels of natural radioactivity caused by different sources. It has been developed and is being maintained by the Joint Research Centre (JRC) of the European Commission, in line with its mission, based on the Euratom Treaty: to collect, validate and report information on radioactivity levels in the environment of the EU Member States. This work describes the first version of the European Atlas of Natural Radiation, available in digital format through a web portal, as well as the methodology and results for the maps already developed. So far the digital Atlas contains: an annual cosmic-ray dose map; a map of indoor radon concentration; maps of uranium, thorium and potassium concentration in soil and in bedrock; a terrestrial gamma dose rate map; and a map of soil permeability. Through these maps, the public will be able to: familiarize itself with natural environmental radioactivity; be informed about the levels of natural radioactivity caused by different sources; have a more balanced view of the annual dose received by the European population, to which natural radioactivity is the largest contributor; and make direct comparisons between doses from natural sources of ionizing radiation and those from man-made (artificial) ones, hence, to better assess the latter. Work will continue on the European Geogenic Radon Map and on estimating the annual dose that the public may receive from natural radioactivity, by combining all the information from the different maps. More maps could be added to the Atlas, such us radon in outdoor air and in water and concentration of radionuclides in water, even if these sources usually contribute less to the total exposure. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Generation of kth-order random toposequences

NASA Astrophysics Data System (ADS)

Odgers, Nathan P.; McBratney, Alex. B.; Minasny, Budiman

2008-05-01

The model presented in this paper derives toposequences from a digital elevation model (DEM). It is written in ArcInfo Macro Language (AML). The toposequences are called kth-order random toposequences, because they take a random path uphill to the top of a hill and downhill to a stream or valley bottom from a randomly selected seed point, and they are located in a streamshed of order k according to a particular stream-ordering system. We define a kth-order streamshed as the area of land that drains directly to a stream segment of stream order k. The model attempts to optimise the spatial configuration of a set of derived toposequences iteratively by using simulated annealing to maximise the total sum of distances between each toposequence hilltop in the set. The user is able to select the order, k, of the derived toposequences. Toposequences are useful for determining soil sampling locations for use in collecting soil data for digital soil mapping applications. Sampling locations can be allocated according to equal elevation or equal-distance intervals along the length of the toposequence, for example. We demonstrate the use of this model for a study area in the Hunter Valley of New South Wales, Australia. Of the 64 toposequences derived, 32 were first-order random toposequences according to Strahler's stream-ordering system, and 32 were second-order random toposequences. The model that we present in this paper is an efficient method for sampling soil along soil toposequences. The soils along a toposequence are related to each other by the topography they are found in, so soil data collected by this method is useful for establishing soil-landscape rules for the preparation of digital soil maps.

Soil depth mapping using seismic surface waves: Evaluation on eroded loess covered hillslopes

NASA Astrophysics Data System (ADS)

Bernardie, Severine; Samyn, Kevin; Cerdan, Olivier; Grandjean, Gilles

2010-05-01

The purposes of the multidisciplinary DIGISOIL project are the integration and improvement of in situ and proximal technologies for the assessment of soil properties and soil degradation indicators. Foreseen developments concern sensor technologies, data processing and their integration to applications of (digital) soil mapping (DSM). Among available techniques, the seismic one is, in this study, particularly tested for characterising soil vulnerability to erosion. The spectral analysis of surface waves (SASW) method is an in situ seismic technique used for evaluation of the stiffnesses (G) and associated depth in layered systems. A profile of Rayleigh wave velocity versus frequency, i.e., the dispersion curve, is calculated from each recorded seismogram before to be inverted to obtain the vertical profile of shear wave velocity Vs. Then, the soil stiffness can easily be calculated from the shear velocity if the material density is estimated, and the soil stiffness as a function of depth can be obtained. This last information can be a good indicator to identify the soil bedrock limit. SASW measurements adapted to soil characterisation is proposed in the DIGISOIL project, as it produces in an easy and quick way a 2D map of the soil. This system was tested for the digital mapping of the depth of loamy material in a catchment of the European loess belt. The validation of this methodology has been performed with the realisation of several acquisitions along the seismic profiles: - Several boreholes were drilled until the bedrock, permitting to get the geological features of the soil and the depth of the bedrock; - Several laboratory measurements of various parameters were done on samples taken from the boreholes at various depths, such as dry density, solid density, and water content; - Dynamic penetration tests were also conducted along the seismic profile, until the bedrock is attained. Some empirical correlations between the parameters measured with laboratory tests, the qc obtained from the dynamic penetration tests and the Vs acquired from the SASW measurements permit to assess the accuracy of the procedure and to evaluate its limitations. The depth to bedrock determined by this procedure can then be combined with the soil erosion susceptibility to produce a risk map. This methodology will help to target measures within areas that show a reduced soil depth associated with a high soil erosion susceptibility.

Assessment of the postagrogenic transformation of soddy-podzolic soils: Cartographic and analytic support

NASA Astrophysics Data System (ADS)

Sorokina, N. P.; Kozlov, D. N.; Kuznetsova, I. V.

2013-10-01

The results of experimental studies of the postagrogenic transformation of loamy soddy-podzolic soils on the southern slope of the Klin-Dmitrov Moraine Ridge are discussed. A chronosequence of soils (arable soils (cropland)-soils under fallow with meadow vegetation-soils under secondary forests of different ages-soils under a conventionally initial native forest) was examined, and the stages of the postagrogenic transformation of the automorphic soddy-podzolic soils were identified. The differentiation of the former plow horizon into the A1 and A1A2 horizons (according to the differences in the humus content, texture, and acidity) served as the major criterion of the soil transformation. A stage of textural differentiation with clay depletion from the uppermost layer was identified in the soils of the 20- to 60-year-old fallows. The specificity of the postagrogenic transformation of the soils on the slopes was demonstrated. From the methodological point of view, it was important to differentiate between the chronosequences of automorphic and semihydromorphic soils of the leveled interfluves and the soils of the slopes. For this purpose, a series of maps reflecting the history of the land use and the soil cover pattern was analyzed. The cartographic model included the attribute data of the soil surveys, the cartographic sources (a series of historical maps of the land use, topographic maps, remote sensing data, and a digital elevation model), and two base maps: (a) the integral map of the land use and (b) the map of the soil combinations with the separation of the zonal automorphic, semihydromorphic, and erosional soil combinations. This scheme served as a matrix for the organization and analysis of the already available and new materials.

Predicting and mapping soil available water capacity in Korea.

PubMed

Hong, Suk Young; Minasny, Budiman; Han, Kyung Hwa; Kim, Yihyun; Lee, Kyungdo

2013-01-01

The knowledge on the spatial distribution of soil available water capacity at a regional or national extent is essential, as soil water capacity is a component of the water and energy balances in the terrestrial ecosystem. It controls the evapotranspiration rate, and has a major impact on climate. This paper demonstrates a protocol for mapping soil available water capacity in South Korea at a fine scale using data available from surveys. The procedures combined digital soil mapping technology with the available soil map of 1:25,000. We used the modal profile data from the Taxonomical Classification of Korean Soils. The data consist of profile description along with physical and chemical analysis for the modal profiles of the 380 soil series. However not all soil samples have measured bulk density and water content at -10 and -1500 kPa. Thus they need to be predicted using pedotransfer functions. Furthermore, water content at -10 kPa was measured using ground samples. Thus a correction factor is derived to take into account the effect of bulk density. Results showed that Andisols has the highest mean water storage capacity, followed by Entisols and Inceptisols which have loamy texture. The lowest water retention is Entisols which are dominated by sandy materials. Profile available water capacity to a depth of 1 m was calculated and mapped for Korea. The western part of the country shows higher available water capacity than the eastern part which is mountainous and has shallower soils. The highest water storage capacity soils are the Ultisols and Alfisols (mean of 206 and 205 mm, respectively). Validation of the maps showed promising results. The map produced can be used as an indication of soil physical quality of Korean soils.

Assimilation of optical and radar remote sensing data in 3D mapping of soil properties over large areas.

PubMed

Poggio, Laura; Gimona, Alessandro

2017-02-01

Soil is very important for many land functions. To achieve sustainability it is important to understand how soils vary over space in the landscape. Remote sensing data can be instrumental in mapping and spatial modelling of soil properties, resources and their variability. The aims of this study were to compare satellite sensors (MODIS, Landsat, Sentinel-1 and Sentinel-2) with varying spatial, temporal and spectral resolutions for Digital Soil Mapping (DSM) of a set of soil properties in Scotland, evaluate the potential benefits of adding Sentinel-1 data to DSM models, select the most suited mix of sensors for DSM to map the considered set of soil properties and validate the results of topsoil (2D) and whole profile (3D) models. The results showed that the use of a mixture of sensors proved more effective to model and map soil properties than single sensors. The use of radar Sentinel-1 data proved useful for all soil properties, improving the prediction capability of models with only optical bands. The use of MODIS time series provided stronger relationships than the use of temporal snapshots. The results showed good validation statistics with a RMSE below 20% of the range for all considered soil properties. The RMSE improved from previous studies including only MODIS sensor and using a coarser prediction grid. The performance of the models was similar to previous studies at regional, national or continental scale. A mix of optical and radar data proved useful to map soil properties along the profile. The produced maps of soil properties describing both lateral and vertical variability, with associated uncertainty, are important for further modelling and management of soil resources and ecosystem services. Coupled with further data the soil properties maps could be used to assess soil functions and therefore conditions and suitability of soils for a range of purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Surficial Geologic Map of the Worcester North-Oxford- Wrentham-Attleboro Nine-Quadrangle Area in South- Central Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2008-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of nine 7.5-minute quadrangles (417 mi2 total) in south-central Massachusetts (fig. 1). Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and in resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, or organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. The mapped distribution of surficial materials that lie between the land surface and the bedrock surface is based on detailed geologic mapping of 7.5-minute topographic quadrangles, produced as part of an earlier (1938-1982) cooperative statewide mapping program between the U.S. Geological Survey and the Massachusetts Department of Public Works (now Massachusetts Highway Department) (Page, 1967; Stone, 1982). Each published geologic map presents a detailed description of local geologic map units, the genesis of the deposits, and age correlations among units. Previously unpublished field compilation maps exist on paper or mylar sheets and these have been digitally rendered for the present map compilation. Regional summaries based on the Massachusetts surficial geologic mapping studies discuss the ages of multiple glaciations, the nature of glaciofluvial, glaciolacustrine, and glaciomarine deposits, and the processes of ice advance and retreat across Massachusetts (Koteff and Pessl, 1981; papers in Larson and Stone, 1982; Oldale and Barlow, 1986; Stone and Borns, 1986; Warren and Stone, 1986). This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This surficial geologic map layer covering nine quadrangles revises previous digital surficial geologic maps (Stone and others, 1993; MassGIS, 1999) that were compiled on base maps at regional scales of 1:125,000 and 1:250,000. The purpose of this study is to provide fundamental geologic data for the evaluation of natural resources, hazards, and land information within the Commonwealth of Massachusetts.

Modelling Soil Erosion in the Densu River Basin Using RUSLE and GIS Tools.

PubMed

Ashiagbori, G; Forkuo, E K; Laari, P; Aabeyir, R

2014-07-01

Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers and policy makers are more interested in the spatial distribution of soil erosion risk than in absolute values of soil erosion loss. The aim of this paper is to model the spatial distribution of soil erosion in Densu River Basin of Ghana using RUSLE and GIS tools and to use the model to explore the relationship between erosion susceptibility, slope and land use/land cover (LULC) in the Basin. The rainfall map, digital elevation model, soil type map, and land cover map, were input data in the soil erosion model developed. This model was then categorized into four different erosion risk classes. The developed soil erosion map was then overlaid with the slope and LULC maps of the study area to explore their effects on erosion susceptibility of the soil in the Densu River Basin. The Model, predicted 88% of the basin as low erosion risk and 6% as moderate erosion risk, 3% as high erosion risk and 3% as severe risk. The high and severe erosion areas were distributed mainly within the areas of high slope gradient and also sections of the moderate forest LULC class. Also, the areas within the moderate forest LULC class found to have high erosion risk, had an intersecting high erodibility soil group.

Global soil-climate-biome diagram: linking soil properties to climate and biota

NASA Astrophysics Data System (ADS)

Zhao, X.; Yang, Y.; Fang, J.

2017-12-01

As a critical component of the Earth system, soils interact strongly with both climate and biota and provide fundamental ecosystem services that maintain food, climate, and human security. Despite significant progress in digital soil mapping techniques and the rapidly growing quantity of observed soil information, quantitative linkages between soil properties, climate and biota at the global scale remain unclear. By compiling a large global soil database, we mapped seven major soil properties (bulk density [BD]; sand, silt and clay fractions; soil pH; soil organic carbon [SOC] density [SOCD]; and soil total nitrogen [STN] density [STND]) based on machine learning algorithms (regional random forest [RF] model) and quantitatively assessed the linkage between soil properties, climate and biota at the global scale. Our results demonstrated a global soil-climate-biome diagram, which improves our understanding of the strong correspondence between soils, climate and biomes. Soil pH decreased with greater mean annual precipitation (MAP) and lower mean annual temperature (MAT), and the critical MAP for the transition from alkaline to acidic soil pH decreased with decreasing MAT. Specifically, the critical MAP ranged from 400-500 mm when the MAT exceeded 10 °C but could decrease to 50-100 mm when the MAT was approximately 0 °C. SOCD and STND were tightly linked; both increased in accordance with lower MAT and higher MAP across terrestrial biomes. Global stocks of SOC and STN were estimated to be 788 ± 39.4 Pg (1015 g, or billion tons) and 63 ± 3.3 Pg in the upper 30-cm soil layer, respectively, but these values increased to 1654 ± 94.5 Pg and 133 ± 7.8 Pg in the upper 100-cm soil layer, respectively. These results reveal quantitative linkages between soil properties, climate and biota at the global scale, suggesting co-evolution of the soil, climate and biota under conditions of global environmental change.

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Evaluating the new soil erosion map of Hungary

NASA Astrophysics Data System (ADS)

Waltner, István; Centeri, Csaba; Takács, Katalin; Pirkó, Béla; Koós, Sándor; László, Péter; Pásztor, László

2017-04-01

With growing concerns on the effects of climate change and land use practices on our soil resources, soil erosion by water is becoming a significant issue internationally. Since the 1964 publication of the first soil erosion map of Hungary, there have been several attempts to provide a countrywide assessment of erosion susceptibility. However, there has been no up-to-date map produced in the last decade. In 2016, a new, 1:100 000 scale soil erosion map was published, based on available soil, elevation, land use and meteorological data for the extremely wet year of 2010. The map utilized combined outputs for two spatially explicit methods: the widely used empirical Universal Soil Loss Equation (USLE) and the process-based Pan-European Soil Erosion Risk Assessment (PESERA) models. The present study aims to provide a detailed analysis of the model results. In lieu of available national monitoring data, information from other sources were used. The Soil Degradation Subsystem (TDR) of the National Environmental Information System (OKIR) is a digital database based on a soil survey and farm dairy data collected from representative farms in Hungary. During the survey all kind of degradation forms - including soil erosion - were considered. Agricultural and demographic data was obtained from the Hungarian Central Statistical Office (KSH). Data from an interview-based survey was also used in an attempt to assess public awareness of soil erosion risks. Point-based evaluation of the model results was complemented with cross-regional assessment of soil erosion estimates. This, combined with available demographic information provides us with an opportunity to address soil erosion on a community level, with the identification of regions with the highest risk of being affected by soil erosion.

Comparing physiographic maps with different categorisations

NASA Astrophysics Data System (ADS)

Zawadzka, J.; Mayr, T.; Bellamy, P.; Corstanje, R.

2015-02-01

This paper addresses the need for a robust map comparison method suitable for finding similarities between thematic maps with different forms of categorisations. In our case, the requirement was to establish the information content of newly derived physiographic maps with regards to set of reference maps for a study area in England and Wales. Physiographic maps were derived from the 90 m resolution SRTM DEM, using a suite of existing and new digital landform mapping methods with the overarching purpose of enhancing the physiographic unit component of the Soil and Terrain database (SOTER). Reference maps were seven soil and landscape datasets mapped at scales ranging from 1:200,000 to 1:5,000,000. A review of commonly used statistical methods for categorical comparisons was performed and of these, the Cramer's V statistic was identified as the most appropriate for comparison of maps with different legends. Interpretation of multiple Cramer's V values resulting from one-by-one comparisons of the physiographic and baseline maps was facilitated by multi-dimensional scaling and calculation of average distances between the maps. The method allowed for finding similarities and dissimilarities amongst physiographic maps and baseline maps and informed the recommendation of the most suitable methodology for terrain analysis in the context of soil mapping.

Quantitative modeling of soil genesis processes

NASA Technical Reports Server (NTRS)

Levine, E. R.; Knox, R. G.; Kerber, A. G.

1992-01-01

For fine spatial scale simulation, a model is being developed to predict changes in properties over short-, meso-, and long-term time scales within horizons of a given soil profile. Processes that control these changes can be grouped into five major process clusters: (1) abiotic chemical reactions; (2) activities of organisms; (3) energy balance and water phase transitions; (4) hydrologic flows; and (5) particle redistribution. Landscape modeling of soil development is possible using digitized soil maps associated with quantitative soil attribute data in a geographic information system (GIS) framework to which simulation models are applied.

Comparison of manually produced and automated cross country movement maps using digital image processing techniques

NASA Technical Reports Server (NTRS)

Wynn, L. K.

1985-01-01

The Image-Based Information System (IBIS) was used to automate the cross country movement (CCM) mapping model developed by the Defense Mapping Agency (DMA). Existing terrain factor overlays and a CCM map, produced by DMA for the Fort Lewis, Washington area, were digitized and reformatted into geometrically registered images. Terrain factor data from Slope, Soils, and Vegetation overlays were entered into IBIS, and were then combined utilizing IBIS-programmed equations to implement the DMA CCM model. The resulting IBIS-generated CCM map was then compared with the digitized manually produced map to test similarity. The numbers of pixels comprising each CCM region were compared between the two map images, and percent agreement between each two regional counts was computed. The mean percent agreement equalled 86.21%, with an areally weighted standard deviation of 11.11%. Calculation of Pearson's correlation coefficient yielded +9.997. In some cases, the IBIS-calculated map code differed from the DMA codes: analysis revealed that IBIS had calculated the codes correctly. These highly positive results demonstrate the power and accuracy of IBIS in automating models which synthesize a variety of thematic geographic data.

Creating soil moisture maps based on radar satellite imagery

NASA Astrophysics Data System (ADS)

Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

2017-10-01

The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

Applying a statewide geospatial leaching tool for assessing soil vulnerability ratings for agrochemicals across the contiguous United States.

PubMed

Ki, Seo Jin; Ray, Chittaranjan; Hantush, Mohamed M

2015-06-15

A large-scale leaching assessment tool not only illustrates soil (or groundwater) vulnerability in unmonitored areas, but also can identify areas of potential concern for agrochemical contamination. This study describes the methodology of how the statewide leaching tool in Hawaii modified recently for use with pesticides and volatile organic compounds can be extended to the national assessment of soil vulnerability ratings. For this study, the tool was updated by extending the soil and recharge maps to cover the lower 48 states in the United States (US). In addition, digital maps of annual pesticide use (at a national scale) as well as detailed soil properties and monthly recharge rates (at high spatial and temporal resolutions) were used to examine variations in the leaching (loads) of pesticides for the upper soil horizons. Results showed that the extended tool successfully delineated areas of high to low vulnerability to selected pesticides. The leaching potential was high for picloram, medium for simazine, and low to negligible for 2,4-D and glyphosate. The mass loadings of picloram moving below 0.5 m depth increased greatly in northwestern and central US that recorded its extensive use in agricultural crops. However, in addition to the amount of pesticide used, annual leaching load of atrazine was also affected by other factors that determined the intrinsic aquifer vulnerability such as soil and recharge properties. Spatial and temporal resolutions of digital maps had a great effect on the leaching potential of pesticides, requiring a trade-off between data availability and accuracy. Potential applications of this tool include the rapid, large-scale vulnerability assessments for emerging contaminants which are hard to quantify directly through vadose zone models due to lack of full environmental data. Copyright © 2015 Elsevier Ltd. All rights reserved.

New generation of integrated geological-geomorphological reconstruction maps in the Rhine-Meuse delta, The Netherlands

NASA Astrophysics Data System (ADS)

Pierik, Harm Jan; Cohen, Kim; Stouthamer, Esther

2016-04-01

Geological-geomorphological reconstructions are important for integrating diverse types of data and improving understanding of landscape formation processes. This works especially well in densely populated Holocene landscapes, where large quantities of raw data are produced by geotechnical, archaeological, soil science and hydrological communities as well as in academic research. The Rhine-Meuse delta, The Netherlands, has a long tradition of integrated digital reconstruction maps and databases. This contributed to improve understanding of delta evolution, especially regarding the channel belt network evolution. In this contribution, we present a new generation of digital map products for the Holocene Rhine-Meuse delta. Our reconstructions expand existing channel belt network maps, with new map layers containing natural levee extent and relative elevation. The maps we present have been based on hundreds of thousands of lithological borehole descriptions, >1000 radiocarbon dates, and further integrate LIDAR data, soil maps and archaeological information. For selected time slices through the Late Holocene, the map products describe the patterns of levee distribution. Additionally, we mapped the palaeo-topography of the levees through the delta, aiming to resolve what parts of the overbank river landscape were the relatively low and high positioned areas in the past landscape. The resulting palaeogeographical maps are integrative products created for a very data-rich research area. They will allow for delta-wide analysis in studying changes in the Late Holocene landscape and the interaction with past habitation.

Prediction of near-surface soil moisture at large scale by digital terrain modeling and neural networks.

PubMed

Lavado Contador, J F; Maneta, M; Schnabel, S

2006-10-01

The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.

Multifractal and Singularity Maps of soil surface moisture distribution derived from 2D image analysis.

NASA Astrophysics Data System (ADS)

Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria

2016-04-01

Soil moisture distribution usually presents extreme variation at multiple spatial scales. Image analysis could be a useful tool for investigating these spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to describe the local scaling of apparent soil moisture distribution and (ii) to define apparent soil moisture patterns from vertical planes of Vertisol pit images. Two soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. One was excavated in April/2011 and the other pit was established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. For more details see Cumbrera et al. (2012). Geochemical exploration have found with increasingly interests and benefits of using fractal (power-law) models to characterize geochemical distribution, using the concentration-area (C-A) model (Cheng et al., 1994; Cheng, 2012). This method is based on the singularity maps of a measure that at each point define areas with self-similar properties that are shown in power-law relationships in Concentration-Area plots (C-A method). The C-A method together with the singularity map ("Singularity-CA" method) define thresholds that can be applied to segment the map. We have applied it to each soil image. The results show that, in spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used to study the dynamical change of soil moisture sampling in agreement with previous results (Millán et al., 2016). REFERENCES Cheng, Q., Agterberg, F. P. and Ballantyne, S. B. (1994). The separation of geochemical anomalies from background by fractal methods. Journal of Geochemical Exploration, 51, 109-130. Cheng, Q. (2012). Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Cumbrera, R., Ana M. Tarquis, Gabriel Gascó, Humberto Millán (2012) Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images. Journal of Hydrology (452-453), 205-212. Martin Sotoca; J.J. Antonio Saa-Requejo, Juan Grau and Ana M. Tarquis (2016). Segmentation of singularity maps in the context of soil porosity. Geophysical Research Abstracts, 18, EGU2016-11402. Millán, H., Cumbrera, R. and Ana M. Tarquis (2016) Multifractal and Levy-stable statistics of soil surface moisture distribution derived from 2D image analysis. Applied Mathematical Modelling, 40(3), 2384-2395.

Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

2013-12-01

Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.

Lots of legacy soil data are available, but which data do we need to collect for regional land use analysis?

NASA Astrophysics Data System (ADS)

Hendriks, Chantal; Stoorvogel, Jetse; Claessens, Lieven

2015-04-01

In the past, soil surveying techniques were mainly developed for qualitative regional land use analysis (RLUA) like land evaluation and land use planning. Conventional soil survey techniques usually describe soil types according to a soil classification scheme (e.g. Soil Taxonomy and World Reference Base). These soil surveys met the requirements of qualitative land evaluation and land use planning. However, during the last decades there is an increased need for quantitative RLUA resulting in an increased demand for quantitative soil data. The rapid developments in computing technology and the availability of auxiliary information (e.g. remote sensing and digital elevation models) allowed for the development of new soil surveying techniques like digital soil mapping. These new soil surveying techniques aim to produce continuous maps of quantitative functional soil properties. However, RLUA nowadays requires soil data that include a description of the spatial variability of the entire pedon in which correlations between soil properties are retained. Current surveying techniques do not fully fulfil these requirements resulting in a gap between the supply and demand of soil data in RLUA. The gap is caused by the fact that legacy soil data are collected for different purposes and inherently have different assumptions on e.g., soil variability. In this study, some of these assumptions are tested and verified using primary soil data collected during a recent field survey in Machakos and Makueni County (Kenya). Subsequently an ongoing RLUA, the Global Yield Gap Atlas (GYGA) project, is taken as a case study to evaluate the effect of different sources of soil data on the results of the RLUA. The results of the study show that various assumptions underlying the soil survey hamper the quality requirements of soil data for the specific objectives of the RLUA. To give a few examples: mapping soil properties individually ignores correlations between them, soil properties differed significantly between natural and agricultural land, discrete soil mapping units described by a representative soil profile showed internal variability. None of the legacy datasets fitted the requirements of the RLUA. However, resources to collect additional primary soil data are limited. Evaluating legacy data allows us to identify the soil data that we need to collect. Legacy data lack information on e.g. soil management and effective rooting depth, while these data are often required for RLUA. This results in the use of assumptions, estimations and simplifications in a RLUA. The choice of legacy data has a profound effect on the results of a RLUA. The GYGA case study shows for example that different sources of soil input data can lead to differences in simulated water-limited maize yields of up to 3 ton/ha.

Mapping soil texture targeting predefined depth range or synthetizing from standard layers?

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Dezső Kaposi, András; Szatmári, Gábor; Takács, Katalin; Pásztor, László

2017-04-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. Physical soil properties, especially particle size distribution play important role in this context. A few of the requirements can be satisfied by the sand-, silt-, and clay content maps compiled according to global standards such as GlobalSoilMap (GSM) or Soil Grids. Soil texture classes (e. g. according to USDA classification) can be derived from these three fraction data, in this way texture map can be compiled based on the proper separate maps. Soil texture class as well as fraction information represent direct input of crop-, meteorological- and hydrological models. The model inputs frequently require maps representing soil features of 0-30 cm depth, which is covered by three consecutive depth intervals according to standard specifications: 0-5 cm, 5-15 cm, 15-30 cm. Becoming GSM and SoilGrids the most detailed freely available spatial soil data sources, the common model users (e. g. meteorologists, agronomists, or hydrologists) would produce input map from (the weighted mean of) these three layers. However, if the basic soil data and proper knowledge is obtainable, a soil texture map targeting directly the 0-30 cm layer could be independently compiled. In our work we compared Hungary's soil texture maps compiled using the same reference and auxiliary data and inference methods but for differing layer distribution. We produced the 0-30 cm clay, silt and sand map as well as the maps for the three standard layers (0-5 cm, 5-15 cm, 15-30 cm). Maps of sand, silt and clay percentage were computed through regression kriging (RK) applying Additive Log-Ratio (alr) transformation. In addition to the Hungarian Soil Information and Monitoring System as reference soil data, digital elevation model and its derived components, soil physical property maps, remotely sensed images, land use -, geological-, as well as meteorological data were applied as auxiliary variables. We compared the directly compiled and the synthetized clay-, sand content, and texture class maps by different tools. In addition to pairwise comparison of basic statistical features (histograms, scatter plots), we examined the spatial distribution of the differences. We quantified the taxonomical distances of the textural classes, in order to investigate the differences of the map-pairs. We concluded that the directly computed and the synthetized maps show various differences. In the case of clay-, and sand content maps, the map-pairs have to be considered statistically different. On the other hand, the differences of the texture class maps are not significant. However, in all cases, the differences rather concern the extreme ranges and categories. Using of synthetized maps can intensify extremities by error propagation in models and scenarios. Based on our results, we suggest the usage of the directly composed maps.

Digital soil mapping for the support of delineation of Areas Facing Natural Constraints defined by common European biophysical criteria

NASA Astrophysics Data System (ADS)

Pásztor, László; Bakacsi, Zsófia; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor; Tóth, Tibor; Szabó, József

2016-04-01

One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in Areas Facing Natural Constraints (ANC) in order to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. ANC assignment has both ecological and severe economical aspects. Recently the delimitation of ANCs is suggested to be carried out by using common biophysical diagnostic criteria on low soil productivity and poor climate conditions all over Europe. The criterion system was elaborated and has been repeatedly upgraded by JRC. The operational implementation is under member state competence. This process requires application of available soil databases and proper thematic and spatial inference methods. In our paper we present the inferences applied for the latest identification and delineation of areas with low soil productivity in Hungary according to JRC biophysical criteria related to soil: limited soil drainage, texture and stoniness (coarse texture, heavy clay, vertic properties), shallow rooting depth, chemical properties (salinity, sodicity, low pH). The compilation of target specific maps were based on the available legacy and recently collected data. In the present work three different data sources were used. The most relevant available data were queried from the datasets for each mapped criterion for either direct application or for the compilation a suitable, synthetic (non-measured) parameter. In some cases the values of the target variable originated from only one, in other cases from more databases. The reference dataset used in the mapping process was set up after substantial statistical analysis and filtering. It consisted of the values of the target variable attributed to the finally selected georeferenced locations. For spatial inference regression kriging was applied. Accuracy assessment was carried out by Leave One Out Cross Validation (LOOCV). In some cases the DSM product directly provided the delineation result by simple querying, in other cases further interpretation of the map was necessary. As the result of our work not only spatial fulfilment of the European biophysical criteria was assessed and provided for decision makers, but unique digital soil map products were elaborated regionalizing specific soil features, which were never mapped before, even nationally with 1 ha spatial resolution. Acknowledgement: Our work was supported by the "European Fund for Agricultural and Rural Development: Europe investing in rural areas" with the support of the European Union and Hungary and by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Evaluation of digital soil mapping approaches with large sets of environmental covariates

NASA Astrophysics Data System (ADS)

Nussbaum, Madlene; Spiess, Kay; Baltensweiler, Andri; Grob, Urs; Keller, Armin; Greiner, Lucie; Schaepman, Michael E.; Papritz, Andreas

2018-01-01

The spatial assessment of soil functions requires maps of basic soil properties. Unfortunately, these are either missing for many regions or are not available at the desired spatial resolution or down to the required soil depth. The field-based generation of large soil datasets and conventional soil maps remains costly. Meanwhile, legacy soil data and comprehensive sets of spatial environmental data are available for many regions. Digital soil mapping (DSM) approaches relating soil data (responses) to environmental data (covariates) face the challenge of building statistical models from large sets of covariates originating, for example, from airborne imaging spectroscopy or multi-scale terrain analysis. We evaluated six approaches for DSM in three study regions in Switzerland (Berne, Greifensee, ZH forest) by mapping the effective soil depth available to plants (SD), pH, soil organic matter (SOM), effective cation exchange capacity (ECEC), clay, silt, gravel content and fine fraction bulk density for four soil depths (totalling 48 responses). Models were built from 300-500 environmental covariates by selecting linear models through (1) grouped lasso and (2) an ad hoc stepwise procedure for robust external-drift kriging (georob). For (3) geoadditive models we selected penalized smoothing spline terms by component-wise gradient boosting (geoGAM). We further used two tree-based methods: (4) boosted regression trees (BRTs) and (5) random forest (RF). Lastly, we computed (6) weighted model averages (MAs) from the predictions obtained from methods 1-5. Lasso, georob and geoGAM successfully selected strongly reduced sets of covariates (subsets of 3-6 % of all covariates). Differences in predictive performance, tested on independent validation data, were mostly small and did not reveal a single best method for 48 responses. Nevertheless, RF was often the best among methods 1-5 (28 of 48 responses), but was outcompeted by MA for 14 of these 28 responses. RF tended to over-fit the data. The performance of BRT was slightly worse than RF. GeoGAM performed poorly on some responses and was the best only for 7 of 48 responses. The prediction accuracy of lasso was intermediate. All models generally had small bias. Only the computationally very efficient lasso had slightly larger bias because it tended to under-fit the data. Summarizing, although differences were small, the frequencies of the best and worst performance clearly favoured RF if a single method is applied and MA if multiple prediction models can be developed.

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

2017-04-01

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

Effects of Soil Data and Simulation Unit Resolution on Quantifying Changes of Soil Organic Carbon at Regional Scale with a Biogeochemical Process Model

PubMed Central

Zhang, Liming; Yu, Dongsheng; Shi, Xuezheng; Xu, Shengxiang; Xing, Shihe; Zhao, Yongcong

2014-01-01

Soil organic carbon (SOC) models were often applied to regions with high heterogeneity, but limited spatially differentiated soil information and simulation unit resolution. This study, carried out in the Tai-Lake region of China, defined the uncertainty derived from application of the DeNitrification-DeComposition (DNDC) biogeochemical model in an area with heterogeneous soil properties and different simulation units. Three different resolution soil attribute databases, a polygonal capture of mapping units at 1∶50,000 (P5), a county-based database of 1∶50,000 (C5) and county-based database of 1∶14,000,000 (C14), were used as inputs for regional DNDC simulation. The P5 and C5 databases were combined with the 1∶50,000 digital soil map, which is the most detailed soil database for the Tai-Lake region. The C14 database was combined with 1∶14,000,000 digital soil map, which is a coarse database and is often used for modeling at a national or regional scale in China. The soil polygons of P5 database and county boundaries of C5 and C14 databases were used as basic simulation units. Results project that from 1982 to 2000, total SOC change in the top layer (0–30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, −3.99 Tg C and −15.38 Tg C based on P5, C5 and C14 databases, respectively. With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively. The comparison illustrates that DNDC simulation is strongly influenced by choice of fundamental geographic resolution as well as input soil attribute detail. The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle. PMID:24523922

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS

PubMed Central

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data. PMID:26090852

Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS.

PubMed

Wang, De-Cai; Zhang, Gan-Lin; Zhao, Ming-Song; Pan, Xian-Zhang; Zhao, Yu-Guo; Li, De-Cheng; Macmillan, Bob

2015-01-01

Numerous studies have investigated the direct retrieval of soil properties, including soil texture, using remotely sensed images. However, few have considered how soil properties influence dynamic changes in remote images or how soil processes affect the characteristics of the spectrum. This study investigated a new method for mapping regional soil texture based on the hypothesis that the rate of change of land surface temperature is related to soil texture, given the assumption of similar starting soil moisture conditions. The study area was a typical flat area in the Yangtze-Huai River Plain, East China. We used the widely available land surface temperature product of MODIS as the main data source. We analyzed the relationships between the content of different particle soil size fractions at the soil surface and land surface day temperature, night temperature and diurnal temperature range (DTR) during three selected time periods. These periods occurred after rainfalls and between the previous harvest and the subsequent autumn sowing in 2004, 2007 and 2008. Then, linear regression models were developed between the land surface DTR and sand (> 0.05 mm), clay (< 0.001 mm) and physical clay (< 0.01 mm) contents. The models for each day were used to estimate soil texture. The spatial distribution of soil texture from the studied area was mapped based on the model with the minimum RMSE. A validation dataset produced error estimates for the predicted maps of sand, clay and physical clay, expressed as RMSE of 10.69%, 4.57%, and 12.99%, respectively. The absolute error of the predictions is largely influenced by variations in land cover. Additionally, the maps produced by the models illustrate the natural spatial continuity of soil texture. This study demonstrates the potential for digitally mapping regional soil texture variations in flat areas using readily available MODIS data.

Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions.

PubMed

Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D

2017-10-01

Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

GlobalSoilMap France: High-resolution spatial modelling the soils of France up to two meter depth.

PubMed

Mulder, V L; Lacoste, M; Richer-de-Forges, A C; Arrouays, D

2016-12-15

This work presents the first GlobalSoilMap (GSM) products for France. We developed an automatic procedure for mapping the primary soil properties (clay, silt, sand, coarse elements, pH, soil organic carbon (SOC), cation exchange capacity (CEC) and soil depth). The procedure employed a data-mining technique and a straightforward method for estimating the 90% confidence intervals (CIs). The most accurate models were obtained for pH, sand and silt. Next, CEC, clay and SOC were found reasonably accurate predicted. Coarse elements and soil depth were the least accurate of all models. Overall, all models were considered robust; important indicators for this were 1) the small difference in model diagnostics between the calibration and cross-validation set, 2) the unbiased mean predictions, 3) the smaller spatial structure of the prediction residuals in comparison to the observations and 4) the similar performance compared to other developed GlobalSoilMap products. Nevertheless, the confidence intervals (CIs) were rather wide for all soil properties. The median predictions became less reliable with increasing depth, as indicated by the increase of CIs with depth. In addition, model accuracy and the corresponding CIs varied depending on the soil variable of interest, soil depth and geographic location. These findings indicated that the CIs are as informative as the model diagnostics. In conclusion, the presented method resulted in reasonably accurate predictions for the majority of the soil properties. End users can employ the products for different purposes, as was demonstrated with some practical examples. The mapping routine is flexible for cloud-computing and provides ample opportunity to be further developed when desired by its users. This allows regional and international GSM partners with fewer resources to develop their own products or, otherwise, to improve the current routine and work together towards a robust high-resolution digital soil map of the world. Copyright © 2016 Elsevier B.V. All rights reserved.

Digital soil mapping in assessment of land suitability for organic farming

NASA Astrophysics Data System (ADS)

Ghambashidze, Giorgi; Kentchiashvili, Naira; Tarkhnishvili, Maia; Jolokhava, Tamar; Meskhi, Tea

2017-04-01

Digital soil mapping (DSM) is a fast-developing sub discipline of soil science which gets more importance along with increased availability of spatial data. DSM is based on three main components: the input in the form of field and laboratory observational methods, the process used in terms of spatial and non-spatial soil inference systems, and the output in the form of spatial soil information systems, which includes outputs in the form of rasters of prediction along with the uncertainty of prediction. Georgia is one of the countries who are under the way of spatial data infrastructure development, which includes soil related spatial data also. Therefore, it is important to demonstrate the capacity of DSM technics for planning and decision making process, in which assessment of land suitability is a major interest for those willing to grow agricultural crops. In that term land suitability assessment for establishing organic farms is in high demand as market for organically produced commodities is still increasing. It is the first attempt in Georgia to use DSM to predict areas with potential for organic farming development. Current approach is based on risk assessment of soil pollution with toxic elements (As, Hg, Pb, Cd, Cr) and prediction of bio-availability of those elements to plants on example of the region of Western Georgia, where detailed soil survey was conducted and spatial database of soil was created. The results of the study show the advantages of DSM at early stage assessment and depending on availability and quality of the input data, it can achieve acceptable accuracy.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1983-01-01

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

Software For Tie-Point Registration Of SAR Data

NASA Technical Reports Server (NTRS)

Rignot, Eric; Dubois, Pascale; Okonek, Sharon; Van Zyl, Jacob; Burnette, Fred; Borgeaud, Maurice

1995-01-01

SAR-REG software package registers synthetic-aperture-radar (SAR) image data to common reference frame based on manual tie-pointing. Image data can be in binary, integer, floating-point, or AIRSAR compressed format. For example, with map of soil characteristics, vegetation map, digital elevation map, or SPOT multispectral image, as long as user can generate binary image to be used by tie-pointing routine and data are available in one of the previously mentioned formats. Written in FORTRAN 77.

Selected Aspects of Soil Science History in the USA - 1980s to the 2010s

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Homburg, Jeffrey A.; Miller, Bradley A.; Fenton, Thomas E.; Doolittle, James A.; Indorante, Samuel J.

2017-04-01

The beginning of the 20th century through the 1970s were good times for soil science in the USA, with relatively strong funding and overall growth in the profession. However, the soil science discipline in the USA hit hard times in the 1980s and 1990s. Federal funding for soil survey work began to decline as did student numbers in university programs and membership in the Soil Science Society of America (SSSA). Despite this, there were still many positive advances within soil science in the USA during these two decades. There was an increased use of geophysical instrumentation, remote sensing, geographic information systems (GIS), and global positioning systems (GPS), and research began in digital soil mapping, all of which lead to better understanding of the spatial distribution and variability of soils. Many NRCS soil products were put online, making them widely available to the general public, and the use of soil knowledge was expanded into new areas such as archaeology and environmental work, and historic connections to geology were re-established. While expansion into new areas required soil science to evolve as a field, separating the discipline to an extent from its agricultural roots, it also helped reinvigorate the discipline. As we move through the early parts of the 21st century, student numbers are increasing in university soil science programs and membership in SSSA is at an all-time high. Digital soil mapping is being incorporated into the National Cooperative Soil Survey, and the impact of humans on the soil system is being fully recognized. The importance of soils is being recognized by events such as the United Nations declaration of 2015 as the "International Year of Soils". The expansion of soils into new areas and widening recognition of the importance of soils gives the field hope for a bright future in the USA.

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning. [Oregon - Newberry Caldera, Mt. Washington, and Big Summit Prairie in Crook County

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Simonson, G. H.; Paine, D. P.; Lawrence, R. D.; Pyott, W. T.; Herzog, J. H.; Murray, R. J.; Norgren, J. A.; Cornwell, J. A.; Rogers, R. A.

1974-01-01

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is complete on 1:250,000 scale enlargements of ERTS imagery and 1:120,000 hi-flight photography. Maps of geology, soils, vegetation-land use and land resources units were interpreted to show limitations, suitabilities, and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS imagery has shown a number of features not previously mapped in Oregon. A multistage timber inventory of Ochoco National Forest was made, using ERTS images as the first stage. Inventory of forest clear-cutting practices was successfully demonstrated with color composites. Soil tonal differences in fallow fields correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic material classes was successful in separating most major classes around Newberry Caldera, Mt. Washington, and Big Summit Prairie.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Mapping soil erosion risk in Serra de Grândola (Portugal)

NASA Astrophysics Data System (ADS)

Neto Paixão, H. M.; Granja Martins, F. M.; Zavala, L. M.; Jordán, A.; Bellinfante, N.

2012-04-01

Geomorphological processes can pose environmental risks to people and economical activities. Information and a better knowledge of the genesis of these processes is important for environmental planning, since it allows to model, quantify and classify risks, what can mitigate the threats. The objective of this research is to assess the soil erosion risk in Serra de Grândola, which is a north-south oriented mountain ridge with an altitude of 383 m, located in southwest of Alentejo (southern Portugal). The study area is 675 km2, including the councils of Grândola, Santiago do Cacém and Sines. The process for mapping of erosive status was based on the guidelines for measuring and mapping the processes of erosion of coastal areas of the Mediterranean proposed by PAP/RAC (1997), developed and later modified by other authors in different areas. This method is based on the application of a geographic information system that integrates different types of spatial information inserted into a digital terrain model and in their derivative models. Erosive status are classified using information from soil erodibility, slope, land use and vegetation cover. The rainfall erosivity map was obtained using the modified Fournier index, calculated from the mean monthly rainfall, as recorded in 30 meteorological stations with influence in the study area. Finally, the soil erosion risk map was designed by ovelaying the erosive status map and the rainfall erosivity map.

The influence of exogenous conditions on mobile measured gamma-ray spectrometry

NASA Astrophysics Data System (ADS)

Dierke, C.; Werban, U.; Dietrich, P.

2012-12-01

In the past, gamma ray measurements have been used for geological surveys and exploration using airborne and borehole logging systems. For these applications, the relationships between the measured physical parameter - the concentration of natural gamma emitters 40K, 238U and 232Th - and geological origin or sedimentary developments are well described. Based on these applications and knowledge in combination with adjusted sensor systems, gamma ray measurements are used to derive soil parameters to create detailed soil maps e.g., in digital soil mapping (DSM) and monitoring of soils. Therefore, not only qualitative but also quantitative comparability is necessary. Grain size distribution, type of clay minerals and organic matter content are soil parameters which directly influence the gamma ray emitter concentration. Additionally, the measured concentration is influenced by endogenous processes like soil moisture variation due to raining events, foggy weather conditions, or erosion and deposition of material. A time series of gamma ray measurements was used to observe changes in gamma ray concentration on a floodplain area in Central Germany. The study area is characterised by high variations in grain size distribution and occurrence of flooding events. For the survey, we used a 4l NaI(Tl) detector with GPS connection mounted on a sledge, which is towed across the field sites by a four-wheel-vehicle. The comparison of data from different time steps shows similar structures with minor variation between the data ranges and shape of structures. However, the data measured during different soil moisture contents differ in absolute value. An average increase of soil moisture of 36% leads to a decrease of Th (by 20%), K (by 29%), and U (by 41%). These differences can be explained by higher attenuation of radiation during higher soil moisture content. The different changes in nuclide concentration will also lead to varying ratios. We will present our experiences concerning the measurement under variable field conditions and their impacts on gamma ray data quality. These activities are done within the iSOIL project. iSOIL- Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment; iSOIL is one member of the SOIL TECHNOLOGY CLUSTER of Research Projects funded by the EC.

Soil erosion assessment using the Universal Soil Loss Equation (USLE) in a GIS framework: A case study of Zacatecas, México

NASA Astrophysics Data System (ADS)

Betanzos Arroyo, L. I.; Prol Ledesma, R. M.; da Silva Pinto da Rocha, F. J. P.

2014-12-01

The Universal Soil Loss Equation (USLE), which is considered to be a contemporary approach in soil loss assessment, was used to assess soil erosion hazard in the Zacatecas mining district. The purpose of this study is to produce erosion susceptibility maps for an area that is polluted with mining tailings which are susceptible to erosion and can disperse the particles that contain heavy metals and other toxic elements. USLE method is based in the estimation of soil loss per unit area and takes into account specific parameters such as precipitation data, topography, soil erodibility, erosivity and runoff. The R-factor (rainfall erosivity) was calculated from monthly and annual precipitation data. The K-factor (soil erodibility) was estimated using soil maps available from the CONABIO at a scale of 1:250000. The LS-factor (slope length and steepness) was determined from a 30-m digital elevation model. A raster-based Geographic Information System (GIS) was used to interactively calculate soil loss and map erosion hazard. The results show that estimated erosion rates ranged from 0 to 4770.48 t/ha year. Maximum proportion of the total area of the Zacatecas mining district have nil to very extremely slight erosion severity. Small areas in the central and south part of the study area shows the critical condition requiring sustainable land management.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

Machine learning for predicting soil classes in three semi-arid landscapes

USGS Publications Warehouse

Brungard, Colby W.; Boettinger, Janis L.; Duniway, Michael C.; Wills, Skye A.; Edwards, Thomas C.

2015-01-01

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

Surficial geologic map of the Heath-Northfield-Southwick-Hampden 24-quadrangle area in the Connecticut Valley region, west-central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2010-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in west-central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text, quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Norton-Manomet-Westport-Sconticut Neck 23-quadrangle area in southeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.; Kincare, Kevin A.

2012-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 23 7.5-minute quadrangles (919 mi2 total) in southeastern Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts

USGS Publications Warehouse

Stone, Janet R.

2013-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction-aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Hungarian contribution to the Global Soil Organic Carbon Map (GSOC17) using advanced machine learning algorithms and geostatistics

NASA Astrophysics Data System (ADS)

Szatmári, Gábor; Laborczi, Annamária; Takács, Katalin; Pásztor, László

2017-04-01

The knowledge about soil organic carbon (SOC) baselines and changes, and the detection of vulnerable hot spots for SOC losses and gains under climate change and changed land management is still fairly limited. Thus Global Soil Partnership (GSP) has been requested to develop a global SOC mapping campaign by 2017. GSPs concept builds on official national data sets, therefore, a bottom-up (country-driven) approach is pursued. The elaborated Hungarian methodology suits the general specifications of GSOC17 provided by GSP. The input data for GSOC17@HU mapping approach has involved legacy soil data bases, as well as proper environmental covariates related to the main soil forming factors, such as climate, organisms, relief and parent material. Nowadays, digital soil mapping (DSM) highly relies on the assumption that soil properties of interest can be modelled as a sum of a deterministic and stochastic component, which can be treated and modelled separately. We also adopted this assumption in our methodology. In practice, multiple regression techniques are commonly used to model the deterministic part. However, this global (and usually linear) models commonly oversimplify the often complex and non-linear relationship, which has a crucial effect on the resulted soil maps. Thus, we integrated machine learning algorithms (namely random forest and quantile regression forest) in the elaborated methodology, supposing then to be more suitable for the problem in hand. This approach has enable us to model the GSOC17 soil properties in that complex and non-linear forms as the soil itself. Furthermore, it has enable us to model and assess the uncertainty of the results, which is highly relevant in decision making. The applied methodology has used geostatistical approach to model the stochastic part of the spatial variability of the soil properties of interest. We created GSOC17@HU map with 1 km grid resolution according to the GSPs specifications. The map contributes to the GSPs GSOC17 proposals, as well as to the development of global soil information system under GSP Pillar 4 on soil data and information. However, we elaborated our adherent code (created in R software environment) in such a way that it can be improved, specified and applied for further uses. Hence, it opens the door to create countrywide map(s) with higher grid resolution for SOC (or other soil related properties) using the advanced methodology, as well as to contribute and support the SOC (or other soil) related country level decision making. Our paper will present the soil mapping methodology itself, the resulted GSOC17@HU map, some of our conclusions drawn from the experiences and their effects on the further uses. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Mapping Arid Vegetation Species Distributions in the White Mountains, Eastern California, Using AVIRIS, Topography, and Geology

NASA Technical Reports Server (NTRS)

VandeVen, C.; Weiss, S. B.

2001-01-01

Our challenge is to model plant species distributions in complex montane environments using disparate sources of data, including topography, geology, and hyperspectral data. From an ecologist's point of view, species distributions are determined by local environment and disturbance history, while spectral data are 'ancillary.' However, a remote sensor's perspective says that spectral data provide picture of what vegetation is there, topographic and geologic data are ancillary. In order to bridge the gap, all available data should be used to get the best possible prediction of species distributions using complex multivariate techniques implemented on a GIS. Vegetation reflects local climatic and nutrient conditions, both of which can be modeled, allowing predictive mapping of vegetation distributions. Geologic substrate strongly affects chemical, thermal, and physical properties of soils, while climatic conditions are determined by local topography. As elevation increases, precipitation increases and temperature decreases. Aspect, slope, and surrounding topography determine potential insolation, so that south-facing slopes are warmer and north-facing slopes cooler at a given elevation. Topographic position (ridge, slope, canyon, or meadow) and slope angle affect sediment accumulation and soil depth. These factors combine as complex environmental gradients, and underlie many features of plant distributions. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, digital elevation models, digitized geologic maps, and 378 ground control points were used to predictively map species distributions in the central and southern White Mountains, along the western boundary of the Basin and Range province. Minimum Noise Fraction (MNF) bands were calculated from the visible and near-infrared AVIRIS bands, and combined with digitized geologic maps and topographic variables using Canonical Correspondence Analysis (CCA). CCA allows for modeling species 'envelopes' in multidimensional environmental space, which can then be projected across entire landscapes.

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1982-01-01

Research projects described include: (1) identifying coniferous forest types in Michigan using LANDSAT imagery; (2) investigating synoptic temperature patterns in Michigan as determined via GOES and HCMM thermal imagery; (3) land surface change detection using satellite data and a geographic data base; (4) determining soil map unit composition by electronic scanning densitometry; and (5) delimiting areas of virus infection in vineyards and blueberry fields in southwestern and western Michigan. Contractual activities involve important farmlands inventory, changes in aquatic vegetation in Saginaw Bay, digitized soil association map of Michigan, and aerial photography for hybrid-poplar research. On-going projects are also being conducted in Jamaica, Honduras, the Dominican Republic and Kenya.

Landsat mapping of rocks associated with copper mineralization, northern Bahia State, Brazil

NASA Technical Reports Server (NTRS)

Stone, T. A.; Birnie, R. W.; Zantop, H.

1983-01-01

This project has applied Landsat digital data to a study of the geology of a mineralized zone in northern Bahia State, Brazil. The study accomplished two tasks: (1) production of a 1:100,000 geologic map of approximately 3300 sq km and (2) development of a two tiered geobotanical index that exploits increased vegetation density and decreased soil brightness on the mafic rock units.

Analyzing existing conventional soil information sources to be incorporated in thematic Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Pascual-Aguilar, J. A.; Rubio, J. L.; Domínguez, J.; Andreu, V.

2012-04-01

New information technologies give the possibility of widespread dissemination of spatial information to different geographical scales from continental to local by means of Spatial Data Infrastructures. Also administrative awareness on the need for open access information services has allowed the citizens access to this spatial information through development of legal documents, such as the INSPIRE Directive of the European Union, adapted by national laws as in the case of Spain. The translation of the general criteria of generic Spatial Data Infrastructures (SDI) to thematic ones is a crucial point for the progress of these instruments as large tool for the dissemination of information. In such case, it must be added to the intrinsic criteria of digital information, such as the harmonization information and the disclosure of metadata, the own environmental information characteristics and the techniques employed in obtaining it. In the case of inventories and mapping of soils, existing information obtained by traditional means, prior to the digital technologies, is considered to be a source of valid information, as well as unique, for the development of thematic SDI. In this work, an evaluation of existing and accessible information that constitutes the basis for building a thematic SDI of soils in Spain is undertaken. This information framework has common features to other European Union states. From a set of more than 1,500 publications corresponding to the national territory of Spain, the study was carried out in those documents (94) found for five autonomous regions of northern Iberian Peninsula (Asturias, Cantabria, Basque Country, Navarra and La Rioja). The analysis was performed taking into account the criteria of soil mapping and inventories. The results obtained show a wide variation in almost all the criteria: geographic representation (projections, scales) and geo-referencing the location of the profiles, map location of profiles integrated with edaphic units, description and taxonomic classification systems of soils (FAO, Soil taxonomy, etc.), amount and type of soil analysis parameters and dates of the inventories. In conclusion, the construction of thematic SDI on soil should take into account, prior to the integration of all maps and inventories, a series of processes of harmonization that allows spatial continuity between existing information and also temporal identification of the inventories and maps. This should require the development of at least two types of integration tools: (1) enabling spatial continuity without contradictions between maps made at different times and with different criteria and (2) the development of information systems data (metadata) to highlight the characteristics of information and connection possibilities with other sources that comprise the Spatial Data Infrastructure. Acknowledgements This research has financed by the European Union within the framework of the GS Soil project (eContentplus Programme ECP-2008-GEO-318004).

Soil property maps of Africa at 250 m resolution

NASA Astrophysics Data System (ADS)

Kempen, Bas; Hengl, Tomislav; Heuvelink, Gerard B. M.; Leenaars, Johan G. B.; Walsh, Markus G.; MacMillan, Robert A.; Mendes de Jesus, Jorge S.; Shepherd, Keith; Sila, Andrew; Desta, Lulseged T.; Tondoh, Jérôme E.

2015-04-01

Vast areas of arable land in sub-Saharan Africa suffer from low soil fertility and physical soil constraints, and significant amounts of nutrients are lost yearly due to unsustainable soil management practices. At the same time it is expected that agriculture in Africa must intensify to meet the growing demand for food and fiber the next decades. Protection and sustainable management of Africa's soil resources is crucial to achieve this. In this context, comprehensive, accurate and up-to-date soil information is an essential input to any agricultural or environmental management or policy and decision-making model. In Africa, detailed soil information has been fragmented and limited to specific zones of interest for decades. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. AfSIS builds on recent advances in digital soil mapping, infrared spectroscopy, remote sensing, (geo)statistics, and integrated soil fertility management to improve the way soils are evaluated, mapped, and monitored. Over the period 2008-2014, the AfSIS project has compiled two soil profile data sets (about 28,000 unique locations): the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site (new soil samples) database -- the two data sets represent the most comprehensive soil sample database of the African continent to date. In addition a large set of high-resolution environmental data layers (covariates) was assembled. The point data were used in the AfSIS project to generate a set of maps of key soil properties for the African continent at 250 m spatial resolution: sand, silt and clay fractions, bulk density, organic carbon, total nitrogen, pH, cation-exchange capacity, exchangeable bases (Ca, K, Mg, Na), exchangeable acidity, and Al content. These properties were mapped for six depth intervals up to 2 m: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. Random forests modelling was used to relate the soil profile observations to a set covariates, that included global soil class and property maps, MODIS imagery and a DEM, in a 3D mapping framework. The model residuals were interpolated by 3D kriging, after which the kriging predictions were added to the random forests predictions to obtain the soil property predictions. The model predictions were validated with 5-fold cross-validation. The random forests models explained between 37% (exch. Na) and 85% (Al content) of the variation in the data. Results also show that globally predicted soil classes help improve continental scale mapping of the soil nutrients and are often among the most important predictors. We conclude that the first mapping results look promising. We used an automated modelling framework that enables re-computing the maps as new data becomes arrives, hereby gradually improving the maps. We showed that global maps of soil classes and properties produced with models that were predominantly calibrated on areas with plentiful observations can be used to improve the accuracy of predictions in regions with less plentiful data, such as Africa.

Use of mobile gammaspectrometry for estimation of texture at regional scale

NASA Astrophysics Data System (ADS)

Dierke, C.; Werban, U.; Dietrich, P.

2012-04-01

In the last years gamma-ray measurements from air and ground were increasingly used for spatial mapping of physical soil parameters. Many applications of gamma-ray measurements for soil characterisation and in digital soil mapping (DSM) are known from Australia or single once from Northern America. During the last years there are attempts to use that method in Europe as well. The measured isotope concentration of the gamma emitter 40K, 238U and 232Th in soils depends on different soil parameters, which are the result of composition and properties of parent rock and processes during soil geneses under different climatic conditions. Grain size distribution, type of clay minerals and organic matter are soil parameters which influence directly the gamma-ray concentration. From former studies we know, that there are site specific relationships at the field scale between gamma-ray measurements and soil properties. One of the target soil properties in DSM is for e.g. the spatial distribution of texture at the landscape scale. Thus there is a need of more regional understanding of gamma-ray concentration and soil properties with regard to the complex geology of Europe. We did systematic measurements at different field sites across Europe to investigate the relationship between the concentrations of gamma radiant and grain size. The areas are characterised by different pedogenesis and varying clay content. For the measurement we used a mobile 4l Na(I) detector with GPS connection, which is mounted on a sledge and can be towed across the agricultural used plane. Additionally we selected points for soil sampling and analysis of soil texture. For the interpretation we used the single nuclide concentration as well as the ratios. The results show site specific relationships dependent from source material. At soils developed from alluvial sediments the K/Th ratio is an indicator for clay content at regional scale. At soils developed from loess sediments Th can be used do discriminate between fine (clay + silt) and coarse (sand) fraction. This knowledge will led to a more conceptual understanding of gamma-ray measurements at regional scale. These activities are done within the iSOIL project. iSOIL- Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment; iSOIL is one member of the SOIL TECHNOLOGY CLUSTER of Research Projects funded by the EC.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

Relationship between forest clearing and biophysical factors in tropical environments: Implications for the design of a forest change monitoring approach. [Costa Rica

NASA Technical Reports Server (NTRS)

Sader, S. A.; Joyce, A. T.

1984-01-01

The relationship between forest clearing, biophysical factors (e.g, ecological zones, slope gradient, soils), and transportation network in Costa Rica was analyzed. The location of forested areas at four reference datas (1940, 1950, 1961, and 1977) as derived from aerial photography and LANDSAT MSS data was digitilized and entered into a geographically-referenced data base. Ecological zones as protrayed by the Holdridge Life Zone Ecology System, and the location of roads and railways were also digitized from maps of the entire country as input to the data base. Information on slope gradient and soils was digitized from maps of a 21,000 square kilometer area. The total area of forest cleared over four decades are related to biophysical factors was analyzed within the data base and deforestation rates and trends were tabulated. The relatiohship between forest clearing and ecological zone and the influence of topography, sils, and transportation network are presented and discussed.

Improvment of the Trapezoid Method Using Raw Landsat Image Digital Count Data for Soil Moisture Estimation in the Texas (usa) High Plains

NASA Astrophysics Data System (ADS)

Shafian, S.; Maas, S. J.

2015-12-01

Variations in soil moisture strongly affect surface energy balances, regional runoff, land erosion and vegetation productivity (i.e., potential crop yield). Hence, the estimation of soil moisture is very valuable in the social, economic, humanitarian (food security) and environmental segments of society. Extensive efforts to exploit the potential of remotely sensed observations to help quantify this complex variable are ongoing. This study aims at developing a new index, the Thermal Ground cover Moisture Index (TGMI), for estimating soil moisture content. This index is based on empirical parameterization of the relationship between raw image digital count (DC) data in the thermal infrared spectral band and ground cover (determined from raw image digital count data in the red and near-infrared spectral bands).The index uses satellite-derived information only, and the potential for its operational application is therefore great. This study was conducted in 18 commercial agricultural fields near Lubbock, TX (USA). Soil moisture was measured in these fields over two years and statistically compared to corresponding values of TGMI determined from Landsat image data. Results indicate statistically significant correlations between TGMI and field measurements of soil moisture (R2 = 0.73, RMSE = 0.05, MBE = 0.17 and AAE = 0.049), suggesting that soil moisture can be estimated using this index. It was further demonstrated that maps of TGMI developed from Landsat imagery could be constructed to show the relative spatial distribution of soil moisture across a region.

Assessment of possibilities and conditions of irrigation in Hungary by digital soil map products

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Bakacsi, Zsófia; Takács, Katalin; Szatmári, Gábor; Szabó, József; Pásztor, László

2016-04-01

Sustaining proper soil moisture is essentially important in agricultural management. However, irrigation can be really worth only, if we lay sufficient emphasis on soil conservation. Nationwide planning of irrigation can be taken place, if we have spatially exhaustive maps and recommendations for the different areas. Soil moisture in the pores originate from 'above' (precipitation), or from 'beneath' (from groundwater by capillary lift). The level of groundwater depends on topography, climatic conditions and water regime of the nearby river. The thickness of capillary zone is basicly related to the physical and water management properties of the soil. Accordingly the capillary rise of sandy soils - with very high infiltration rate and very poor water retaining capacity - are far smaller than in the case of clay soils - with very poor infiltration rate and high water retaining capacity. Applying irrigation water can be considered as a reinforcement from 'above', and it affects the salinity and sodicity as well as the soil structure, nutrient supply and soil formation. We defined the possibilities of irrigation according to the average salt content of the soil profile. The nationwide mapping of soil salinity was based on legacy soil profile data, and it was carried out by regression kriging. This method allows that environmental factors with exhaustive spatial extension, such as climatic-, vegetation-, topographic-, soil- and geologic layers can be taken into consideration to the spatial extension of the reference data. According to soil salinity content categories, the areas were delineated as 1. to be irrigated, 2. to be irrigated conditionally, 3. not to be irrigated. The conditions of irrigation was determined by the comparison of the 'actual' and the 'critical' depth of the water table. Since, if the water rises above the critical level, undesirable processes, such as salinization and alkalinization can be developed. The critical depth of the water table was calculated according to the literature, and based on average soil content of the soil profile, the water regime category of soil, salt content of the groundwater, and soil pH. The water regime category map originated from legacy polygon-based map of physical soil properties. The soil content, and the actual level of groundwater as well as the soil pH map - similarly to the soil salinity map - was compiled by regression kriging. The conditions are classified into the following three categories: 1. level of groundwater have to be sinked, 2. rising of groundwater level have to be hindered, 3. level of groundwater have to be regularly controlled. The newly compiled maps can help decision makers to improve land use management, taking soil conservation into consideration. Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167) and the Research Institute of Agricultural Economics.

Evaluating the effect of remote sensing image spatial resolution on soil exchangeable potassium prediction models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P

2017-09-15

Major end users of Digital Soil Mapping (DSM) such as policy makers and agricultural extension workers are faced with choosing the appropriate remote sensing data. The objective of this research is to analyze the spatial resolution effects of different remote sensing images on soil prediction models in two smallholder farms in Southern India called Kothapally (Telangana State), and Masuti (Karnataka State), and provide empirical guidelines to choose the appropriate remote sensing images in DSM. Bayesian kriging (BK) was utilized to characterize the spatial pattern of exchangeable potassium (K ex ) in the topsoil (0-15 cm) at different spatial resolutions by incorporating spectral indices from Landsat 8 (30 m), RapidEye (5 m), and WorldView-2/GeoEye-1/Pleiades-1A images (2 m). Some spectral indices such as band reflectances, band ratios, Crust Index and Atmospherically Resistant Vegetation Index from multiple images showed relatively strong correlations with soil K ex in two study areas. The research also suggested that fine spatial resolution WorldView-2/GeoEye-1/Pleiades-1A-based and RapidEye-based soil prediction models would not necessarily have higher prediction performance than coarse spatial resolution Landsat 8-based soil prediction models. The end users of DSM in smallholder farm settings need select the appropriate spectral indices and consider different factors such as the spatial resolution, band width, spectral resolution, temporal frequency, cost, and processing time of different remote sensing images. Overall, remote sensing-based Digital Soil Mapping has potential to be promoted to smallholder farm settings all over the world and help smallholder farmers implement sustainable and field-specific soil nutrient management scheme. Copyright © 2017 Elsevier Ltd. All rights reserved.

A soil map of a large watershed in China: applying digital soil mapping in a data sparse region

NASA Astrophysics Data System (ADS)

Barthold, F.; Blank, B.; Wiesmeier, M.; Breuer, L.; Frede, H.-G.

2009-04-01

Prediction of soil classes in data sparse regions is a major research challenge. With the advent of machine learning the possibilities to spatially predict soil classes have increased tremendously and given birth to new possibilities in soil mapping. Digital soil mapping is a research field that has been established during the last decades and has been accepted widely. We now need to develop tools to reduce the uncertainty in soil predictions. This is especially challenging in data sparse regions. One approach to do this is to implement soil taxonomic distance as a classification error criterion in classification and regression trees (CART) as suggested by Minasny et al. (Geoderma 142 (2007) 285-293). This approach assumes that the classification error should be larger between soils that are more dissimilar, i.e. differ in a larger number of soil properties, and smaller between more similar soils. Our study area is the Xilin River Basin, which is located in central Inner Mongolia in China. It is characterized by semi arid climate conditions and is representative for the natural occurring steppe ecosystem. The study area comprises 3600 km2. We applied a random, stratified sampling design after McKenzie and Ryan (Geoderma 89 (1999) 67-94) with landuse and topography as stratifying variables. We defined 10 sampling classes, from each class 14 replicates were randomly drawn and sampled. The dataset was split into 100 soil profiles for training and 40 soil profiles for validation. We then applied classification and regression trees (CART) to quantify the relationships between soil classes and environmental covariates. The classification tree explained 75.5% of the variance with land use and geology as most important predictor variables. Among the 8 soil classes that we predicted, the Kastanozems cover most of the area. They are predominantly found in steppe areas. However, even some of the soils at sand dune sites, which were thought to show only little soil formation, can be classified as Kastanozems. Besides the Kastanozems, Regosols are most common at the sand dune sites as well as at sites that are defined as bare soil which are characterized by little or no vegetation. Gleysols are mostly found at sites in the vicinity of the Xilin river, which are connected to the groundwater. They can also be found in small valleys or depressions where sub-surface waters from neighboring areas collect. The richest soils are found in mountain meadow areas. Pedogenetic conditions here are most favorable and lead to the formation of Chernozems with deep humic Ah horizons. Other soil types that occur in the study area are Arenosols, Calcisols, Cambisol and Phaeozems. In addition, soil taxonomic distance is implemented into the decision tree procedure as a measure of classification error. The results of incorporating taxonomic distance as a loss function in the decision tree will be compared with the standard application of the decision tree.

Age discrimination among eruptives of Menengai Caldera, Kenya, using vegetation parameters from satellite imagery

NASA Technical Reports Server (NTRS)

Blodget, Herbert W.; Heirtzler, James R.

1993-01-01

Results are presented of an investigation to determine the degree to which digitally processed Landsat TM imagery can be used to discriminate among vegetated lava flows of different ages in the Menengai Caldera, Kenya. A selective series of five images, consisting of a color-coded Landsat 5 classification and four color composites, are compared with geologic maps. The most recent of more than 70 postcaldera flows within the caldera are trachytes, which are variably covered by shrubs and subsidiary grasses. Soil development evolves as a function of time, and as such supports a changing plant community. Progressively older flows exhibit the increasing dominance of grasses over bushes. The Landsat images correlated well with geologic maps, but the two mapped age classes could be further subdivided on the basis of different vegetation communities. It is concluded that field maps can be modified, and in some cases corrected by use of such imagery, and that digitally enhanced Landsat imagery can be a useful aid to field mapping in similar terrains.

Remote Sensing-based Models of Soil Vulnerability to Compaction and Erosion from Off-highway Vehicles

NASA Astrophysics Data System (ADS)

Villarreal, M. L.; Webb, R. H.; Norman, L.; Psillas, J.; Rosenberg, A.; Carmichael, S.; Petrakis, R.; Sparks, P.

2014-12-01

Intensive off-road vehicle use for immigration, smuggling, and security of the United States-Mexico border has prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from vehicle disturbances, we developed a series of erosion potential models based on factors from the Revised Universal Soil Loss Equation (RUSLE), with particular focus on the management factor (P-factor) and vegetation cover (C-factor). To better express the vulnerability of soils to human disturbances, a soil compaction index (applied as the P-factor) was calculated as the difference in saturated hydrologic conductivity (Ks) between disturbed and undisturbed soils, which was then scaled up to remote sensing-based maps of vehicle tracks and digital soils maps. The C-factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover (r2 = 0.77) than data derived from regional land cover maps (r2 = 0.06). RUSLE factors were normalized to give equal weight to all contributing factors, which provided more management-specific information on vulnerable areas where vehicle compaction of sensitive soils intersects with steep slopes and low vegetation cover. Resulting spatial data on vulnerability and erosion potential provide land managers with information to identify critically disturbed areas and potential restoration sites where off-road driving should be restricted to reduce further degradation.

Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

PubMed Central

Adhikari, Kabindra; Hartemink, Alfred E.; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B.; Greve, Mogens H.

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg−1 was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg−1 at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg−1 was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha−1 and in the top 1 m there was 120 t SOC ha−1. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories. PMID:25137066

Digital mapping of soil organic carbon contents and stocks in Denmark.

PubMed

Adhikari, Kabindra; Hartemink, Alfred E; Minasny, Budiman; Bou Kheir, Rania; Greve, Mette B; Greve, Mogens H

2014-01-01

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0-5, 5-15, 15-30, 30-60 and 60-100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg(-1) was reported for 0-5 cm soil, whereas there was on average 2.2 g SOC kg(-1) at 60-100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg(-1) was found at 60-100 cm soil depth. Average SOC stock for 0-30 cm was 72 t ha(-1) and in the top 1 m there was 120 t SOC ha(-1). In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.

Digital soil mapping as a tool for quantifying state-and-transition models

USDA-ARS?s Scientific Manuscript database

Ecological sites and associated state-and-transition models (STMs) are rapidly becoming important land management tools in rangeland systems in the US and around the world. Descriptions of states and transitions are largely developed from expert knowledge and generally accepted species and community...

Soil properties, soil functions and soil security

NASA Astrophysics Data System (ADS)

Poggio, Laura; Gimona, Alessandro

2017-04-01

Soil plays a crucial role in the ecosystem functioning such as food production, capture and storage of water, carbon and nutrients and in the realisation of a number of UN Sustainable Developments Goals. In this work we present an approach to spatially and jointly assess the multiple contributions of soil to the delivery of ecosystem services within multiple land-use system. We focussed on the modelling of the impact of soil on sediment retention, carbon storage, storing and filtering of nutrients, habitat for soil organisms and water regulation, taking into account examples of land use and climate scenarios. Simplified models were used for the single components. Spatialised Bayesian Belief networks were used for the jointly assessment and mapping of soil contribution to multiple land use and ecosystem services. We integrated continuous 3D soil information derived from digital soil mapping approaches covering the whole of mainland Scotland, excluding the Northern Islands. Uncertainty was accounted for and propagated across the whole process. The Scottish test case highlights the differences in roles between mineral and organic soils and provides an example of integrated study assessing the contributions of soil. The results show the importance of the multi-functional analysis of the contribution of soils to the ecosystem service delivery and UN SDGs.

DSM for soil erosion risk in Scotland

NASA Astrophysics Data System (ADS)

Poggio, Laura; Gimona, Alessandro; McLeaod, Jim; Castellazzi, Marie; Baggio Compagnucci, Andrea; Irvine, Justin

2017-04-01

Soils play a crucial role in ecosystem functioning, and modelling its risk of degradation is fundamental, especially in the context of climate change. In this work we used continuous 3D soil information derived from digital soil mapping (DSM) approaches to map sediment erosion and deposition patterns due to rainfall. The test area covers the whole of mainland Scotland, excluding the Northern Islands. Soil profiles data were interpolated using a geo-statistical hybrid Generalised Additive Models method for a range of soil properties such as organic matter, texture, soil depth and peat presence. The same method was used to interpolate climatic data and management information. Remote sensing data were integrated in the process and land use data included. Information on grazing (sheep and deer) pressure was taken into account in the modelling. The uncertainty was accounted and propagated across the whole process. The Scottish test case highlights the differences in roles between mineral and organic soils with an assessment adapted to each of them. The results and intermediate steps were compared with available continental scale results. The results show the importance of the use of DSM approaches for modeling soils and ecosystem functions and assessing uncertainty propagation.

Groundwater sensitivity mapping in Kentucky using GIS and digitally vectorized geologic quadrangles

NASA Astrophysics Data System (ADS)

Croskrey, Andrea; Groves, Chris

2008-05-01

Groundwater sensitivity (Ray and O’dell in Environ Geol 22:345 352, 1993a) refers to the inherent ease with which groundwater can be contaminated based on hydrogeologic characteristics. We have developed digital methods for identifying areas of varying groundwater sensitivity for a ten county area of south central Kentucky at a scale of 1:100,000. The study area includes extensive limestone karst sinkhole plains, with groundwater extremely sensitive to contamination. Digitally vectorized geologic quadrangles (DVGQs) were combined with elevation data to identify both hydrogeologic groundwater sensitivity regions and zones of “high risk runoff” where contaminants could be transported in runoff from less sensitive to higher sensitivity (particularly karst) areas. While future work will fine-tune these maps with additional layers of data (soils for example) as digital data have become available, using DVGQs allows a relatively rapid assessment of groundwater sensitivity for Kentucky at a more useful scale than previously available assessment methods, such as DRASTIC and DIVERSITY.

Using historical aerial photography and softcopy photogrammetry for waste unit mapping in L Lake.

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

Christel, L.M.

1997-10-01

L Lake was developed as a cooling water reservoir for the L Reactor at the Savannah River Site. The construction of the lake, which began in the fall of 1984, altered the structure and function of Steel Creek. Completed in the fall of 1985, L Lake has a capacity of 31 million cubic meters and a normal pool of 58 meters. When L Reactor operations ceased in 1988, the water level in the lake still had to be maintained. Site managers are currently trying to determine the feasibility of draining or drawing down the lake in order to save taxmore » dollars. In order to understand the full repercussions of such an undertaking, it was necessary to compile a comprehensive inventory of what the lake bottom looked like prior to filling. Aerial photographs, acquired nine days before the filling of the lake began, were scanned and used for softcopy photogrammetry processing. A one-meter digital elevation model was generated and a digital orthophoto mosaic was created as the base map for the project. Seven categories of features, including the large waste units used to contain the contaminated soil removed from the dam site, were screen digitized and used to generate accurate maps. Other map features include vegetation waste piles, where contaminated vegetation from the flood plain was contained, and ash piles, which are sites where vegetation debris was burned and then covered with clean soil. For all seven categories, the area of disturbance totaled just over 63 hectares. When the screen digitizing was completed, the elevation at the centroid of each disturbance was determined. When the information is used in the Savannah River Site Geographical Information System, it can be used to visualize the various L Lake draw-down scenarios suggested by site managers and hopefully, to support evaluations of the cost effectiveness for each proposed activity.« less

Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

NASA Astrophysics Data System (ADS)

Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

2018-05-01

In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

Loess Thickness Variations Across the Loess Plateau of China

NASA Astrophysics Data System (ADS)

Zhu, Yuanjun; Jia, Xiaoxu; Shao, Mingan

2018-07-01

The soil thickness is very important for investigating and modeling soil-water processes, especially on the Loess Plateau of China with its deep loess deposit and limited water resources. A digital elevation map (DEM) of the Loess Plateau and neighborhood analysis in ArcGIS software were used to generate a map of loess thickness, which was then validated by 162 observations across the plateau. The generated loess thickness map has a high resolution of 100 m × 100 m. The map indicates that loess is thick in the central part of the plateau and becomes gradually shallower in the southeast and northwest directions. The areas near mountains and river basins have the shallowest loess deposit. The mean loess thickness is the deepest in the zones with 400-600-mm precipitation and decreases gradually as precipitation varies beyond this range. Our validation indicates that the map just slightly overestimates loess thickness and is reliable. The loess thickness is mostly between 0 and 350 m in the Loess Plateau region. The calculated mean loess thickness is 105.7 m, with the calibrated value being 92.2 m over the plateau exclusive of the mountain areas. Our findings provide very basic data of loess thickness and demonstrate great progress in mapping the loess thickness distribution for the plateau, which are valuable for a better study of soil-water processes and for more accurate estimations of soil water, carbon, and solute reservoirs in the Loess Plateau of China.

Loess Thickness Variations Across the Loess Plateau of China

NASA Astrophysics Data System (ADS)

Zhu, Yuanjun; Jia, Xiaoxu; Shao, Mingan

2018-01-01

The soil thickness is very important for investigating and modeling soil-water processes, especially on the Loess Plateau of China with its deep loess deposit and limited water resources. A digital elevation map (DEM) of the Loess Plateau and neighborhood analysis in ArcGIS software were used to generate a map of loess thickness, which was then validated by 162 observations across the plateau. The generated loess thickness map has a high resolution of 100 m × 100 m. The map indicates that loess is thick in the central part of the plateau and becomes gradually shallower in the southeast and northwest directions. The areas near mountains and river basins have the shallowest loess deposit. The mean loess thickness is the deepest in the zones with 400-600-mm precipitation and decreases gradually as precipitation varies beyond this range. Our validation indicates that the map just slightly overestimates loess thickness and is reliable. The loess thickness is mostly between 0 and 350 m in the Loess Plateau region. The calculated mean loess thickness is 105.7 m, with the calibrated value being 92.2 m over the plateau exclusive of the mountain areas. Our findings provide very basic data of loess thickness and demonstrate great progress in mapping the loess thickness distribution for the plateau, which are valuable for a better study of soil-water processes and for more accurate estimations of soil water, carbon, and solute reservoirs in the Loess Plateau of China.

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average OC content predictions for each land cover class compared well between models, with our model always showing smaller standard deviations. We concluded that the chosen model and covariates are appropriate for the prediction of OC content in European mineral soils. We presented in this work the first map of topsoil OC content at European scale based on a harmonised soil dataset. The associated uncertainty map shall support the end-users in a careful use of the predictions.

Thematic mapping, land use, geological structure and water resources in central Spain

NASA Technical Reports Server (NTRS)

Delascuevas, N. (Principal Investigator)

1976-01-01

The author has identified the following significant results. The images can be positioned in an absolute reference system (geographical coordinates or polar stereographic coordinates) by means of their marginal indicators. By digital analysis of LANDSAT data and geometric positioning of pixels in UTM projection, accuracy was achieved for corrected MSS information which could be used for updating maps at scale 1:200,000 or smaller. Results show that adjustment of the UTM grid was better obtained by a first order, or even second order, algorithm of geometric correction. Digital analysis of LANDSAT data from the Madrid area showed that this line of study was promising for automatic classification of data applied to thematic cartography and soils identification.

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

PubMed Central

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

PubMed

Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

2016-01-01

Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

Classifying and mapping wetlands and peat resources using digital cartography

USGS Publications Warehouse

Cameron, Cornelia C.; Emery, David A.

1992-01-01

Digital cartography allows the portrayal of spatial associations among diverse data types and is ideally suited for land use and resource analysis. We have developed methodology that uses digital cartography for the classification of wetlands and their associated peat resources and applied it to a 1:24 000 scale map area in New Hampshire. Classifying and mapping wetlands involves integrating the spatial distribution of wetlands types with depth variations in associated peat quality and character. A hierarchically structured classification that integrates the spatial distribution of variations in (1) vegetation, (2) soil type, (3) hydrology, (4) geologic aspects, and (5) peat characteristics has been developed and can be used to build digital cartographic files for resource and land use analysis. The first three parameters are the bases used by the National Wetlands Inventory to classify wetlands and deepwater habitats of the United States. The fourth parameter, geological aspects, includes slope, relief, depth of wetland (from surface to underlying rock or substrate), wetland stratigraphy, and the type and structure of solid and unconsolidated rock surrounding and underlying the wetland. The fifth parameter, peat characteristics, includes the subsurface variation in ash, acidity, moisture, heating value (Btu), sulfur content, and other chemical properties as shown in specimens obtained from core holes. These parameters can be shown as a series of map data overlays with tables that can be integrated for resource or land use analysis.

High-resolution mapping and spatial variability of soil organic carbon storage of permafrost-affected soils

NASA Astrophysics Data System (ADS)

Siewert, Matthias; Hugelius, Gustaf

2017-04-01

Permafrost-affected soils store large amounts of soil organic carbon (SOC). Mapping of this SOC provides a first order spatial input variable for research that relates carbon stored in permafrost regions to carbon cycle dynamics. High-resolution satellite imagery is becoming increasingly available even in circum-polar regions. The presented research highlights findings of high-resolution mapping efforts of SOC from five study areas in the northern circum-polar permafrost region. These study areas are located in Siberia (Kytalyk, Spasskaya Pad /Neleger, Lena delta), Northern Sweden (Abisko) and Northwestern Canada (Herschel Island). Our high spatial resolution analyses show how geomorphology has a strong influence on the distribution of SOC. This is organized at different spatial scales. Periglacial landforms and processes dictate local scale SOC distribution due to patterned ground. Such landforms are non-sorted circles and ice-wedge polygons of different age and scale. Palsas and peat plateaus are formed and can cover larger areas in Sub-Arctic environments. Study areas that have not been affected by Pleistocene glaciation feature ice-rich Yedoma sediments that dominate the local relief through thermokarst formation and create landscape scale macro environments that dictate the distribution of SOC. A general trend indicates higher SOC storage in Arctic tundra soils compared to forested Boreal or Sub-Arctic taiga soils. Yet, due to the shallower active layer depth in the Arctic, much of the SOC may be permanently frozen and thus not be available to ecosystem processes. Significantly more SOC is stored in soils compared to vegetation, indicating that vegetation growth and incorporation of the carbon into the plant phytomass alone will not be able to offset SOC released from permafrost. This contribution also addresses advances in thematic mapping methods and digital soil mapping of SOC in permafrost terrain. In particular machine-learning methods, such as support vector machines, artificial neural networks and random forests show promising results as a toolbox for mapping permafrost-affected soils. Yet, these new methods do not decrease our dependency from soil pedon data from the field. In contrary, soil pedon data represents an urgent research priority. Statistical analyses are provided as an indication for best practice of soil pedon sampling for the quantification and the model representation of SOC stored in permafrost-affected soils.

The illuminating role of laser scanning digital elevation models in precision agriculture experimental designs - an agro-ecology perspective

USDA-ARS?s Scientific Manuscript database

Laser scanning data streams, when linked with multi-spectral, hyperspectral, apparent soil electro-conductivity (ECa), or other kinds of geo-referenced data streams, aid in the creation of maps that allow useful applications in agricultural systems. These combinations of georeferenced information p...

Geologic Map of the Carlton Quadrangle, Yamhill County, Oregon

USGS Publications Warehouse

Wheeler, Karen L.; Wells, Ray E.; Minervini, Joseph M.; Block, Jessica L.

2009-01-01

The Carlton, Oregon, 7.5-minute quadrangle is located in northwestern Oregon, about 35 miles (57 km) southwest of Portland. It encompasses the towns of Yamhill and Carlton in the northwestern Willamette Valley and extends into the eastern flank of the Oregon Coast Range. The Carlton quadrangle is one of several dozen quadrangles being mapped by the U.S. Geological Survey (USGS) and the Oregon Department of Geology and Mineral Industries (DOGAMI) to provide a framework for earthquake- hazard assessments in the greater Portland, Oregon, metropolitan area. The focus of USGS mapping is on the structural setting of the northern Willamette Valley and its relation to the Coast Range uplift. Mapping was done in collaboration with soil scientists from the National Resource Conservation Service, and the distribution of geologic units is refined over earlier regional mapping (Schlicker and Deacon, 1967). Geologic mapping was done on 7.5-minute topographic base maps and digitized in ArcGIS to produce ArcGIS geodatabases and PDFs of the map and text. The geologic contacts are based on numerous observations and samples collected in 2002 and 2003, National Resource Conservation Service soils maps, and interpretations of 7.5-minute topography. The map was completed before new, high-resolution laser terrain mapping was flown for parts of the northern Willamette Valley in 2008.

Exploring the spatial variability of soil properties in an Alfisol Catena

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

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

A data base approach for prediction of deforestation-induced mass wasting events

NASA Technical Reports Server (NTRS)

Logan, T. L.

1981-01-01

A major topic of concern in timber management is determining the impact of clear-cutting on slope stability. Deforestation treatments on steep mountain slopes have often resulted in a high frequency of major mass wasting events. The Geographic Information System (GIS) is a potentially useful tool for predicting the location of mass wasting sites. With a raster-based GIS, digitally encoded maps of slide hazard parameters can be overlayed and modeled to produce new maps depicting high probability slide areas. The present investigation has the objective to examine the raster-based information system as a tool for predicting the location of the clear-cut mountain slopes which are most likely to experience shallow soil debris avalanches. A literature overview is conducted, taking into account vegetation, roads, precipitation, soil type, slope-angle and aspect, and models predicting mass soil movements. Attention is given to a data base approach and aspects of slide prediction.

Reflectance measurements for the detection and mapping of soil limitations

NASA Technical Reports Server (NTRS)

Benson, L. A.; Frazee, C. J.

1973-01-01

During 1971 and 1972 research was conducted on two fallow fields in the proposed Oahe Irrigation Project to investigate the relationship between the tonal variations observed on aerial photographs and the principal soil limitations of the area. A grid sampling procedure was used to collected detailed field data during the 1972 growing season. The field data was compared to imagery collected on May 14, 1971 at 3050 meters altitude. The imagery and field data were initially evaluated by a visual analysis. Correlation and regression analysis revealed a highly significant correlation and regression analysis revealed a highly significant correlation between the digitized color infrared film data and soil properties such as organic matter content, color, depth to carbonates, bulk density and reflectivity. Computer classification of the multiemulsion film data resulted in maps delineating the areas containing claypan and erosion limitations. Reflectance data from the red spectral band provided the best results.

Predicting risk of rill initiation in a sub-catchment of Lake Balaton, Hungary

NASA Astrophysics Data System (ADS)

Hausner, C.; Sisák, I.

2009-04-01

Rill erosion is an accelerated form of soil degradation. It removes much more soil and nutrients from the agricultural land than sheet erosion. Soils in the southern sub-watershed of Lake Balaton are especially prone to rill erosion and they contribute to siltation of ditches, to muddy floods and to eutrofication of the lake. The parent material in this region is mainly (sandy) loess and the soils are already moderately or strongly eroded thus, the low tolerance of loess against erosion determines erodibility. Identification of soils with high risk of rill erosion is crucial to plan mitigation measures. Soil erodibility has been investigated in this study in the catchment of Tetves stream. The USLE soil erodibility factor and soil slaking are widely accepted indicators for soil erosion. Both of them are published for all soil texture classes in handbooks of soil mapping. We have found that erodibility derived from our physical model has a close linear correlation with the product of the USLE soil erodibility factor and soil slaking grade thus, USLE could be directly used to assess parameters for physical based models. Rill erosion is highly probable if the product of KUSLE X slaking grade is above 2. Digital maps were produced to delineate soils with high potential for rill erosion. The basic data for the soil properties were drawn from the 1:10,000 soil map. Soil texture classes were used to assign KUSLE and slaking grade to the soil units. Beyond soil properties, other factors also influence rill formation: slope, surface cover, rainfall intensity. However, identifying soil properties, which make soils prone to rill erosion, is an important initial step for the reduction of diffuse agricultural loads to Lake Balaton. It might be the objective of River Basin Management Plans in the Water Framework Directive to prevent rill erosion and our study provides scientific evidence for targeting this policy.

Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

PubMed Central

Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

2016-01-01

The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

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 a surrogate for the susceptibility of the overlying surficial materials. The maps of susceptibility were created from those physical attributes learned to be important from the inventories. The multiple inventories allow a model to be created from one set of inventory data and evaluated with others. The resultant maps of relative susceptibility represent the best estimate generated from available inventory and DEM data. Slope and aspect values used in the susceptibility analysis were 10-meter DEM cells at a scale of 1:24,000. For most of the area 10-meter DEMs were available; for those quadrangles that have only 30-meter DEMs, the 30-meter DEMS were resampled to 10-meters to maintain resolution of 10-meter cells. Geologic unit values used in the susceptibility analysis were five-meter cells. For convenience, the soil slip susceptibility values are assembled on 1:100,000-scale bases. Any area of the 1:100,000-scale maps can be transferred to 1:24,000-scale base without any loss of accuracy. Figure 32 is an example of part of a 1:100,000-scale susceptibility map transferred back to a 1:24,000-scale quadrangle.

Soil Security Assessment of Tasmania

NASA Astrophysics Data System (ADS)

Field, Damien; Kidd, Darren; McBratney, Alex

2017-04-01

The concept of soil security aligns well with the aspirational and marketing policies of the Tasmanian Government, where increased agricultural expansion through new irrigation schemes and multiple-use State managed production forests co-exists beside pristine World Heritage conservation land, a major drawcard of the economically important tourism industry . Regarding the Sustainable Development Gaols (SDG's) this could be seen as a exemplar of the emerging tool for quantification of spatial soil security to effectively protect our soil resource in terms of food (SDG 2.4, 3.9) and water security (SDG 6.4, 6.6), biodiversity maintenance and safeguarding fragile ecosystems (SDG 15.3, 15.9). The recent development and application of Digital Soil Mapping and Assessment capacities in Tasmania to stimulate agricultural production and better target appropriate soil resources has formed the foundational systems that can enable the first efforts in quantifying and mapping Tasmanian Soil Security, in particular the five Soil Security dimensions (Capability, Condition, Capital, Codification and Connectivity). However, to provide a measure of overall soil security, it was necessary to separately assess the State's three major soil uses; Agriculture, Conservation and Forestry. These products will provide an indication of where different activities are sustainable or at risk, where more soil data is needed, and provide a tool to better plan for a State requiring optimal food and fibre production, without depleting its natural soil resources and impacting on the fragile ecosystems supporting environmental benefits and the tourism industry.

Mapping elemental contamination on Palmyra Atoll National Wildlife Refuge.

PubMed

Struckhoff, Matthew A; Orazio, Carl E; Tillitt, Donald E; Shaver, David K; Papoulias, Diana M

2018-03-01

Palmyra Atoll, once a WWII U.S. Navy air station, is now a U.S. National Wildlife Refuge with nearly 50km 2 of coral reef and 275ha of emergent lands with forests of Pisonia grandis trees and colonies of several bird species. Due to the known elemental and organic contamination from chemicals associated with aviation, power generation and transmission, waste management, and other air station activities, a screening survey to map elemental concentrations was conducted. A map of 1944 Navy facilities was georeferenced and identifiable features were digitized. These data informed a targeted survey of 25 elements in soils and sediment at locations known or suspected to be contaminated, using a hand-held X-ray fluorescence spectrometer. At dozens of locations, concentrations of elements exceeded established soil and marine sediment thresholds for adverse ecological effects. Results were compiled into a publically available geospatial dataset to inform potential remediation and habitat restoration activities. Published by Elsevier Ltd.

Evaluation of HCMM satellite data for estuarine tidal circulation patterns and thermal inertia soil moisture measurements. [Delaware Bay, Cooper River, and the Potomac River estuaries; Luverne, Minnesota, soil moisture, and water temperature of Lake Anna, Virginia

NASA Technical Reports Server (NTRS)

Wiesnet, D. R.; Mcginnis, D. F., Jr. (Principal Investigator); Matson, M.; Pritchard, J. A.

1981-01-01

Digital thermal maps of the Cooper River (SC) and the Potomac River estuaries were prepared from heat capacity mapping radiometer (HCMR) tapes. Tidal phases were correctly interpreted and verified. Synoptic surface circulation patterns were charted by location thermal fronts and water mass boundaries within the estuaries. Thermal anomalies were detected adjacent of a conventional power plant on the Potomac. Under optimum conditions, estuaries as small as the Cooper River can be monitored for generalized thermal/tidal circulation patterns by the HCMM-type IR sensors. The HCMM thermal inertia approach to estimating soil moisture at the Luverne (MN) test site was found to be unsatisfactory as a NESS operational satellite technique because of cloud cover interference. Thermal-IR data show similar structure of the Baltimore and Washington heat islands when compared to NOAA AVHRR thermal-IR data. Thermal anomalies from the warm water discharge water of a nuclear power plant were mapped in Lake Anna, Virginia.

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

Mapping Vegetation Community Types in a Highly-Disturbed Landscape: Integrating Hiearchical Object-Based Image Analysis with Digital Surface Models

NASA Astrophysics Data System (ADS)

Snavely, Rachel A.

Focusing on the semi-arid and highly disturbed landscape of San Clemente Island, California, this research tests the effectiveness of incorporating a hierarchal object-based image analysis (OBIA) approach with high-spatial resolution imagery and light detection and range (LiDAR) derived canopy height surfaces for mapping vegetation communities. The study is part of a large-scale research effort conducted by researchers at San Diego State University's (SDSU) Center for Earth Systems Analysis Research (CESAR) and Soil Ecology and Restoration Group (SERG), to develop an updated vegetation community map which will support both conservation and management decisions on Naval Auxiliary Landing Field (NALF) San Clemente Island. Trimble's eCognition Developer software was used to develop and generate vegetation community maps for two study sites, with and without vegetation height data as input. Overall and class-specific accuracies were calculated and compared across the two classifications. The highest overall accuracy (approximately 80%) was observed with the classification integrating airborne visible and near infrared imagery having very high spatial resolution with a LiDAR derived canopy height model. Accuracies for individual vegetation classes differed between both classification methods, but were highest when incorporating the LiDAR digital surface data. The addition of a canopy height model, however, yielded little difference in classification accuracies for areas of very dense shrub cover. Overall, the results show the utility of the OBIA approach for mapping vegetation with high spatial resolution imagery, and emphasizes the advantage of both multi-scale analysis and digital surface data for accuracy characterizing highly disturbed landscapes. The integrated imagery and digital canopy height model approach presented both advantages and limitations, which have to be considered prior to its operational use in mapping vegetation communities.

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.

An evaluation of the utility of ERTS-1 data for mapping and developing natural resources of Iran

NASA Technical Reports Server (NTRS)

Ebtehadj, K. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Results are reported in structural mapping leading to tectonic interpretation; in surficial deposits mapping; in analysis of salt diapirism in southwest Iran; in updating and correcting existing hydrological maps; in monitoring fluctuations of water in some intermittent lakes; in the delineation of wetland areas and the study of fluvial suspended load of the head of the Persian Gulf in relation to the fishing industry; in exercises in soil mapping; in range and agricultural surveys and inventory using multistage sampling methods, and in the computer analysis of ERTS-1 digital tapes for urban land use. The completion of a 1:1,000,000 false color photomosaic of Iran is also discussed.

Case studies: Soil mapping using multiple methods

NASA Astrophysics Data System (ADS)

Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald

2010-05-01

Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful application of geophysical methods, e.g. GPR on wet loessy soils will result in a high attenuation of signals. Furthermore, with this knowledge we support the development of geophysical pedo-transfer-functions, i.e. the link between geophysical to soil parameters, which is active researched in another work package of the iSOIL project. Acknowledgement: iSOIL-Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment.

Site Suitability Analysis for Dissemination of Salt-tolerant Rice Varieties in Southern Bangladesh

NASA Astrophysics Data System (ADS)

Sinha, D. D.; Singh, A. N.; Singh, U. S.

2014-11-01

Bangladesh is a country of 14.4 million ha geographical area and has a population density of more than 1100 persons per sq. km. Rice is the staple food crop, growing on about 72 % of the total cultivated land and continues to be the most important crop for food security of the country. A project "Sustainable Rice Seed Production and Delivery Systems for Southern Bangladesh" has been executed by the International Rice Research Institute (IRRI) in twenty southern districts of Bangladesh. These districts grow rice in about 2.9 million ha out of the country's total rice area of 11.3 million ha. The project aims at contributing to the Government of Bangladesh's efforts in improving national and household food security through enhanced and sustained productivity by using salinity-, submergence- and drought- tolerant and high yielding rice varieties. Out of the 20 project districts, 12 coastal districts are affected by the problem of soil salinity. The salt-affected area in Bangladesh has increased from about 0.83 million ha in 1973 to 1.02 million ha in 2000, and 1.05 million ha in 2009 due to the influence of cyclonic storms like "Sidr", "Laila" and others, leading to salt water intrusion in croplands. Three salinity-tolerant rice varieties have recently been bred by IRRI and field tested and released by the Bangladesh Rice Research Institute (BRRI) and Bangladesh Institute of Nuclear Agriculture (BINA). These varieties are BRRI dhan- 47 and Bina dhan-8 and - 10. However, they can tolerate soil salinity level up to EC 8-10 dSm-1, whereas the EC of soils in several areas are much higher. Therefore, a large scale dissemination of these varieties can be done only when a site suitability analysis of the area is carried out. The present study was taken up with the objective of preparing the site suitability of the salt-tolerant varieties for the salinity-affected districts of southern Bangladesh. Soil salinity map prepared by Soil Resources Development Institute of Bangladesh shows five classes of salinity. viz., non-saline with some very slight saline soil, very slightly saline with some slight saline soil, slightly saline with some moderately saline soil, strongly saline with some moderately saline soil, and very strongly saline with some strongly saline soil. The soil EC level of different classes range from 2 dSm-1 to >16 dSm-1. The soil map was geo-referenced and digitized using Arc GIS. Salinity tolerance characteristics of the rice varieties were matched with the soil characteristics shown on the map. Three suitability classes were made; soils suitable for salt-tolerant varieties, not suitable for salt-tolerant varieties due to high soil salinity, and suitable for other high yielding varieties due to slight salinity. The mauza (smallest revenue unit) boundary provided by the Bangladesh Agriculture Research Council was also geo-referenced and digitized in the same projection. Overlaying and intersecting the mauza boundary on the soil suitability map provided the suitable and not suitable mauza. A total of 4070 mauzas in the 12 salinity-affected districts were listed and maps showing suitability of mauza prepared. About 0.6 million ha out of total 0.87 million ha salinity affected area were found suitable for growing the salinity-tolerant BRRI dhan-47, Bina dhan-8 and -10 in these districts. The maps and other generated information have helped the Dept. of Agriculture Extension (DAE) of Bangladesh in large scale dissemination of seeds of the salinity-tolerant rice varieties in different districts during the past two years.

Modelling and mapping the topsoil organic carbon content for Tanzania

NASA Astrophysics Data System (ADS)

Kempen, Bas; Kaaya, Abel; Ngonyani Mhaiki, Consolatha; Kiluvia, Shani; Ruiperez-Gonzalez, Maria; Batjes, Niels; Dalsgaard, Soren

2014-05-01

Soil organic carbon (SOC), held in soil organic matter, is a key indicator of soil health and plays an important role in the global carbon cycle. The soil can act as a net source or sink of carbon depending on land use and management. Deforestation and forest degradation lead to the release of vast amounts of carbon from the soil in the form of greenhouse gasses, especially in tropical countries. Tanzania has a high deforestation rate: it is estimated that the country loses 1.1% of its total forested area annually. During 2010-2013 Tanzania has been a pilot country under the UN-REDD programme. This programme has supported Tanzania in its initial efforts towards reducing greenhouse gas emission from forest degradation and deforestation and towards preserving soil carbon stocks. Formulation and implementation of the national REDD strategy requires detailed information on the five carbon pools among these the SOC pool. The spatial distribution of SOC contents and stocks was not available for Tanzania. The initial aim of this research, was therefore to develop high-resolution maps of the SOC content for the country. The mapping exercise was carried out in a collaborative effort with four Tanzanian institutes and data from the Africa Soil Information Service initiative (AfSIS). The mapping exercise was provided with over 3200 field observations on SOC from four sources; this is the most comprehensive soil dataset collected in Tanzania so far. The main source of soil samples was the National Forest Monitoring and Assessment (NAFORMA). The carbon maps were generated by means of digital soil mapping using regression-kriging. Maps at 250 m spatial resolution were developed for four depth layers: 0-10 cm, 10-20 cm, 20-30 cm, and 0-30 cm. A total of 37 environmental GIS data layers were prepared for use as covariates in the regression model. These included vegetation indices, terrain parameters, surface temperature, spectral reflectances, a land cover map and a small-scale Soil and Terrain (SOTER) map. Prediction uncertainty was quantified by the 90% prediction interval and the predictions were validated by cross-validation. The SOTER map proved to be the best predictor of SOC content, followed by the terrain parameters, mid-infrared reflectance, surface temperature, several vegetation indices, and the land cover map. The maps show that the SOC content decreases with depth, which is typically observed in soils. For the 0-10 cm layer the average predicted SOC content is 1.31%, for the 10-20 cm layer this is 0.93%, for the 20-30cm layer 0.72%, and for the 0-30cm layer 1.00%. The mean absolute error of the 0-10cm layer was 0.54%, that of the 10-20cm layer 0.38%, that of the 20-30cm layer 0.31%, and that of the 0-30cm layer 0.34%. The R2-value of the 0-10 cm layer was 0.47, that of the 10-20cm layer 0.49, that of the 20-30cm layer 0.44, and that of the 0-30cm layer 0.59. The next step will be the development of maps of SOC stock and key properties that are of interest for soil fertility management such as pH and the textural fractions.

3D imaging of soil apparent electrical conductivity from VERIS data using a 1D spatially constrained inversion algorithm

NASA Astrophysics Data System (ADS)

Jesús Moral García, Francisco; Rebollo Castillo, Francisco Javier; Monteiro Santos, Fernando

2016-04-01

Maps of apparent electrical conductivity of the soil are commonly used in precision agriculture to indirectly characterize some important properties like salinity, water, and clay content. Traditionally, these studies are made through an empirical relationship between apparent electrical conductivity and properties measured in soil samples collected at a few locations in the experimental area and at a few selected depths. Recently, some authors have used not the apparent conductivity values but the soil bulk conductivity (in 2D or 3D) calculated from measured apparent electrical conductivity through the application of an inversion method. All the published works used data collected with electromagnetic (EM) instruments. We present a new software to invert the apparent electrical conductivity data collected with VERIS 3100 and 3150 (or the more recent version with three pairs of electrodes) using the 1D spatially constrained inversion method (1D SCI). The software allows the calculation of the distribution of the bulk electrical conductivity in the survey area till a depth of 1 m. The algorithm is applied to experimental data and correlations with clay and water content have been established using soil samples collected at some boreholes. Keywords: Digital soil mapping; inversion modelling; VERIS; soil apparent electrical conductivity.

3D Visualization Tools to Support Soil Management In Relation to Sustainable Agriculture and Ecosystem Services

NASA Astrophysics Data System (ADS)

Wang, Chen

2017-04-01

Visualization tools [1][2][6] have been used increasingly as part of information, consultation, and collaboration in relation to issues of global significance. Visualization techniques can be used in a variety of different settings, depending on their association with specific types of decision. Initially, they can be used to improve awareness of the local community and landscape, either individually or in groups [5]. They can also be used to communicate different aspects of change, such as digital soil mapping, ecosystem services and climate change [7][8]. A prototype 3D model was developed to present Tarland Catchment on the North East Scotland which includes 1:25000 soil map data and 1:50000 land capability for agriculture (LCA) data [4]. The model was used to identify issues arising between the growing interest soil monitoring and management, and the potential effects on existing soil characteristics. The online model was also created which can capture user/stakeholder comments they associate with soil features. In addition, people are located physically within the real-world bounds of the current soil management scenario, they can use Augmented Reality to see the scenario overlaid on their immediate surroundings. Models representing alternative soil use and management were used in the virtual landscape theatre (VLT) [3]with electronic voting designed to elicit public aspirations and concerns regarding future soil uses, and to develop scenarios driven by local input. Preliminary findings suggest positive audience responses to the relevance of the inclusion of soil data within a scene when considering questions regarding the impact of land-use change, such as woodland, agricultural land and open spaces. A future development is the use of the prototype virtual environment in a preference survey of scenarios of changes in land use, and in stakeholder consultations on such changes.END Rua, H. and Alvito, P. (2011) Living the past: 3D models, virtual reality and game engines as tools for supporting archaeology and the reconstruction of cultural heritage - the case-study of the Roman villa of Casal de Freiria, Journal of Archaeological Science, 38(12): 3296-3308. Wang, C., Miller, D.R., Brown I., Jiang Y., Castellazzi M, "Visualisation Techniques to Support Public Interpretation of Future Climate Change and Land Use Choices: A Case Study from N-E Scotland", International Journal of Digital Earth, Volume 9, Issue 6, pp.586-605, 2016. VLT, http://www.hutton.ac.uk/learning/exhibits/vlt Scotland's soil, http://www.soils-scotland.gov.uk/ Wang, C., Miller, D.R., Jiang Y., Donaldson-Selby, "Use of 3D Visualisation Tools for Representing Urban Greenspace Spatial Planning", 2015 IEEE International Conference on Information Science and Control Engineering Shanghai, China, April 24-26, 2015. Tobias, S., Buser, T., Buchecker, M. (2016) Does real-time visualization support local stakeholders in developing landscape visions? Environment and Planning B:Planning and Design, 43: 84¨ C197. Li.Y, Zhu. A-Xing, Shi. Z, Liu. J and Du. F, "Supplemental sampling for digital soil mapping based on prediction uncertainty from both the feature domain and the spatial domain", The Global Journal of Soil Science, Volume 284, pp 73-84, 2016. Warren-Kretzschmar. B and Haaren, C, "Communicating spatial planning decisions at the landscape and farm level with landscape visualization", Journal of Biogeosciences and Forestry, volume 7, pp 434-442, 2014.

3D-Digital soil property mapping by geoadditive models

NASA Astrophysics Data System (ADS)

Papritz, Andreas

2016-04-01

In many digital soil mapping (DSM) applications, soil properties must be predicted not only for a single but for multiple soil depth intervals. In the GlobalSoilMap project, as an example, predictions are computed for the 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, 100-200 cm depth intervals (Arrouays et al., 2014). Legacy soil data are often used for DSM. It is common for such datasets that soil properties were measured for soil horizons or for layers at varying soil depth and with non-constant thickness (support). This poses problems for DSM: One strategy is to harmonize the soil data to common depth prior to the analyses (e.g. Bishop et al., 1999) and conduct the statistical analyses for each depth interval independently. The disadvantage of this approach is that the predictions for different depths are computed independently from each other so that the predicted depth profiles may be unrealistic. Furthermore, the error induced by the harmonization to common depth is ignored in this approach (Orton et al. 2016). A better strategy is therefore to process all soil data jointly without prior harmonization by a 3D-analysis that takes soil depth and geographical position explicitly into account. Usually, the non-constant support of the data is then ignored, but Orton et al. (2016) presented recently a geostatistical approach that accounts for non-constant support of soil data and relies on restricted maximum likelihood estimation (REML) of a linear geostatistical model with a separable, heteroscedastic, zonal anisotropic auto-covariance function and area-to-point kriging (Kyriakidis, 2004.) Although this model is theoretically coherent and elegant, estimating its many parameters by REML and selecting covariates for the spatial mean function is a formidable task. A simpler approach might be to use geoadditive models (Kammann and Wand, 2003; Wand, 2003) for 3D-analyses of soil data. geoAM extend the scope of the linear model with spatially correlated errors to account for nonlinear effects of covariates by fitting componentwise smooth, nonlinear functions to the covariates (additive terms). REML estimation of model parameters and computing best linear unbiased predictions (BLUP) builds in the geoAM framework on the fact that both geostatistical and additive models can be parametrized as linear mixed models Wand, 2003. For 3D-DSM analysis of soil data, it is natural to model depth profiles of soil properties by additive terms of soil depth. Including interactions between these additive terms and covariates of the spatial mean function allows to model spatially varying depth profiles. Furthermore, with suitable choice of the basis functions of the additive term (e.g. polynomial regression splines), non-constant support of the soil data can be taken into account. Finally, boosting (Bühlmann and Hothorn, 2007) can be used for selecting covariates for the spatial mean function. The presentation will detail the geoAM approach and present an example of geoAM for 3D-analysis of legacy soil data. Arrouays, D., McBratney, A. B., Minasny, B., Hempel, J. W., Heuvelink, G. B. M., MacMillan, R. A., Hartemink, A. E., Lagacherie, P., and McKenzie, N. J. (2014). The GlobalSoilMap project specifications. In GlobalSoilMap Basis of the global spatial soil information system, pages 9-12. CRC Press. Bishop, T., McBratney, A., and Laslett, G. (1999). Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma, 91(1-2), 27-45. Bühlmann, P. and Hothorn, T. (2007). Boosting algorithms: Regularization, prediction and model fitting. Statistical Science, 22(4), 477-505. Kammann, E. E. and Wand, M. P. (2003). Geoadditive models. Journal of the Royal Statistical Society. Series C: Applied Statistics, 52(1), 1-18. Kyriakidis, P. (2004). A geostatistical framework for area-to-point spatial interpolation. Geographical Analysis, 36(3), 259-289. Orton, T., Pringle, M., and Bishop, T. (2016). A one-step approach for modelling and mapping soil properties based on profile data sampled over varying depth intervals. Geoderma, 262, 174-186. Wand, M. P. (2003). Smoothing and mixed models. Computational Statistics, 18(2), 223-249.

Simulating climate change impact on soil erosion using RUSLE model - A case study in a watershed of mid-Himalayan landscape

NASA Astrophysics Data System (ADS)

Gupta, Surya; Kumar, Suresh

2017-06-01

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011-2040, 2041-2070, and 2071-2099, at large scale. Rainfall erosivity ( R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data - IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility ( K) factor map of the watershed. Topographic factors, slope length ( L) and steepness ( S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985-2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.

The natural resources inventory system ASVT project

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1979-01-01

The hardware/software and the associated procedures for a natural resource inventory and information system based on the use of LANDSAT-acquired multispectral scanner digital data is described. The system is designed to derive land cover/vegetation information from LANDSAT data and geographically reference this information for the production of various types of maps and for the compilation of acreage by land cover/vegetation category. The system also provides for data base building so that the LANDSAT-derived information can be related to information digitized from other sources (e.g., soils maps) in a geographic context in order to address specific applications. These applications include agricultural crop production estimation, erosion hazard-reforestation need assessment, whitetail deer habitat assessment, and site selection. The system is tested in demonstration areas located in the state of Mississippi, and the results of these application demonstrations are presented. A cost-efficiency comparison of producing land cover/vegetation maps and statistics with this system versus the use of small-scale aerial photography is made.

Mapping contact metamorphic aureoles in Extremadura, Spain, using Landsat thematic mapper images

USGS Publications Warehouse

Rowan, L.C.; Anton-Pacheco, C.; Brickey, D.W.; Kingston, M.J.; Payas, A.

1987-01-01

In the Extremadura region of western Spain, Ag, Pb, Zn, and Sn deposits occur in the pieces of late Hercynian granitic plutons and near the pluton contacts in late Proterozoic slate and metagraywacke that have been regionally metamorphosed to the green schist facies. The plutons generally are well exposed and have distinctive geomorphological expression and vegetation; poor exposures of the metasedimentary host rocks and extensive cultivation, however, make delineation of the contact aureoles difficult. Landsat Thematic Mapper (TM) images have been used to distinguish soil developed on the contact metamorphic rocks from soil formed on the stratigraphically equivalent slate-metagraywacke sequence. The mineral constituents of these soils are similar, except that muscovite is more common in the contact metamorphic soil; carbonaceous material is common in both soils. Contact metamorphic soil have lower reflectance, especially in the 1.6-micrometers wavelength region (TM 5), and weaker Al-OH, Mg-OH, and Fe3+ absorption features than do spectra of the slate-metagraywacke soil. The low-reflectance and subdued absorption features exhibited by the contact metamorphic soil spectra are attributed to the high absorption coefficient f the carbonaceous material caused by heating during emplacement of the granitic plutons. These spectral differences are evident in a TM 4/3, 4/5, 3/1 color-composite image. Initially, this image was used to outline the contact aureoles, but digital classification of the TM data was necessary for generating internally consistent maps of the distribution of the exposed contact metamorphic soil. In an August 1984, TM scene of the Caceras area, the plowed, vegetation-free fields were identified by their low TM 4/3 values. Then, ranges of TM 4/5 and 3/1 values were determine for selected plower fields within and outside the contact aureoles; TM 5 produced results similar to TM 4/5. Field evaluation, supported by X-ray diffraction and petrographic studies, confirmed the presence of more extensive aureoles than shown in published geologic maps; few misclassified areas were noted. Additional plowed fields consisting of exposed contact metamorphic soil were mapped digitally in an August 1985 TM scene. Subsequently, this approach was used to map two 1-km-wide linear zones of contact metamorphosed rock and oil in the San Nicolas-Sn-W Mine area, which is located approximated 125 km southeast of the Caceras study area. Exposures of granite in the San Nicolas area are limited to a few unaltered granitic dikes in the mine and a small exposure of unaltered pegmatite-bearing granite in a quarry about 1.5 km west of the mine. The present of coarsely crystalline biotite and beryl in the granite in the quarry and of contact metamorphosed slate up to 2.5 km from the nearest granite exposure suggest that only the apical part of a pluton is exposed in the quarry and that a larger, shallowly buried body is probably present. These results indicate that potential application of TM image analysis to mineral exploration in lithologically similar areas that are cultivated in spite of poor rock exposures.

Construction of a Distributed-network Digital Watershed Management System with B/S Techniques

NASA Astrophysics Data System (ADS)

Zhang, W. C.; Liu, Y. M.; Fang, J.

2017-07-01

Integrated watershed assessment tools for supporting land management and hydrologic research are becoming established tools in both basic and applied research. The core of these tools are mainly spatially distributed hydrologic models as they can provide a mechanism for investigating interactions among climate, topography, vegetation, and soil. However, the extensive data requirements and the difficult task of building input parameter files for driving these distributed models, have long been an obstacle to the timely and cost-effective use of such complex models by watershed managers and policy-makers. Recently, a web based geographic information system (GIS) tool to facilitate this process has been developed for a large watersheds of Jinghe and Weihe catchments located in the loess plateau of the Huanghe River basin in north-western China. A web-based GIS provides the framework within which spatially distributed data are collected and used to prepare model input files of these two watersheds and evaluate model results as well as to provide the various clients for watershed information inquiring, visualizing and assessment analysis. This Web-based Automated Geospatial Watershed Assessment GIS (WAGWA-GIS) tool uses widely available standardized spatial datasets that can be obtained via the internet oracle databank designed with association of Map Guide platform to develop input parameter files for online simulation at different spatial and temporal scales with Xing’anjiang and TOPMODEL that integrated with web-based digital watershed. WAGWA-GIS automates the process of transforming both digital data including remote sensing data, DEM, Land use/cover, soil digital maps and meteorological and hydrological station geo-location digital maps and text files containing meteorological and hydrological data obtained from stations of the watershed into hydrological models for online simulation and geo-spatial analysis and provides a visualization tool to help the user interpret results. The utility of WAGWA-GIS in jointing hydrologic and ecological investigations has been demonstrated on such diverse landscapes as Jinhe and Weihe watersheds, and will be extended to be utilized in the other watersheds in China step by step in coming years

Monitoring land cover changes by remote sensing in north west Egypt

NASA Astrophysics Data System (ADS)

Richards, Timothy Steven

The Mediterratiean coastal strip of Egypt is a semi-arid environment which supports a variety of agricultural practices ranging from irrigated sedentary agriculture to semi-nomadic pastoralism. The sedentarisation of the nomadic Bedouin coupled with an increase in population of both people and livestock and a decrease in the extent of the rangelands, has resulted in severe pressure being exerted upon the environment. Satellite remote sensing of vegetation offers the potential to aid regional management by complementing conventional techniques of vegetation mapping and monitoring. This thesis examines the different techniques available for vegetation mapping using visible and near infrared spectral wave bands. The different techniques available for vegetation mapping using remotely sensed data are reviewed and discussed with reference to semi-arid environments. The underlying similarity of many of the techniques is emphasised and their individual merits discussed. The spectral feature-space of Landsat data of two representative study areas in northern Egypt is explored and examined using graphical techniques and principal components analysis. Hand held radiometric field data are also presented for individual soil types within the region. It is proposed that by using reference data for individual soil types, improved estimates of vegetation cover can be ascertained. A number of radiometric corrections are applied to the digital Landsat data in order to convert the arbitrary digital values of the different spectral bands into physical values of reflectance. The effect of this standardization on the principal components is examined. The stratified approach to vegetation mapping which was explored using the field data is applied in turn to the digital Landsat images. Whilst the stratified approach was not found to offer significant advantages over the non-stratified approach in this case, the analysis does serve to provide an accurate datum against which to measure vegetation. In conclusion a satellite based system for operational vegetation monitoring is proposed.

Landmarks of History of Soil Science in Sri Lanka

NASA Astrophysics Data System (ADS)

Mapa, R.

2012-04-01

Sri Lanka is a tropical Island in the Southern tip of Indian subcontinent positioned at 50 55' to 90 50' N latitude and 790 42' to 810 53' E longitude surrounded by the Indian Ocean. It is an island 435 km in length and 224 km width consisting of a land are of 6.56 million ha with a population of 20 million. In area wise it is ranked as 118th in the world, where at present ranked as 47 in population wise and ranked 19th in population density. The country was under colonial rule under Portuguese, Dutch and British from 1505 to 1948. The majority of the people in the past and present earn their living from activities based on land, which indicates the important of the soil resource. The objective of this paper is to describe the landmarks of the history of Soil Science to highlight the achievements and failures, which is useful to enrich our present understanding of Sri Lankan soils. The landmarks of the history of Soil Science in Sri Lanka can be divided to three phases namely, the early period (prior to 1956), the middle period (1956 to 1972) and the present period (from 1972 onwards). During the early period, detailed analytical studies of coffee and tea soils were compiled, and these gave mainly information on up-country soils which led to fertilizer recommendations based on field trials. In addition, rice and forest soils were also studied in less detail. The first classification of Sri Lankan soils and a provisional soil map based on parent material was published by Joachim in 1945 which is a major landmark of history of Soil Science in Sri Lanka. In 1959 Ponnamperuma proposed a soil classification system for wetland rice soils. From 1963 to 1968 valuable information on the land resource was collected and documented by aerial resource surveys funded by Canada-Ceylon Colombo plan aid project. This covered 18 major river basins and about 1/4th of Sri Lanka, which resulted in producing excellent soil maps and information of the areas called the Kelani Aruvi Ara and Walawe basins. The provisional soil map was updated by many other workers as Moorman and Panabokke in 1961 and 1972 using this information. The soil map produced by De Alwis and Panabokke in 1972 at a scale of 1:500,000 was the soil maps mostly used during the past years During the present era, the need for classification of Soils of Sri Lanka according to international methods was felt. A major leap forward in Soil Survey, Classification leading to development of a soil data base was initiated in 1995 with the commencement of the "SRICANSOL" project which was a twining project between the Soil Science Societies of Sri Lanka and Canada. This project is now completed with detail soil maps at a scale of 1:250,000 and soil classified according to international methods for the Wet, Intermediate and Dry zones of Sri Lanka. A digital database consisting of soil profile description and physical and chemical data is under preparation for 28, 40 and 51 benchmark sites of the Wet, Intermediate and Dry zones respectively. The emphases on studies on Soil Science in the country at present is more towards environmental conservation related to soil erosion control, reducing of pollution of soil and water bodies from nitrates, pesticide residues and heavy metal accumulation. Key words: Sri Lanka, Provisional soil map

Application of mobile gamma-ray spectrometry for soil mapping

NASA Astrophysics Data System (ADS)

Werban, Ulrike; Lein, Claudia; Pohle, Marco; Dietrich, Peter

2017-04-01

Gamma-ray measurements have a long tradition for geological surveys and deposit exploration using airborne and borehole logging systems. For these applications, the relationships between the measured physical parameter - the concentration of natural gamma emitters 40K, 238U and 232Th - and geological origin or sedimentary developments are well described. Thus, Gamma-ray spectrometry seems a useful tool for carrying out spatial mapping of physical parameters related to soil properties. The isotope concentration in soils depends on different soil parameters (e.g. geochemical composition, grain size fractions), which are a result of source rock properties and processes during soil geneses. There is a rising interest in the method for application in Digital Soil Mapping or as input data for environmental, ecological or hydrological modelling, e.g. as indicator for clay content. However, the gamma-ray measurement is influenced by endogenous factors and processes like soil moisture variation, erosion and deposition of material or cultivation. We will present results from a time series of car borne gamma-ray measurements to observe heterogeneity of soil on a floodplain area in Central Germany. The study area is characterised by high variations in grain size distribution and occurrence of flooding events. For the survey, we used a 4 l NaI(Tl) detector with GPS connection mounted on a sledge, which is towed across the field sites by a four-wheel-vehicle. The comparison of data from different dates shows similar structures with small variation between the data ranges and shape of structures. We will present our experiences concerning the application of gamma-ray measurements under variable field conditions and their impacts on data quality.

Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei

NASA Astrophysics Data System (ADS)

Seutloali, Khoboso E.; Dube, Timothy; Mutanga, Onisimo

2017-08-01

Soil erosion is increasingly recognised as the principal cause of land degradation, loss of agricultural land area and siltation of surrounding water waterbodies. Accurate and up-to-date soil erosion mapping is key in understanding its severity if these negative impacts are to be minimised and affected areas rehabilitated. The aim of this work was to map the severity of soil erosion, based on the 30-m Landsat series multispectral satellite data in the former South African homelands of Transkei between the year 1994 and 2010. Further, the study assessed if the observed soil erosion trends and morphology that existed in this area could be explained by biophysical factors (i.e. slope, stream erosivity, topographic wetness index) retrieved from the 30-m ASTER Digital Elevation Model (DEM). The results of this study indicate that the Transkei region experiences varying erosion levels from moderate to very severe. The large portion of the land area under the former homelands was largely affected by rill erosion with approximately 74% occurring in the year 1984 and 54% in 2010. The results also revealed specific thresholds of soil erosion drivers. These include steeper areas (≥30°), high stream power index greater than 2.0 (stream erosivity), relatively lower vegetation cover (≤15%) and low topographic wetness index (≤5%). The results of this work demonstrate the severity of soil erosion in the Southern African former homelands of Transkei for the year 1984 and 2010. Additionally, this work has demonstrated the significance of the 30-m Landsat multispectral sensor in examining soil erosion occurrence at a regional scale where in-depth field work still remains a challenging task.

Soil and Land Resources Information System (SLISYS-Tarim) for Sustainable Management of River Oases along the Tarim River, China

NASA Astrophysics Data System (ADS)

Othmanli, Hussein; Zhao, Chengyi; Stahr, Karl

2017-04-01

The Tarim River Basin is the largest continental basin in China. The region has extremely continental desert climate characterized by little rainfall <50 mm/a and high potential evaporation >3000 mm/a. The climate change is affecting severely the basin causing soil salinization, water shortage, and regression in crop production. Therefore, a Soil and Land Resources Information System (SLISYS-Tarim) for the regional simulation of crop yield production in the basin was developed. The SLISYS-Tarim consists of a database and an agro-ecological simulation model EPIC (Environmental Policy Integrated Climate). The database comprises relational tables including information about soils, terrain conditions, land use, and climate. The soil data implicate information of 50 soil profiles which were dug, analyzed, described and classified in order to characterize the soils in the region. DEM data were integrated with geological maps to build a digital terrain structure. Remote sensing data of Landsat images were applied for soil mapping, and for land use and land cover classification. An additional database for climate data, land management and crop information were linked to the system, too. Construction of the SLISYS-Tarim database was accomplished by integrating and overlaying the recommended thematic maps within environment of the geographic information system (GIS) to meet the data standard of the global and national SOTER digital database. This database forms appropriate input- and output data for the crop modelling with the EPIC model at various scales in the Tarim Basin. The EPIC model was run for simulating cotton production under a constructed scenario characterizing the current management practices, soil properties and climate conditions. For the EPIC model calibration, some parameters were adjusted so that the modeled cotton yield fits to the measured yield on the filed scale. The validation of the modeling results was achieved in a later step based on remote sensing data. The simulated cotton yield varied according to field management, soil type and salinity level, where soil salinity was the main limiting factor. Furthermore, the calibrated and validated EPIC model was run under several scenarios of climate conditions and land management practices to estimate the effect of climate change on cotton production and sustainability of agriculture systems in the basin. The application of SLISYS-Tarim showed that this database can be a suitable framework for storage and retrieval of soil and terrain data at various scales. The simulation with the EPIC model can assess the impact of climate change and management strategies. Therefore, SLISYS-Tarim can be a good tool for regional planning and serve the decision support system on regional and national scale.

X-ray digital imaging petrography of lunar mare soils: modal analyses of minerals and glasses

NASA Technical Reports Server (NTRS)

Taylor, L. A.; Patchen, A.; Taylor, D. H.; Chambers, J. G.; McKay, D. S.

1996-01-01

It is essential that accurate modal (i.e., volume) percentages of the various mineral and glass phases in lunar soils be used for addressing and resolving the effects of space weathering upon reflectance spectra, as well as for their calibration such data are also required for evaluating the resource potential of lunar minerals for use at a lunar base. However, these data are largely lacking. Particle-counting information for lunar soils, originally obtained to study formational processes, does not provide these necessary data, including the percentages of minerals locked in multi-phase lithic fragments and fused-soil particles, such as agglutinates. We have developed a technique for modal analyses, sensu stricto, of lunar soils, using digital imaging of X-ray maps obtained with an energy-dispersive spectrometer mounted on an electron microprobe. A suite of nine soils (90 to 150 micrometers size fraction) from the Apollo 11, 12, 15, and 17 mare sites was used for this study. This is the first collection of such modal data on soils from all Apollo mare sites. The abundances of free-mineral fragments in the mare soils are greater for immature and submature soils than for mature soils, largely because of the formation of agglutinitic glass as maturity progresses. In considerations of resource utilization at a lunar base, the best lunar soils to use for mineral beneficiation (i.e., most free-mineral fragments) have maturities near the immature/submature boundary (Is/FeO approximately or = 30), not the mature soils with their complications due to extensive agglutination. The particle data obtained from the nine mare soils confirm the generalizations for lunar soils predicted by L.A. Taylor and D.S. McKay (1992, Lunar Planet Sci. Conf. 23rd, pp. 1411-1412 [Abstract]).

The UK Soil Observatory (UKSO) and mySoil app: crowdsourcing and disseminating soil information.

NASA Astrophysics Data System (ADS)

Robinson, David; Bell, Patrick; Emmett, Bridget; Panagos, Panos; Lawley, Russell; Shelley, Wayne

2017-04-01

Digital technologies in terms of web based data portals and mobiles apps offer a new way to provide both information to the public, and to engage the public in becoming involved in contributing to the effort of collecting data through crowdsourcing. We are part of the Landpotential.org consortium which is a global partnership committed to developing and supporting the adoption of freely available technology and tools for sustainable land use management, monitoring, and connecting people across the globe. The mySoil app was launched in 2012 and is an example of a free mobile application downloadable from iTunes and Google Play. It serves as a gateway tool to raise interest in, and awareness of, soils. It currently has over 50,000 dedicated users and has crowd sourced more than 4000 data records. Recent developments have expanded the coverage of mySoil from the United Kingdom to Europe, introduced a new user interface and provided language capability, while the UKSO displays the crowd-sourced records from across the globe. We are now trying to identify which industry, education and citizen sectors are using these platforms and how they can be improved. Please help us by providing feedback or taking the survey on the UKSO website. www.UKSO.org The UKSO is a collaboration between major UK soil-data holders to provide maps, spatial data and real-time temporal data from observing platforms such as the UK soil moisture network. Both UKSO and mySoil have crowdsourcing capability and are slowly building global citizen science maps of soil properties such as pH and texture. Whilst these data can't replace professional monitoring data, the information they provide both stimulates public interest and can act as 'soft data' that can help support the interpretation of monitoring data, or guide future monitoring, identifying areas that don't correspond with current analysis. In addition, soft data can be used to map soils with machine learning approaches, such as SoilGrids.

Soil erosion modelling for NSW coastal catchments using RUSLE in a GIS environment

NASA Astrophysics Data System (ADS)

Yang, Xihua; Chapman, Greg

2006-10-01

In this study, hillslope erosion risk has been estimated for all eastern New South Wales (NSW) catchments, Australia using Revised Universal Soil Loss Equation (RUSLE) in a geographic information system (GIS) environment. Rainfall-runoff erosivity (R) factor was interpolated from NSW rainfall-erosivity contour (isoerodent) data. Soil erodibility (K) factor was based on the soil regolith stability and sediment yield classification. The classification was derived from soil landscape and related soil map data. The slope length and steepness (LS) factor was derived from high resolution digital elevation model (DEM). A fully-automated program using Arc Macro Language (AML) produced RUSLE-based LS factor grids for all coastal catchments. The outputs are comparable to the range of LS values summarised in the literature. Cover and management (C) factor and conservation support-practices (P) factor were set to one. They are intended to be allocated according to land use, ground cover and erosion control provisions for particular land management actions. The resulting erosion risk map, with pixel size of 25-m, provides unprecedented resolution of relative expected sheet and rill erosion across all NSW costal catchments and can be adapted for a range of erosion control purposes such as bushfire hazard reduction and comprehensive costal assessment.

Data compilation, synthesis, and calculations used for organic-carbon storage and inventory estimates for mineral soils of the Mississippi River Basin

USGS Publications Warehouse

Buell, Gary R.; Markewich, Helaine W.

2004-01-01

U.S. Geological Survey investigations of environmental controls on carbon cycling in soils and sediments of the Mississippi River Basin (MRB), an area of 3.3 x 106 square kilometers (km2), have produced an assessment tool for estimating the storage and inventory of soil organic carbon (SOC) by using soil-characterization data from Federal, State, academic, and literature sources. The methodology is based on the linkage of site-specific SOC data (pedon data) to the soil-association map units of the U.S. Department of Agriculture State Soil Geographic (STATSGO) and Soil Survey Geographic (SSURGO) digital soil databases in a geographic information system. The collective pedon database assembled from individual sources presently contains 7,321 pedon records representing 2,581 soil series. SOC storage, in kilograms per square meter (kg/m2), is calculated for each pedon at standard depth intervals from 0 to 10, 10 to 20, 20 to 50, and 50 to 100 centimeters. The site-specific storage estimates are then regionalized to produce national-scale (STATSGO) and county-scale (SSURGO) maps of SOC to a specified depth. Based on this methodology, the mean SOC storage for the top meter of mineral soil in the MRB is approximately 10 kg/m2, and the total inventory is approximately 32.3 Pg (1 petagram = 109 metric tons). This inventory is from 2.5 to 3 percent of the estimated global mineral SOC pool.

Mapping elemental contamination on Palmyra Atoll National Wildlife Refuge

USGS Publications Warehouse

Struckhoff, Matthew A.; Orazio, Carl E.; Tillitt, Donald E.; Shaver, David K.; Papoulias, Diana M.

2018-01-01

Palmyra Atoll, once a WWII U.S. Navy air station, is now a U.S. National Wildlife Refuge with nearly 50 km2 of coral reef and 275 ha of emergent lands with forests of Pisonia grandistrees and colonies of several bird species. Due to the known elemental and organic contamination from chemicals associated with aviation, power generation and transmission, waste management, and other air station activities, a screening survey to map elemental concentrations was conducted. A map of 1944 Navy facilities was georeferenced and identifiable features were digitized. These data informed a targeted survey of 25 elements in soils and sediment at locations known or suspected to be contaminated, using a hand-held X-ray fluorescence spectrometer. At dozens of locations, concentrations of elements exceeded established soil and marine sediment thresholds for adverse ecological effects. Results were compiled into a publically available geospatial dataset to inform potential remediation and habitat restoration activities.

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia

PubMed Central

McBratney, Alex B.; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson’s correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (−0.34), mid-slope position (−0.29), multi-resolution valley bottom flatness index (−0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged. PMID:29682425

Description and spatial inference of soil drainage using matrix soil colours in the Lower Hunter Valley, New South Wales, Australia.

PubMed

Malone, Brendan P; McBratney, Alex B; Minasny, Budiman

2018-01-01

Soil colour is often used as a general purpose indicator of internal soil drainage. In this study we developed a necessarily simple model of soil drainage which combines the tacit knowledge of the soil surveyor with observed matrix soil colour descriptions. From built up knowledge of the soils in our Lower Hunter Valley, New South Wales study area, the sequence of well-draining → imperfectly draining → poorly draining soils generally follows the colour sequence of red → brown → yellow → grey → black soil matrix colours. For each soil profile, soil drainage is estimated somewhere on a continuous index of between 5 (very well drained) and 1 (very poorly drained) based on the proximity or similarity to reference soil colours of the soil drainage colour sequence. The estimation of drainage index at each profile incorporates the whole-profile descriptions of soil colour where necessary, and is weighted such that observation of soil colour at depth and/or dominantly observed horizons are given more preference than observations near the soil surface. The soil drainage index, by definition disregards surficial soil horizons and consolidated and semi-consolidated parent materials. With the view to understanding the spatial distribution of soil drainage we digitally mapped the index across our study area. Spatial inference of the drainage index was made using Cubist regression tree model combined with residual kriging. Environmental covariates for deterministic inference were principally terrain variables derived from a digital elevation model. Pearson's correlation coefficients indicated the variables most strongly correlated with soil drainage were topographic wetness index (-0.34), mid-slope position (-0.29), multi-resolution valley bottom flatness index (-0.29) and vertical distance to channel network (VDCN) (0.26). From the regression tree modelling, two linear models of soil drainage were derived. The partitioning of models was based upon threshold criteria of VDCN. Validation of the regression kriging model using a withheld dataset resulted in a root mean square error of 0.90 soil drainage index units. Concordance between observations and predictions was 0.49. Given the scale of mapping, and inherent subjectivity of soil colour description, these results are acceptable. Furthermore, the spatial distribution of soil drainage predicted in our study area is attuned with our mental model developed over successive field surveys. Our approach, while exclusively calibrated for the conditions observed in our study area, can be generalised once the unique soil colour and soil drainage relationship is expertly defined for an area or region in question. With such rules established, the quantitative components of the method would remain unchanged.

For multidisciplinary research on the application of remote sensing to water resources problems. [including crop yield, watershed soils, and vegetation mapping in Wisconsin

NASA Technical Reports Server (NTRS)

Kiefer, R. W. (Principal Investigator)

1979-01-01

Research on the application of remote sensing to problems of water resources was concentrated on sediments and associated nonpoint source pollutants in lakes. Further transfer of the technology of remote sensing and the refinement of equipment and programs for thermal scanning and the digital analysis of images were also addressed.

Distribution of late Pleistocene ice-rich syngenetic permafrost of the Yedoma Suite in east and central Siberia, Russia

USGS Publications Warehouse

Grosse, Guido; Robinson, Joel E.; Bryant, Robin; Taylor, Maxwell D.; Harper, William; DeMasi, Amy; Kyker-Snowman, Emily; Veremeeva, Alexandra; Schirrmeister, Lutz; Harden, Jennifer

2013-01-01

This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.

The Soil Atlas of Africa: raising awareness and educate to the importance of soil

NASA Astrophysics Data System (ADS)

Dewitte, Olivier; Jones, Arwyn; Bosco, Claudio; Spaargaren, Otto; Montanarella, Luca

2010-05-01

The richness of African soil resources need to be protected for future generations. A number of threats are affecting the functioning of African soils, not only for the purpose of agricultural production, but also for other important environmental services that soil delivers to all of us. This is of particular importance once we know that many health-related problems in Africa are indirectly related to the services of soils. To raise the awareness of the general public, policy makers and other scientists to the importance of soil in Africa, the Joint Research Centre of the European Commission is to produce the first ever Soil Atlas of Africa. This is in collaboration with the African Union Commission, the Food and Agriculture Organization of the United Nations (FAO), the Africa Soil Science Society, ISRIC - World Soil Information and scientists from both Europe and Africa. The Atlas compiles existing information on different soil types as easily understandable maps (both at regional and continental scale) covering the African continent. The Soil Atlas of Africa intends to produce derived maps at continental scale with descriptive text (e.g. vulnerability to desertification, soil nutrient status, carbon stocks and sequestration potential, irrigable areas and water resources) as well as specific maps to illustrate threats such as soil erosion for instance. For each regional overview, large scale examples of soil maps and derived products are presented too. The Atlas will be published as a hardcover book containing 174 A3 pages, which will allow soils maps to be displayed at the A2 scale. Both French and English versions of the Atlas will be edited. The Atlas will be sold at a low cost and will be for free for educational purpose (Schools and Universities). A digital version on CD and eventually freely downloadable on internet will also be available. Together with the publication of the Atlas, associated datasets on soil characteristics for Africa will be made available. These datasets will be useful for making broad distinction among soil types and provide general trends at the global and regional scales. The datasets will be made accessible for free downloading from the portals of the SOIL Action (http://eusoils.jrc.ec.europa.eu/) and the ACP Observatory for Sustainable Development (http://acpobservatory.jrc.ec.europa.eu). The Atlas links the theme of soil with rural development and, at the same time, supports the goals of the EU Thematic Strategy for Soil Protection in conserving a threatened natural resource that is vital to human existence. Not only climate change, but also desertification and loss of biodiversity are strongly affecting soils globally, making the "Soil Atlas of Africa" relevant to a much larger community of stakeholders involved in the implementation of the three "Rio-Conventions" and allowing to explore possible synergies among international multilateral agreements towards global soil protection.

Digital Data Set of Orchards Where Arsenical Pesticides Were Likely Used in Clarke and Frederick Counties, Virginia, and Berkeley and Jefferson Counties, West Virginia

USGS Publications Warehouse

Reed, Bradley W.; Larkins, Peter; Robinson, Gilpin R.

2006-01-01

This data set shows orchard locations in Clarke and Frederick Counties, Virginia and Berkeley and Jefferson Counties, West Virginia where arsenical pesticides were likely used. The orchard locations are based on air photos and topographic maps prepared using information from the time period of extensive use of arsenical pesticides between the 1920s and 1960s. An orchard's presence in this data set does not necessarily indicate the use of arsenical pesticides on the site or that elevated arsenic and metal concentrations are present. Arsenical pesticides may have been used on part, or none, of the land and, under current land use, the land may have been remediated and no longer contain elevated arsenic and metal concentrations in soil. The data set was created to be used in an assessment of soil contamination related to past use of arsenical pesticides in orchards in the northern part of the Great Valley region, Virginia and West Virginia. Previous studies have documented that elevated concentrations of arsenic, lead, and sometimes copper occur in the soils of former apple orchards (Veneman et al., 1983; Jones and Hatch, 1937). Arsenical pesticide use was most extensive and widespread in agricultural applications from the 1920s to the late 1950s, and largely ceased agricultural use by the early 1960s in the nation. During this time period, lead arsenate was the most extensively used arsenical pesticide (Peryea, 1998), particularly in apple orchards. Other metal-bearing pesticides, such as copper acetoarsenite (Paris Green), Bordeaux Blue (a mixture of copper sulfate and calcium hydroxide), and organic mercury fumigants were used to a lesser degree in orchards (Peryea, 1998; Shepard, 1939; Veneman et al., 1983). During the time arsenical pesticides were extensively used, federal and state pesticide laws did not require farmers to keep accurate records of the quantity, location, and type of arsenical pesticides used on their property, thus the quantity and distribution of this past arsenical pesticide use is not known in the region. Based on estimates from other areas (D'Angelo et al., 1996), cumulate application over the period of arsenical pesticide use may have been as much as 22.4 g/m2 of arsenic and 100 g/m2 of lead in orchard areas. In minimally disturbed orchard soils, arsenic and lead are largely retained in the top few centimeters of the soil horizon; intra-soil redistribution of these metals occurs but appears to be limited (Veneman et al. 1983; Peryea, 1998). Surface concentrations of arsenic and lead in undisturbed orchard soils where arsenical pesticides were used commonly exceed 20 mg/kg As and 100 mg/kg Pb (Veneman et al., 1983; Jones and Hatch, 1937). The digital data set of orchard locations was used to aid assessment of the likely occurrence and distribution of arsenical pesticide residues in surface soils. Most areas of orchard cultivation were sited in areas overlying carbonate bedrock in the Valley and Ridge province. This data set needed to be created since there was no reliable and complete land cover data set identifying areas under orchard cultivation during the time period of extensive use of arsenical pesticides in the study area as of the time of the study. The spatial database of orchard areas was compiled using twenty-seven USGS 7.5 minute series topographical maps covering the study area of Clarke and Frederick Counties, Virginia, and Berkeley and Jefferson Counties, West Virginia. These maps were published between 1943 and 1972 at 1:24,000 scale, with the oldest topographic map available from the US Geological Survey map archive for each area being chosen, going back only as far as the 1920s when use of arsenical pesticides started. Orchard areas on the topographic maps were traced in order to aid in the digitization of the sites. The topographic maps were then scanned and geographically referenced using ERDAS Imagine version 8.7, a raster editing program, turning them into rectifi

Covariance of biophysical data with digital topograpic and land use maps over the FIFE site

NASA Technical Reports Server (NTRS)

Davis, F. W.; Schimel, D. S.; Friedl, M. A.; Michaelsen, J. C.; Kittel, T. G. F.; Dubayah, R.; Dozier, J.

1992-01-01

This paper discusses the biophysical stratification of the FIFE site, implementation of the stratification utilizing geographic information system methods, and validation of the stratification with respect to field measurements of biomass, Bowen ratio, soil moisture, and the greenness vegetation index (GVI) derived from TM satellite data. Maps of burning and topographic position were significantly associated with variation in GVI, biomass, and Bowen ratio. The stratified design did not significantly alter the estimated site-wide means for surface climate parameters but accounted for between 25 and 45 percent of the sample variance depending on the variable.

The role of remotely sensed and other special data for predictive modeling: the Umatilla, Oregon example

USGS Publications Warehouse

Loveland, Thomas R.; Johnson, Gary E.

1983-01-01

Landsat data and 1:24 000-scale aerial photographs were initially used to map the expansion of irrigation from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), landownership, soil irrigability, slope gradient, and potential energy costs.

Modelling soil erosion in a head catchment of Jemma Basin on the Ethiopian highlands

NASA Astrophysics Data System (ADS)

Cama, Mariaelena; Schillaci, Calogero; Kropáček, Jan; Hochschild, Volker; Maerker, Michael

2017-04-01

Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality especially in developing countries such as Ethiopia where rapid population growth and climatic changes affect wide mountainous areas. The catchment of Andit-Tid is a head catchment of Jemma Basin draining to the Blue Nile (Central Ethiopia). It is located in an extremely variable topographical environment and it is exposed to high degradation dynamics especially in the lower part of the catchment. The increasing agricultural activity and grazing, lead to an intense use of the steep slopes which altered the soil structure. As a consequence, water erosion processes accelerated leading to the evolution of sheet erosion, gullies and badlands. This study is aimed at a geomorphological assessment of soil erosion susceptibility. First, a geomorphological map is generated using high resolution digital elevation model (DEM) derived from high resolution stereoscopic satellite data, multispectral imagery from Rapid Eye satellite system . The map was then validated by a detailed field survey. The final maps contains three inventories of landforms: i) sheet, ii) gully erosion and iii) badlands. The water erosion susceptibility is calculated with a Maximum Entropy approach. In particular, three different models are built using the three inventories as dependent variables and a set of spatial attributes describing the lithology, terrain, vegetation and land cover from remote sensing data and DEMs as independent variables. The single susceptibility maps for sheet, gully erosion as well as badlands showed good to excellent predictive performances. Moreover, we reveal and discuss the importance of different sets of variables among the three models. In order to explore the mutual overlap of the three susceptibility maps we generated a combined map as color composite whereas each color represents one component of water erosion. The latter map yield a useful information for land use managers and planning purposes.

Evaluation of a color-coded Landsat 5/6 ratio image for mapping lithologic differences in western South Dakota

USGS Publications Warehouse

Raines, Gary L.; Bretz, R.F.; Shurr, George W.

1979-01-01

From analysis of a color-coded Landsat 5/6 ratio, image, a map of the vegetation density distribution has been produced by Raines of 25,000 sq km of western South Dakota. This 5/6 ratio image is produced digitally calculating the ratios of the bands 5 and 6 of the Landsat data and then color coding these ratios in an image. Bretz and Shurr compared this vegetation density map with published and unpublished data primarily of the U.S. Geological Survey and the South Dakota Geological Survey; good correspondence is seen between this map and existing geologic maps, especially with the soils map. We believe that this Landsat ratio image can be used as a tool to refine existing maps of surficial geology and bedrock, where bedrock is exposed, and to improve mapping accuracy in areas of poor exposure common in South Dakota. In addition, this type of image could be a useful, additional tool in mapping areas that are unmapped.

Modeling rainfall conditions for shallow landsliding in Seattle, Washington

USGS Publications Warehouse

Godt, Jonathan W.; Schulz, William H.; Baum, Rex L.; Savage, William Z.

2008-01-01

We describe the results from an application of a distributed, transient infiltration–slope-stability model for an 18 km2 area of southwestern Seattle, Washington, USA. The model (TRIGRS) combines an infinite slope-stability calculation and an analytic, one-dimensional solution for pore-pressure diffusion in a soil layer of finite depth in response to time-varying rainfall. The transient solution for pore-pressure response can be superposed on any steady-state groundwater-flow field that is consistent with model assumptions. Applied over digital topography, the model computes a factor of safety for each grid cell at any time during a rainstorm. Input variables may vary from cell to cell, and the rainfall rate can vary in both space and time. For Seattle, topographic slope derived from an airborne laser swath mapping (ALSM)–based 3 m digital elevation model (DEM), maps of soil and water-table depths derived from geotechnical borings, and hourly rainfall intensities were used as model inputs. Material strength and hydraulic properties used in the model were determined from field and laboratory measurements, and a tension-saturated initial condition was assumed. Results are given in terms of a destabilizing intensity and duration of rainfall, and they were evaluated by comparing the locations of 212 historical landslides with the area mapped as potentially unstable. Because the equations of groundwater flow are explicitly solved with respect to time, the results from TRIGRS simulations can be portrayed quantitatively to assess the potential landslide hazard based on rainfall conditions.

Using high-resolution radar images to determine vegetation cover for soil erosion assessments.

PubMed

Bargiel, D; Herrmann, S; Jadczyszyn, J

2013-07-30

Healthy soils are crucial for human well-being. Because soils are threatened worldwide, politicians recognize the need for soil protection. For example, the European Commission has launched the Thematic Strategy for Soil Protection, which requests the European member states to identify high risk areas for soil degradation. Most states use the Universal Soil Loss Equation (USLE) to assess soil erosion risk at the national scale. The USLE includes different factors, one of them is the vegetation cover and management factor (C factor). Modern satellite-based radar sensors now provide highly accurate vegetation cover data, enabling opportunities to improve the accuracy of the C factor. The presented study proves the suitability for C factor determination based on a multi-temporal classification of high-resolution radar images. Further USLE factors were derived from existing data sources (meteorological data, soil maps, digital elevation model) to conduct an USLE-based soil erosion assessment. The resulting map illustrates a qualitative assessment for soil erosion risk within a plot of about 7*12 km in an agricultural region in Poland that is very susceptible to soil erosion processes. A high erosion risk of more than 10 tonnes per ha and year was assessed to occur on 13.6% (646 ha) of the agricultural areas within the investigated plot. Further 7.8% (372 ha) of agricultural land is threaten by a medium risk of 5-10 tonnes per ha and year. Such a spatial information about areas of high or medium soil erosion risk are crucial for the development of strategies for the protection of soils. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions

NASA Astrophysics Data System (ADS)

Hugelius, G.; Tarnocai, C.; Broll, G.; Canadell, J. G.; Kuhry, P.; Swanson, D. K.

2012-08-01

High latitude terrestrial ecosystems are key components in the global carbon (C) cycle. Estimates of global soil organic carbon (SOC), however, do not include updated estimates of SOC storage in permafrost-affected soils or representation of the unique pedogenic processes that affect these soils. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify the SOC stocks in the circumpolar permafrost region (18.7 × 106 km2). The NCSCD is a polygon-based digital database compiled from harmonized regional soil classification maps in which data on soil order coverage has been linked to pedon data (n = 1647) from the northern permafrost regions to calculate SOC content and mass. In addition, new gridded datasets at different spatial resolutions have been generated to facilitate research applications using the NCSCD (standard raster formats for use in Geographic Information Systems and Network Common Data Form files common for applications in numerical models). This paper describes the compilation of the NCSCD spatial framework, the soil sampling and soil analyses procedures used to derive SOC content in pedons from North America and Eurasia and the formatting of the digital files that are available online. The potential applications and limitations of the NCSCD in spatial analyses are also discussed. The database has the doi:10.5879/ecds/00000001. An open access data-portal with all the described GIS-datasets is available online at: http://dev1.geo.su.se/bbcc/dev/ncscd/.

The Northern Circumpolar Soil Carbon Database: spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions

NASA Astrophysics Data System (ADS)

Hugelius, G.; Tarnocai, C.; Broll, G.; Canadell, J. G.; Kuhry, P.; Swanson, D. K.

2013-01-01

High-latitude terrestrial ecosystems are key components in the global carbon (C) cycle. Estimates of global soil organic carbon (SOC), however, do not include updated estimates of SOC storage in permafrost-affected soils or representation of the unique pedogenic processes that affect these soils. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify the SOC stocks in the circumpolar permafrost region (18.7 × 106 km2). The NCSCD is a polygon-based digital database compiled from harmonized regional soil classification maps in which data on soil order coverage have been linked to pedon data (n = 1778) from the northern permafrost regions to calculate SOC content and mass. In addition, new gridded datasets at different spatial resolutions have been generated to facilitate research applications using the NCSCD (standard raster formats for use in geographic information systems and Network Common Data Form files common for applications in numerical models). This paper describes the compilation of the NCSCD spatial framework, the soil sampling and soil analytical procedures used to derive SOC content in pedons from North America and Eurasia and the formatting of the digital files that are available online. The potential applications and limitations of the NCSCD in spatial analyses are also discussed. The database has the doi:10.5879/ecds/00000001. An open access data portal with all the described GIS-datasets is available online at: http://www.bbcc.su.se/data/ncscd/.

Landscape Metrics to Predict Soil Spatial Patterns

NASA Astrophysics Data System (ADS)

Gillin, C. P.; McGuire, K. J.; Bailey, S.; Prisley, S.

2012-12-01

Recent literature has advocated the application of hydropedology, or the integration of hydrology and pedology, to better understand hydrologic flowpaths and soil spatial heterogeneity in a landscape. Hydropedology can be used to describe soil units affected by distinct topography, geology, and hydrology. Such a method has not been applied to digital soil mapping in the context of spatial variations in hydrological and biogeochemical processes. The purpose of this study is to use field observations of soil morphology, geospatial information technology, and a multinomial logistic regression model to predict the distribution of five hydropedological units (HPUs) across a 41-hectare forested headwater catchment in New England. Each HPU reflects varying degrees of lateral flow influence on soil development. Ninety-six soil characterization pits were located throughout the watershed, and HPU type was identified at each pit based on the presence and thickness of genetic soil horizons. Digital terrain analysis was conducted using ArcGIS and SAGA software to compute topographic and landscape metrics. Results indicate that each HPU occurs under specific topographic settings that influence subsurface hydrologic conditions. Among the most important landscape metrics are distance from stream, distance from bedrock outcrop, upslope accumulated area, the topographic wetness index, the downslope index, and curvature. Our project is unique in that it delineates high resolution soil units using a process-based morphological approach rather than a traditional taxonomical method taken by conventional soil surveys. Hydropedological predictor models can be a valuable tool for informing forest and land management decisions, water quality planning, soil carbon accounting, and understanding subsurface hydrologic dynamics. They can also be readily calibrated for regions of differing geology, topography, and climate regimes.

Evaluation and comparison of ERTS measurements of major crops and soil associations for selected test sites in the central United States. [Texas, Indiana, Kansas, Iowa, Nebraska, and North Dakota

NASA Technical Reports Server (NTRS)

Baumgardner, M. F. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Multispectral scanner data obtained by ERTS-1 over six test sites in the Central United States were analyzed and interpreted. ERTS-1 data for some of the test sites were geometrically corrected and temporally overlayed. Computer-implemented pattern recognition techniques were used in the analysis of all multispectral data. These techniques were used to evaluate ERTS-1 data as a tool for soil survey. Geology maps and land use inventories were prepared by digital analysis of multispectral data. Identification and mapping of crop species and rangelands were achieved throught the analysis of 1972 and 1973 ERTS-1 data. Multiple dates of ERTS-1 data were examined to determine the variation with time of the areal extent of surface water resources on the Southern Great Plain.

Impact of Sub-grid Soil Textural Properties on Simulations of Hydrological Fluxes at the Continental Scale Mississippi River Basin

NASA Astrophysics Data System (ADS)

Kumar, R.; Samaniego, L. E.; Livneh, B.

2013-12-01

Knowledge of soil hydraulic properties such as porosity and saturated hydraulic conductivity is required to accurately model the dynamics of near-surface hydrological processes (e.g. evapotranspiration and root-zone soil moisture dynamics) and provide reliable estimates of regional water and energy budgets. Soil hydraulic properties are commonly derived from pedo-transfer functions using soil textural information recorded during surveys, such as the fractions of sand and clay, bulk density, and organic matter content. Typically large scale land-surface models are parameterized using a relatively coarse soil map with little or no information on parametric sub-grid variability. In this study we analyze the impact of sub-grid soil variability on simulated hydrological fluxes over the Mississippi River Basin (≈3,240,000 km2) at multiple spatio-temporal resolutions. A set of numerical experiments were conducted with the distributed mesoscale hydrologic model (mHM) using two soil datasets: (a) the Digital General Soil Map of the United States or STATSGO2 (1:250 000) and (b) the recently collated Harmonized World Soil Database based on the FAO-UNESCO Soil Map of the World (1:5 000 000). mHM was parameterized with the multi-scale regionalization technique that derives distributed soil hydraulic properties via pedo-transfer functions and regional coefficients. Within the experimental framework, the 3-hourly model simulations were conducted at four spatial resolutions ranging from 0.125° to 1°, using meteorological datasets from the NLDAS-2 project for the time period 1980-2012. Preliminary results indicate that the model was able to capture observed streamflow behavior reasonably well with both soil datasets, in the major sub-basins (i.e. the Missouri, the Upper Mississippi, the Ohio, the Red, and the Arkansas). However, the spatio-temporal patterns of simulated water fluxes and states (e.g. soil moisture, evapotranspiration) from both simulations, showed marked differences; particularly at a shorter time scale (hours to days) in regions with coarse texture sandy soils. Furthermore, the partitioning of total runoff into near-surface interflows and baseflow components was also significantly different between the two simulations. Simulations with the coarser soil map produced comparatively higher baseflows. At longer time scales (months to seasons) where climatic factors plays a major role, the integrated fluxes and states from both sets of model simulations match fairly closely, despite the apparent discrepancy in the partitioning of total runoff.

Scoping of Flood Hazard Mapping Needs for Coos County, New Hampshire

DTIC Science & Technology

2006-01-01

Technical Partner DEM Digital Elevation Model DFIRM Digital Flood Insurance Rate Map DOQ Digital Orthophoto Quadrangle DOQQ Digital Ortho Quarter Quadrangle...color Digital Orthophoto Quadrangles (DOQs)). Remote sensing, base map information, GIS data (for example, contour data, E911 data, Digital Elevation...the feature types found on USGS topographic maps. More recently developed data were derived from digital orthophotos providing improved base map

Preliminary Evaluation of TM for Soils Information

NASA Technical Reports Server (NTRS)

Thompson, D. R.; Henderson, K. E.; Houston, A. G.; Pitts, D. E.

1984-01-01

Thematic mapper data acquired over Mississippi County, Arkansas, were examined for utility in separating soil associations within generally level alluvium deposited by the Mississippi River. The 0.76 to 0.90 micron (Band 4) and the 1.55 to 1.75 micron (Band 5) were found to separate the different soil associations fairly well when compared to the USDA-SCS general soil map. The thermal channel also appeared to provide information at this level. A detailed soil survey was available at the field level along with ground observations of crop type, plant height, percent cover and growth stage. Soils within the fields ranged from uniform to soils that occur as patches of sand that stand out strongly against the intermingled areas of dark soil. Examination of the digital values of individual TM bands at the field level indicates that the influence of the soil is greater in TM than it was in MSS bands. The TM appears to provide greater detail of within field variability caused by soils than MSS and thus should provide improved information relating to crop and soil properties. However, this soil influence may cause crop identification classification procedures to have to account for the soil in their algorithms.

Agricultural land use mapping. [Pennsylvania, Montana, and Texas

NASA Technical Reports Server (NTRS)

Mcmurtry, G. J.; Petersen, G. W. (Principal Investigator); Wilson, A. D.

1973-01-01

The author has identified the following significant results. Agricultural areas were selected or analysis in southeastern Pennsylvania, north central Montana, and southern Texas. These three sites represent a broad range of soils, soil parent materials, climate, modes of agricultural operation, crops, and field sizes. In each of these three sites, ERTS-1 digital data were processed to determine the feasibility of automatically mapping agricultural land use. In Pennsylvania, forest land, cultivated land, and water were separable within a 25,000 acre area. Four classes of water were also classified and identified, using ground truth. A less complex land use pattern was analyzed in Hill County, Montana. A land use map was prepared shown alternating patterns of summer fallow and stubble fields. The location of farmsteads could be inferred, along with that of a railroad line. A river and a creek flowing into the river were discernible. Six categories of water, related to sediment content and depth, were defined in the reservoir held by the Fresno dam. These classifications were completed on a 150 square mile area. Analysis of the data from Texas is in its formative stages. A test site has been selected and a brightness map has been produced.

An integrated remote sensing approach for identifying ecological range sites. [parker mountain

NASA Technical Reports Server (NTRS)

Jaynes, R. A.

1983-01-01

A model approach for identifying ecological range sites was applied to high elevation sagebrush-dominated rangelands on Parker Mountain, in south-central Utah. The approach utilizes map information derived from both high altitude color infrared photography and LANDSAT digital data, integrated with soils, geological, and precipitation maps. Identification of the ecological range site for a given area requires an evaluation of all relevant environmental factors which combine to give that site the potential to produce characteristic types and amounts of vegetation. A table is presented which allows the user to determine ecological range site based upon an integrated use of the maps which were prepared. The advantages of identifying ecological range sites through an integrated photo interpretation/LANDSAT analysis are discussed.

The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

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

Drover, Damion, Ryan

2011-12-01

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would thereforemore » be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.« less

Spatio-temporal interpolation of soil moisture in 3D+T using automated sensor network data

NASA Astrophysics Data System (ADS)

Gasch, C.; Hengl, T.; Magney, T. S.; Brown, D. J.; Gräler, B.

2014-12-01

Soil sensor networks provide frequent in situ measurements of dynamic soil properties at fixed locations, producing data in 2- or 3-dimensions and through time (2D+T and 3D+T). Spatio-temporal interpolation of 3D+T point data produces continuous estimates that can then be used for prediction at unsampled times and locations, as input for process models, and can simply aid in visualization of properties through space and time. Regression-kriging with 3D and 2D+T data has successfully been implemented, but currently the field of geostatistics lacks an analytical framework for modeling 3D+T data. Our objective is to develop robust 3D+T models for mapping dynamic soil data that has been collected with high spatial and temporal resolution. For this analysis, we use data collected from a sensor network installed on the R.J. Cook Agronomy Farm (CAF), a 37-ha Long-Term Agro-Ecosystem Research (LTAR) site in Pullman, WA. For five years, the sensors have collected hourly measurements of soil volumetric water content at 42 locations and five depths. The CAF dataset also includes a digital elevation model and derivatives, a soil unit description map, crop rotations, electromagnetic induction surveys, daily meteorological data, and seasonal satellite imagery. The soil-water sensor data, combined with the spatial and temporal covariates, provide an ideal dataset for developing 3D+T models. The presentation will include preliminary results and address main implementation strategies.

Development and validation of a method to estimate the potential wind erosion risk in Germany

NASA Astrophysics Data System (ADS)

Funk, Roger; Deumlich, Detlef; Völker, Lidia

2017-04-01

The introduction of the Cross Compliance (CC) regulations for soil protection resulted in the demand for the classification of the the wind erosion risk on agricultural areas in Germany nationwide. A spatial highly resolved method was needed based on uniform data sets and validation principles, which provides a fair and equivalent procedure for all affected farmers. A GIS-procedure was developed, which derives the site specific wind erosion risk from the main influencing factors: soil texture, wind velocity, wind direction and landscape structure following the German standard DIN 19706. The procedure enables different approaches in the Federal States and comparable classification results. Here, we present the approach of the Federal State of Brandenburg. In the first step a complete soil data map was composed in a grid size of 10 x 10 m. Data were taken from 1.) the Soil quality Appraisal (scale 1:10.000), 2.) the Medium-scale Soil Mapping (MMK, 1:25.000), 3.) extrapolating the MMK, 4.) new Soil quality Appraisal (new areas after coal-mining). Based on the texture and carbon content the wind erosion susceptibility was divided in 6 classes. This map was combined with data of the annual average wind velocity resulting in an increase of the risk classes for wind velocities > 5 ms-1 and a decrease for < 3 ms-1. The sheltering effect of landscape structure is regarded by allocating a height to each landscape element, corresponding to the described features in the digital "Biotope and Land Use Map". The "hill shade" procedure of ArcGIS was used to set virtual shadows behind the landscape elements for eight directions. The relative frequency of wind from each direction was used as a weighting factor and multiplied with the numerical values of the shadowed cells. Depending on the distance to the landscape element the shadowing effect was combined with the risk classes. The results show that the wind erosion risk is obviously reduced by integrating landscape structures into the risk assessment. After the renewed classification for the entire Federal State, about 60% of the area in the highest, and 40% in the medium risk classes changed into lower classes. The area of the highest potential risk class decreased from 40% to 17% in relation to the total area. A validation of this approach was made by data of the Digital Surface Model (DSM, first pulse) from laser scanning of an area of 144 km2 with a spatial resolution of 1 x 1 m. It could be shown that the allocated height values of the landscape elements were correct in 75% per cent, too low in 15% and too high in 11% off all cases. The current landscape element map of the Federal State of Brandenburg will be replaced, when the DSM is available for the entire area in the near future.

Predicting active-layer soil thickness using topographic variables at a small watershed scale

PubMed Central

Li, Aidi; Tan, Xing; Wu, Wei; Liu, Hongbin; Zhu, Jie

2017-01-01

Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters. PMID:28877196

Comparison of SWAT and GeoWEPP model in predicting the impact of stone bunds on runoff and erosion processes in the Northern Ethiopian Highlands

NASA Astrophysics Data System (ADS)

Demelash, Nigus; Flagler, Jared; Renschler, Chris; Strohmeier, Stefan; Holzmann, Hubert; Feras, Ziadat; Addis, Hailu; Zucca, Claudio; Bayu, Wondimu; Klik, Andreas

2017-04-01

Soil degradation is a major issue in the Ethiopian highlands which are most suitable for agriculture and, therefore, support a major part of human population and livestock. Heavy rainstorms during the rainy season in summer create soil erosion and runoff processes which affect soil fertility and food security. In the last years programs for soil conservation and afforestation were initiated by the Ethiopian government to reduce erosion risk, retain water in the landscape and improve crop yields. The study was done in two adjacent watersheds in the Northwestern highlands of Ethiopia. One of the watersheds is developed by soil and water conservation structures (stone bunds) in 2011 and the other one is without soil and water conservation structures. Spatial distribution of soil textures and other soil properties were determined in the field and in the laboratory and a soil map was derived. A land use map was evaluated based on satellite images and ground truth data. A Digital Elevation Model of the watershed was developed based on conventional terrestrial surveying using a total station. At the outlet of the watersheds weirs with cameras were installed to measure surface runoff. During each event runoff samples were collected and sediment concentration was analyzed. The objective of this study is 1) to assess the impact of stone bunds on runoff and erosion processes by using simulation models, and 2) to compare the performance of two soil erosion models in predicting the measurements. The selected erosion models were the Soil and Water Assessment Tool (SWAT) and the Geospatial Interface to the Water Erosion Prediction Project (GeoWEPP). The simulation models were calibrated/verified for the 2011-2013 periods and validated with 2014-2015 data. Results of this comparison will be presented.

Scoping of Flood Hazard Mapping Needs for Belknap County, New Hampshire

DTIC Science & Technology

2006-01-01

DEM Digital Elevation Model DFIRM Digital Flood Insurance Rate Map DOQ Digital Orthophoto Quadrangle DOQQ Digital Ortho Quarter Quadrangle DTM...Agriculture Imag- ery Program (NAIP) color Digital Orthophoto Quadrangles (DOQs)). Remote sensing, base map information, GIS data (for example, contour data...found on USGS topographic maps. More recently developed data were derived from digital orthophotos providing improved base map accuracy. NH GRANIT is

Geographic information systems and logistic regression for high-resolution malaria risk mapping in a rural settlement of the southern Brazilian Amazon.

PubMed

de Oliveira, Elaine Cristina; dos Santos, Emerson Soares; Zeilhofer, Peter; Souza-Santos, Reinaldo; Atanaka-Santos, Marina

2013-11-15

In Brazil, 99% of the cases of malaria are concentrated in the Amazon region, with high level of transmission. The objectives of the study were to use geographic information systems (GIS) analysis and logistic regression as a tool to identify and analyse the relative likelihood and its socio-environmental determinants of malaria infection in the Vale do Amanhecer rural settlement, Brazil. A GIS database of georeferenced malaria cases, recorded in 2005, and multiple explanatory data layers was built, based on a multispectral Landsat 5 TM image, digital map of the settlement blocks and a SRTM digital elevation model. Satellite imagery was used to map the spatial patterns of land use and cover (LUC) and to derive spectral indices of vegetation density (NDVI) and soil/vegetation humidity (VSHI). An Euclidian distance operator was applied to measure proximity of domiciles to potential mosquito breeding habitats and gold mining areas. The malaria risk model was generated by multiple logistic regression, in which environmental factors were considered as independent variables and the number of cases, binarized by a threshold value was the dependent variable. Out of a total of 336 cases of malaria, 133 positive slides were from inhabitants at Road 08, which corresponds to 37.60% of the notifications. The southern region of the settlement presented 276 cases and a greater number of domiciles in which more than ten cases/home were notified. From these, 102 (30.36%) cases were caused by Plasmodium falciparum and 174 (51.79%) cases by Plasmodium vivax. Malaria risk is the highest in the south of the settlement, associated with proximity to gold mining sites, intense land use, high levels of soil/vegetation humidity and low vegetation density. Mid-resolution, remote sensing data and GIS-derived distance measures can be successfully combined with digital maps of the housing location of (non-) infected inhabitants to predict relative likelihood of disease infection through the analysis by logistic regression. Obtained findings on the relation between malaria cases and environmental factors should be applied in the future for land use planning in rural settlements in the Southern Amazon to minimize risks of disease transmission.

Evaluation of GIS Technology in Assessing and Modeling Land Management Practices

NASA Technical Reports Server (NTRS)

Archer, F.; Coleman, T. L.; Manu, A.; Tadesse, W.; Liu, G.

1997-01-01

There is an increasing concern of land owners to protect and maintain healthy and sustainable agroecosystems through the implementation of best management practices (BMP). The objectives of this study were: (1) To develop and evaluate the use of a Geographic Information System (GIS) technology for enhancing field-scale management practices; (2) evaluate the use of 2-dimensional displays of the landscape and (3) define spatial classes of variables from interpretation of geostatistical parameters. Soil samples were collected to a depth of 2 m at 15 cm increments. Existing data from topographic, land use, and soil survey maps of the Winfred Thomas Agricultural Research Station were converted to digital format. Additional soils data which included texture, pH, and organic matter were also generated. The digitized parameters were used to create a multilayered field-scale GIS. Two dimensional (2-D) displays of the parameters were generated using the ARC/INFO software. The spatial distribution of the parameters evaluated in both fields were similar which could be attributed to the similarity in vegetation and surface elevation. The ratio of the nugget to total semivariance, expressed as a percentage, was used to assess the degree of spatial variability. The results indicated that most of the parameters were moderate spatially dependent Biophysical constraint maps were generated from the database layers, and used in multiple combination to visualize results of the BMP. Understanding the spatial relationships of physical and chemical parameters that exists within a field should enable land managers to more effectively implement BMP to ensure a safe and sustainable environment.

Mapping the Spectral and Biochemical Characteristics of Riparian Vegetation and Soils

NASA Astrophysics Data System (ADS)

Balaji Bhaskar, M. S.

2016-12-01

Salt cedar (Tamarix ramosissima), an invasive plant species, has successfully invaded large extents of several riparian zones along the western United States and northern Mexico. Mapping the distribution and abundance of Tamarix over these large areas through a, multi-seasonal, cost-effective monitoring approach using satellite remote sensing is very essential. Hence, the objectives of this study are: 1) to identify the spectral characteristics of the major riparian, agricultural vegetation types and soils in the Lower Colorado River (LCR) region; and 2) to determine the biochemical characteristics of the vegetation and soils. Ground truth surveys were conducted at 79 locations where the spectral reflectance measurements of vegetation, type of plant species, plant heights, soil samples and GPS co-ordinates were recorded. All the sampling was designed to coincide with the satellite overpass period. From the LANDSAT TM image, dark-object-subtracted (DOS) digital number (DN) values of six LANDSAT single bands (1-5 and 7) were extracted and all the spectral ratios and vegetative indices were calculated. The NDVI, R1,5 and R1,7 were identified as the best ratios to distinguish the major vegetation types. The LANDSAT TM color-composite spectral ratio image (NDVI, R1,5 and R1,7 as GBR) can clearly identify and map the areas infested with Tamarix. The salt cedar infested riparian soils showed high concentrations of Ca, Mg and Na concentrations compared to other soils and the spectral reflectance of soils with high Na concentrations were significantly higher in the 350-2500 nm spectral range compared to other soils. The Leaf Area Index (LAI) data shows that the salt cedar has higher LAI compared to other riparian vegetation. The spectral and satellite image analysis shows that the selected spectral ratios can be applied to multiple satellite overpasses for monitoring the seasonal progression of the riparian growth over time. Extending the image analysis over wider areas of western United States can improve the understanding of the riparian dynamics in this region.

Utilisation of Indian Remote Sensing Satellite (IRS) data for assessment of soil erosion process of a watershed in Chhotanagpur plateau region, India

NASA Astrophysics Data System (ADS)

Pramod Krishna, Akhouri

A watershed in Chhotanagpur plateau region was investigated utilizing space data from Indian Remote Sensing (IRS) Satellite towards spatial and temporal soil erosion process study. Geomorphologically, this plateau region is an undulating pediplain. The watershed namely Potpoto river watershed covering an area of 8160 hectares is situated in the vicinity of Ranchi, capital city of newly created Jharkahnd state. As per the national watershed atlas, Potpoto river is a tributary of Subarnarekha river system within the Upper Subarnarekha river basin under watershed no. 4H3C8. This rural to semi-urban watershed is important towards various services to Ranchi city as well as experiencing direct or indirect pressures of development. Drivers of land use changes at ground level are responsible for change in soil erosion rates in any watershed in coupled human-environment systems. This may adversely affect the soil cover of such watersheds depicted through changed rates of erosion. In a rural to semi-urban watershed like this, there are general tendencies of land use and thereby land cover changes from forests to agricultural lands, within agricultural land in terms of cropping pattern changes to cash-crops, orchards, commercial plantations and conversions to other land use categories as well towards infrastructure expansions. Universal Soil Loss Equation (USLE) was used as a basis to observe the intensity of erosion using remote sensing, rainfall data, soil data and land use/land cover map. IRS1C LISSIII and IRSP6 LISSIII data were used to identify land use status for the years 1996 and 2004 respectively. LISSIII sensor provides data in the visible to near infrared (Bands 2, 3, 4) as well as short wave infrared (Band 5) range of electromagnetic spectrum. In this study, bands 2 (0.52-0.59 microns), 3 (0.62-0.68 microns) and 4 (0.77-0.86 microns) were used with spatial resolution of 23.5 meters at nadir. Digital image processing was carried out using ERDAS Imagine software. Based on maximum likelihood classifier, the study area was classified into suitable land use/land cover classes. Digital elevation model (DEM) was created through contour heights from topographic maps. Watershed based erosion estimation was carried out including assessment of soil erosion due to land use land cover changes. This provides predictive assessment capability in soil erosion studies particularly with methods such as USLE. Soil erosion problem varies largely depending upon climate, topography, soil and land use etc. Multi-factor computations on rainfall erosivity, soil erodibility, topographic, cover and management, and conservation practice were carried out. Quantified details on soil erosion rates were generated in terms of land use land cover classes of the watershed for the years 1996 and 2004. Annual average soil loss for the watershed was calculated and erosion intensity maps were generated. Thus, space data utilized from the satellites IRS1C LISSIII and IRSP6 LISSIII greatly helped in important research assessment of an important land surface process like soil erosion spatially as well as temporally for a watershed under pressures of development, land use changes and land cover fragmentations.

Mapping CO2 emission in highly urbanized region using standardized microbial respiration approach

NASA Astrophysics Data System (ADS)

Vasenev, V. I.; Stoorvogel, J. J.; Ananyeva, N. D.

2012-12-01

Urbanization is a major recent land-use change pathway. Land conversion to urban has a tremendous and still unclear effect on soil cover and functions. Urban soil can act as a carbon source, although its potential for CO2 emission is also very high. The main challenge in analysis and mapping soil organic carbon (SOC) in urban environment is its high spatial heterogeneity and temporal dynamics. The urban environment provides a number of specific features and processes that influence soil formation and functioning and results in a unique spatial variability of carbon stocks and fluxes at short distance. Soil sealing, functional zoning, settlement age and size are the predominant factors, distinguishing heterogeneity of urban soil carbon. The combination of these factors creates a great amount of contrast clusters with abrupt borders, which is very difficult to consider in regional assessment and mapping of SOC stocks and soil CO2 emission. Most of the existing approaches to measure CO2 emission in field conditions (eddy-covariance, soil chambers) are very sensitive to soil moisture and temperature conditions. They require long-term sampling set during the season in order to obtain relevant results. This makes them inapplicable for the analysis of CO2 emission spatial variability at the regional scale. Soil respiration (SR) measurement in standardized lab conditions enables to overcome this difficulty. SR is predominant outgoing carbon flux, including autotrophic respiration of plant roots and heterotrophic respiration of soil microorganisms. Microbiota is responsible for 50-80% of total soil carbon outflow. Microbial respiration (MR) approach provides an integral CO2 emission results, characterizing microbe CO2 production in optimal conditions and thus independent from initial difference in soil temperature and moisture. The current study aimed to combine digital soil mapping (DSM) techniques with standardized microbial respiration approach in order to analyse and map CO2 emission and its spatial variability in highly urbanized Moscow region. Moscow region with its variability of bioclimatic conditions and high urbanization level (10 % from the total area) was chosen as an interesting case study. Random soil sampling in different soil zones (4) and land-use types (3 non-urban and 3 urban) was organized in Moscow region in 2010-2011 (n=242). Both topsoil (0-10 cm) and subsoil (10-150 cm) were included. MR for each point was analysed using standardized microbial (basal) respiration approach, including the following stages: 1) air dried soil samples were moisturised up to 55% water content and preincubated (7 days, 22° C) in a plastic bag with air exchange; 2) soil MR (in μg CO2-C g-1) was measured as the rate of CO2 production (22° C, 24 h) after incubating 2g soil with 0.2 μl distilled water; 3) the MR results were used to estimate CO2 emission (kg C m-2 yr-1). Point MR and CO2 emission results obtained were extrapolated for the Moscow region area using regression model. As a result, two separate CO2 maps for topsoil and subsoil were created. High spatial variability was demonstrated especially for the urban areas. Thus standardized MR approach combined with DSM techniques provided a unique opportunity for spatial analysis of soil carbon temporal dynamics at the regional scale.

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.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

Or, D.; von Ruette, J.; Lehmann, P.

2017-12-01

Landslides and subsequent debris-flows initiated by rainfall represent a common natural hazard in mountainous regions. We integrated a landslide hydro-mechanical triggering model with a simple model for debris flow runout pathways and developed a graphical user interface (GUI) to represent these natural hazards at catchment scale at any location. The STEP-TRAMM GUI provides process-based estimates of the initiation locations and sizes of landslides patterns based on digital elevation models (SRTM) linked with high resolution global soil maps (SoilGrids 250 m resolution) and satellite based information on rainfall statistics for the selected region. In the preprocessing phase the STEP-TRAMM model estimates soil depth distribution to supplement other soil information for delineating key hydrological and mechanical properties relevant to representing local soil failure. We will illustrate this publicly available GUI and modeling platform to simulate effects of deforestation on landslide hazards in several regions and compare model outcome with satellite based information.

Designation of less favorable areas by the regionalization of soil degradation on various spatial scales

NASA Astrophysics Data System (ADS)

Pásztor, L.; Szabó, J.; Bakacsi, Zs.; Laborczi, A.

2009-04-01

One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in less favorable areas (LFA) in order (among others) to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. LFA assignment has both ecological and severe economical aspects. Delimitation of LFAs can be carried out by using biophysical diagnostic criteria on low soil productivity and poor climate conditions. Identification of low-productivity areas requires regionalization of soil functions related to food and other biomass production. This process can be carried out in different scales from national to local level, but always requires map-based pedological and further environmental information with appropriate spatial resolution. For the regionalization of less productive areas in national scale a functional approach was used which integrates the knowledge on soil degradation processes in nationwide level. Specific soil threats were classified into ranked categories. Supposing (quasi)uniform distribution of vulnerability measure along these classes, we introduced a "standardized" value as a ratio of the class order to the maximum class order expressed in percentage. For the overall spatial characterization of degradation status, spatial information was integrated in a result map by summarizing the degradation specific "standardized" cell values. This map in one hand has been used for the delineation of soil degradation regions. On the other hand appropriate spatial aggregation of index values on geographical and administrative regions is suitable for their quantitative comparison thus they can be ranked and this feature can be used for the identification of less favorable areas. At the more detailed, county level the Digital Kreybig Soil Information System was used as a tool of the regionalization of soil functions related to soil productivity. Concurrent spatial analysis of the suitability of soils for agricultural use and their sensitivity to physical and chemical degradation were carried out which resulted in a so-called ecotype-based characterization of land. As a spin-off, this classification was used for the designation of low productive areas suitable for hypogenous and cap fungi plantations as landuse alternative for croplands.

Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

NASA Astrophysics Data System (ADS)

Chang, C. H.; Chan, H. C.; Chen, B. A.

2016-12-01

Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.

Ch'ol nomenclature for soil classification in the ejido Oxolotán, Tacotalpa, Tabasco, México.

PubMed

Sánchez-Hernández, Rufo; Méndez-De la Cruz, Lucero; Palma-López, David J; Bautista-Zuñiga, Francisco

2018-05-30

The traditional ecological knowledge of land of the Ch'ol originary people from southeast Mexico forms part of their cultural identity; it is local and holistic and implies an integrated physical and spiritual worldview that contributes to improve their living conditions. We analyzed the nomenclature for soil classification used in the Mexican state of Tabasco by the Ch'ol farmers with the objective of contributing to the knowledge of the Maya soil classification. A map of the study area was generated from the digital database of parcels in the ejido Oxolotán in the municipality of Tacotalpa, to which a geopedological map was overlaid in order to obtain modeled topographic profiles (Zavala-Cruz et al., Ecosistemas y Recursos Agropecuarios 3:161-171, 2016). In each modeled profile, a soil profile was made and classified according to IUSS Working Group WRB (181, 2014) in order to generate a map of soil groups, which was used to survey the study area with the participation of 245 local Ch'ol farmers for establishing an ethnopedological soil classification (Ortiz et al.: 62, 1990). In addition, we organized a participatory workshop with 35 people to know details of the names of the soils and their indicators of fertility and workability, from which we selected 15 participants for field trips and description of soil profiles. The color, texture, and stoniness are attributes important in the Ch'ol nomenclature, although the names do not completely reflect the visible characteristic of the soil surface. On the other hand, the mere presence of stones is sufficient to name a land class, while according to IUSS Working Group WRB (181, 2014), a certain amount and distribution of stones in the soil profiles is necessary to be taken into consideration in the name. Perception of soil quality by local farmers considers the compaction or hardness of the cultivable soil layer, because of which black or sandy soils are perceived as better for cultivation of banana, or as secondary vegetation in fallow. Red, yellow, or brown soils are seen as of less quality and are only used for establishing grasslands, while maize is cultivated in all soil classes. Farmers provided the Ch'ol nomenclature, perceived problems, and uses of each class of soil. Translation of Ch'ol soil names and comparison with descriptions of soil profiles revealed that the Ch'ol soil nomenclature takes into account the soil profile, given it is based on characteristics of both surface and subsurface horizons including color of soil matrix and mottles, stoniness, texture, and vegetation.

Spatial prediction of Soil Organic Carbon contents in croplands, grasslands and forests using environmental covariates and Generalized Additive Models (Southern Belgium)

NASA Astrophysics Data System (ADS)

Chartin, Caroline; Stevens, Antoine; van Wesemael, Bas

2015-04-01

Providing spatially continuous Soil Organic Carbon data (SOC) is needed to support decisions regarding soil management, and inform the political debate with quantified estimates of the status and change of the soil resource. Digital Soil Mapping techniques are based on relations existing between a soil parameter (measured at different locations in space at a defined period) and relevant covariates (spatially continuous data) that are factors controlling soil formation and explaining the spatial variability of the target variable. This study aimed at apply DSM techniques to recent SOC content measurements (2005-2013) in three different landuses, i.e. cropland, grassland, and forest, in the Walloon region (Southern Belgium). For this purpose, SOC databases of two regional Soil Monitoring Networks (CARBOSOL for croplands and grasslands, and IPRFW for forests) were first harmonized, totalising about 1,220 observations. Median values of SOC content for croplands, grasslands, and forests, are respectively of 12.8, 29.0, and 43.1 g C kg-1. Then, a set of spatial layers were prepared with a resolution of 40 meters and with the same grid topology, containing environmental covariates such as, landuses, Digital Elevation Model and its derivatives, soil texture, C factor, carbon inputs by manure, and climate. Here, in addition to the three classical texture classes (clays, silt, and sand), we tested the use of clays + fine silt content (particles < 20 µm and related to stable carbon fraction) as soil covariate explaining SOC variations. For each of the three land uses (cropland, grassland and forest), a Generalized Additive Model (GAM) was calibrated on two thirds of respective dataset. The remaining samples were assigned to a test set to assess model performance. A backward stepwise procedure was followed to select the relevant environmental covariates using their approximate p-values (the level of significance was set at p < 0.05). Standard errors were estimated for each of the three models. The backward stepwise procedure selected coordinates, elevation and clays + fine silt content as environment covariates to model SOC variation in cropland soils; latitude, precipitation, and clays + fine silt content (< 20 µm) for grassland soils; and latitude, elevation, topographic position index and clays + fine silt content (< 20 µm) for forest soils. The validation of the models gave a R² of 0.62 for croplands, 0.38 for grasslands, and 0.35 for forests. These results will be developed and discussed based on implications of natural against anthropogenic drivers on SOC distribution for these three landuses. To finish, a map combining detailed information of SOC content for agricultural soils and forests was for the first time computed for the Walloon region.

Multi-discipline resource inventory of soils, vegetation and geology

NASA Technical Reports Server (NTRS)

Simonson, G. H. (Principal Investigator); Paine, D. P.; Lawrence, R. D.; Norgren, J. A.; Pyott, W. Y.; Herzog, J. H.; Murray, R. J.; Rogers, R.

1973-01-01

The author has identified the following significant results. Computer classification of natural vegetation, in the vicinity of Big Summit Prairie, Crook County, Oregon was carried out using MSS digital data. Impure training sets, representing eleven vegetation types plus water, were selected from within the area to be classified. Close correlations were visually observed between vegetation types mapped from the large scale photographs and the computer classification of the ERTS data (Frame 1021-18151, 13 August 1972).

Integration of land-use data and soil survey data

NASA Technical Reports Server (NTRS)

Cox, T. L.

1977-01-01

Approaches are discussed for increasing the utility of remotely sensed interpretations through the use of a computer-assisted process which provides capabilities for merging several types of data of varying formats. The resulting maps and summary data are used for planning and zoning in a rapidly developing area (34,000 ha) adjacent to the Black Hills in South Dakota. Attention is given to the data source, data digitization, and aspects of data handling and analysis.

Soil Erosion map of Europe based on high resolution input datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Ballabio, Cristiano; Alewell, Christine

2015-04-01

Modelling soil erosion in European Union is of major importance for agro-environmental policies. Soil erosion estimates are important inputs for the Common Agricultural Policy (CAP) and the implementation of the Soil Thematic Strategy. Using the findings of a recent pan-European data collection through the EIONET network, it was concluded that most Member States are applying the empirical Revised Universal Soil Loss Equation (RUSLE) for the modelling soil erosion at National level. This model was chosen for the pan-European soil erosion risk assessment and it is based on 6 input factors. Compared to past approaches, each of the factors is modelled using the latest pan-European datasets, expertise and data from Member states and high resolution remote sensing data. The soil erodibility (K-factor) is modelled using the recently published LUCAS topsoil database with 20,000 point measurements and incorporating the surface stone cover which can reduce K-factor by 15%. The rainfall erosivity dataset (R-factor) has been implemented using high temporal resolution rainfall data from more than 1,500 precipitation stations well distributed in Europe. The cover-management (C-factor) incorporates crop statistics and management practices such as cover crops, tillage practices and plant residuals. The slope length and steepness (combined LS-factor) is based on the first ever 25m Digital Elevation Model (DEM) of Europe. Finally, the support practices (P-factor) is modelled for first time at this scale taking into account the 270,000 LUCAS earth observations and the Good Agricultural and Environmental Condition (GAEC) that farmers have to follow in Europe. The high resolution input layers produce the final soil erosion risk map at 100m resolution and allow policy makers to run future land use, management and climate change scenarios.

The status of soil mapping for the Idaho National Engineering Laboratory

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

Olson, G.L.; Lee, R.D.; Jeppesen, D.J.

This report discusses the production of a revised version of the general soil map of the 2304-km{sup 2} (890-mi{sup 2}) Idaho National Engineering Laboratory (INEL) site in southeastern Idaho and the production of a geographic information system (GIS) soil map and supporting database. The revised general soil map replaces an INEL soil map produced in 1978 and incorporates the most current information on INEL soils. The general soil map delineates large soil associations based on National Resources Conservation Services [formerly the Soil Conservation Service (SCS)] principles of soil mapping. The GIS map incorporates detailed information that could not be presentedmore » on the general soil map and is linked to a database that contains the soil map unit descriptions, surficial geology codes, and other pertinent information.« less

Feasibility study for locating archaeological village sites by satellite remote sensing techniques. [multispectral photography of Alaska

NASA Technical Reports Server (NTRS)

Cook, J. P. (Principal Investigator); Stringer, W. J.

1974-01-01

The author has identified the following significant results. The objective is to determine the feasibility of detecting large Alaskan archaeological sites by satellite remote sensing techniques and mapping such sites. The approach used is to develop digital multispectral signatures of dominant surface features including vegetation, exposed soils and rock, hydrological patterns and known archaeological sites. ERTS-1 scenes are then printed out digitally in a map-like array with a letter reflecting the most appropriate classification representing each pixel. Preliminary signatures were developed and tested. It was determined that there was a need to tighten up the archaeological site signature by developing accurate signatures for all naturally-occurring vegetation and surface conditions in the vicinity of the test area. These second generation signatures have been tested by means of computer printouts and classified tape displays on the University of Alaska CDU-200 and by comparison with aerial photography. It has been concluded that the archaeological signatures now in use are as good as can be developed. Plans are to print out signatures for the entire test area and locate on topographic maps the likely locations of archaeological sites within the test area.

A Brief History of Soil Mapping and Classification in the USA

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Hartemink, Alfred E.

2014-05-01

Soil maps show the distribution of soils across an area but also depict soil science theory and ideas on soil formation and classification at the time the maps were created. The national soil mapping program in the USA was established in 1899. The first nation-wide soil map was published by M. Whitney in 1909 and showed soil provinces that were largely based on geology. In 1912, G.N. Coffey published the first country-wide map based on soil properties. The map showed 5 broad soil units that used parent material, color and drainage as diagnostic criteria. The 1913 national map was produced by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham and showed broad physiographic units that were further subdivided into soil series, soil classes and soil types. In 1935, Marbut drafted a series of maps based on soil properties, but these maps were replaced as official U.S. soil maps in 1938 with the work of M. Baldwin, C.E. Kellogg, and J. Thorp. A series of soil maps similar to modern USA maps appeared in the 1960s with the 7th Approximation followed by revisions with the 1975 and 1999 editions of Soil Taxonomy. This review has shown that soil maps in the United States produced since the early 1900s moved initially from a geologic-based concept to a pedologic concept of soils. Later changes were from property-based systems to process-based, and then back to property-based. The information in this presentation is based on Brevik and Hartemink (2013). Brevik, E.C., and A.E. Hartemink. 2013. Soil Maps of the United States of America. Soil Science Society of America Journal 77:1117-1132. doi:10.2136/sssaj2012.0390.

Aquifer sensitivity to pesticide leaching: Testing a soils and hydrogeologic index method

USGS Publications Warehouse

Mehnert, E.; Keefer, D.A.; Dey, W.S.; Wehrmann, H.A.; Wilson, S.D.; Ray, C.

2005-01-01

For years, researchers have sought index and other methods to predict aquifer sensitivity and vulnerability to nonpoint pesticide contamination. In 1995, an index method and map were developed to define aquifer sensitivity to pesticide leaching based on a combination of soil and hydrogeologic factors. The soil factor incorporated three soil properties: hydraulic conductivity, amount of organic matter within individual soil layers, and drainage class. These properties were obtained from a digital soil association map. The hydrogeologic factor was depth to uppermost aquifer material. To test this index method, a shallow ground water monitoring well network was designed, installed, and sampled in Illinois. The monitoring wells had a median depth of 7.6 m and were located adjacent to corn and soybean fields where the only known sources of pesticides were those used in normal agricultural production. From September 1998 through February 2001, 159 monitoring wells were sampled for 14 pesticides but no pesticide metabolites. Samples were collected and analyzed to assess the distribution of pesticide occurrence across three units of aquifer sensitivity. Pesticides were detected in 18% of all samples and nearly uniformly from samples from the three units of aquifer sensitivity. The new index method did not predict pesticide occurrence because occurrence was not dependent on the combined soil and hydrogeologic factors. However, pesticide occurrence was dependent on the tested hydrogeologic factor and was three times higher in areas where the depth to the uppermost aquifer was <6 m than in areas where the depth to the uppermost aquifer was 6 to <15 m. Copyright ?? 2005 National Ground Water Association.

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.

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.

Use of carborne measured gamma-ray K/Th ratio for estimation of texture at different field sites across Europe

NASA Astrophysics Data System (ADS)

Dierke, C.; Werban, U.; Dietrich, P.

2011-12-01

In the past gamma-ray measurements were used for geological survey from aircraft and in borehole logging for deposit exploration and geological survey. For these applications the relationships between the physical measured parameter - the concentration of natural gamma emitter 40K, 238U and 232Th - and geological origin or sedimentary developments are described well. Based on these applications and knowledge in combination with adjusted sensor systems, gamma-ray measurements seem to be also a useful and fast tool for soil characterization. The measured isotope concentration in soils depends on different soil parameters, which are the result of composition and properties of parent rock and processes during soil geneses under different climatic conditions. Grain size distribution, type of clay minerals and organic matter are soil parameters which influence the gamma-ray concentration directly. Many applications of gamma-ray measurements for soil characterisation and digital soil mapping (DSM) are known from e.g. Australia and during the last years there are attempts to use that method in Europe as well. One main influencing factor for nuclide concentration in soils is the grain size. Megumi (1977) found with decreasing particle size an increase in nuclide concentration, which can be explained by higher specific surface and resulting higher surface adsorption for smaller particles. We did systematic measurements at different field sites across Central Europe to investigate the relationship between concentration of gamma emitter and the grain size distribution of top soil. For the measurements we choose field sites with different pedogenesis and range in clay content. For survey we used a 4l NaI(Tl) detector, which is mounted on a sledge an can be towed by a four-wheel-vehicle across the agricultural used field sites. The measured nuclide concentrations were compared with grain size distribution data of fine soil (< 2 mm). For interpretation we used single nuclide concentrations as well as K/Th ratios. The results show site specific relationships depending on pedogenesis and geological background. With this knowledge it is possible to develop a more regional approach for γ-ray interpretation. Our studies are a basis to enhance physical understanding of the measured data at landscape scale across Europe. These activities are done within the iSOIL project. iSOIL- Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment; iSOIL is one member of the SOIL TECHNOLOGY CLUSTER of Research Projects funded by the EC. Megumi, K. and T. Mamuro (1977). "Concentration Of Uranium Series Nuclides In Soil Particles In Relation To Their Size." Journal Of Geophysical Research 82(2): 353-356.

Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

2016-04-01

Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under different hydrologic conditions and the factors controlling the temporal variability of the ECa-soil moisture relationship. The approach provided valuable insight into the time-varying contribution of local and nonlocal factors to the characteristic spatial patterns of soil moisture and the transition mechanisms. The spatial organization of soil moisture was controlled by different processes in different soil horizons, and the topsoil's moisture did not mirror processes that take place within the soil profile. Results show that, for the Schäfertal hillslope site which is presumed to be representative for non-intensively managed soils with moderate clay content, local soil properties (e.g., soil texture and porosity) are the major control on the spatial pattern of ECa. In contrast, the ECa-soil moisture relationship is small and varies over time indicating that ECa is not a good proxy for soil moisture estimation at the investigated site.Occasionally observed stronger correlations between ECa and soil moisture may be explained by background dependencies of ECa to other state variables such as pore water electrical conductivity. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales, and to transfer observation concepts and process understanding to larger or less instrumented sites, as well as to constrain the use of EMI-based ECa data for hydrological applications.

Semiannual progress report, April - September 1991

NASA Technical Reports Server (NTRS)

1991-01-01

Research conducted during the past year in the climate and modeling programs has concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three dimensional global climate model, and an upper ocean model. Principal applications have been the study of the impact of CO2, aerosols, and the solar constant on climate. Progress was made in the 3-D model development towards physically realistic treatment of these processes. In particular, a map of soil classifications on 1 degree by 1 degree resolution has now been digitized, and soil properties have been assigned to each soil type. Using this information about soil properties, a method has been developed to simulate the hydraulic behavior of the soils of the world. This improved treatment of soil hydrology, together with the seasonally varying vegetation cover, will provide a more realistic study of the role of the terrestrial biota in climate change. A new version of the climate model was created which follows the isotopes of water and sources of water throughout the planet.

Land cover mapping of the upper Kuskokwim Resource Managment Area using LANDSAT and a digital data base approach

USGS Publications Warehouse

Markon, Carl J.

1988-01-01

Digital land cover and terrain data for the Upper Kuskokwim Resource Hanagement Area (UKRMA) were produced by the U.S. Geological Survey, Earth Resources Observation Systems Field Office, Anchorage, Alaska for the Bureau of Land Management. These and other environmental data, were incorporated into a digital data base to assist in the management and planning of the UKRMA. The digital data base includes land cover classifications, elevation, slope, and aspect data centering on the UKRMA boundaries. The data are stored on computer compatible tapes at a 50-m pixel size. Additional digital data in the data base include: (a) summer and winter Landsat multispectral scanner (MSS) data registered to a 50-m Universal Transverse Mercator grid; (b) elevation, slope, aspect, and solar illumination data; (c) soils and surficial geology; and (e) study area boundary. The classification of Landsat MSS data resulted in seven major classes and 24 subclasses. Major classes include: forest, shrubland, dwarf scrub, herbaceous, barren, water, and other. The final data base will be used by resource personnel for management and planning within the UKRMA.

Application of GIS-based Procedure on Slopeland Use Classification and Identification

NASA Astrophysics Data System (ADS)

KU, L. C.; LI, M. C.

2016-12-01

In Taiwan, the "Slopeland Conservation and Utilization Act" regulates the management of the slopelands. It categorizes the slopeland into land suitable for agricultural or animal husbandry, land suitable for forestry and land for enhanced conservation, according to the environmental factors of average slope, effective soil depth, soil erosion and parental rock. Traditionally, investigations of environmental factors require cost-effective field works. It has been confronted with many practical issues such as non-evaluated cadastral parcels, evaluation results depending on expert's opinion, difficulties in field measurement and judgment, and time consuming. This study aimed to develop a GIS-based procedure involved in the acceleration of slopeland use classification and quality improvement. First, the environmental factors of slopelands were analyzed by GIS and SPSS software. The analysis involved with the digital elevation model (DEM), soil depth map, land use map and satellite images. Second, 5% of the analyzed slopelands were selected to perform the site investigations and correct the results of classification. Finally, a 2nd examination was involved by randomly selected 2% of the analyzed slopelands to perform the accuracy evaluation. It was showed the developed procedure is effective in slopeland use classification and identification. Keywords: Slopeland Use Classification, GIS, Management

Digital geologic map of the Coeur d'Alene 1:100,000 quadrangle, Idaho and Montana

USGS Publications Warehouse

digital compilation by Munts, Steven R.

2000-01-01

Between 1961 and 1969, Alan Griggs and others conducted fieldwork to prepare a geologic map of the Spokane 1:250,000 map (Griggs, 1973). Their field observations were posted on paper copies of 15-minute quadrangle maps. In 1999, the USGS contracted with the Idaho Geological Survey to prepare a digital version of the Coeur d’Alene 1:100,000 quadrangle. To facilitate this work, the USGS obtained the field maps prepared by Griggs and others from the USGS Field Records Library in Denver, Colorado. The Idaho Geological Survey (IGS) digitized these maps and used them in their mapping program. The mapping focused on field checks to resolve problems in poorly known areas and in areas of disagreement between adjoining maps. The IGS is currently in the process of preparing a final digital spatial database for the Coeur d’Alene 1:100,000 quadrangle. However, there was immediate need for a digital version of the geologic map of the Coeur d’Alene 1:100,000 quadrangle and the data from the field sheets along with several other sources were assembled to produce this interim product. This interim product is the digital geologic map of the Coeur d’Alene 1:100,000 quadrangle, Idaho and Montana. It was compiled from the preliminary digital files prepared by the Idaho Geological, and supplemented by data from Griggs (1973) and from digital databases by Bookstrom and others (1999) and Derkey and others (1996). The resulting digital geologic map (GIS) database can be queried in many ways to produce a variety of geologic maps. Digital base map data files (topography, roads, towns, rivers and lakes, etc.) are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:100,000 (e.g., 1:62,500 or 1:24,000). The digital geologic map graphics (of00-135_map.pdf) that are provided are representations of the digital database. The map area is located in north Idaho. This open-file report describes the geologic map units, the methods used to convert the geologic map data into a digital format, the ArcInfo GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet.

Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

NASA Astrophysics Data System (ADS)

Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

1998-12-01

In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope, aspect, curvature, and specific catchment area. Finally remote sensing provided a means of assessing soil and crop conditions over large scales from the air, without excessive sampling on the ground. There are two objectives for this work. The first objective is to analyze the spatial variability of yield across a spectrum of scales to identify the spatial characteristics of yield variation; in essence, we are trying to answer the following questions, at what scale of management unit we should resolve the field level variability and what is the relationship between this resolution and the observed variability form a yield map? The second objective is to identify the soil and topographical attributes that control yield variation over the landscape topography. We already know that, because erosion and deposition are major processes in the formation of a catena, soil variations occur in response to surface and subsurface flow over the landscape. Also landscape positions corresponding to low elevation tend to have high catchment area which usually results in high soil water content in the root zone and thick A horizon. Can topographical attributes explain yield variation observed in the landscape? Will topographical attributes extracted from a DEM compensate for the relatively poor spatial resolution from a soil survey?

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

A stratified two-stage sampling design for digital soil mapping in a Mediterranean basin

NASA Astrophysics Data System (ADS)

Blaschek, Michael; Duttmann, Rainer

2015-04-01

The quality of environmental modelling results often depends on reliable soil information. In order to obtain soil data in an efficient manner, several sampling strategies are at hand depending on the level of prior knowledge and the overall objective of the planned survey. This study focuses on the collection of soil samples considering available continuous secondary information in an undulating, 16 km²-sized river catchment near Ussana in southern Sardinia (Italy). A design-based, stratified, two-stage sampling design has been applied aiming at the spatial prediction of soil property values at individual locations. The stratification based on quantiles from density functions of two land-surface parameters - topographic wetness index and potential incoming solar radiation - derived from a digital elevation model. Combined with four main geological units, the applied procedure led to 30 different classes in the given test site. Up to six polygons of each available class were selected randomly excluding those areas smaller than 1ha to avoid incorrect location of the points in the field. Further exclusion rules were applied before polygon selection masking out roads and buildings using a 20m buffer. The selection procedure was repeated ten times and the set of polygons with the best geographical spread were chosen. Finally, exact point locations were selected randomly from inside the chosen polygon features. A second selection based on the same stratification and following the same methodology (selecting one polygon instead of six) was made in order to create an appropriate validation set. Supplementary samples were obtained during a second survey focusing on polygons that have either not been considered during the first phase at all or were not adequately represented with respect to feature size. In total, both field campaigns produced an interpolation set of 156 samples and a validation set of 41 points. The selection of sample point locations has been done using ESRI software (ArcGIS) extended by Hawth's Tools and later on its replacement the Geospatial Modelling Environment (GME). 88% of all desired points could actually be reached in the field and have been successfully sampled. Our results indicate that the sampled calibration and validation sets are representative for each other and could be successfully used as interpolation data for spatial prediction purposes. With respect to soil textural fractions, for instance, equal multivariate means and variance homogeneity were found for the two datasets as evidenced by significant (P > 0.05) Hotelling T²-test (2.3 with df1 = 3, df2 = 193) and Bartlett's test statistics (6.4 with df = 6). The multivariate prediction of clay, silt and sand content using a neural network residual cokriging approach reached an explained variance level of 56%, 47% and 63%. Thus, the presented case study is a successful example of considering readily available continuous information on soil forming factors such as geology and relief as stratifying variables for designing sampling schemes in digital soil mapping projects.

An interactive method for digitizing zone maps

NASA Technical Reports Server (NTRS)

Giddings, L. E.; Thompson, E. J.

1975-01-01

A method is presented for digitizing maps that consist of zones, such as contour or climatic zone maps. A color-coded map is prepared by any convenient process. The map is then read into memory of an Image 100 computer by means of its table scanner, using colored filters. Zones are separated and stored in themes, using standard classification procedures. Thematic data are written on magnetic tape and these data, appropriately coded, are combined to make a digitized image on tape. Step-by-step procedures are given for digitization of crop moisture index maps with this procedure. In addition, a complete example of the digitization of a climatic zone map is given.

The Soil Spectroscopy Group and the development of a global soil spectral library

NASA Astrophysics Data System (ADS)

Rossel, R. Viscarra Rossel; Soil Spectroscopy Group

2009-04-01

This collaboration aims to develop a global soil spectral library and to establish a community of practice for soil spectroscopy. This will help progress soil spectroscopy from an almost purely research tool to a more widely adopted and useful technique for soil analysis, proximal soil sensing, soil monitoring and digital soil mapping. The initiative started in April 2008 with a proposal for the project to be conducted in a number of stages to investigate the following topics: Global soil diversity and variation can be characterised using diffuse reflectance spectra. Soil spectral calibrations can be used to predict soil properties globally. Soil spectroscopy can be a useful tool for digital soil mapping. Currently, the soil spectral library is being developed using legacy soil organic carbon (OC) and clay content data and vis-NIR (350-2500 nm) spectra, but in future we aim to include other soil properties and mid-IR (2500-25000 nm) spectra. The group already has more than 40 collaborators from six continents and 20 countries and the library consists of 5223 spectra from 43 countries. The library accounts for spectra from approximately only 22% of the world's countries, some of which are poorly represented with only very few spectra. We would like to encourage participation from as many countries as possible, particularly, we would like contributions from counties in Central and South America, Mexico, Canada, Russia and countries in Eastern Europe, Africa and Asia. We are missing a lot of countries and for some, e.g. China we have only very few data! Do you want to join the group and contribute spectra to the global library? The requirements for contributing spectra to the global library are as follows: Spectra collected in the 350-2500 nm range every 1 nm. At least soil OC and clay content data but also any other soil chemical, physical, biological and mineralogical data, noting which analytical techniques were used. Coordinates (in WGS84 format) for each sample. Soil classification for each sample, preferably using FAO-WRB (FAO, 1998). Future access to soil samples for mid-IR scanning. If you do not have all of the requested metadata for every sample, but would like to contribute to the library, please let us know. Also, if you do not have access to a spectrometer but have a good set of soils that you would like to contribute to the library, we can arrange to have the soils scanned at CSIRO in Australia or in a collaborating institution nearer to you. We have done this with a number of countries already. There are leading collaborators in each continent: Bo Stenberg in Europe, David Brown in USA, Alexandre Dematte in South America, Keith Shepherd in Africa, Eyal Ben-Dor in the Middle East and Asia and Raphael Viscarra Rossel in Oceania and Asia. To make this work we need participation from as many people around the world as possible. If you are interested in contributing spectra to the global library please send me an email (raphael.viscarra-rossel@csiro.au) and join the group!

Assessing the legacy effects of historic charcoal production in Brandenburg, Germany

NASA Astrophysics Data System (ADS)

Schneider, Anna; Hirsch, Florian; Raab, Alexandra; Bonhage, Alexander; Raab, Thomas

2017-04-01

Charcoal produced in kilns or hearths was an important source of energy in many regions of Europe and Northern America until the 19th century, and charcoal production in hearths is still common in many other regions of the world. The remains of charcoal hearths are therefore a widespread legacy of historic land use in forest areas. Soils on charcoal hearth sites are characterized by a technogenic layer rich in charcoal and ash on top of the soil profile, and by a pyrogenic modification of substrates below the former hearth. The aims of our study are to examine how these alterations to the natural soil profiles affect the soil water regime and other soil physical properties, and to assess the relevance of these effects on the landscape scale. We present first results of a mapping of hearth site occurrence in forest areas in the state of Brandenburg, Germany, and of a characterization of the infiltration behaviour on hearth sites as compared with undisturbed forest soils. Results of mapping small-scale relief features from LIDAR-based digital elevation models show that charcoal hearths occur in a high density in many large forest areas throughout Brandenburg. In the areas studied so far, up to almost 3% of the soil surface were found to be affected by the remains of historic hearths. First analyses of soil physical properties indicate differences in the infiltration characteristics of hearth site soils and undisturbed forest soils: Hood infiltrometer measurements show a very high spatial variability of hydraulic conductivity for hearth site soils, and water-drop-penetration-time tests reflect extremely high hydrophobicity of the technogenic layer on the sites. Results of dye tracer experiment show considerably strong preferential flow and therefore a higher spatial variability of soil wetness below the hearth remains. Overall, our first results therefore indicate that the legacy effects of historic charcoal production might significantly affect overall site conditions in forest areas with a high density of charcoal hearth remains.

Quantification of Plume-Soil Interaction and Excavation Due to the Sky Crane Descent Stage

NASA Technical Reports Server (NTRS)

Vizcaino, Jeffrey; Mehta, Manish

2015-01-01

The quantification of the particulate erosion that occurs as a result of a rocket exhaust plume impinging on soil during extraterrestrial landings is critical for future robotic and human lander mission design. The aerodynamic environment that results from the reflected plumes results in dust lifting, site alteration and saltation, all of which create a potentially erosive and contaminant heavy environment for the lander vehicle and any surrounding structures. The Mars Science Lab (MSL), weighing nearly one metric ton, required higher levels of thrust from its retro propulsive systems and an entirely new descent system to minimize these effects. In this work we seek to quantify plume soil interaction and its resultant soil erosion caused by the MSL's Sky Crane descent stage engines by performing three dimensional digital terrain and elevation mapping of the Curiosity rover's landing site. Analysis of plume soil interaction altitude and time was performed by detailed examination of the Mars Descent Imager (MARDI) still frames and reconstructed inertial measurement unit (IMU) sensor data. Results show initial plume soil interaction from the Sky Crane's eight engines began at ground elevations greater than 60 meters and more than 25 seconds before the rovers' touchdown event. During this time, viscous shear erosion (VSE) was dominant typically resulting in dusting of the surface with flow propagating nearly parallel to the surface. As the vehicle descended and decreased to four powered engines plume-plume and plume soil interaction increased the overall erosion rate at the surface. Visibility was greatly reduced at a height of roughly 20 meters above the surface and fell to zero ground visibility shortly after. The deployment phase of the Sky Crane descent stage hovering at nearly six meters above the surface showed the greatest amount of erosion with several large particles of soil being kicked up, recirculated, and impacting the bottom of the rover chassis. Image data obtained from MSL's navigation camera (NAVCAM) pairs on Sols 002, 003, and 016 were used to virtually recreate local surface topography and features around the rover by means of stereoscopic depth mapping. Images taken simultaneously by the left and right navigation cameras located on the rover's mast assembly spaced 42 centimeters were used to generate a three dimensional depth map from flat, two dimensional images of the same feature at slightly different angles. Image calibration with physical hardware on the rover and known terrain features were used to provide scaling information that accurately sizes features and regions of interest within the images. Digital terrain mapping analysis performed in this work describe the crater geometry (shape, radius, and depth), eroded volume, volumetric erosion rate, and estimated mass erosion rate of the Hepburn, Sleepy Dragon, Burnside, and Goulburn craters. Crater depths ranged from five to ten centimeters deep influencing an area as wide as two meters in some cases. The craters formed were highly asymmetrical and generally oblong primarily due to the underlying bedrock formations underneath the surface. Comparison with ground tests performed at the NASA AMES Planetary Aeolian Laboratory (PAL) by Mehta showed good agreement with volumetric erosion rates and crater sizes of large particle soil simulants, providing validation to Earth based ground tests of Martian regolith.

On the interpolation of volumetric water content in research catchments

NASA Astrophysics Data System (ADS)

Dlamini, Phesheya; Chaplot, Vincent

Digital Soil Mapping (DSM) is widely used in the environmental sciences because of its accuracy and efficiency in producing soil maps compared to the traditional soil mapping. Numerous studies have investigated how the sampling density and the interpolation process of data points affect the prediction quality. While, the interpolation process is straight forward for primary attributes such as soil gravimetric water content (θg) and soil bulk density (ρb), the DSM of volumetric water content (θv), the product of θg by ρb, may either involve direct interpolations of θv (approach 1) or independent interpolation of ρb and θg data points and subsequent multiplication of ρb and θg maps (approach 2). The main objective of this study was to compare the accuracy of these two mapping approaches for θv. A 23 ha grassland catchment in KwaZulu-Natal, South Africa was selected for this study. A total of 317 data points were randomly selected and sampled during the dry season in the topsoil (0-0.05 m) for θg by ρb estimation. Data points were interpolated following approaches 1 and 2, and using inverse distance weighting with 3 or 12 neighboring points (IDW3; IDW12), regular spline with tension (RST) and ordinary kriging (OK). Based on an independent validation set of 70 data points, OK was the best interpolator for ρb (mean absolute error, MAE of 0.081 g cm-3), while θg was best estimated using IDW12 (MAE = 1.697%) and θv by IDW3 (MAE = 1.814%). It was found that approach 1 underestimated θv. Approach 2 tended to overestimate θv, but reduced the prediction bias by an average of 37% and only improved the prediction accuracy by 1.3% compared to approach 1. Such a great benefit of approach 2 (i.e., the subsequent multiplication of interpolated maps of primary variables) was unexpected considering that a higher sampling density (∼14 data point ha-1 in the present study) tends to minimize the differences between interpolations techniques and approaches. In the context of much lower sampling densities, as generally encountered in environmental studies, one can thus expect approach 2 to yield significantly greater accuracy than approach 1. This approach 2 seems promising and can be further tested for DSM of other secondary variables.

City of Flagstaff Project: Ground Water Resource Evaluation, Remote Sensing Component

USGS Publications Warehouse

Chavez, Pat S.; Velasco, Miguel G.; Bowell, Jo-Ann; Sides, Stuart C.; Gonzalez, Rosendo R.; Soltesz, Deborah L.

1996-01-01

Many regions, cities, and towns in the Western United States need new or expanded water resources because of both population growth and increased development. Any tools or data that can help in the evaluation of an area's potential water resources must be considered for this increasingly critical need. Remotely sensed satellite images and subsequent digital image processing have been under-utilized in ground water resource evaluation and exploration. Satellite images can be helpful in detecting and mapping an area's regional structural patterns, including major fracture and fault systems, two important geologic settings for an area's surface to ground water relations. Within the United States Geological Survey's (USGS) Flagstaff Field Center, expertise and capabilities in remote sensing and digital image processing have been developed over the past 25 years through various programs. For the City of Flagstaff project, this expertise and these capabilities were combined with traditional geologic field mapping to help evaluate ground water resources in the Flagstaff area. Various enhancement and manipulation procedures were applied to the digital satellite images; the results, in both digital and hardcopy format, were used for field mapping and analyzing the regional structure. Relative to surface sampling, remotely sensed satellite and airborne images have improved spatial coverage that can help study, map, and monitor the earth surface at local and/or regional scales. Advantages offered by remotely sensed satellite image data include: 1. a synoptic/regional view compared to both aerial photographs and ground sampling, 2. cost effectiveness, 3. high spatial resolution and coverage compared to ground sampling, and 4. relatively high temporal coverage on a long term basis. Remotely sensed images contain both spectral and spatial information. The spectral information provides various properties and characteristics about the surface cover at a given location or pixel (that is, vegetation and/or soil type). The spatial information gives the distribution, variation, and topographic relief of the cover types from pixel to pixel. Therefore, the main characteristics that determine a pixel's brightness/reflectance and, consequently, the digital number (DN) assigned to the pixel, are the physical properties of the surface and near surface, the cover type, and the topographic slope. In this application, the ability to detect and map lineaments, especially those related to fractures and faults, is critical. Therefore, the extraction of spatial information from the digital images was of prime interest in this project. The spatial information varies among the different spectral bands available; in particular, a near infrared spectral band is better than a visible band when extracting spatial information in highly vegetated areas. In this study, both visible and near infrared bands were analyzed and used to extract the desired spatial information from the images. The wide swath coverage of remotely sensed satellite digital images makes them ideal for regional analysis and mapping. Since locating and mapping highly fractured and faulted areas is a major requirement for ground water resource evaluation and exploration this aspect of satellite images was considered critical; it allowed us to stand back (actually up about 440 miles), look at, and map the regional structural setting of the area. The main focus of the remote sensing and digital image processing component of this project was to use both remotely sensed digital satellite images and a Digital Elevation Model (DEM) to extract spatial information related to the structural and topographic patterns in the area. The data types used were digital satellite images collected by the United States' Landsat Thematic Mapper (TM) and French Systeme Probatoire d'Observation de laTerre (SPOT) imaging systems, along with a DEM of the Flagstaff region. The USGS Mini Image Processing Sy

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

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.

The Use of a Geographic Information System and Remote Sensing Technology for Monitoring Land Use and Soil Carbon Change in the Subtropical Dry Forest Life Zone of Puerto Rico

NASA Technical Reports Server (NTRS)

Velez-Rodriguez, Linda L. (Principal Investigator)

1996-01-01

Aerial photography, one of the first form of remote sensing technology, has long been an invaluable means to monitor activities and conditions at the Earth's surface. Geographic Information Systems or GIS is the use of computers in showing and manipulating spatial data. This report will present the use of geographic information systems and remote sensing technology for monitoring land use and soil carbon change in the subtropical dry forest life zone of Puerto Rico. This research included the south of Puerto Rico that belongs to the subtropical dry forest life zone. The Guanica Commonwealth Forest Biosphere Reserve and the Jobos Bay National Estuarine Research Reserve are studied in detail, because of their location in the subtropical dry forest life zone. Aerial photography, digital multispectral imagery, soil samples, soil survey maps, field inspections, and differential global positioning system (DGPS) observations were used.

A Field-Scale Sensor Network Data Set for Monitoring and Modeling the Spatial and Temporal Variation of Soil Water Content in a Dryland Agricultural Field

NASA Astrophysics Data System (ADS)

Gasch, C. K.; Brown, D. J.; Campbell, C. S.; Cobos, D. R.; Brooks, E. S.; Chahal, M.; Poggio, M.

2017-12-01

We describe a soil water content monitoring data set and auxiliary data collected at a 37 ha experimental no-till farm in the Northwestern United States. Water content measurements have been compiled hourly since 2007 by ECH2O-TE and 5TE sensors installed at 42 locations and five depths (0.3, 0.6, 0.9, 1.2, and 1.5 m, 210 sensors total) across the R.J. Cook Agronomy Farm, a Long-Term Agro-Ecosystem Research Site stationed on complex terrain in a Mediterranean climate. In addition to soil water content readings, the data set includes hourly and daily soil temperature readings, annual crop histories, a digital elevation model, Bt horizon maps, seasonal apparent electrical conductivity, soil texture, and soil bulk density. Meteorological records are also available for this location. We discuss the unique challenges of maintaining the network on an operating farm and demonstrate the nature and complexity of the soil water content data. This data set is accessible online through the National Agriculture Library, has been assigned a DOI, and will be maintained for the long term.

An assessment of gas emanation hazard using a geographic information system and geostatistics.

PubMed

Astorri, F; Beaubien, S E; Ciotoli, G; Lombardi, S

2002-03-01

This paper describes the use of geostatistical analysis and GIS techniques to assess gas emanation hazards. The Mt. Vulsini volcanic district was selected for this study because of the wide range of natural phenomena locally present that affect gas migration in the near surface. In addition, soil gas samples that were collected in this area should allow for a calibration between the generated risk/hazard models and the measured distribution of toxic gas species at surface. The approach used during this study consisted of three general stages. First data were digitally organized into thematic layers, then software functions in the GIS program "ArcView" were used to compare and correlate these various layers, and then finally the produced "potential-risk" map was compared with radon soil gas data in order to validate the model and/or to select zones for further, more-detailed soil gas investigations.

The MAP program: building the digital terrain model.

Treesearch

R.H. Twito; R.W. Mifflin; R.J. McGaughey

1987-01-01

PLANS, a software package for integrated timber-harvest planning, uses digital terrain models to provide the topographic data needed to fit harvest and transportation designs to specific terrain. MAP, an integral program in the PLANS package, is used to construct the digital terrain models required by PLANS. MAP establishes digital terrain models using digitizer-traced...

Soil color - a window for public and educators to understands soils

NASA Astrophysics Data System (ADS)

Libohova, Zamir; Beaudette, Dylan; Wills, Skye; Monger, Curtis; Lindbo, David

2017-04-01

Soil color is one of the most visually striking properties recorded by soil scientists around the world. Soil color is an important characteristic related to soil properties such organic matter, parent materials, drainage. It is a simplified way for the public and educators alike to understand soils and their functions. Soil color is a quick measurement that can be recorded by people using color charts or digital cameras, offering an opportunity for the citizen science projects to contribute to soil science. The US Soil Survey has recorded soil colors using Munsell color system for over 20,000 soil types representing a wide range of conditions throughout the Unites States. The objective of this research was to generate a US soil color map based on color descriptions from the Official Series Descriptions (OSDs). A color calculator developed in R and ArcMap were used to spatially display the soil colors. Soil colors showed vertical trends related to soil depth and horizontal trends related to parent material and climate. Soil colors represent development processes depending upon environment and time that have influenced their appearance and geographic distribution. Dark colors represent soils that are rich in organic matter, such as the soils of the Midwest USA, which are some of the most fertile soils in the world. These soils are relatively "young" in that they developed over the last 20,000 years in materials left behind after continental Glaciers retreated and reflect long- term prairie vegetation that dominated this area prior to European settlements. Dark soils of the Pacific Northwest reflect the influence of forests (and volcanic activity) but are shallower and less fertile than the deep dark Midwest soils. Soils of the eastern and southern Coastal Plains are older and are enriched with iron oxides ('rust') which gives them their red coloring. Soils of flood plains, like the broad Mississippi Valley, have multi-colored soils that reflect the process of flooding, scouring, depositions and standing water areas, providing a mosaic of process-driven colors. In the drier areas of the High Plains and Desert Southwest, soils are lighter in color and reflect the presence of sands like Nebraska Sand Hills or enrichment with light-colored carbonates and salts. The mountainous regions such as Appalachians, Ozarks etc., were predominantly red to brown due to higher clay content and older soils.

Integrated Digital Platform for the Valorization of a Cultural Landscape

NASA Astrophysics Data System (ADS)

Angheluţǎ, L. M.; Ratoiu, L.; Chelmus, A. I.; Rǎdvan, R.; Petculescu, A.

2017-05-01

This paper presents a newly started demonstrative project regarding the implementation and validation of an interdisciplinary research model for the Aluniş-Bozioru (Romania) cultural landscape, with the development of an online interactive digital product. This digital product would provide complementary data about the historical monuments and their environment, and also, constant updates and statistical comparison in order to generate an accurate evaluation of the state of conservation for this specific cultural landscape. Furthermore, the resulted information will contribute in the decision making process for the regional development policies. The project is developed by an interdisciplinary joint team of researchers consisted of technical scientists with great experience in advanced non-invasive characterization of the cultural heritage (NIRD for Optoelectronics - INOE 2000) and a group of experts from geology and biology (Romanian Academy's "Emil Racoviţǎ" Institute of Speleology - ISER). Resulted scientific data will include: 3D digital models of the selected historical monuments, microclimate monitoring, Ground Penetrating Radar survey, airborne LIDAR, multispectral and thermal imaging, soil and rock characterization, environmental studies. This digital product is constituted by an intuitive website with a database that allows data corroboration, visualization and comparison of the 3D digital models, as well as a digital mapping in the GIS system.

Lithology and aggregate quality attributes for the digital geologic map of Colorado

USGS Publications Warehouse

Knepper, Daniel H.; Green, Gregory N.; Langer, William H.

1999-01-01

This geologic map was prepared as a part of a study of digital methods and techniques as applied to complex geologic maps. The geologic map was digitized from the original scribe sheets used to prepare the published Geologic Map of Colorado (Tweto 1979). Consequently the digital version is at 1:500,000 scale using the Lambert Conformal Conic map projection parameters of the state base map. Stable base contact prints of the scribe sheets were scanned on a Tektronix 4991 digital scanner. The scanner automatically converts the scanned image to an ASCII vector format. These vectors were transferred to a VAX minicomputer, where they were then loaded into ARC/INFO. Each vector and polygon was given attributes derived from the original 1979 geologic map.

Map of surficial deposits and materials in the eastern and central United States (east of 102 degrees West longitude)

USGS Publications Warehouse

Fullerton, David S.; Bush, Charles A.; Pennell, Jean N.

2003-01-01

This data set contains surficial geologic units in the Eastern and Central United States, as well as a glacial limit line showing the position of maximum glacial advance during various geologic time periods. The geologic units represent surficial deposits and other surface materials that accumulated or formed during the past 2+ million years, such as soils, alluvium, and glacial deposits. These surface materials are referred to collectively by many geologists as regolith, the mantle of fragmented and generally unconsolidated material that overlies the bedrock foundation of a continent. This data set and the printed map produced from it, U.S. Geological Survey (USGS) Geologic Investigation Series I-2789, were based on 31 published maps in the USGS's Quaternary Geologic Atlas of the United States map series (USGS Miscellaneous Investigations Series I-1420). The data were compiled at 1:1,000,000 scale, to be viewed as a digital map at 1:2,000,000 nominal scale and to be printed as a conventional paper map at 1:2,500,000 scale.

Geomatics for Mapping of Groundwater Potential Zones in Northern Part of the United Arab Emiratis - Sharjah City

NASA Astrophysics Data System (ADS)

Al-Ruzouq, R.; Shanableh, A.; Merabtene, T.

2015-04-01

In United Arab Emirates (UAE) domestic water consumption has increased rapidly over the last decade. The increased demand for high-quality water, create an urgent need to evaluate the groundwater production of aquifers. The development of a reasonable model for groundwater potential is therefore crucial for future systematic developments, efficient management, and sustainable use of groundwater resources. The objective of this study is to map the groundwater potential zones in northern part of UAE and assess the contributing factors for exploration of potential groundwater resources. Remote sensing data and geographic information system will be used to locate potential zones for groundwater. Various maps (i.e., base, soil, geological, Hydro-geological, Geomorphologic Map, structural, drainage, slope, land use/land cover and average annual rainfall map) will be prepared based on geospatial techniques. The groundwater availability of the basin will qualitatively classified into different classes based on its hydro-geo-morphological conditions. The land use/land cover map will be also prepared for the different seasons using a digital classification technique with a ground truth based on field investigation.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

von Ruette, Jonas; Lehmann, Peter; Fan, Linfeng; Bickel, Samuel; Or, Dani

2017-04-01

Landslides and subsequent debris-flows initiated by rainfall represent a ubiquitous natural hazard in steep mountainous regions. We integrated a landslide hydro-mechanical triggering model and associated debris flow runout pathways with a graphical user interface (GUI) to represent these natural hazards in a wide range of catchments over the globe. The STEP-TRAMM GUI provides process-based locations and sizes of landslides patterns using digital elevation models (DEM) from SRTM database (30 m resolution) linked with soil maps from global database SoilGrids (250 m resolution) and satellite based information on rainfall statistics for the selected region. In a preprocessing step STEP-TRAMM models soil depth distribution and complements soil information that jointly capture key hydrological and mechanical properties relevant to local soil failure representation. In the presentation we will discuss feature of this publicly available platform and compare landslide and debris flow patterns for different regions considering representative intense rainfall events. Model outcomes will be compared for different spatial and temporal resolutions to test applicability of web-based information on elevation and rainfall for hazard assessment.

Citizen-Scientist Digitization of a Complex Geologic Map of the McDowell Mountains (Scottsdale, Arizona).

NASA Astrophysics Data System (ADS)

Gruber, D.; Skotnicki, S.; Gootee, B.

2016-12-01

The work of citizen scientists has become very important to researchers doing field work and internet-based projects but has not been widely utilized in digital mapping. The McDowell Mountains - located in Scottsdale, Arizona, at the edge of the basin-and-range province and protected as part of the McDowell Sonoran Preserve - are geologically complex. Until recently, no comprehensive geologic survey of the entire range had been done. Over the last 9 years geologist Steven Skotnicki spent 2000 hours mapping the complex geology of the range. His work, born of personal interest and partially supported by the McDowell Sonoran Conservancy, resulted in highly detailed hand-drawn survey maps. Dr. Skotnicki's work provides important new information and raises interesting research questions about the geology of this range. Citizen scientists of the McDowell Sonoran Conservancy Field Institute digitized Dr. Skotnicki's maps. A team of 10 volunteers, trained in ArcMap digitization techniques and led by volunteer project leader Daniel Gruber, performed the digitization work. Technical oversight of mapping using ArcMap, including provision of USGS-based mapping toolbars, was provided by Arizona Geological Survey (AZGS) research geologist Brian Gootee. The map digitization process identified and helped resolve a number of mapping questions. The citizen-scientist team spent 900 hours on training, digitization, quality checking, and project coordination with support and review by Skotnicki and Gootee. The resulting digital map has approximately 3000 polygons, 3000 points, and 86 map units with complete metadata and unit descriptions. The finished map is available online through AZGS and can be accessed in the field on mobile devices. User location is shown on the map and metadata can be viewed with a tap. The citizen scientist map digitization team has made this important geologic information available to the public and accessible to other researchers quickly and efficiently.

Geologic map and digital database of the Cougar Buttes 7.5' quadrangle, San Bernardino County, California

USGS Publications Warehouse

Powell, R.E.; Matti, J.C.; Cossette, P.M.

2000-01-01

The Southern California Areal Mapping Project (SCAMP) of Geologic Division has undertaken regional geologic mapping investigations in the Lucerne Valley area co-sponsored by the Mojave Water Agency and the San Bernardino National Forest. These investigations span the Lucerne Valley basin from the San Bernardino Mountains front northward to the basin axis on the Mojave Desert floor, and from the Rabbit Lake basin east to the Old Woman Springs area. Quadrangles mapped include the Cougar Buttes 7.5' quadrangle, the Lucerne Valley 7.5' quadrangle (Matti and others, in preparation b), the Fawnskin 7.5' quadrangle (Miller and others, 1998), and the Big Bear City 7.5' quadrangle (Matti and others, in preparation a). The Cougar Buttes quadrangle has been mapped previously at scales of 1:62,500 (Dibblee, 1964) and 1:24,000 (Shreve, 1958, 1968; Sadler, 1982a). In line with the goals of the National Cooperative Geologic Mapping Program (NCGMP), our mapping of the Cougar Buttes quadrangle has been directed toward generating a multipurpose digital geologic map database. Guided by the mapping of previous investigators, we have focused on improving our understanding and representation of late Pliocene and Quaternary deposits. In cooperation with the Water Resources Division of the U.S. Geological Survey, we have used our mapping in the Cougar Buttes and Lucerne Valley quadrangles together with well log data to construct cross-sections of the Lucerne Valley basin (R.E. Powell, unpublished data, 1996-1998) and to develop a hydrogeologic framework for the basin. Currently, our mapping in these two quadrangles also is being used as a base for studying soils on various Quaternary landscape surfaces on the San Bernardino piedmont (Eppes and others, 1998). In the Cougar Buttes quadrangle, we have endeavored to represent the surficial geology in a way that provides a base suitable for ecosystem assessment, an effort that has entailed differentiating surficial veneers on piedmont and pediment surfaces and distinguishing the various substrates found beneath these veneers.

The use of a GIS Red-Amber-Green (RAG) system to define search priorities for burials

NASA Astrophysics Data System (ADS)

Somma, Roberta; Silvestro, Massimiliano; Cascio, Maria; Dawson, Lorna; Donnelly, Laurance; Harrison, Mark; McKinley, Jennifer; Ruffell, Alastair

2016-04-01

The aim of this research is to promote among the Italian police, magistrates, and geologists, the applications of a Geographical Information System (GIS)-based RAG system for use in ground searches for burials. To date the RAG system has not been used and documented in Italy and would potentially be useful for searches related to clandestine burial sites. This technique, was originally documented by the British Army in the 1st World War. The RAG method is based on the construction of theme maps. RAG maps can facilitate the deployment of appropriate search assets (such as geophysics, probe or search dogs) and therefore applied to ground searches for the potential location of homicide graves or other buried objects (including weapons, explosives, etc.). RAG maps also may assist in the management of resources such as the deployment of search personnel, search teams and dogs. A GIS RAG (Red-Amber-Green) system related to a search for a homicide grave was applied to a test site in Italy, simulating the concealment of a victim in the area of Alì. This is an area of hill in Sicily, characterized by Palaeozoic phyllites. It was assumed during this test that information was provided by an observer who saw a suspect carrying tools on his land during daylight hours. A desktop study of the rural area was first implemented. Data was collated from previous geological, geomorphological, hydrogeological, geophysical and land use surveys. All these data were stored and independently analysed in a GIS using ArcGIS software. For the development of the GIS-based RAG map a digital elevation model (DEM) including a digital surface model (DTS) and digital terrain model (DTM) types were used. These were integrated with data from soil surveys to provide a preliminary assessment of "diggability" - including the possible thickness of loose superficial deposits and soils. Data were stored in different layers within the GIS. These included the delineation of the search area with consideration of access/exit points, diggability (easy: red, difficult: green), ground slope (<27°: red, >27°: green), vegetation type (easy access: red, difficult access: green), geomorphology (stable area: red, unstable area: green), anthropogenic structures (not present: red, present: green), visibility of the site from a potential eyewitnesses perspective (not visible: red, visible: green). Overlaying these layers, using the ArcGIS tools, enabled the RAG map to be composed with red showing the high priority search areas, amber the intermediate priority search areas and green the low priority search areas. The GIS-based RAG map of the simulated test-site allowed the original extent of the search area of 39.315m2, to be significantly reduced to 7.45% (2.930m2: extension red area) by desktop study and to 2.93% (1.152m2) with a further reconnaissance site visit. During subsequent field training conducted by forensic geology students at Messina University, the grave was found after 2 hours of searching, both using the RAG map and a soil probe and observing topographic disturbances. A subsidence of some centimeters and an anomalous growth of vegetation was found on the superficial surface of the grave (75cm deep).

Reducing the Dynamical Degradation by Bi-Coupling Digital Chaotic Maps

NASA Astrophysics Data System (ADS)

Liu, Lingfeng; Liu, Bocheng; Hu, Hanping; Miao, Suoxia

A chaotic map which is realized on a computer will suffer dynamical degradation. Here, a coupled chaotic model is proposed to reduce the dynamical degradation. In this model, the state variable of one digital chaotic map is used to control the parameter of the other digital map. This coupled model is universal and can be used for all chaotic maps. In this paper, two coupled models (one is coupled by two logistic maps, the other is coupled by Chebyshev map and Baker map) are performed, and the numerical experiments show that the performances of these two coupled chaotic maps are greatly improved. Furthermore, a simple pseudorandom bit generator (PRBG) based on coupled digital logistic maps is proposed as an application for our method.

Scoping of Flood Hazard Mapping Needs for Merrimack County, New Hampshire

DTIC Science & Technology

2006-01-01

DOQ Digital Orthophoto Quadrangle DOQQ Digital Ortho Quarter Quadrangle DTM Digital Terrain Model FBFM Flood Boundary and Floodway Map FEMA Federal...discussed available data and coverages within New Hampshire (for example, 2003 National Agriculture Imag- ery Program (NAIP) color Digital Orthophoto ... orthophotos providing improved base map accuracy. NH GRANIT is presently converting the standard, paper FIRMs and Flood Boundary and Floodway maps (FBFMs

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.

[Spatial variation of soil properties and quality evaluation for arable Ustic Cambosols in central Henan Province].

PubMed

Zhang, Xue-Lei; Feng, Wan-Wan; Zhong, Guo-Min

2011-01-01

A GIS-based 500 m x 500 m soil sampling point arrangement was set on 248 points at Wenshu Town of Yuzhou County in central Henan Province, where the typical Ustic Cambosols locates. By using soil digital data, the spatial database was established, from which, all the needed latitude and longitude data of the sampling points were produced for the field GPS guide. Soil samples (0-20 cm) were collected from 202 points, of which, bulk density measurement were conducted for randomly selected 34 points, and the ten soil property items used as the factors for soil quality assessment, including organic matter, available K, available P, pH, total N, total P, soil texture, cation exchange capacity (CEC), slowly available K, and bulk density, were analyzed for the other points. The soil property items were checked by statistic tools, and then, classified with standard criteria at home and abroad. The factor weight was given by analytic hierarchy process (AHP) method, and the spatial variation of the major 10 soil properties as well as the soil quality classes and their occupied areas were worked out by Kriging interpolation maps. The results showed that the arable Ustic Cambosols in study area was of good quality soil, over 95% of which ranked in good and medium classes and only less than 5% were in poor class.

Geologic exploration: The contribution of LANDSAT-4 thematic mapper data

NASA Technical Reports Server (NTRS)

Everett, J. R.; Dykstra, J. D.; Sheffield, C. A.

1983-01-01

The major advantages of the TM data over that of MSS systems are increased spatial resolution and a greater number of narrow, strategically placed spectral bands. The 30 meter pixel size permits finer definition of ground features and improves reliability of the photointerpretation of geologic structure. The value of the spatial data increases relative to the value of the spectral data as soil and vegetation cover increase. In arid areas with good exposure, it is possible with careful digital processing and some inventive color compositing to produce enough spectral differentiation of rock types and thereby produce facsimiles of standard geologic maps with a minimum of field work or reference to existing maps. Hue-saturation value images are compared with geological maps of Death Valley, California, the Big Horn/Wind River Basin of Wyoming, the area around Cement, Oklahoma, and Detroit. False color composites of the Ontario region are also examined.

American Society for Photogrammetry and Remote Sensing and ACSM, Fall Convention, Reno, NV, Oct. 4-9, 1987, ASPRS Technical Papers

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

Not Available

1987-01-01

Recent advances in remote-sensing technology and applications are examined in reviews and reports. Topics addressed include the use of Landsat TM data to assess suspended-sediment dispersion in a coastal lagoon, the use of sun incidence angle and IR reflectance levels in mapping old-growth coniferous forests, information-management systems, Large-Format-Camera soil mapping, and the economic potential of Landsat TM winter-wheat crop-condition assessment. Consideration is given to measurement of ephemeral gully erosion by airborne laser ranging, the creation of a multipurpose cadaster, high-resolution remote sensing and the news media, the role of vegetation in the global carbon cycle, PC applications in analytical photogrammetry,more » multispectral geological remote sensing of a suspected impact crater, fractional calculus in digital terrain modeling, and automated mapping using GP-based survey data.« less

Spatial digital database of the geologic map of Catalina Core Complex and San Pedro Trough, Pima, Pinal, Gila, Graham, and Cochise counties, Arizona

USGS Publications Warehouse

Dickinson, William R.; digital database by Hirschberg, Douglas M.; Pitts, G. Stephen; Bolm, Karen S.

2002-01-01

The geologic map of Catalina Core Complex and San Pedro Trough by Dickinson (1992) was digitized for input into a geographic information system (GIS) by the U.S. Geological Survey staff and contractors in 2000-2001. This digital geospatial database is one of many being created by the U.S. Geological Survey as an ongoing effort to provide geologic information in a geographic information system (GIS) for use in spatial analysis. The resulting digital geologic map database data can be queried in many ways to produce a variety of geologic maps and derivative products. Digital base map data (topography, roads, towns, rivers, lakes, and so forth) are not included; they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:125,000 (for example, 1:100,000 or 1:24,000). The digital geologic map plot files that are provided herein are representations of the database. The map area is located in southern Arizona. This report lists the geologic map units, the methods used to convert the geologic map data into a digital format, the ArcInfo GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. The manuscript and digital data review by Lorre Moyer (USGS) is greatly appreciated.

Remote Sensing Application to Land Use Classification in a Rapidly Changing Agricultural/Urban Area: City of Virginia Beach, Virginia. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Odenyo, V. A. O.

1975-01-01

Remote sensing data on computer-compatible tapes of LANDSAT 1 multispectral scanner imager were analyzed to generate a land use map of the City of Virginia Beach. All four bands were used in both the supervised and unsupervised approaches with the LAYSYS software system. Color IR imagery of a U-2 flight of the same area was also digitized and two sample areas were analyzed via the unsupervised approach. The relationships between the mapped land use and the soils of the area were investigated. A land use land cover map at a scale of 1:24,000 was obtained from the supervised analysis of LANDSAT 1 data. It was concluded that machine analysis of remote sensing data to produce land use maps was feasible; that the LAYSYS software system was usable for this purpose; and that the machine analysis was capable of extracting detailed information from the relatively small scale LANDSAT data in a much shorter time without compromising accuracy.

Application of cattle slurry containing Mycobacterium avium subsp. paratuberculosis (MAP) to grassland soil and its effect on the relationship between MAP and free-living amoeba.

PubMed

Salgado, M; Alfaro, M; Salazar, F; Badilla, X; Troncoso, E; Zambrano, A; González, M; Mitchell, R M; Collins, M T

2015-01-30

Slurry from dairy farms is commonly used to fertilize crops and pastures. This mixture of manure, urine and water can harbor multiple microbial pathogens among which Mycobacterium avium subsp. paratuberculosis (MAP) is a major concern. Persistence of MAP in soil and infection of soil Acanthamoeba was evaluated by culture, real-time IS900 PCR, and by staining of amoeba with acid-fast and vital stains comparing soils irrigated with MAP-spiked or control dairy farm slurry. MAP DNA was detected in soil for the 8 month study duration. MAP was detected by PCR from more soil samples for plots receiving MAP-spiked slurry (n=61/66) than from soils receiving control slurry (n=10/66 samples). Vital stains verified that intracellular MAP in amoeba was viable. More MAP was found in amoeba at the end of the study than immediately after slurry application. There was no relationship between MAP presence in soil and in amoeba over time. Infection of amoeba by MAP provides a protected niche for the persistence and even possibly the replication of MAP in soils. As others have suggested, MAP-infected amoeba may act like a "Trojan horse" providing a means for persistence in soils and potentially a source of infection for grazing animals. Copyright © 2014 Elsevier B.V. All rights reserved.

Preliminary geologic map of the Piru 7.5' quadrangle, southern California: a digital database

USGS Publications Warehouse

Yerkes, R.F.; Campbell, Russell H.

1995-01-01

This Open-File report is a digital geologic map database. This pamphlet serves to introduce and describe the digital data. There is no paper map included in the Open-File report. This digital map database is compiled from previously published sources combined with some new mapping and modifications in nomenclature. The geologic map database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U. S. Geological Survey. For detailed descriptions of the units, their stratigraphic relations and sources of geologic mapping consult Yerkes and Campbell (1995). More specific information about the units may be available in the original sources.

Geologic Map of the Utukok River Quadrangle, Alaska

USGS Publications Warehouse

Mull, Charles G.; Houseknecht, David W.; Pessel, G.H.; Garrity, Christopher P.

2006-01-01

This map is a product of the USGS Digital Geologic Maps of Northern Alaska project, which captures in digital format quadrangles across the entire width of northern Alaska. Sources include geologic maps previously published in hardcopy format and recent updates and revisions based on field mapping by the Alaska Department of Natural Resources, Division of Geological and Geophysical Surveys and Division of Oil and Gas, and the U.S. Geological Survey. Individual quadrangles are digitized at either 1:125,000 or 1:250,000 depending on the resolution of source maps. The project objective is to produce a set of digital geologic maps with uniform stratigraphic nomenclature and structural annotation, and publish those maps electronically.

Evaluation and comparison of ERTS measurements of major crops and soil associations for selected sites in the central United States

NASA Technical Reports Server (NTRS)

Baumgardner, M. F. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The most significant result was the use of the temporal overlay technique where the computer was used to overlay ERTS-1 data from three different dates (9 Oct., 14 Nov., 2 Dec.). The registration of MSS digital data from different dates was estimated to be accurate within one half resolution element. The temporal overlay capability provides a significant advance in machine-processing of MSS data. It is no longer essential to go through the tedious exercise of locating ground observation sites on the digital data from each ERTS-1 overpass. Once the address of a ground observation site has been located on a digital tape from any ERTS-1 overpass, the overlay technique can be used to locate the same address on a digital tape of MSS data from any other ERTS-1 pass over the same area. The temporal overlay technique also adds a valuable dimension for identifying and mapping changes in vegetation, water, and other dynamic surface features.

Benefit assessment of soil and water conservation from cropland to forest in hilly Loess Plateau at Qinghai.

PubMed

Zhao, Chuanchuan; Yang, Ninggui; Wang, Zhen; Liu, Sili; Dong, Xu; Xin, Wenrong

2013-01-01

The information of slope and vegetation coverage of the monitoring region were extracted, based on DEM (Digital Evaluation Model) and Spot5 Satellite data images, and fishnet grid was generated using GIS (Geographic Information System) and RS (Remote Sensing) technique. Applying the information of slop and vegetation coverage layers into the corresponding space grid by using the function of zonal statistics and analysis, it can realize overlay analysis based on Standards for Classification and Gradation of Soil Erosion (SL190-2007), and obtains the map of soil erosion intensity of the monitoring region. Finally, according to Specifications for Assessment of Forest Ecosystem Services (LY/T1721-2008) and monitoring data of typical plot, the soil and water conservation value from cropland to forest was evaluated quantitatively in 2009. The results showed that the area, on and below the moderate level, was 93600 ha, taking up 50.03% of total conversion of farmland to forest area (185100 ha), which indicates a 14.64 million (t/a) of soil conversion, and a 1520 million Yuan for erosion control. The results of the study showed that the soil and water conservation was very effective.

Soil maps as data input for soil erosion models: errors related to map scales

NASA Astrophysics Data System (ADS)

van Dijk, Paul; Sauter, Joëlle; Hofstetter, Elodie

2010-05-01

Soil erosion rates depend in many ways on soil and soil surface characteristics which vary in space and in time. To account for spatial variations of soil features, most distributed soil erosion models require data input derived from soil maps. Ideally, the level of spatial detail contained in the applied soil map should correspond to the objective of the modelling study. However, often the model user has only one soil map available which is then applied without questioning its suitability. The present study seeks to determine in how far soil map scale can be a source of error in erosion model output. The study was conducted on two different spatial scales, with for each of them a convenient soil erosion model: a) the catchment scale using the physically-based Limbourg Soil Erosion Model (LISEM), and b) the regional scale using the decision-tree expert model MESALES. The suitability of the applied soil map was evaluated with respect to an imaginary though realistic study objective for both models: the definition of erosion control measures at strategic locations at the catchment scale; the identification of target areas for the definition of control measures strategies at the regional scale. Two catchments were selected to test the sensitivity of LISEM to the spatial detail contained in soil maps: one catchment with relatively little contrast in soil texture, dominated by loess-derived soil (south of the Alsace), and one catchment with strongly contrasted soils at the limit between the Alsatian piedmont and the loess-covered hills of the Kochersberg. LISEM was run for both catchments using different soil maps ranging in scale from 1/25 000 to 1/100 000 to derive soil related input parameters. The comparison of the output differences was used to quantify the map scale impact on the quality of the model output. The sensitivity of MESALES was tested on the Haut-Rhin county for which two soil maps are available for comparison: 1/50 000 and 1/100 000. The order of resulting target areas (communes) was compared to evaluate the error induced by using the coarser soil data at 1/100 000. Results shows that both models are sensitive to the soil map scale used for model data input. A low sensitivity was found for the catchment with relatively homogeneous soil textures and the use of 1/100 000 soil maps seems allowed. The results for the catchment with strong soil texture variations showed significant differences depending on soil map scale on 75% of the catchment area. Here, the use of 1/100 000 soil map will indeed lead to wrong erosion diagnostics and will hamper the definition of a sound erosion control strategy. The regional scale model MESALES proved to be very sensitive to soil information. The two soil related model parameters (crusting sensitivity, and soil erodibility) reacted very often in the same direction therewith amplifying the change in the final erosion hazard class. The 1/100 000 soil map yielded different results on 40% of the sloping area compared to the 1/50 000 map. Significant differences in the order of target areas were found as well. The present study shows that the degree of sensitivity of the model output to soil map scale is rather variable and depends partly on the spatial variability of soil texture within the study area. Soil (textural) diversity needs to be accounted for to assure a fruitful use of soil erosion models. In some situations this might imply that additional soil data need to be collected in the field to refine the available soil map.

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps.

PubMed

Ibáñez, J J; Pérez-Gómez, R; Brevik, Eric C; Cerdà, A

2016-12-15

Many maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research indicates that comparing results of related maps (e.g., soil and geology maps) may aid in identifying mapping deficiencies. Therefore, this study was undertaken in Almeria Province, Spain to (i) compare the underlying map structures of soil and vegetation maps and (ii) investigate if a vegetation map can provide useful soil information that was not shown on a soil map. Soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis, and results then exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence: (i) climatophilous (ii) lithologic-climate; and (iii) edaphophylous. The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophilous units were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved. Copyright © 2016 Elsevier B.V. All rights reserved.

Coupling transfer function and GIS for assessing non-point-source groundwater vulnerability at regional scale

NASA Astrophysics Data System (ADS)

Coppola, A.; Comegna, V.; de Simone, L.

2009-04-01

Non-point source (NPS) pollution in the vadose zone is a global environmental problem. The knowledge and information required to address the problem of NPS pollutants in the vadose zone cross several technological and sub disciplinary lines: spatial statistics, geographic information systems (GIS), hydrology, soil science, and remote sensing. The main issues encountered by NPS groundwater vulnerability assessment, as discussed by Stewart [2001], are the large spatial scales, the complex processes that govern fluid flow and solute transport in the unsaturated zone, the absence of unsaturated zone measurements of diffuse pesticide concentrations in 3-D regional-scale space as these are difficult, time consuming, and prohibitively costly, and the computational effort required for solving the nonlinear equations for physically-based modeling of regional scale, heterogeneous applications. As an alternative solution, here is presented an approach that is based on coupling of transfer function and GIS modeling that: a) is capable of solute concentration estimation at a depth of interest within a known error confidence class; b) uses available soil survey, climatic, and irrigation information, and requires minimal computational cost for application; c) can dynamically support decision making through thematic mapping and 3D scenarios This result was pursued through 1) the design and building of a spatial database containing environmental and physical information regarding the study area, 2) the development of the transfer function procedure for layered soils, 3) the final representation of results through digital mapping and 3D visualization. One side GIS modeled environmental data in order to characterize, at regional scale, soil profile texture and depth, land use, climatic data, water table depth, potential evapotranspiration; on the other side such information was implemented in the up-scaling procedure of the Jury's TFM resulting in a set of texture based travel time probability density functions for layered soils each describing a characteristic leaching behavior for soil profiles with similar hydraulic properties. Such behavior, in terms of solute travel time to water table, was then imported back into GIS and finally estimation groundwater vulnerability for each soil unit was represented into a map as well as visualized in 3D.

Spatial digital database for the tectonic map of Southeast Arizona

USGS Publications Warehouse

map by Drewes, Harald; digital database by Fields, Robert A.; Hirschberg, Douglas M.; Bolm, Karen S.

2002-01-01

A spatial database was created for Drewes' (1980) tectonic map of southeast Arizona: this database supercedes Drewes and others (2001, ver. 1.0). Staff and a contractor at the U.S. Geological Survey in Tucson, Arizona completed an interim digital geologic map database for the east part of the map in 2001, made revisions to the previously released digital data for the west part of the map (Drewes and others, 2001, ver. 1.0), merged data files for the east and west parts, and added additional data not previously captured. Digital base map data files (such as topography, roads, towns, rivers and lakes) are not included: they may be obtained from a variety of commercial and government sources. This digital geospatial database is one of many being created by the U.S. Geological Survey as an ongoing effort to provide geologic information in a geographic information system (GIS) for use in spatial analysis. The resulting digital geologic map database can be queried in many ways to produce a variety of geologic maps and derivative products. Because Drewes' (1980) map sheets include additional text and graphics that were not included in this report, scanned images of his maps (i1109_e.jpg, i1109_w.jpg) are included as a courtesy to the reader. This database should not be used or displayed at any scale larger than 1:125,000 (for example, 1:100,000 or 1:24,000). The digital geologic map plot files (i1109_e.pdf and i1109_w.pdf) that are provided herein are representations of the database (see Appendix A). The map area is located in southeastern Arizona (fig. 1). This report describes the map units (from Drewes, 1980), the methods used to convert the geologic map data into a digital format, the ArcInfo GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. The manuscript and digital data review by Helen Kayser (Information Systems Support, Inc.) is greatly appreciated.

Using Vegetation Maps to Provide Information on Soil Distribution

NASA Astrophysics Data System (ADS)

José Ibáñez, Juan; Pérez-Gómez, Rufino; Brevik, Eric C.; Cerdà, Artemi

2016-04-01

Many different types of maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research has indicated that comparing the results of different but related maps (e.g., soil and geology maps) may aid in identifying deficiencies in those maps. Therefore, this study was undertaken in the Almería Province (Andalusia, Spain) to (i) compare the underlying map structures of soil and vegetation maps and (ii) to investigate if a vegetation map can provide useful soil information that was not shown on a soil map. To accomplish this soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis. Results of the spatial analysis were exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence (P/A): (i) climatophilous (climate is the only determinant of P/A) (ii); lithologic-climate (climate and parent material determine PNV P/A); and (iii) edaphophylous (soil features determine PNV P/A). The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophylous units (which demand more soil water than is supplied by other soil types in the surrounding landscape) were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas in Almería Province that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved.

Preliminary digital geologic maps of the Mariposa, Kingman, Trona, and Death Valley Sheets, California

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

D`Agnese, F.A.; Faunt, C.C.; Turner, A.K.

1995-10-01

Parts of four 1:250,000-scale geologic maps by the California Department of Natural Resources, Division of Mines and Geology have been digitized for use in hydrogeologic characterization. These maps include the area of California between lat. 35{degree}N; Long. 115{degree}W and lat. 38{degree}N, long. 118{degree}W of the Kingman Sheet (Jennings, 1961), Trona Sheet (Jennings and others, 1962), Mariposa Sheet (Strand, 1967), and Death Valley Sheet (Streitz and Stinson, 1974). These digital maps are being released by the US Geological Survey in the ARC/INFO Version 6.1 Export format. The digitized data include geologic unit boundaries, fault traces, and identity of geologic units. Themore » procedure outlined in US Geological Survey Circular 1054 (Soller and others, 1990) was sued during the map construction. The procedure involves transferring hard-copy data into digital format by scanning manuscript maps, manipulating the digital map data, and outputting the data. Most of the work was done using Environmental Systems Research Institute`s ARC/INFO software. The digital maps are available in ARC/INFO Rev. 6.1 Export format, from the USGS, Yucca Mountain Project, in Denver, Colorado.« less

GEMAS: Spatial pattern analysis of Ni by using digital image processing techniques on European agricultural soil data

NASA Astrophysics Data System (ADS)

Jordan, Gyozo; Petrik, Attila; De Vivo, Benedetto; Albanese, Stefano; Demetriades, Alecos; Sadeghi, Martiya

2017-04-01

Several studies have investigated the spatial distribution of chemical elements in topsoil (0-20 cm) within the framework of the EuroGeoSurveys Geochemistry Expert Group's 'Geochemical Mapping of Agricultural and Grazing Land Soil' project . Most of these studies used geostatistical analyses and interpolated concentration maps, Exploratory and Compositional Data and Analysis to identify anomalous patterns. The objective of our investigation is to demonstrate the use of digital image processing techniques for reproducible spatial pattern recognition and quantitative spatial feature characterisation. A single element (Ni) concentration in agricultural topsoil is used to perform the detailed spatial analysis, and to relate these features to possible underlying processes. In this study, simple univariate statistical methods were implemented first, and Tukey's inner-fence criterion was used to delineate statistical outliers. The linear and triangular irregular network (TIN) interpolation was used on the outlier-free Ni data points, which was resampled to a 10*10 km grid. Successive moving average smoothing was applied to generalise the TIN model and to suppress small- and at the same time enhance significant large-scale features of Nickel concentration spatial distribution patterns in European topsoil. The TIN map smoothed with a moving average filter revealed the spatial trends and patterns without losing much detail, and it was used as the input into digital image processing, such as local maxima and minima determination, digital cross sections, gradient magnitude and gradient direction calculation, second derivative profile curvature calculation, edge detection, local variability assessment, lineament density and directional variogram analyses. The detailed image processing analysis revealed several NE-SW, E-W and NW-SE oriented elongated features, which coincide with different spatial parameter classes and alignment with local maxima and minima. The NE-SW oriented linear pattern is the dominant feature to the south of the last glaciation limit. Some of these linear features are parallel to the suture zone of the Iapetus Ocean, while the others follow the Alpine and Carpathian Chains. The highest variability zones of Ni concentration in topsoil are located in the Alps and in the Balkans where mafic and ultramafic rocks outcrop. The predominant NE-SW oriented pattern is also captured by the strong anisotropy in the semi-variograms in this direction. A single major E-W oriented north-facing feature runs along the southern border of the last glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated spatial features are less dominant and are located in the Pyrenees and Scandinavia. This study demonstrates the efficiency of systematic image processing analysis in identifying and characterising spatial geochemical patterns that often remain uncovered by the usual visual map interpretation techniques.

Extracting spectral contrast in Landsat Thematic Mapper image data using selective principal component analysis

USGS Publications Warehouse

Chavez, P.S.; Kwarteng, A.Y.

1989-01-01

A challenge encountered with Landsat Thematic Mapper (TM) data, which includes data from size reflective spectral bands, is displaying as much information as possible in a three-image set for color compositing or digital analysis. Principal component analysis (PCA) applied to the six TM bands simultaneously is often used to address this problem. However, two problems that can be encountered using the PCA method are that information of interest might be mathematically mapped to one of the unused components and that a color composite can be difficult to interpret. "Selective' PCA can be used to minimize both of these problems. The spectral contrast among several spectral regions was mapped for a northern Arizona site using Landsat TM data. Field investigations determined that most of the spectral contrast seen in this area was due to one of the following: the amount of iron and hematite in the soils and rocks, vegetation differences, standing and running water, or the presence of gypsum, which has a higher moisture retention capability than do the surrounding soils and rocks. -from Authors

Cartography of irregularly shaped satellites

NASA Technical Reports Server (NTRS)

Batson, R. M.; Edwards, Kathleen

1987-01-01

Irregularly shaped satellites, such as Phobos and Amalthea, do not lend themselves to mapping by conventional methods because mathematical projections of their surfaces fail to convey an accurate visual impression of the landforms, and because large and irregular scale changes make their features difficult to measure on maps. A digital mapping technique has therefore been developed by which maps are compiled from digital topographic and spacecraft image files. The digital file is geometrically transformed as desired for human viewing, either on video screens or on hard copy. Digital files of this kind consist of digital images superimposed on another digital file representing the three-dimensional form of a body.

Application of ERTS-1 imagery to land use, forest density and soil investigations

NASA Technical Reports Server (NTRS)

Yassoglou, N. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Photographic and digital imagery obtained by ERTS-1 was analyzed and assigned to land features related to agricultural and forest resources. Land use and forest site evaluation maps were prepared by comparing remote sensing and ground truth data. Relationships found in this investigation between spectral signatures recorded by ERTS-1 and land features can be used for the assessment and development of agricultural and forest resources. The results are applicable to areas with ecological and geological conditions similar to those of Greece.

Enhanced digital mapping project : final report

DOT National Transportation Integrated Search

2004-11-19

The Enhanced Digital Map Project (EDMap) was a three-year effort launched in April 2001 to develop a range of digital map database enhancements that enable or improve the performance of driver assistance systems currently under development or conside...

The sustainable management of ameliorated peatlands on changed land use conditions; scenarios of constrains and possibilities

NASA Astrophysics Data System (ADS)

Shanskiy, , Merrit; Vollmer, Elis; Penu, Priit

2015-04-01

The utilization of organic soils for forestry or agriculture requires the land amelioration that could result on the peat losses from 15 to 20 t ha-1 in a year on following five years. After five years, the peat losses will be 5 - 15 t ha-1 in a year. The agricultural land resource on different types of organic soils (including ameliorated bogs) in Estonia is 360 000 ha that comprises 41% of total agricultural land area. The landscape iself is a valuable resource that considered to be a set of characteristics that satisfy needs of people using the landscape: economical or non-economical value; ecological, social, recreational, aesthetical, educational, scientific or even protective value. More diverse landscapes have higher biodiversity and yield more services to public, they are also seen as more sustainable and resilient to short-term changes. In order to maintain landscape diversity, sustainable maintenance is important. The purpose of current study was to estimate the land use potential on three different ameliorated peat areas and to develop the methodology for the futher sustainable utilization in order to secure the best ecological functioning of soil while taking into account maintaining and increasing landscape value. Therefore, site specific soil sampling (n=77) was carried out on predetermined eight study sites. Soil samples were analyzed for main agrochemical parameters (n=17; pHKCl, P, K, C%, N%, S%, ash, main anions and cations). This enables determing site-specific best suitable crops and land use scenarios. For the land resource description (soils type, topology) the digital soil map (1: 10,000) and field sudy based database were used for describing the model areas. For more specific identification of the field layers the Agricultural Registers and Information Board (ARIB) and databases of the Common Agricultural Policy (CAP) payments were used for subsidy schemes chekout. Estonian Nature Information System map tool was used to specify the restrictions on study sites by nature conversation on the maps data about nature protected objects and buffer zones or forming restricted areas around those objects. The results will indicate the utilization possibility and most sustainable scenarios for different land use cases. Moreover, the possible changes in soil functioning accordingly to site specific soil conditions will be discussed and presented.

Application of remote sensing in South Dakota to provide accurate inventories of agricultural crops, enhance contrast in photographic products, monitor rangeland habitat loss, map Aspen, and prepare hydrogeologic surveys

NASA Technical Reports Server (NTRS)

Myers, V. I. (Principal Investigator); Dalsted, K. J.; Best, R. G.; Smith, J. R.; Eidenshink, J. C.; Schmer, F. A.; Andrawis, A. S.; Rahn, P. H.

1977-01-01

The author has identified the following significant results. Digital analysis of LANDSAT CCT's indicated that two discrete spectral background zones occurred among the five soil zone. K-CLASS classification of corn revealed that accuracy increased when two background zones were used, compared to the classification of corn stratified by five soil zones. Selectively varying film type developer and development time produces higher contract in reprocessed imagery. Interpretation of rangeland and cropped land data from 1968 aerial photography and 1976 LANDSAT imagery indicated losses in rangeland habitat. Thermal imagery was useful in locating potential sources of sub-surface water and geothermal energy, estimating evapotranspiration, and inventorying the land.

Identification and Quantification Soil Redoximorphic Features by Digital Image Processing

USDA-ARS?s Scientific Manuscript database

Soil redoximorphic features (SRFs) have provided scientists and land managers with insight into relative soil moisture for approximately 60 years. The overall objective of this study was to develop a new method of SRF identification and quantification from soil cores using a digital camera and imag...

Spatial Digital Database for the Geologic Map of Oregon

USGS Publications Warehouse

Walker, George W.; MacLeod, Norman S.; Miller, Robert J.; Raines, Gary L.; Connors, Katherine A.

2003-01-01

Introduction This report describes and makes available a geologic digital spatial database (orgeo) representing the geologic map of Oregon (Walker and MacLeod, 1991). The original paper publication was printed as a single map sheet at a scale of 1:500,000, accompanied by a second sheet containing map unit descriptions and ancillary data. A digital version of the Walker and MacLeod (1991) map was included in Raines and others (1996). The dataset provided by this open-file report supersedes the earlier published digital version (Raines and others, 1996). This digital spatial database is one of many being created by the U.S. Geological Survey as an ongoing effort to provide geologic information for use in spatial analysis in a geographic information system (GIS). This database can be queried in many ways to produce a variety of geologic maps. This database is not meant to be used or displayed at any scale larger than 1:500,000 (for example, 1:100,000). This report describes the methods used to convert the geologic map data into a digital format, describes the ArcInfo GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. Scanned images of the printed map (Walker and MacLeod, 1991), their correlation of map units, and their explanation of map symbols are also available for download.

Geologic Map of the Point Lay Quadrangle, Alaska

USGS Publications Warehouse

Mull, Charles G.; Houseknecht, David W.; Pessel, G.H.; Garrity, Christopher P.

2008-01-01

This map is a product of the USGS Digital Geologic Maps of Northern Alaska project, which captures in digital format quadrangles across the entire width of northern Alaska. Sources include geologic maps previously published in hardcopy format and recent updates and revisions based on field mapping by the Alaska Department of Natural Resources, Division of Geological and Geophysical Surveys and Division of Oil and Gas, and the U.S. Geological Survey. Individual quadrangles are digitized at either 1:125,000 or 1:250,000 depending on the resolution of source maps. The project objective is to produce a set of digital geologic maps with uniform stratigraphic nomenclature and structural annotation, and publish those maps electronically. The paper version of this map is available for purchase from the USGS Store.

Geologic Map of the Ikpikpuk River Quadrangle, Alaska

USGS Publications Warehouse

Mull, Charles G.; Houseknecht, David W.; Pessel, G.H.; Garrity, Christopher P.

2005-01-01

This map is a product of the USGS Digital Geologic Maps of Northern Alaska project, which captures in digital format quadrangles across the entire width of northern Alaska. Sources include geologic maps previously published in hardcopy format and recent updates and revisions based on field mapping by the Alaska Department of Natural Resources, Division of Geological and Geophysical Surveys and Division of Oil and Gas, and the U.S. Geological Survey. Individual quadrangles are digitized at either 1:125,000 or 1:250,000 depending on the resolution of source maps. The project objective is to produce a set of digital geologic maps with uniform stratigraphic nomenclature and structural annotation, and publish those maps electronically. The paper version of this map is available for purchase from the USGS Store.

Geologic Map of the Lookout Ridge Quadrangle, Alaska

USGS Publications Warehouse

Mull, Charles G.; Houseknecht, David W.; Pessel, G.H.; Garrity, Christopher P.

2006-01-01

This map is a product of the USGS Digital Geologic Maps of Northern Alaska project, which captures in digital format quadrangles across the entire width of northern Alaska. Sources include geologic maps previously published in hardcopy format and recent updates and revisions based on field mapping by the Alaska Department of Natural Resources, Division of Geological and Geophysical Surveys and Division of Oil and Gas, and the U.S. Geological Survey. Individual quadrangles are digitized at either 1:125,000 or 1:250,000 depending on the resolution of source maps. The project objective is to produce a set of digital geologic maps with uniform stratigraphic nomenclature and structural annotation, and publish those maps electronically. The paper version of this map is available for purchase from the USGS Store.

A comparison between probability and information measures of uncertainty in a simulated soil map and the economic value of imperfect soil information.

NASA Astrophysics Data System (ADS)

Lark, R. Murray

2014-05-01

Conventionally the uncertainty of a conventional soil map has been expressed in terms of the mean purity of its map units: the probability that the soil profile class examined at a site would be found to correspond to the eponymous class of the simple map unit that is delineated there (Burrough et al, 1971). This measure of uncertainty has an intuitive meaning and is used for quality control in soil survey contracts (Western, 1978). However, it may be of limited value to the manager or policy maker who wants to decide whether the map provides a basis for decision making, and whether the cost of producing a better map would be justified. In this study I extend a published analysis of the economic implications of uncertainty in a soil map (Giasson et al., 2000). A decision analysis was developed to assess the economic value of imperfect soil map information for agricultural land use planning. Random error matrices for the soil map units were then generated, subject to constraints which ensure consistency with fixed frequencies of the different soil classes. For each error matrix the mean map unit purity was computed, and the value of the implied imperfect soil information was computed by the decision analysis. An alternative measure of the uncertainty in a soil map was considered. This is the mean soil map information which is the difference between the information content of a soil observation, at a random location in the region, and the information content of a soil observation given that the map unit is known. I examined the relationship between the value of imperfect soil information and the purity and information measures of map uncertainty. In both cases there was considerable variation in the economic value of possible maps with fixed values of the uncertainty measure. However, the correlation was somewhat stronger with the information measure, and there was a clear upper bound on the value of an imperfect soil map when the mean information takes some particular value. This suggests that the information measure may be a useful one for general communication of the value of soil and similar thematic data. Burrough, P.A., Beckett, P.H.T., Jarvis, M.G., 1971. The relation between cost and utility in soil survey. J. Soil Sci. 22, 359-394. Giasson, E., van Es, C, van Wambeke, A., Bryant, R.B. 2000. Assessing the economic value of soil information using decision analysis techniques. Soil Science 165, 971-978 Western, S., 1978. Soil survey contracts and quality control. Oxford Univ. Press, Oxford.

Modelling landscape-scale erosion potential related to vehicle disturbances along the U.S.-Mexico border

USGS Publications Warehouse

Villarreal, Miguel; Webb, Robert H.; Norman, Laura M.; Psillas, Jennifer L.; Rosenberg, Abigail S.; Carmichael, Shinji; Petrakis, Roy E.; Sparks, Philip E.

2014-01-01

Decades of intensive off-road vehicle use for border security, immigration, smuggling, recreation, and military training along the USA–Mexico border have prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from anthropogenic activities, we developed a series of erosion potential models based on factors from the Universal Soil Loss Equation (USLE). To better express the vulnerability of soils to human disturbances, we refined two factors whose categorical and spatial representations limit the application of the USLE for non-agricultural landscapes: the C-factor (vegetation cover) and the P-factor (support practice/management). A soil compaction index (P-factor) was calculated as the difference in saturated hydrologic conductivity (Ks) between disturbed and undisturbed soils, which was then scaled up to maps of vehicle disturbances digitized from aerial photography. The C-factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover (r2 = 0·77) than data derived from land cover (r2 = 0·06). We identified 9,780 km of unauthorized off-road tracks in the 2,800-km2 study area. Maps of these disturbances, when integrated with soil compaction data using the USLE, provided landscape-scale information on areas vulnerable to erosion from both natural processes and human activities and are detailed enough for adaptive management and restoration planning. The models revealed erosion potential hotspots adjacent to the border and within areas managed as critical habitat for the threatened flat-tailed horned lizard and endangered Sonoran pronghorn.

Evaluation of groundwater potential using geospatial techniques

NASA Astrophysics Data System (ADS)

Hussein, Abdul-Aziz; Govindu, Vanum; Nigusse, Amare Gebre Medhin

2017-09-01

The issue of unsustainable groundwater utilization is becoming increasingly an evident problem and the key concern for many developing countries. One of the problems is the absence of updated spatial information on the quantity and distribution of groundwater resource. Like the other developing countries, groundwater evaluation in Ethiopia has been usually conducted using field survey which is not feasible in terms of time and resource. This study was conducted in Northern Ethiopia, Wollo Zone, in Gerardo River Catchment district to spatially delineate the groundwater potential areas using geospatial and MCDA tools. To do so, eight major biophysical and environmental factors like geomorphology, lithology, slope, rainfall, land use land cover (LULC), soil, lineament density and drainage density were considered. The sources of these data were satellite image, digital elevation model (DEM), existing thematic maps and metrological station data. Landsat image was used in ERDAS Imagine to drive the LULC of the area, while the geomorphology, soil, and lithology of the area were identified and classified through field survey and digitized from existing maps using the ArcGIS software. The slope, lineament and drainage density of the area were derived from DEM using spatial analysis tools. The rainfall surface map was generated using the thissen polygon interpolation. Finally, after all these thematic maps were organized, weighted value determination for each factor and its field value was computed using IDRSI software. At last, all the factors were integrated together and computed the model using the weighted overlay so that potential groundwater areas were mapped. The findings depicted that the most potential groundwater areas are found in the central and eastern parts of the study area, while the northern and western parts of the Gerado River Catchment have poor potential of groundwater availability. This is mainly due to the cumulative effect of steep topographic and high drainage density. At last, once the potential groundwater areas were identified, cross validation of the resultant model was carefully carried out using existing data of dung wells and bore holes. The point data of dung wells and bore holes were overlaid on groundwater potential suitability map and coincide with the expected values. Generally, from this study, it can be concluded that RS and GIS with the help of MCDA are important tools in monitoring and evaluation of groundwater resource potential areas.

Assessment and visualization of uncertainty for countrywide soil organic matter map of Hungary using local entropy

NASA Astrophysics Data System (ADS)

Szatmári, Gábor; Pásztor, László

2016-04-01

Uncertainty is a general term expressing our imperfect knowledge in describing an environmental process and we are aware of it (Bárdossy and Fodor, 2004). Sampling, laboratory measurements, models and so on are subject to uncertainty. Effective quantification and visualization of uncertainty would be indispensable to stakeholders (e.g. policy makers, society). Soil related features and their spatial models should be stressfully targeted to uncertainty assessment because their inferences are further used in modelling and decision making process. The aim of our present study was to assess and effectively visualize the local uncertainty of the countrywide soil organic matter (SOM) spatial distribution model of Hungary using geostatistical tools and concepts. The Hungarian Soil Information and Monitoring System's SOM data (approximately 1,200 observations) and environmental related, spatially exhaustive secondary information (i.e. digital elevation model, climatic maps, MODIS satellite images and geological map) were used to model the countrywide SOM spatial distribution by regression kriging. It would be common to use the calculated estimation (or kriging) variance as a measure of uncertainty, however the normality and homoscedasticity hypotheses have to be refused according to our preliminary analysis on the data. Therefore, a normal score transformation and a sequential stochastic simulation approach was introduced to be able to model and assess the local uncertainty. Five hundred equally probable realizations (i.e. stochastic images) were generated. The number of the stochastic images is fairly enough to provide a model of uncertainty at each location, which is a complete description of uncertainty in geostatistics (Deutsch and Journel, 1998). Furthermore, these models can be applied e.g. to contour the probability of any events, which can be regarded as goal oriented digital soil maps and are of interest for agricultural management and decision making as well. A standardized measure of the local entropy was used to visualize uncertainty, where entropy values close to 1 correspond to high uncertainty, whilst values close to 0 correspond low uncertainty. The advantage of the usage of local entropy in this context is that it combines probabilities from multiple members into a single number for each location of the model. In conclusion, it is straightforward to use a sequential stochastic simulation approach to the assessment of uncertainty, when normality and homoscedasticity are violated. The visualization of uncertainty using the local entropy is effective and communicative to stakeholders because it represents the uncertainty through a single number within a [0, 1] scale. References: Bárdossy, Gy. & Fodor, J., 2004. Evaluation of Uncertainties and Risks in Geology. Springer-Verlag, Berlin Heidelberg. Deutsch, C.V. & Journel, A.G., 1998. GSLIB: geostatistical software library and user's guide. Oxford University Press, New York. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Seeing the soil through the net: an eye-opener on the soil map of the Flemish region (Belgium)

NASA Astrophysics Data System (ADS)

Dondeyne, Stefaan; Vanierschot, Laura; Langohr, Roger; Van Ranst, Eric; Deckers, Jozef; Oorts, Katrien

2017-04-01

A systematic soil survey of Belgium was conducted from 1948 to 1991. Field surveys were done at the detailed scale of 1:5000 with the final maps published at a 1:20,000 scale. The legend of these detailed soil maps (scale 1:20,000) has been converted to the 3rd edition of the international soil classification system 'World Reference Base for Soil Resources' (WRB). Over the last years, the government of the Flemish region made great efforts to make these maps, along with other environmental data, available to the general audience through the internet. The soil maps are widely used and consulted by researchers, teachers, land-use planners, environmental consultancy agencies and archaeologists. The maps can be downloaded and consulted in the viewer 'Visual Soil Explorer' ('Bodemverkenner'). To increase the legibility of the maps, we assembled a collection of photographs from soil profiles representing 923 soil types and 413 photos of related landscape settings. By clicking on a specific location in the 'Visual Soil Explorer', pictures of the corresponding soil type and landscape appear in a pop-up window, with a brief explanation about the soil properties. The collection of photographs of soil profiles cover almost 80% of the total area of the Flemish region, and include the 100 most common soil types. Our own teaching experience shows that these information layers are particular valuable for teaching soil geography and earth sciences in general. Overall, such visual information layers should contribute to a better interpretation of the soil maps and legacy soil data by serving as an eye-opener on the soil map to the wider community.

Insights into bird wing evolution and digit specification from polarizing region fate maps.

PubMed

Towers, Matthew; Signolet, Jason; Sherman, Adrian; Sang, Helen; Tickle, Cheryll

2011-08-09

The proposal that birds descended from theropod dinosaurs with digits 2, 3 and 4 was recently given support by short-term fate maps, suggesting that the chick wing polarizing region-a group that Sonic hedgehog-expressing cells-gives rise to digit 4. Here we show using long-term fate maps that Green fluorescent protein-expressing chick wing polarizing region grafts contribute only to soft tissues along the posterior margin of digit 4, supporting fossil data that birds descended from theropods that had digits 1, 2 and 3. In contrast, digit IV of the chick leg with four digits (I-IV) arises from the polarizing region. To determine how digit identity is specified over time, we inhibited Sonic hedgehog signalling. Fate maps show that polarizing region and adjacent cells are specified in parallel through a series of anterior to posterior digit fates-a process of digit specification that we suggest is involved in patterning all vertebrate limbs with more than three digits.

Preliminary integrated geologic map databases for the United States : Central states : Montana, Wyoming, Colorado, New Mexico, Kansas, Oklahoma, Texas, Missouri, Arkansas, and Louisiana

USGS Publications Warehouse

Stoeser, Douglas B.; Green, Gregory N.; Morath, Laurie C.; Heran, William D.; Wilson, Anna B.; Moore, David W.; Van Gosen, Bradley S.

2005-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for regional and national digital geologic maps attributed with age and lithology information. Such maps can be conveniently used to generate derivative maps for purposes including mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This Open-File Report is a preliminary version of part of a series of integrated state geologic map databases that cover the entire United States. The only national-scale digital geologic maps that portray most or all of the United States for the conterminous U.S. are the digital version of the King and Beikman (1974a, b) map at a scale of 1:2,500,000, as digitized by Schruben and others (1994) and the digital version of the Geologic Map of North America (Reed and others, 2005a, b) compiled at a scale of 1:5,000,000 which is currently being prepared by the U.S. Geological Survey. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. In a few cases, new digital compilations were prepared (e.g. OH, SC, SD) or existing paper maps were digitized (e.g. KY, TX). For Alaska and Hawaii, new regional maps are being compiled and ultimately new state maps will be produced. The digital geologic maps are presented in standardized formats as ARC/INFO (.e00) export files and as ArcView shape (.shp) files. Accompanying these spatial databases are a set of five supplemental data tables that relate the map units to detailed lithologic and age information. The maps for the CONUS have been fitted to a common set of state boundaries based on the 1:100,000 topographic map series of the United States Geological Survey (USGS). When the individual state maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps. No attempt has been made to reconcile differences in mapped geology across state lines. This is the first version of this product and it will be subsequently updated to include four additional states (North Dakota, South Dakota, Nebraska, and Iowa)

Quantitative and Qualitative Assessment of Soil Erosion Risk in Małopolska (Poland), Supported by an Object-Based Analysis of High-Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Drzewiecki, Wojciech; Wężyk, Piotr; Pierzchalski, Marcin; Szafrańska, Beata

2014-06-01

In 2011 the Marshal Office of Małopolska Voivodeship decided to evaluate the vulnerability of soils to water erosion for the entire region. The quantitative and qualitative assessment of the erosion risk for the soils of the Małopolska region was done based on the USLE approach. The special work-flow of geoinformation technologies was used to fulfil this goal. A high-resolution soil map, together with rainfall data, a detailed digital elevation model and statistical information about areas sown with particular crops created the input information for erosion modelling in GIS environment. The satellite remote sensing technology and the object-based image analysis (OBIA) approach gave valuable support to this study. RapidEye satellite images were used to obtain the essential up-to-date data about land use and vegetation cover for the entire region (15,000 km2). The application of OBIA also led to defining the direction of field cultivation and the mapping of contour tillage areas. As a result, the spatially differentiated values of erosion control practice factor were used. Both, the potential and the actual soil erosion risk were assessed quantificatively and qualitatively. The results of the erosion assessment in the Małopolska Voivodeship reveal the fact that a majority of its agricultural lands is characterized by moderate or low erosion risk levels. However, high-resolution erosion risk maps show its substantial spatial diversity. According to our study, average or higher actual erosion intensity levels occur for 10.6 % of agricultural land, i.e. 3.6 % of the entire voivodeship area. In 20 % of the municipalities there is a very urgent demand for erosion control. In the next 23 % an urgent erosion control is needed. Our study showed that even a slight improvement of P-factor estimation may have an influence on modeling results. In our case, despite a marginal change of erosion assessment figures on a regional scale, the influence on the final prioritization of areas (municipalities) according to erosion control needs is visible. The study shows that, high-resolution satellite imagery and OBIA may be efficiently used for P-factor mapping and thus contribute to a refined soil erosion risk assessment.

High Resolution UAV-based Passive Microwave L-band Imaging of Soil Moisture

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Stachura, M.; Elston, J.; McIntyre, E. M.

2013-12-01

Due to long electrical wavelengths and aperture size limitations the scaling of passive microwave remote sensing of soil moisture from spaceborne low-resolution applications to high resolution applications suitable for precision agriculture requires use of low flying aerial vehicles. This presentation summarizes a project to develop a commercial Unmanned Aerial Vehicle (UAV) hosting a precision microwave radiometer for mapping of soil moisture in high-value shallow root-zone crops. The project is based on the use of the Tempest electric-powered UAV and a compact digital L-band (1400-1427 MHz) passive microwave radiometer developed specifically for extremely small and lightweight aerial platforms or man-portable, tractor, or tower-based applications. Notable in this combination are a highly integrated UAV/radiometer antenna design and use of both the upwelling emitted signal from the surface and downwelling cold space signal for precise calibration using a lobe-correlating radiometer architecture. The system achieves a spatial resolution comparable to the altitude of the UAV above the ground while referencing upwelling measurements to the constant and well-known background temperature of cold space. The radiometer incorporates digital sampling and radio frequency interference mitigation along with infrared, near-infrared, and visible (red) sensors for surface temperature and vegetation biomass correction. This NASA-sponsored project is being developed both for commercial application in cropland water management, L-band satellite validation, and estuarian plume studies.

US GeoData: Digital cartographic and geographic data

USGS Publications Warehouse

,

1985-01-01

The increasing use of computers for storing and analyzing earth science information has sparked a growth in the demand for various types of cartographic data in digital form. The production of map data in computerized form is called digital cartography, and it involves the collection, storage, processing, analysis, and display of map data with the aid of computers. The U.S. Geological Survey, the Nation's largest earth science research agency, has expanded its national mapping program to incorporate operations associated with digital cartography, including the collection of planimetric, elevation, and geographic names information in digital form. This digital information is available for use in meeting the multipurpose needs and applications of the map user community.

Radiometric Survey in Western Afghanistan: A Website for Distribution of Data

USGS Publications Warehouse

Sweeney, Ronald E.; Kucks, Robert P.; Hill, Patricia L.; Finn, Carol A.

2007-01-01

Radiometric (uranium content, thorium content, potassium content, and gamma-ray intensity) and related data were digitized from radiometric and survey route location maps of western Afghanistan published in 1976. The uranium content data were digitized along contour lines from 33 maps in a series entitled 'Map of Uranium (Radium) Contents of Afghanistan (Western Area),' compiled by V. N. Kirsanov and R. S. Dershimanov. The thorium content data were digitized along contour lines from 33 maps in a series entitled 'Map of Thorium Contents of Afghanistan (Western Area),' compiled by V. N. Kirsanov and R. S. Dershimanov. The potassium content data were digitized along contour lines from 33 maps in a series entitled 'Map of Potassium Contents of Afghanistan (Western Area),' compiled by V. N. Kirsanov and R. S. Dershimanov. The gamma-ray intensity data were digitized along contour lines from 33 maps in a series entitled 'Map of Gamma-Field of Afghanistan (Western Area),' compiled by V. N. Kirsanov and R. S. Dershimanov. The survey route location data were digitized along flight-lines located on 33 maps in a series entitled 'Survey Routes Location and Contours of Flight Equal Altitudes. Western Area of Afghanistan,' compiled by Z. A. Alpatova, V. G. Kurnosov, and F. A. Grebneva.

Geologic Map of the Tucson and Nogales Quadrangles, Arizona (Scale 1:250,000): A Digital Database

USGS Publications Warehouse

Peterson, J.A.; Berquist, J.R.; Reynolds, S.J.; Page-Nedell, S. S.; Digital database by Oland, Gustav P.; Hirschberg, Douglas M.

2001-01-01

The geologic map of the Tucson-Nogales 1:250,000 scale quadrangle (Peterson and others, 1990) was digitized by U.S. Geological Survey staff and University of Arizona contractors at the Southwest Field Office, Tucson, Arizona, in 2000 for input into a geographic information system (GIS). The database was created for use as a basemap in a decision support system designed by the National Industrial Minerals and Surface Processes project. The resulting digital geologic map database can be queried in many ways to produce a variety of geologic maps. Digital base map data files (topography, roads, towns, rivers and lakes, etc.) are not included; they may be obtained from a variety of commercial and government sources. Additionally, point features, such as strike and dip, were not captured from the original paper map and are not included in the database. This database is not meant to be used or displayed at any scale larger than 1:250,000 (for example, 1:100,000 or 1:24,000). The digital geologic map graphics and plot files that are provided in the digital package are representations of the digital database. They are not designed to be cartographic products.

3D mapping of breast surface using digital fringe projection

NASA Astrophysics Data System (ADS)

Vairavan, Rajendaran; Retnasamy, Vithyacharan; Mohamad Shahimin, Mukhzeer; Sauli, Zaliman; Leng, Lai Siang; Wan Norhaimi, Wan Mokhzani; Marimuthu, Rajeswaran; Abdullah, Othman; Kirtsaeng, Supap

2017-02-01

Optical sensing technique has inherited non-contact nature for generating 3D surface mapping where its application ranges from MEMS component characterization, corrosion analysis, and vibration analysis. In particular, the digital fringe projection is utilized for 3D mapping of objects through the illumination of structured light for medical application extending from oral dental measurements, lower back deformation analysis, monitoring of scoliosis and 3D face reconstruction for biometric identification. However, the usage of digital fringe projection for 3D mapping of human breast is very minimal. Thus, this paper addresses the application of digital fringe projection for 3D mapping of breast surface based on total non-contact nature. In this work, phase shift method is utilized to perform the 3D mapping. The phase shifted fringe pattern are displayed through a digital projector onto the breast surface, and the distorted fringe patterns are captured by a CCD camera. A phase map is produced, and phase unwrapping was executed to obtain the 3D surface mapping of the breast. The surface height profile from 3D fringe projection was compared with the surface height measured by a direct method using electronic digital vernier caliper. Preliminary results showed the feasibility of digital fringe projection in providing a 3D mapping of breast and its application could be further extended for breast carcinoma detection.

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 utilized to identify the relevant pluviometric triggering scenarios. By using 205 daily rainfall series, different triggering pluviometric scenarios have been identified with reference to CG and FG covers: a value of 365 mm of the total rainfall of the event and/or 170 mm/d of the rainfall maximum intensity and a value of 325 mm of the total rainfall of the event and/or 158 mm/d of the rainfall maximum intensity are able to trigger shallow landsliding events for CG and FG covers, respectively. The results obtained from this study can help administrative authorities to plan future development activities and mitigation measures in shallow landslide-prone areas. In addition, the proposed methodology can be useful in managing emergency situations at a regional scale for shallow landsliding events triggered by intense rainfalls; through this approach, the susceptibility and the pluviometric triggering scenario maps will be improved by means of finer calibration of the involved factors.

Specification for the U.S. Geological Survey Historical Topographic Map Collection

USGS Publications Warehouse

Allord, Gregory J.; Walter, Jennifer L.; Fishburn, Kristin A.; Shea, Gale A.

2014-01-01

This document provides the detailed requirements for producing, archiving, and disseminating a comprehensive digital collection of topographic maps for the U.S. Geological Survey (USGS) Historical Topographic Map Collection (HTMC). The HTMC is a digital archive of about 190,000 printed topographic maps published by the USGS from the inception of the topographic mapping program in 1884 until the last paper topographic map using lithographic printing technology was published in 2006. The HTMC provides a comprehensive digital repository of all scales and all editions of USGS printed topographic maps that is easily discovered, browsed, and downloaded by the public at no cost. The HTMC provides ready access to maps that are no longer available for distribution in print. A digital file representing the original paper historical topographic map is produced for each historical map in the HTMC in georeferenced PDF (GeoPDF) format (a portable document format [PDF] with a geospatial extension).

Producing Alaska interim land cover maps from Landsat digital and ancillary data

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine; Doughty, Eileen Flanagan; Shasby, Mark; Loveland, Thomas R.; Benjamin, Susan

1987-01-01

In 1985, the U.S. Geological Survey initiated a research program to produce 1:250,000-scale land cover maps of Alaska using digital Landsat multispectral scanner data and ancillary data and to evaluate the potential of establishing a statewide land cover mapping program using this approach. The geometrically corrected and resampled Landsat pixel data are registered to a Universal Transverse Mercator (UTM) projection, along with arc-second digital elevation model data used as an aid in the final computer classification. Areas summaries of the land cover classes are extracted by merging the Landsat digital classification files with the U.S. Bureau of Land Management's Public Land Survey digital file. Registration of the digital land cover data is verified and control points are identified so that a laser plotter can products screened film separate for printing the classification data at map scale directly from the digital file. The final land cover classification is retained both as a color map at 1:250,000 scale registered to the U.S. Geological Survey base map, with area summaries by township and range on the reverse, and as a digital file where it may be used as a category in a geographic information system.

Spatial digital database for the geologic map of the east part of the Pullman 1° x 2° quadrangle, Idaho

USGS Publications Warehouse

Rember, William C.; Bennett, Earl H.

2001-01-01

he paper geologic map of the east part of the Pullman 1·x 2· degree quadrangle, Idaho (Rember and Bennett, 1979) was scanned and initially attributed by Optronics Specialty Co., Inc. (Northridge, CA) and remitted to the U.S. Geological Survey for further attribution and publication of the geospatial digital files. The resulting digital geologic map GIS can be queried in many ways to produce a variety of geologic maps. This digital geospatial database is one of many being created by the U.S. Geological Survey as an ongoing effort to provide geologic information in a geographic information system (GIS) for use in spatial analysis. Digital base map data files (topography, roads, towns, rivers and lakes, and others.) are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:250,000 (for example, 1:100,000 or 1:24,000). The digital geologic map graphics and plot files (pull250k.gra/.hp /.eps) that are provided in the digital package are representations of the digital database.

Mapping mine wastes and analyzing areas affected by selenium-rich water runoff in southeast Idaho using AVIRIS imagery and digital elevation data

USGS Publications Warehouse

Mars, J.C.; Crowley, J.K.

2003-01-01

Remotely sensed hyperspectral and digital elevation data from southeastern Idaho are combined in a new method to assess mine waste contamination. Waste rock from phosphorite mining in the area contains selenium, cadmium, vanadium, and other metals. Toxic concentrations of selenium have been found in plants and soils near some mine waste dumps. Eighteen mine waste dumps and five vegetation cover types in the southeast Idaho phosphate district were mapped by using Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) imagery and field data. The interaction of surface water runoff with mine waste was assessed by registering the AVIRIS results to digital elevation data, enabling determinations of (1) mine dump morphologies, (2) catchment watershed areas above each mine dump, (3) flow directions from the dumps, (4) stream gradients, and (5) the extent of downstream wetlands available for selenium absorption. Watersheds with the most severe selenium contamination, such as the South Maybe Canyon watershed, are associated with mine dumps that have large catchment watershed areas, high stream gradients, a paucity of downstream wetlands, and dump forms that tend to obstruct stream flow. Watersheds associated with low concentrations of dissolved selenium, such as Angus Creek, have mine dumps with small catchment watershed areas, low stream gradients, abundant wetlands vegetation, and less obstructing dump morphologies. ?? 2002 Elsevier Science Inc. All rights reserved.

Digital floodplain mapping and an analysis of errors involved

USGS Publications Warehouse

Hamblen, C.S.; Soong, D.T.; Cai, X.

2007-01-01

Mapping floodplain boundaries using geographical information system (GIS) and digital elevation models (DEMs) was completed in a recent study. However convenient this method may appear at first, the resulting maps potentially can have unaccounted errors. Mapping the floodplain using GIS is faster than mapping manually, and digital mapping is expected to be more common in the future. When mapping is done manually, the experience and judgment of the engineer or geographer completing the mapping and the contour resolution of the surface topography are critical in determining the flood-plain and floodway boundaries between cross sections. When mapping is done digitally, discrepancies can result from the use of the computing algorithm and digital topographic datasets. Understanding the possible sources of error and how the error accumulates through these processes is necessary for the validation of automated digital mapping. This study will evaluate the procedure of floodplain mapping using GIS and a 3 m by 3 m resolution DEM with a focus on the accumulated errors involved in the process. Within the GIS environment of this mapping method, the procedural steps of most interest, initially, include: (1) the accurate spatial representation of the stream centerline and cross sections, (2) properly using a triangulated irregular network (TIN) model for the flood elevations of the studied cross sections, the interpolated elevations between them and the extrapolated flood elevations beyond the cross sections, and (3) the comparison of the flood elevation TIN with the ground elevation DEM, from which the appropriate inundation boundaries are delineated. The study area involved is of relatively low topographic relief; thereby, making it representative of common suburban development and a prime setting for the need of accurately mapped floodplains. This paper emphasizes the impacts of integrating supplemental digital terrain data between cross sections on floodplain delineation. ?? 2007 ASCE.

An integrated and open source GIS environmental management system for a protected area in the south of Portugal

NASA Astrophysics Data System (ADS)

Teodoro, A.; Duarte, L.; Sillero, N.; Gonçalves, J. A.; Fonte, J.; Gonçalves-Seco, L.; Pinheiro da Luz, L. M.; dos Santos Beja, N. M. R.

2015-10-01

Herdade da Contenda (HC), located in Moura municipality, Beja district (Alentejo province) in the south of Portugal (southwestern Iberia Peninsula), is a national hunting area with 5270ha. The development of an integrated system that aims to make the management of the natural and cultural heritage resources will be very useful for an effective management of this area. This integrated system should include the physical characterization of the territory, natural conservation, land use and land management themes, as well the cultural heritage resources. This paper presents a new tool for an integrated environmental management system of the HC, which aims to produce maps under a GIS open source environment (QGIS). The application is composed by a single button which opens a window. The window is composed by twelve menus (File, DRASTIC, Forest Fire Risk, Revised Universal Soil Loss Equation (RUSLE), Bioclimatic Index, Cultural Heritage, Fauna and Flora, Ortofoto, Normalizes Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Land Use Land Cover Cover (LULC) and Help. Several inputs are requires to generate these maps, e.g. DEM, geologic information, soil map, hydraulic conductivity information, LULC map, vulnerability and economic information, NDVI. Six buttons were added to the toolbar which allows to manipulate the information in the map canvas: Zoom in, Zoom out, Pan, Print/Layout and Clear. This integrated and open source GIS environment management system was developed for the HC area, but could be easily adapted to other natural or protected area. Despite the lack of data, the methodology presented fulfills the objectives.

Global hierarchical classification of deepwater and wetland environments from remote sensing products

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.; Aires, F.; Prigent, C.; McIntyre, P. B.

2017-12-01

Global surface water maps have improved in spatial and temporal resolutions through various remote sensing methods: open water extents with compiled Landsat archives and inundation with topographically downscaled multi-sensor retrievals. These time-series capture variations through time of open water and inundation without discriminating between hydrographic features (e.g. lakes, reservoirs, river channels and wetland types) as other databases have done as static representation. Available data sources present the opportunity to generate a comprehensive map and typology of aquatic environments (deepwater and wetlands) that improves on earlier digitized inventories and maps. The challenge of classifying surface waters globally is to distinguishing wetland types with meaningful characteristics or proxies (hydrology, water chemistry, soils, vegetation) while accommodating limitations of remote sensing data. We present a new wetland classification scheme designed for global application and produce a map of aquatic ecosystem types globally using state-of-the-art remote sensing products. Our classification scheme combines open water extent and expands it with downscaled multi-sensor inundation data to capture the maximal vegetated wetland extent. The hierarchical structure of the classification is modified from the Cowardin Systems (1979) developed for the USA. The first level classification is based on a combination of landscape positions and water source (e.g. lacustrine, riverine, palustrine, coastal and artificial) while the second level represents the hydrologic regime (e.g. perennial, seasonal, intermittent and waterlogged). Class-specific descriptors can further detail the wetland types with soils and vegetation cover. Our globally consistent nomenclature and top-down mapping allows for direct comparison across biogeographic regions, to upscale biogeochemical fluxes as well as other landscape level functions.

Digital geologic map of the Spokane 1:100,000 quadrangle, Washington and Idaho: a digital database for the 1990 N.L. Joseph map

USGS Publications Warehouse

Johnson, Bruce R.; Derkey, Pamela D.

1998-01-01

Geologic data from the geologic map of the Spokane 1:100,000-scale quadrangle compiled by Joseph (1990) were entered into a geographic information system (GIS) as part of a larger effort to create regional digital geology for the Pacific Northwest. The map area is located in eastern Washington and extends across the state border into western Idaho (Fig. 1). This open-file report describes the methods used to convert the geologic map data into a digital format, documents the file structures, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet.

Visualizing Soil Landscapes on Mobile Devices

NASA Astrophysics Data System (ADS)

Schulze, Darrell; Lindbo, David

2016-04-01

The Integrating Spatial Educational Experiences (Isee) project utilizes the most detailed US soil survey data to create thematic maps of soil properties that are then combined with a highly optimized hillshade basemap for display. The Isee app, currently available for the iPad platform from the Apple App Store, allows the cached maps to be zoomed and panned quickly to any location down to a scale of 1:18,000. Maps currently available for the states of Indiana, Illinois, Kentucky, Ohio, Texas, West Virginia, and Wisconsin include, Dominant Soil Parent Materials, Natural Soil Drainage Classes, Limiting Layers, Surface Soil Colors, and Acid Subsoils. Other thematic maps will be added in the future. The ability to zoom, pan, and change maps quickly allows the user to see and understand soil landscape relationships that are not often apparent using static maps, while the ability to access the maps conveniently in the field allows the user to see how soil landscape features on the maps appear in the field.

Geologic and structure map of the Choteau 1 degree by 2 degrees Quadrangle, western Montana

USGS Publications Warehouse

Mudge, Melville R.; Earhart, Robert L.; Whipple, James W.; Harrison, Jack E.

1982-01-01

The geologic and structure map of Choteau 1 x 2 degree quadrangle (Mudge and others, 1982) was originally converted to a digital format by Jeff Silkwood (U.S. Forest Service and completed by the U.S. Geological Survey staff and contractor at the Spokane Field Office (WA) in 2000 for input into a geographic information system (GIS). The resulting digital geologic map (GIS) database can be queried in many ways to produce a variey of geologic maps. Digital base map data files (topography, roads, towns, rivers and lakes, etc.) are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:250,000 (e.g. 1:100,000 or 1:24,000. The digital geologic map graphics and plot files (chot250k.gra/.hp/.eps and chot-map.pdf) that are provided in the digital package are representations of the digital database. They are not designed to be cartographic products.

Hyperspectral Technique for Detecting Soil Parameters

NASA Astrophysics Data System (ADS)

Garfagnoli, F.; Ciampalini, A.; Moretti, S.; Chiarantini, L.

2011-12-01

In satellite and airborne remote sensing, hyperspectral technique has become a very powerful tool, due to the possibility of rapidly realizing chemical/mineralogical maps of the studied areas. Many studies are trying to customize the algorithms to identify several geo-physical soil properties. The specific objective of this study is to investigate those soil characteristics, such as clay mineral content, influencing degradation processes (soil erosion and shallow landslides), by means of correlation analysis, in order to examine the possibility of predicting the selected property using high-resolution reflectance spectra and images. The study area is located in the Mugello basin, about 30 km north of Firenze (Tuscany, Italy). Agriculturally suitable terrains are assigned mainly to annual crops, marginally to olive groves, vineyards and orchards. Soils mostly belong to Regosols and Cambisols orders. An ASD FieldSpec spectroradiometer was used to obtain reflectance spectra from about 80 dried, crushed and sieved samples under controlled laboratory conditions. Samples were collected simultaneously with the flight of SIM.GA hyperspectral camera from Selex Galileo, over an area of about 5 km2 and their positions were recorded with a differential GPS. The quantitative determination of clay minerals content was performed by means of XRD and Rietveld refinement. Different chemometric techniques were preliminarily tested to correlate mineralogical records with reflectance data. A one component partial least squares regression model yielded a preliminary R2 value of 0.65. A slightly better result was achieved by plotting the absorption peak depth at 2210 versus total clay content (band-depth analysis). The complete SIM.GA hyperspectral geocoded row dataset, with an approximate pixel resolution of 0.6 m (VNIR) and 1.2 m (SWIR), was firstly transformed into at sensor radiance values, by applying calibration coefficients and parameters from laboratory measurements to non-georeferred VNIR/SWIR DN values. Then, airborne imagery needed to be corrected for the influence of the atmosphere, solar illumination, sensor viewing geometry and terrain geometry information, for the retrieval of inherent surface reflectance properties. The geocoded products were obtained for each flight line by using a procedure developed in IDL Language and PARGE (PARametric Geocoding) software. When all compensation parameters were applied to hyperspectral data or to the final thematic map, orthorectified, georeferred and coregistered VNIR to SWIR images or maps were available for GIS application and 3D view as well as for the retrieval of different geophysical parameters by means of inversion algorithms. The experimental fitting of laboratory data on mineral content is used for airborne data inversion, whose results are in agreement with laboratory records, demonstrating the possibility to use this methodology for digital mapping of soil properties. In this study, we established a complete procedure for mapping clay content areal variations in agricultural soils starting form airborne hyperspectral imagery.

Quaternary geologic map of the Blue Ridge 4 degrees x 6 degrees quadrangle, United States

USGS Publications Warehouse

Howard, Alan D.; Behling, Robert E.; Wheeler, Walter H.; Daniels, Raymond B.; Swadley, W.C.; Richmond, Gerald M.; Goldthwait, Richard P.; Fullerton, David S.; Sevon, William D.; Miller, Robert A.; Bush, Charles A.; Richmond, Gerald M.; Fullerton, David S.; Christiansen, Ann Coe

1991-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1986. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Blue Ridge 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the "soil" in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Quaternary geologic map of the Hatteras 4° x 6° quadrangle, United States

USGS Publications Warehouse

State compilations by Johnson, Gerald H.; Richmond, Gerald Martin; edited and integrated by Richmond, G. M.; Fullerton, D.S.; Weide, D.L.; Bush, Charles A.

1986-01-01

This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1986. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files. The Quaternary Geologic Map of the Hatteras 4° x 6° Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the Earth. They make up the "ground" on which we walk, the "dirt" in which we dig foundations, and the "soil" in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale.

Development of predictive mapping techniques for soil survey and salinity mapping

NASA Astrophysics Data System (ADS)

Elnaggar, Abdelhamid A.

Conventional soil maps represent a valuable source of information about soil characteristics, however they are subjective, very expensive, and time-consuming to prepare. Also, they do not include explicit information about the conceptual mental model used in developing them nor information about their accuracy, in addition to the error associated with them. Decision tree analysis (DTA) was successfully used in retrieving the expert knowledge embedded in old soil survey data. This knowledge was efficiently used in developing predictive soil maps for the study areas in Benton and Malheur Counties, Oregon and accessing their consistency. A retrieved soil-landscape model from a reference area in Harney County was extrapolated to develop a preliminary soil map for the neighboring unmapped part of Malheur County. The developed map had a low prediction accuracy and only a few soil map units (SMUs) were predicted with significant accuracy, mostly those shallow SMUs that have either a lithic contact with the bedrock or developed on a duripan. On the other hand, the developed soil map based on field data was predicted with very high accuracy (overall was about 97%). Salt-affected areas of the Malheur County study area are indicated by their high spectral reflectance and they are easily discriminated from the remote sensing data. However, remote sensing data fails to distinguish between the different classes of soil salinity. Using the DTA method, five classes of soil salinity were successfully predicted with an overall accuracy of about 99%. Moreover, the calculated area of salt-affected soil was overestimated when mapped using remote sensing data compared to that predicted by using DTA. Hence, DTA could be a very helpful approach in developing soil survey and soil salinity maps in more objective, effective, less-expensive and quicker ways based on field data.

The Definition of Groundwater Recharge Area Using GIS Approach -A Case Study of Choshuihsi Alluvial Fan, Taiwan

NASA Astrophysics Data System (ADS)

Tsai, JuiPin; Chen, Yu Wen; Chang, Liang Cheng; Chiang, Chun Jung; Chen, Jui Er; Chen, You Cheng

2013-04-01

Groundwater recharge areas are regions with high permeability that accept surface water more readily than other regions. If the land use/cover were changed, it would affect the groundwater recharge. Also, if this area were polluted, the contamination easily infiltrates into the groundwater system. Therefore, the goal of this study is to delineate the recharge area of Choshuihsi Alluvial Fan. This study applies 6 recharge potential scale factors, including land use/land cover, soil, drainage density, annual average rainfall, hydraulic conductivity and aquifer thickness to estimate the infiltration ability and storage capacity of study area. The fundamental data of these factors were digitized using GIS (Geographic Information System) technology and their GIS maps were created. Then each of these maps was translated to a score map ranged from 1 to 100. Moreover, these score maps are integrated as a recharge potential map using arithmetic average, and this map shows recharge potential in 5 levels, such as very poor, poor, moderate, good and excellent. The result shows that majority of "good" and "excellent" areas is located at the top of the fan. This is because the land use of top-fan is agricultural and its surface soil type is gravel and coarse. The top-fan, which is close to mountain areas, has a higher average annual rainfall than other areas. Also, the aquifer thickness of top-fan is much thicker than other areas. The percentage of the areas ranged as "good" and above is 9.63% of total area, and most areas located at top-fan. As a result, we suggest that the top-fan of study area should be protected and more field surveys are required to accurately delineate the recharge area boundary.

Three-dimensional prediction of soil physical, chemical, and hydrological properties in a forested catchment of the Santa Catalina CZO

NASA Astrophysics Data System (ADS)

Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.

2014-12-01

Understanding critical zone evolution and function requires an accurate assessment of local soil properties. Two-dimensional (2D) digital soil mapping provides a general assessment of soil characteristics across a sampled landscape, but lacks the ability to predict soil properties with depth. The utilization of mass-preserving spline functions enable the extrapolation of soil properties with depth, extending predictive functions to three-dimensions (3D). The present study was completed in the Marshall Gulch (MG) catchment, located in the Santa Catalina Mountains, 30 km northwest of Tucson, Arizona, as part of the Santa Catalina-Jemez Mountains Critical Zone Observatory. Twenty-four soil pits were excavated and described following standard procedures. Mass-preserving splines were used to extrapolate mass carbon (kg C m-2); percent clay, silt, and sand (%); sodium mass flux (kg Na m-2); and pH for 24 sampled soil pits in 1-cm depth increments. Saturated volumetric water content (θs) and volumetric water content at 10 kPa (θ10) were predicted using ROSETTA and established empirical relationships. The described profiles were all sampled to differing depths; to compensate for the unevenness of the profile descriptions, the soil depths were standardized from 0.0 to 1.0 and then split into five equal standard depth sections. A logit-transformation was used to normalize the target variables. Step-wise regressions were calculated using available environmental covariates to predict the properties of each variable across the catchment in each depth section, and interpolated model residuals added back to the predicted layers to generate the final soil maps. Logit-transformed R2 for the predictive functions varied widely, ranging from 0.20 to 0.79, with logit-transformed RMSE ranging from 0.15 to 2.77. The MG catchment was further classified into clusters with similar properties based on the environmental covariates, and representative depth functions for each target variable in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.

Selection of a Geostatistical Method to Interpolate Soil Properties of the State Crop Testing Fields using Attributes of a Digital Terrain Model

NASA Astrophysics Data System (ADS)

Sahabiev, I. A.; Ryazanov, S. S.; Kolcova, T. G.; Grigoryan, B. R.

2018-03-01

The three most common techniques to interpolate soil properties at a field scale—ordinary kriging (OK), regression kriging with multiple linear regression drift model (RK + MLR), and regression kriging with principal component regression drift model (RK + PCR)—were examined. The results of the performed study were compiled into an algorithm of choosing the most appropriate soil mapping technique. Relief attributes were used as the auxiliary variables. When spatial dependence of a target variable was strong, the OK method showed more accurate interpolation results, and the inclusion of the auxiliary data resulted in an insignificant improvement in prediction accuracy. According to the algorithm, the RK + PCR method effectively eliminates multicollinearity of explanatory variables. However, if the number of predictors is less than ten, the probability of multicollinearity is reduced, and application of the PCR becomes irrational. In that case, the multiple linear regression should be used instead.

Wetlands of Argonne National Laboratory-East DuPage County, Illinois

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

Van Lonkhuyzen, R.A.; LaGory, K.E.

1994-03-01

Jurisdictional wetlands of the Argonne National Laboratory-East (ANL-E) site in DuPage County, Illinois, were delineated in the summer and autumn of 1993 in accordance with the 1987 US Army Corps of Engineers methodology. Potential wetland sites with an area greater than 500 m{sup 2} (0.05 ha [0.124 acre]) were identified for delineation on the basis of aerial photographs, the DuPage County soil survey, and reconnaissance-level field studies. To qualify as a jurisdictional wetland, an area had to support a predominance of hydrophytic vegetation as well as have hydric soil and wetland hydrology. Thirty-five individual jurisdictional wetlands were delineated at ANL-E,more » totaling 180,604 m{sup 2} (18.1 ha [44.6 acres]). These wetlands were digitized onto the ANL-E site map for use in project planning. Characteristics of each wetland are presented -- including size, dominant plant species and their indicator status, hydrologic characteristics (including water source), and soil characteristics.« less

Permeability of soils in Mississippi

USGS Publications Warehouse

O'Hara, Charles G.

1994-01-01

The permeability of soils in Mississippi was determined and mapped using a geographic information system (GIS). Soil permeabilities in Mississippi were determined to range in value from nearly 0.0 to values exceeding 5.0 inches per hour. The U.S. Soil Conservation Service's State Soil Geographic Data Base (STATSGO) was used as the primary source of data for the determination of area-weighted soil permeability. STATSGO provides soil layer properties that are spatially referenced to mapped areas. These mapped areas are referred to as polygons in the GIS. The polygons arc boundaries of soils mapped as a group and are given unique Map Unit Identifiers (MUIDs). The data describing the physical characteristics of the soils within each polygon are stored in a tabular data base format and are referred to as attributes. The U.S. Soil Conservation Service developed STATSGO to be primarily used as a guide for regional resource planning, management, and monitoring. STATSGO was designed so that soil information could be extracted from properties tables at the layer level, combined by component, and statistically expanded to cover the entire map unit. The results of this study provide a mapped value for permeability which is representative of the vertical permeability of soils in that area. The resultant permeability map provides a representative vertical soil permeability for a given area sufficient for county, multi- county, and area planning, and will be used as the soil permeability data component in the evaluation of the susceptibility of major aquifers to contami- nation in Mississippi.

Remote Sensing Soil Moisture Analysis by Unmanned Aerial Vehicles Digital Imaging

NASA Astrophysics Data System (ADS)

Yeh, C. Y.; Lin, H. R.; Chen, Y. L.; Huang, S. Y.; Wen, J. C.

2017-12-01

In recent years, remote sensing analysis has been able to apply to the research of climate change, environment monitoring, geology, hydro-meteorological, and so on. However, the traditional methods for analyzing wide ranges of surface soil moisture of spatial distribution surveys may require plenty resources besides the high cost. In the past, remote sensing analysis performed soil moisture estimates through shortwave, thermal infrared ray, or infrared satellite, which requires lots of resources, labor, and money. Therefore, the digital image color was used to establish the multiple linear regression model. Finally, we can find out the relationship between surface soil color and soil moisture. In this study, we use the Unmanned Aerial Vehicle (UAV) to take an aerial photo of the fallow farmland. Simultaneously, we take the surface soil sample from 0-5 cm of the surface. The soil will be baking by 110° C and 24 hr. And the software ImageJ 1.48 is applied for the analysis of the digital images and the hue analysis into Red, Green, and Blue (R, G, B) hue values. The correlation analysis is the result from the data obtained from the image hue and the surface soil moisture at each sampling point. After image and soil moisture analysis, we use the R, G, B and soil moisture to establish the multiple regression to estimate the spatial distributions of surface soil moisture. In the result, we compare the real soil moisture and the estimated soil moisture. The coefficient of determination (R2) can achieve 0.5-0.7. The uncertainties in the field test, such as the sun illumination, the sun exposure angle, even the shadow, will affect the result; therefore, R2 can achieve 0.5-0.7 reflects good effect for the in-suit test by using the digital image to estimate the soil moisture. Based on the outcomes of the research, using digital images from UAV to estimate the surface soil moisture is acceptable. However, further investigations need to be collected more than ten days (four times a day) data to verify the relation between the image hue and the soil moisture for reliable moisture estimated model. And it is better to use the digital single lens reflex camera to prevent the deformation of the image and to have a better auto exposure. Keywords: soil, moisture, remote sensing

Proceedings of a workshop on digital mapping techniques; methods for geologic map data capture, management, and publication - June 2 - 5, 1997, Lawrence, Kansas

USGS Publications Warehouse

Soller, David R.

1997-01-01

Introduction: From June 2-5, 1997, selected technical representatives of the USGS and State geological surveys participated in the 'AASG/USGS Digital Mapping Techniques' workshop in Lawrence, Kansas. The workshop was initiated by the AASG/USGS Data Capture Working Group, and was hosted by the Kansas Geological Survey (KGS). With a focus on methods for data capture and digital map production, the goal was to help move the state surveys and the USGS toward development of more cost-effective, flexible, and useful systems for digital mapping and GIS analysis.

Digital Mapping Techniques '09-Workshop Proceedings, Morgantown, West Virginia, May 10-13, 2009

USGS Publications Warehouse

Soller, David R.

2011-01-01

As in the previous years' meetings, the objective was to foster informal discussion and exchange of technical information, principally in order to develop more efficient methods for digital mapping, cartography, GIS analysis, and information management. At this meeting, oral and poster presentations and special discussion sessions emphasized (1) methods for creating and publishing map products (here, "publishing" includes Web-based release); (2) field data capture software and techniques, including the use of LiDAR; (3) digital cartographic techniques; (4) migration of digital maps into ArcGIS Geodatabase format; (5) analytical GIS techniques; and (6) continued development of the National Geologic Map Database.

Current trends in geomorphological mapping

NASA Astrophysics Data System (ADS)

Seijmonsbergen, A. C.

2012-04-01

Geomorphological mapping is a world currently in motion, driven by technological advances and the availability of new high resolution data. As a consequence, classic (paper) geomorphological maps which were the standard for more than 50 years are rapidly being replaced by digital geomorphological information layers. This is witnessed by the following developments: 1. the conversion of classic paper maps into digital information layers, mainly performed in a digital mapping environment such as a Geographical Information System, 2. updating the location precision and the content of the converted maps, by adding more geomorphological details, taken from high resolution elevation data and/or high resolution image data, 3. (semi) automated extraction and classification of geomorphological features from digital elevation models, broadly separated into unsupervised and supervised classification techniques and 4. New digital visualization / cartographic techniques and reading interfaces. Newly digital geomorphological information layers can be based on manual digitization of polygons using DEMs and/or aerial photographs, or prepared through (semi) automated extraction and delineation of geomorphological features. DEMs are often used as basis to derive Land Surface Parameter information which is used as input for (un) supervised classification techniques. Especially when using high-res data, object-based classification is used as an alternative to traditional pixel-based classifications, to cluster grid cells into homogeneous objects, which can be classified as geomorphological features. Classic map content can also be used as training material for the supervised classification of geomorphological features. In the classification process, rule-based protocols, including expert-knowledge input, are used to map specific geomorphological features or entire landscapes. Current (semi) automated classification techniques are increasingly able to extract morphometric, hydrological, and in the near future also morphogenetic information. As a result, these new opportunities have changed the workflows for geomorphological mapmaking, and their focus have shifted from field-based techniques to using more computer-based techniques: for example, traditional pre-field air-photo based maps are now replaced by maps prepared in a digital mapping environment, and designated field visits using mobile GIS / digital mapping devices now focus on gathering location information and attribute inventories and are strongly time efficient. The resulting 'modern geomorphological maps' are digital collections of geomorphological information layers consisting of georeferenced vector, raster and tabular data which are stored in a digital environment such as a GIS geodatabase, and are easily visualized as e.g. 'birds' eye' views, as animated 3D displays, on virtual globes, or stored as GeoPDF maps in which georeferenced attribute information can be easily exchanged over the internet. Digital geomorphological information layers are increasingly accessed via web-based services distributed through remote servers. Information can be consulted - or even build using remote geoprocessing servers - by the end user. Therefore, it will not only be the geomorphologist anymore, but also the professional end user that dictates the applied use of digital geomorphological information layers.

Digital Mapping Techniques '11–12 workshop proceedings

USGS Publications Warehouse

Soller, David R.

2014-01-01

At these meetings, oral and poster presentations and special discussion sessions emphasized: (1) methods for creating and publishing map products (here, "publishing" includes Web-based release); (2) field data capture software and techniques, including the use of LiDAR; (3) digital cartographic techniques; (4) migration of digital maps into ArcGIS Geodatabase formats; (5) analytical GIS techniques; and (6) continued development of the National Geologic Map Database.

Concepts of soil mapping as a basis for the assessment of soil functions

NASA Astrophysics Data System (ADS)

Baumgarten, Andreas

2014-05-01

Soil mapping systems in Europe have been designed mainly as a tool for the description of soil characteristics from a morphogenetic viewpoint. Contrasting to the American or FAO system, the soil development has been in the main focus of European systems. Nevertheless , recent developments in soil science stress the importance of the functions of soils with respect to the ecosystems. As soil mapping systems usually offer a sound and extensive database, the deduction of soil functions from "classic" mapping parameters can be used for local and regional assessments. According to the used pedo-transfer functions and mapping systems, tailored approaches can be chosen for different applications. In Austria, a system mainly for spatial planning purposes has been developed that will be presented and illustrated by means of best practice examples.

Procedure for extraction of disparate data from maps into computerized data bases

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1979-01-01

A procedure is presented for extracting disparate sources of data from geographic maps and for the conversion of these data into a suitable format for processing on a computer-oriented information system. Several graphic digitizing considerations are included and related to the NASA Earth Resources Laboratory's Digitizer System. Current operating procedures for the Digitizer System are given in a simplified and logical manner. The report serves as a guide to those organizations interested in converting map-based data by using a comparable map digitizing system.

An objective and reproducible landform and topography description approach based on digital terrain analysis used for soil profile site characteristics

NASA Astrophysics Data System (ADS)

Gruber, Fabian E.; Baruck, Jasmin; Hastik, Richard; Geitner, Clemens

2015-04-01

All major soil description and classification systems, including the World Reference Base (WRB) and the German Soil description guidelines (KA5), require the characterization of landform and topography for soil profile sites. This is commonly done at more than one scale, for instance at macro-, meso- and micro scale. However, inherent when humans perform such a task, different surveyors will reach different conclusions due to their subjective perception of landscape structure, based on their individual mind-model of soil-landscape structure, emphasizing different aspects and scales of the landscape. In this study we apply a work-flow using the GRASS GIS extension module r.geomorphon to make use of high resolution digital elevation models (DEMs) to characterize the landform elements and topography of soil profile sites at different scales, and compare the results with a large number of soil profile site descriptions performed during the course of forestry surveys in South and North Tyrol (Italy and Austria, respectively). The r.geomorphon extension module for the open source geographic information system GRASS GIS applies a pattern recognition algorithm to delineate landform elements based on an input DEM. For each raster cell it computes and characterizes the visible neighborhood using line-of-sight calculations and then applies a lookup-table to classify the raster cell into one of ten landform elements (flat, peak, ridge, shoulder, slope, spur, hollow, footslope, valley and pit). The input parameter search radius (L) represents the maximum number of pixels for line-of-sight calculation, resulting in landforms larger than L to be split into landform components. The use of these visibility calculations makes this landform delineation approach suitable for comparison with the landform descriptions of soil surveyors, as their spatial perception of the landscape surrounding a soil profile site certainly influences their classification of the landform on which the profile is situated (aided by additional information such as topographic maps and aerial images). Variation of the L-value furthermore presents the opportunity to mimic the different scales at which surveyors describe soil profile locations. We first illustrate the use of r.geomorphon for site descriptions using exemplary artificial elevation profiles resembling typic catenas at different scales (L-values). We then compare the results of a landform element map computed with r.geomorphon to the relief descriptions in the test dataset. We link the surveyors' landform classification to the computed landform elements. Using a multi-scale approach we characterize raster cell locations in a way similar to the micro-, meso- and macroscale definitions used in soil survey, resulting in so-called geomorphon-signatures, such as "pit (meso-scale) located on a ridge (macro-scale)". We investigate which ranges of L-values best represent the different observation-scales as noted by soil surveyors and discuss the impacts of using a large dataset of profile location descriptions performed by different surveyors. Issues that arise are possible individual differences in landscape structure perception, but also questions regarding the accuracy of position and resulting topographic measurements in soil profile site description.

Some History and Accomplishments of the IUSS

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Hartemink, Alfred E.

2013-04-01

The International Society of Soil Science (ISSS) was founded in 1924 in Rome, Italy, by European agro-geologists who were interested in establishing standardized methods of soil analysis and soil classification. It was admitted as a Union member of the International Council for Science (ICSU) in 1993 and was restructured into the International Union of Soil Sciences (IUSS) in 1998. The objectives of the IUSS are to promote all branches of soil science, and to support all soil scientists across the world in the pursuit of their activities. The IUSS has encouraged international exchanges of ideas and collaborations through the organization of international congresses, known as the World Congress of Soil Science. A total of 19 international congresses have been organized, with eight of these congresses held in Europe, five in the Americas, three in Asia, two in Australia, and one in Africa. The 20th congress will be held in Korea in 2014. The IUSS maintains a website (www.iuss.org) since 2001 with a variety of information about soils, publishes twice per year a Bulletin (since 1952) and publishes a monthly electronic newsletter (IUSS Alert) since 2005. The IUSS initiated the Soil Map of the World, which was prepared in the 1960s and 1970s and a whole range of other scientific initiatives, publications and cooperating journals. Divisions, commissions, working groups and standing committees have been established to deal with all aspects of soil science and its applications. There are four divisions (Division 1 - Soil in Space and Time, Division 2 - Soil properties and processes, Division 3 - Soil Use and Management, and Division 4 - The Role of Soils in Sustaining Society and the Environment). Each division is further divided into five or six commissions. In addition, there are eight active working groups (Acid Sulphate Soils, Cryosols, Digital Soil Mapping, International Actions for the Sustainable Use of Soils, Land Degradation, World Reference Base, Forest soils, and Urban Soils) and three standing committees (Committee on awards and prizes, Committee on budget and finances, and Committee on statutes and byelaws). Membership in ISSS/IUSS increased from around 550 after WWII to over 60,000 today. The IUSS also provides Honorary Membership to soil scientists who have significant accomplishments in the field; to date 87 soil scientists have been so recognized from all over the globe. The IUSS is the most important global link to the world's leading soil science and soil scientists.

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

Toth, B.; Weynants, M.; Pasztor, L.; Hengl, T.

2017-12-01

Reliable quantitative information on soil hydraulic properties is crucial for modelling hydrological, meteorological, ecological and biological processes of the Critical Zone. Most of the Earth system models need information on soil moisture retention capacity and hydraulic conductivity in the full matric potential range. These soil hydraulic properties can be quantified, but their measurement is expensive and time consuming, therefore measurement-based catchment scale mapping of these soil properties is not possible. The increasing availability of soil information and methods describing relationships between simple soil characteristics and soil hydraulic properties provide the possibility to derive soil hydraulic maps based on spatial soil datasets and pedotransfer functions (PTFs). Over the last decade there has been a significant development in preparation of soil hydraulic maps. Spatial datasets on model parameters describing the soil hydraulic processes have become available for countries, continents and even for the whole globe. Our aim is to present European soil hydraulic maps, show their performance, highlight their advantages and drawbacks, and propose possible ways to further improve the performance of those.

Intrusive Rock Database for the Digital Geologic Map of Utah

USGS Publications Warehouse

Nutt, C.J.; Ludington, Steve

2003-01-01

Digital geologic maps offer the promise of rapid and powerful answers to geologic questions using Geographic Information System software (GIS). Using modern GIS and database methods, a specialized derivative map can be easily prepared. An important limitation can be shortcomings in the information provided in the database associated with the digital map, a database which is often based on the legend of the original map. The purpose of this report is to show how the compilation of additional information can, when prepared as a database that can be used with the digital map, be used to create some types of derivative maps that are not possible with the original digital map and database. This Open-file Report consists of computer files with information about intrusive rocks in Utah that can be linked to the Digital Geologic Map of Utah (Hintze et al., 2000), an explanation of how to link the databases and map, and a list of references for the databases. The digital map, which represents the 1:500,000-scale Geologic Map of Utah (Hintze, 1980), can be obtained from the Utah Geological Survey (Map 179DM). Each polygon in the map has a unique identification number. We selected the polygons identified on the geologic map as intrusive rock, and constructed a database (UT_PLUT.xls) that classifies the polygons into plutonic map units (see tables). These plutonic map units are the key information that is used to relate the compiled information to the polygons on the map. The map includes a few polygons that were coded as intrusive on the state map but are largely volcanic rock; in these cases we note the volcanic rock names (rhyolite and latite) as used in the original sources Some polygons identified on the digital state map as intrusive rock were misidentified; these polygons are noted in a separate table of the database, along with some information about their true character. Fields may be empty because of lack of information from references used or difficulty in finding information. The information in the database is from a variety of sources, including geologic maps at scales ranging from 1:500,000 to 1:24,000, and thesis monographs. The references are shown twice: alphabetically and by region. The digital geologic map of Utah (Hintze and others, 2000) classifies intrusive rocks into only 3 categories, distinguished by age. They are: Ti, Tertiary intrusive rock; Ji, Upper to Middle Jurassic granite to quartz monzonite; and pCi, Early Proterozoic to Late Archean intrusive rock. Use of the tables provided in this report will permit selection and classification of those rocks by lithology and age. This database is a pilot study by the Survey and Analysis Project of the U.S. Geological Survey to characterize igneous rocks and link them to a digital map. The database, and others like it, will evolve as the project continues and other states are completed. We release this version now as an example, as a reference, and for those interested in Utah plutonic rocks.

Preliminary integrated geologic map databases for the United States: Digital data for the geology of southeast Alaska

USGS Publications Warehouse

Gehrels, George E.; Berg, Henry C.

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set of 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Digital Data for the reconnaissance geologic map for the Kuskokwim Bay Region of Southwest Alaska

USGS Publications Warehouse

Wilson, Frederic H.; Hults, Chad P.; Mohadjer, Solmaz; Coonrad, Warren L.; Shew, Nora B.; Labay, Keith A.

2008-01-01

INTRODUCTION The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Analyzing spatial variability of soil properties in the urban park before and after reconstruction to support decision-making in landscaping

NASA Astrophysics Data System (ADS)

Romzaikina, Olga; Vasenev, Viacheslav; Khakimova, Rita

2017-04-01

On-going urbanization stresses a necessity for structural and aesthetically organized urban landscapes to improve citizen's life quality. Urban soils and vegetation are the main components of urban ecosystems. Urban greenery regulates the climate, controls and air quality and supports biodiversity in urban areas. Soils play a key role in supporting urban greenery. However, soils of urban parks also perform other important environmental functions. Urban soils are influenced by a variety of environmental and anthropogenic factors and, in the result, are highly heterogeneous and dynamic. Reconstructions of green zones and urban parks, usually occurring in cities, alter soil properties. Analyzing spatial variability and dynamics of soil properties is important to support decision-making in landscaping. Therefore, the research aimed to analyze the spatial distribution of the key soil properties (acidity, soil organic carbon (SOC) and nutrient contents) in the urban park before and after reconstruction to support decision-making in selecting ornamental plants for landscaping. The research was conducted in the urban park named after Artyom Borovik in Moscow before (2012) and after (2014) the reconstruction. Urban soil's properties maps for both periods were created by interpolation of the field data. The observed urban soils included recreazems, urbanozems and constuctozems. Before the reconstruction soils were sampled using the uniform design (the net with 100 m side and key plots with 50m size). After the reconstructions the additional samples were collected at locations, where the land cover and functional zones changed in a result of the reconstruction.We sample from the depths 0-30, 30-50 and 50-100 cm. The following soil properties were measured: pH, SOC, K2O and P2O5. The maps of the analyzed properties were developed using open QGIS2.4 software by IDW. The vegetation in the park was examined using the scale of the visual assessment. The results of the visual assessment were processed using QGIS2.4 and the maps of the vegetation condition were created. High spatial variability was shown for observed soil properties with the highest variance reported for nutrient concentrations. High heterogeneity in P2O5 and K2O was obtained both in topsoil and subsoil, before and after reconstruction. We showed that average concentrations of P2O5 and K2O were correspondingly above and below legal threshold taken for the Moscow city. In result of the reconstruction the pH has changed from slightly acid and acidic to neutral and slightly alkaline. The topsoil SOC content has increased in the result of reconstruction but still was below threshold, recommended by municipal regulations. The potassium content and acidity were the main factors, influencing the vegetation condition. The 'weakened' condition of wood vegetation was reported with the lowest values obtained for the Pinus sylvestris, Thuja occidentals and, Sorbus aucuparia. References have developed for planting vegetation. The spatial heterogeneity and high dynamics of urban soils constraints the quantitative assessment of their properties and functions and the use of this information in landscaping. The successful experience of digital soil mapping techniques in urban park allowed solving this problem and highlighted the importance of soil data for creating urban green infrastructure.

Digital geologic map of part of the Thompson Falls 1:100,000 quadrangle, Idaho

USGS Publications Warehouse

Lewis, Reed S.; Derkey, Pamela D.

1999-01-01

The geology of the Thompson Falls 1:100,000 quadrangle, Idaho was compiled by Reed S. Lewis in 1997 onto a 1:100,000-scale greenline mylar of the topographic base map for input into a geographic information system (GIS). The resulting digital geologic map GIS can be queried in many ways to produce a variety of geologic maps. Digital base map data files (topography, roads, towns, rivers and lakes, etc.) are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:100,000 (e.g., 1:62,500 or 1:24,000). The map area is located in north Idaho. This open-file report describes the geologic map units, the methods used to convert the geologic map data into a digital format, the Arc/Info GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet.

One perspective on spatial variability in geologic mapping

USGS Publications Warehouse

Markewich, H.W.; Cooper, S.C.

1991-01-01

This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.

Updating categorical soil maps using limited survey data by Bayesian Markov chain cosimulation.

PubMed

Li, Weidong; Zhang, Chuanrong; Dey, Dipak K; Willig, Michael R

2013-01-01

Updating categorical soil maps is necessary for providing current, higher-quality soil data to agricultural and environmental management but may not require a costly thorough field survey because latest legacy maps may only need limited corrections. This study suggests a Markov chain random field (MCRF) sequential cosimulation (Co-MCSS) method for updating categorical soil maps using limited survey data provided that qualified legacy maps are available. A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. The method indicates the following characteristics: (1) if a soil type indicates no change in an update survey or it has been reclassified into another type that similarly evinces no change, it will be simply reproduced in the updated map; (2) if a soil type has changes in some places, it will be simulated with uncertainty quantified by occurrence probability maps; (3) if a soil type has no change in an area but evinces changes in other distant areas, it still can be captured in the area with unobvious uncertainty. We concluded that Co-MCSS might be a practical method for updating categorical soil maps with limited survey data.

Updating Categorical Soil Maps Using Limited Survey Data by Bayesian Markov Chain Cosimulation

PubMed Central

Dey, Dipak K.; Willig, Michael R.

2013-01-01

Updating categorical soil maps is necessary for providing current, higher-quality soil data to agricultural and environmental management but may not require a costly thorough field survey because latest legacy maps may only need limited corrections. This study suggests a Markov chain random field (MCRF) sequential cosimulation (Co-MCSS) method for updating categorical soil maps using limited survey data provided that qualified legacy maps are available. A case study using synthetic data demonstrates that Co-MCSS can appreciably improve simulation accuracy of soil types with both contributions from a legacy map and limited sample data. The method indicates the following characteristics: (1) if a soil type indicates no change in an update survey or it has been reclassified into another type that similarly evinces no change, it will be simply reproduced in the updated map; (2) if a soil type has changes in some places, it will be simulated with uncertainty quantified by occurrence probability maps; (3) if a soil type has no change in an area but evinces changes in other distant areas, it still can be captured in the area with unobvious uncertainty. We concluded that Co-MCSS might be a practical method for updating categorical soil maps with limited survey data. PMID:24027447

Prediction of Rainfall-Induced Landslides in Tegucigalpa, Honduras, Using a Hydro-Geotechnical Model

NASA Astrophysics Data System (ADS)

Garcia Urquia, Elias; Axelsson, K.

2010-05-01

Central America is constantly being affected by natural hazards. Among these events are hurricanes and earthquakes, capable of triggering landslides that can alter the natural landscape, destroy infrastructure and cause the death of people in the most important settlements of the region. Hurricane Mitch in October of 1998 was of particular interest for the region, since it provoked hundreds of rainfall-induced landslides, mainly in 4 different countries. Studies carried out after Hurricane Mitch have allowed researchers to identify the factors that contribute to slope instability in many vulnerable areas. As Tegucigalpa, Honduras was partially destroyed due to the various landslide and flooding events triggered by this devastating hurricane, various research teams have deepened in their investigations and have proposed measures to mitigate the effects of similar future incidents. A model coupling an infinite-slope analysis and a simple groundwater flow approach can serve as a basis to predict the occurrence of landslides in Tegucigalpa, Honduras as a function of topographic, hydrological and soil variables. A safety map showing the rainfall-triggered landslide risk zones for Tegucigalpa, Honduras is to be created. As opposed to previous safety maps in which only steady-state conditions are studied, this analysis is extended and different steady-state and quasi-dynamic scenarios are considered for comparison. For the purpose of the latter settings, a hydrological analysis that determines the rainfall extreme values and their return periods in Tegucigalpa will account for the influence of rainfall on the groundwater flow and strength of soils. It is known that the spatial distribution of various factors that contribute to the risk of landslides (i.e. soil thickness, conductivity and strength properties; rainfall intensity and duration; root strength; subsurface flow orientation) is hard to determine. However, an effort is done to derive correlations for these parameters based on the existing information (i.e. rainfall data, soil testing data, land-use data). In addition, the spatial data management and manipulation is done by means of a Geographic Information System (GIS). For such purpose, maps of land-use, topography and geology provided by JICA have bee manually digitized and converted into GIS raster maps. The resulting safety map is then validated by comparing it with existing slope-failure-maps that have been created to show the affected areas during Hurricane Mitch. This safety map represents a useful tool in the prevention of landslide-related disasters, as it would be able to point out which segments of the population are at risk as a consequence of the rainfall-slope interaction in Tegucigalpa.

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

NASA Technical Reports Server (NTRS)

Giardino, Marco J.; Haley, Bryan S.

2005-01-01

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously unknown features. All of these applications are pertinent to the goals of site discovery and assessment in cultural resource management.

Digital Geologic Map of the Rosalia 1:100,000 Quadrangle, Washington and Idaho: A Digital Database for the 1990 S.Z. Waggoner Map

USGS Publications Warehouse

Derkey, Pamela D.; Johnson, Bruce R.; Lackaff, Beatrice B.; Derkey, Robert E.

1998-01-01

The geologic map of the Rosalia 1:100,000-scale quadrangle was compiled in 1990 by S.Z. Waggoner of the Washington state Division of Geology and Earth Resources. This data was entered into a geographic information system (GIS) as part of a larger effort to create regional digital geology for the Pacific Northwest. The intent was to provide a digital geospatial database for a previously published black and white paper geologic map. This database can be queried in many ways to produce a variety of geologic maps. Digital base map data files are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:100,000 (e.g., 1:62,500 or 1:24,000) as it has been somewhat generalized to fit the 1:100,000 scale map. The map area is located in eastern Washington and extends across the state border into western Idaho. This open-file report describes the methods used to convert the geologic map data into a digital format, documents the file structures, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. We wish to thank J. Eric Schuster of the Washington Division of Geology and Earth Resources for providing the original stable-base mylar and the funding for it to be scanned. We also thank Dick Blank and Barry Moring of the U.S. Geological Survey for reviewing the manuscript and digital files, respectively.

Mapping tillage operations over peri-urban croplands using a synchronous SPOT4/ASAR ENVISAT pair and soil roughness measurements

NASA Astrophysics Data System (ADS)

Vaudour, Emmanuelle; Baghdadi, Nicolas; Gilliot, Jean-Marc

2014-05-01

Tillage operations (TOs) affect nutrient uptake, carbon sequestration, water and CO2 exchanges in soil, and therefore impact soil ecology together with biophysical processes such as soil erosion, leaching, run-off and infiltration. They are critical for parameterizing complex dynamic models of carbon and nitrogen. This study done in the framework of the Prostock-Gessol3 project presents an approach for mapping TOs of bare agricultural fields over a peri-urban area characterized by conventional tillage system in the western suburbs of Paris (France), combining synchronous SPOT4 and ENVISAT/ASAR images (HH and HV polarizations). Spatial modeling relied on 57 reference within-field areas named 'reference zones' (RZs) homogeneous for their soil properties, constructed in the vicinity of 57 roughness measurement locations and spread across 20 agricultural fields for which TOs were known. Soil roughness expressed as the standard deviation of surface height (Hrms) was estimated on the ground with a fully automatic photogrammetric method based on the processing of a set of overlapping pictures taken from different viewpoints from a simple digital camera all around a rectangular frame. The relationship was studied between the mean backscattering coefficient of the ASAR image and Hrms choosing a limited set of 28 RZs, on which successive random selections of training/validating RZs were then performed; the remaining 29 RZs were kept for validating the final map results. Six supervised per-pixel classifiers were used in order to map 2 TOs classes (seedbed&harrowed and late winter plough) in addition to 4 landuse classes (forest, urban,crops and grass, water bodies): support vector machine with polynomial kernel (pSVM), SVM with radial basis kernel (rSVM), artificial neural network (ANN), Maximum Likelihood (ML), regression tree (RT), and random forests (RF). All 6 classifiers were implemented in a bootstrapping approach in order to assess the uncertainty of map results. The best results were obtained with pSVM for the SPOT4/ASAR pair with producer's and user's mean validation accuracies of 91.7%/89.8% and 73.2%/73.3% for seedbed&harrowed and late winter plough conditions, respectively. Whatever classifier, the SPOT4/ASAR pair appeared to perform better than each of the single images, particularly for late winter plough: producer's and user's mean validation accuracies were 61.6%/53.0% for the single SPOT4 image; 0%/6% for the single ASAR image. About 73% of the validation agricultural fields (79% of the RZs) were correctly predicted in terms of TOs in the best pSVM-derived final map. Final map results could be improved through masking non-agricultural areas with land use identification system layer prior to classifying images. These results show promises for further monitoring of TOs within a crop production campaign, in the perspective of the ESA Sentinel-1/2 time series. Such knowledge of cultural operations is likely to facilitate the mapping of agricultural systems which otherwise proceed from time-consuming surveys to farmers.

Gully erosion: A comparison of contributing factors in two catchments in South Africa

NASA Astrophysics Data System (ADS)

Mararakanye, Ndifelani; Sumner, Paul D.

2017-07-01

Gully erosion is an environmental, agricultural and social problem requiring extensive research and mitigation actions to control. This study assesses the influence of factors contributing to gully erosion using Geographic Information System (GIS) and Information Value (InfVal) statistics from two catchments coded X12 and W55 in the Mpumalanga province of South Africa. Existing spatial data representing contributing factors; soil, geology, vegetation and land use were analyzed. Topographic variables were extracted from a 10 m Digital Elevation Model (DEM) interpolated from map contours, and gullies were mapped from aerial photos with 0.5 m spatial resolution. A zonal approach was used to extract the proportion of gullies in each of the contributing factor classes using GIS software packages, and InfVal weighting was performed to determine the influence of each class. Comparison of the results shows the variation in the level of influence of factors contributing to gully erosion. The findings in catchment X12 support a commonly held assumption that gully formation is influenced by duplex soils underlain by colluvium and alluvial deposits on a lower slope position where overland flow converges and accumulates, resulting in high soil moisture. Gullies were also influenced by soils developed over weathered granite, gneiss and ultramafic rocks. The influence of a granite rock was further highlighted in catchment W55 where there is a variable thickness of very deep Hutton dominant soil form and shallow Lithosols with sandy texture, on an area of moderate to steep slopes where overland flow converges and accumulates, with high stream power in overgrazed grassland. An understanding of these factors will assist future modelling of the vulnerability to gully erosion over a wider geographical area.

Modelling runoff depth and connectivity in commercial vineyards (DO Somontano, Huesca, NE Spain)

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel, , Dr.; Navas, Ana, , Dr.

2015-04-01

Surface runoff, soil redistribution and sediment delivery are non-linear processes that depend on many parameters, and thus, numerical simulation of overland flow, sediments and other solutes connectivity is a complex and non-solved task. Additionally, man-made landscape linear elements (LLEs: unpaved and paved trails, roads, land levelling, irrigation ditches, stone walls, dams, etc.) modify the natural patterns of connectivity. Mediterranean soils have been cultivated for hundreds and thousands of years and landscapes appear intensively modified. Vineyards are one of the most ancient crops in Mediterranean countries and recently in other countries around the World. In this study, we run the IC model of connectivity (Borselli et al., 2008, doi:10.1016/j.catena.2008.07.006) and the water balance DR2-2013© SAGA v1.1 model (López-Vicente et al., 2014, doi:10.1016/j.envsoft.2014.08.025; software freely downloaded at http://digital.csic.es/handle/10261/93543) in a vineyard (26.4 ha) composed by four fields (6.2 ha) and their upslope drainage area. These commercial fields belong to a winery included in the Somontano certificate of origin. All input maps are generated at 5 x 5 m of cell size and the digital elevation model is based on LIDAR technology. The map of connectivity showed the typical spatial pattern of overland flow though values of connectivity varied along the whole map. The average value was -2.65 (sd = -0.62) and within the four vineyards was -2.46 (sd = -0.65). High connectivity appeared in bare soil areas, in the unpaved trail and within some sections of the main pathways. The lowest connectivity appeared in the forest and in small areas within the vineyards. The effective rainfall (ER) that reaches the soils, was 88% on average (384 mm) from the total rainfall depth (436 mm yr-1) and the average initial runoff, before overland flow processes, was 382 mm yr-1 (sd = 31 mm). The ER within the vineyards was 81%. The effective runoff (CQeff) ranged from 0.5 until 985.5 mm yr-1 with an average value of 51.4 mm and 52.4 mm within the vineyards. The corresponding map showed numerous disruptions along the hillslope due to the presence of LLEs and topographic changes. The total depth of annual runoff corresponds to only 28.3% of the total effective rainfall (TER) and 24.9% of the total rainfall depth (TR). Within the vineyards these percentages were of 21.6 and 17.5%. The remaining water associated with the runoff and rainfall events (Waa) meant 71.7% and 63.2% of the TER and TR, respectively, and 78.4 and 63.2% within the vineyards. The average values of Waa were 130 and 189 mm for the whole study area and within the vineyards. The map of the Waa presented a different spatial pattern where the land uses play a more important role than the processes of cumulative overland flow. The highest values of CQeff appeared in April, September, October and November. The joint analysis of the results and the correlation between the predicted values with the IC and DR2 models adds valuable information about the processes of surface water dynamics in hillslopes with cultivated and forested soils.

Acid deposition sensitivity map of the Southern Appalachian Assessment area; Virginia, North Carolina, South Carolina, Tennessee, Georgia, and Alabama

USGS Publications Warehouse

Pepper, John D.; Grosz, Andrew E.; Kress, Thomas H.; Collins, Thomas K.; Kappesser, Gary B.; Huber, Cindy M.; Webb, James R.

1995-01-01

Project Summary: The following digital product represents the Acid Deposition Sensitivity of the Southern Appalachian Assessment Area. Areas having various susceptibilities to acid deposition from air pollution are designated on a three tier ranking in the region of the Southern Appalachian Assessment (SAA). The assessment is being conducted by Federal agencies that are members of the Southern Appalachian Man and Biosphere (SAMAB) Cooperative. Sensitivities to acid deposition, ranked high, medium, and low are assigned on the basis of bedrock compositions and their associated soils, and their capacities to neutralize acid precipitation.

Using Digital Mapping Tool in Ill-Structured Problem Solving

ERIC Educational Resources Information Center

Bai, Hua

2013-01-01

Scaffolding students' problem solving and helping them to improve problem solving skills are critical in instructional design courses. This study investigated the effects of students' uses of a digital mapping tool on their problem solving performance in a design case study. It was found that the students who used the digital mapping tool…

Using Digital Mapping Programs to Augment Student Learning in Social Studies

ERIC Educational Resources Information Center

Chandler, Thomas; An, Heejung

2007-01-01

Thomas Chandler and Heejung An describe how digital mapping technology can be incorporated into community-based K-12 social studies projects. According to Chandler and An, digital mapping can add value to the social studies curriculum by enabling students to better understand the interdependence between the lives of individuals and their…

Surficial materials in the conterminous United States

USGS Publications Warehouse

Soller, David R.; Reheis, Marith C.

2004-01-01

Introduction: The Earth's bedrock is overlain in many places by a loosely compacted and mostly unconsolidated blanket of sediments in which soils commonly are developed. These sediments generally were eroded from underlying rock, and then were transported and deposited. In places, they exceed 1,000 ft (330 m) in thickness. Where the sediment blanket is absent, bedrock is either exposed or has been weathered to produce a residual soil. This map shows the sediments and the weathered, residual material; for ease of discussion, these are referred to here as 'surficial materials.' Certain areas on this map include a significant number of rock outcrops, which cannot be shown at the scale of the map; this is noted in the 'Description of Map Units' section. Most daily human activities occur on or near the Earth's surface. Homeowners, communities, and governments can make improved decisions about hazard, resource, and environmental issues, when they understand the nature of surficial materials and how they vary from place to place. For example, are the surficial materials upon which a home is built stable enough to resist subsidence or lateral movement during an earthquake? Do these materials support a ground water resource adequate for new homes? Can they adequately filter contaminants and protect buried aquifers both in underlying sediments and in bedrock? Are they suitable for development of a new wetland? Where can we find materials suitable for aggregate? The USGS National Cooperative Geologic Mapping Program (NCGMP) works with the State geological surveys to identify priority areas for mapping of surficial materials (for example, in areas of complex and poorly understood deposits of various sediment types, where metropolitan areas are experiencing rapid growth). To help establish these priorities, a modern, synoptic overview of the geology is needed. This map represents an overview of our current knowledge of the composition and distribution of surficial materials in the conterminous United States. (The map covers only the conterminous U.S. because similar geologic information in digital form was not readily available for Alaska and Hawaii.) The best available map has been a highly generalized depiction at 1:7,500,000-scale (about 120 miles to the inch), prepared for the USGS National Atlas (Hunt, 1979; 1986). This map is compiled at a slightly more detailed scale (about 80 miles to the inch) than Hunt (1979; 1986). We used digital methods, which enabled us to rapidly incorporate the variety of source maps available to us. State-scale geologic maps from the western United States were brought directly into this map, without expending the time needed to resolve interpretive differences among them. Therefore, abrupt changes in surficial materials are indicated along many State boundaries. This of course is an artifact of our compilation technique, and a limitation on its utility. However, this approach supports the basic premise of the map -- to provide an overview of surficial materials, and to identify areas where additional work may be needed in order to resolve scientific issues that can, in turn, lead to improved mapping.

Cartographic services contract...for everything geographic

USGS Publications Warehouse

,

2003-01-01

The U.S. Geological Survey's (USGS) Cartographic Services Contract (CSC) is used to award work for photogrammetric and mapping services under the umbrella of Architect-Engineer (A&E) contracting. The A&E contract is broad in scope and can accommodate any activity related to standard, nonstandard, graphic, and digital cartographic products. Services provided may include, but are not limited to, photogrammetric mapping and aerotriangulation; orthophotography; thematic mapping (for example, land characterization); analog and digital imagery applications; geographic information systems development; surveying and control acquisition, including ground-based and airborne Global Positioning System; analog and digital image manipulation, analysis, and interpretation; raster and vector map digitizing; data manipulations (for example, transformations, conversions, generalization, integration, and conflation); primary and ancillary data acquisition (for example, aerial photography, satellite imagery, multispectral, multitemporal, and hyperspectral data); image scanning and processing; metadata production, revision, and creation; and production or revision of standard USGS products defined by formal and informal specification and standards, such as those for digital line graphs, digital elevation models, digital orthophoto quadrangles, and digital raster graphics.

Application of multispectral remote sensing to soil survey research in Indiana

NASA Technical Reports Server (NTRS)

Zachary, A. L.; Cipra, J. E.; Diderickson, R. I.; Kristof, S. J.; Baumgardner, M. F.

1972-01-01

Computer-implemented mappings based on spectral properties of bare soil surfaces were compared with mapping units of interest to soil surveyors. Some soil types could be differentiated by their spectral properties. In other cases, soils with similar surface colors and textures could not be distinguished spectrally. The spectral maps seemed useful for delineating boundaries between soils in many cases.

A Double Perturbation Method for Reducing Dynamical Degradation of the Digital Baker Map

NASA Astrophysics Data System (ADS)

Liu, Lingfeng; Lin, Jun; Miao, Suoxia; Liu, Bocheng

2017-06-01

The digital Baker map is widely used in different kinds of cryptosystems, especially for image encryption. However, any chaotic map which is realized on the finite precision device (e.g. computer) will suffer from dynamical degradation, which refers to short cycle lengths, low complexity and strong correlations. In this paper, a novel double perturbation method is proposed for reducing the dynamical degradation of the digital Baker map. Both state variables and system parameters are perturbed by the digital logistic map. Numerical experiments show that the perturbed Baker map can achieve good statistical and cryptographic properties. Furthermore, a new image encryption algorithm is provided as a simple application. With a rather simple algorithm, the encrypted image can achieve high security, which is competitive to the recently proposed image encryption algorithms.

Revisiting Melton: Analyzing the correlation structure of geomorphological and climatological parameters

NASA Astrophysics Data System (ADS)

Carothers, R. A.; Sangireddy, H.; Passalacqua, P.

2013-12-01

In his expansive 1957 study of over 80 basins in Arizona, Colorado, New Mexico, and Utah, Mark Melton measured key morphometric, soil, land cover, and climatic parameters [Melton, 1957]. He identified correlations between morphological parameters and climatic regimes in an attempt to characterize the geomorphology of the basin as a function of climate and vegetation. Using modern techniques such as high resolution digital terrain models in combination with high spatial resolution weather station records, vector soil maps, seamless raster geological data, and land cover vector maps, we revisit Melton's 1957 dataset with the following hypotheses: (1) Patterns of channelization carry strong, codependent signatures in the form of statistical correlations of rainfall variability, soil type, and vegetation patterns. (2) Channelization patterns reflect the erosion processes on sub-catchment scale and the subsequent processes of vegetation recovery and gullying. In order to characterize various topographic and climatic parameters, we obtain elevation and land cover data from the USGS National Elevation dataset, climate data from the Western Regional Climate Center and PRISM climate group database, and soil type from the USDA STATSGO soil database. We generate a correlative high resolution database on vegetation, soil cover, lithology, and climatology for the basins identified by Melton in his 1957 study. Using the GeoNet framework developed by Passalacqua et al. [2010], we extract various morphological parameters such as slope, drainage density, and stream frequency. We also calculate metrics for patterns of channelization such as number of channelized pixels in a basin and channel head density. In order to understand the correlation structure between climate and morphological variables, we compute the Pearson's correlation coefficient similar to Melton's analysis and also explore other statistical procedures to characterize the feedbacks between these variables. By identifying the differences in Melton's and our results, we address the influence of climate over the degree of channel dissection in the landscape. References: Melton, M. A. (1957). An analysis of the relations among elements of climate, surface properties, and geomorphology (No. CU-TR-11). COLUMBIA UNIV NEW YORK Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface (2003-2012), 115(F1). PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 4 Feb 2004 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. U.S. General Soil Map (STATSGO2). Available online at http://soildatamart.nrcs.usda.gov USGS National Map Viewer, United States Geological Survey. Web. 10 June 2013. http://viewer.nationalmap.gov/viewer/ Western U.S. Historical Climate Summaries, Western Regional Climate Group, 2013. Web. 10 June 2013. http://www.wrcc.dri.edu/Climsum.html

Successful Teaching, Learning, and Use of Digital Mapping Technology in Mazvihwa, Rural Zimbabwe

NASA Astrophysics Data System (ADS)

Eitzel Solera, M. V.; Madzoro, S.; Solera, J.; Mhike Hove, E.; Changarara, A.; Ndlovu, D.; Chirindira, A.; Ndlovu, A.; Gwatipedza, S.; Mhizha, M.; Ndlovu, M.

2016-12-01

Participatory mapping is now a staple of community-based work around the world. Particularly for indigenous and rural peoples, it can represent a new avenue for environmental justice and can be a tool for culturally appropriate management of local ecosystems. We present a successful example of teaching and learning digital mapping technology in rural Zimbabwe. Our digital mapping project is part of the long-term community-based participatory research of The Muonde Trust in Mazvihwa, Zimbabwe. By gathering and distributing local knowledge and also bringing in visitors to share knowledge, Muonde has been able to spread relevant information among rural farmers. The authors were all members of Muonde or were Muonde's visitors, and were mentors and learners of digital mapping technologies at different times. Key successful characteristics of participants included patience, compassion, openness, perseverance, respect, and humility. Important mentoring strategies included: 1) instruction in Shona and in English, 2) locally relevant examples, assignments, and analogies motivated by real needs, 3) using a variety of teaching methods for different learning modalities, 4) building on and modifying familiar teaching methods, and 5) paying attention to the social and relational aspects of teaching and learning. The Muonde mapping team has used their new skills for a wide variety of purposes, including: identifying, discussing, and acting on emerging needs; using digital mapping for land-use and agropastoral planning; and using mapping as a tool for recording and telling important historical and cultural stories. Digital mapping has built self-confidence as well as providing employable skills and giving Muonde more visibility to other local and national non-governmental organizations, utility companies, and educational institutions. Digital mapping, as taught in a bottom-up, collaborative way, has proven to be both accessible and of enormous practical use to rural Zimbabweans.

Geologic map of the eastern part of the Challis National Forest and vicinity, Idaho

USGS Publications Warehouse

Wilson, A.B.; Skipp, B.A.

1994-01-01

The paper version of the Geologic Map of the eastern part of the Challis National Forest and vicinity, Idaho was compiled by Anna Wilson and Betty Skipp in 1994. The geology was compiled on a 1:250,000 scale topographic base map. TechniGraphic System, Inc. of Fort Collins Colorado digitized this map under contract for N.Shock. G.Green edited and prepared the digital version for publication as a GIS database. The digital geologic map database can be queried in many ways to produce a variety of geologic maps.

Surficial Geologic Map of the Great Smoky Mountains National Park Region, Tennessee and North Carolina

USGS Publications Warehouse

Southworth, Scott; Schultz, Art; Denenny, Danielle; Triplett, James

2004-01-01

The Surficial Geology of the Great Smoky Mountains National Park Region, Tennessee and North Carolina was mapped from 1993 to 2003 under a cooperative agreement between the U.S. Geological Survey (USGS) and the National Park Service (NPS). This 1:100,000-scale digital geologic map was compiled from 2002 to 2003 from unpublished field investigations maps at 1:24,000-scale. The preliminary surficial geologic data and map support cooperative investigations with NPS, the U.S. Natural Resource Conservation Service, and the All Taxa Biodiversity Inventory (http://www.dlia.org/) (Southworth, 2001). Although the focus of our work was within the Park, the geology of the surrounding area is provided for regional context. Surficial deposits document the most recent part of the geologic history of this part of the western Blue Ridge and eastern Tennessee Valley of the Valley and Ridge of the Southern Appalachians. Additionally, there is great variety of surficial materials, which directly affect the different types of soil and associated flora and fauna. The surficial deposits accumulated over tens of millions of years under varied climatic conditions during the Cenozoic era and resulted from a composite of geologic processes.

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.

Flexible, reconfigurable, power efficient transmitter and method

NASA Technical Reports Server (NTRS)

Bishop, James W. (Inventor); Zaki, Nazrul H. Mohd (Inventor); Newman, David Childress (Inventor); Bundick, Steven N. (Inventor)

2011-01-01

A flexible, reconfigurable, power efficient transmitter device and method is provided. In one embodiment, the method includes receiving outbound data and determining a mode of operation. When operating in a first mode the method may include modulation mapping the outbound data according a modulation scheme to provide first modulation mapped digital data, converting the first modulation mapped digital data to an analog signal that comprises an intermediate frequency (IF) analog signal, upconverting the IF analog signal to produce a first modulated radio frequency (RF) signal based on a local oscillator signal, amplifying the first RF modulated signal to produce a first RF output signal, and outputting the first RF output signal via an isolator. In a second mode of operation method may include modulation mapping the outbound data according a modulation scheme to provide second modulation mapped digital data, converting the second modulation mapped digital data to a first digital baseband signal, conditioning the first digital baseband signal to provide a first analog baseband signal, modulating one or more carriers with the first analog baseband signal to produce a second modulated RF signal based on a local oscillator signal, amplifying the second RF modulated signal to produce a second RF output signal, and outputting the second RF output signal via the isolator. The digital baseband signal may comprise an in-phase (I) digital baseband signal and a quadrature (Q) baseband signal.

Digital Mapping Techniques '07 - Workshop Proceedings

USGS Publications Warehouse

Soller, David R.

2008-01-01

The Digital Mapping Techniques '07 (DMT'07) workshop was attended by 85 technical experts from 49 agencies, universities, and private companies, including representatives from 27 state geological surveys. This year's meeting, the tenth in the annual series, was hosted by the South Carolina Geological Survey, from May 20-23, 2007, on the University of South Carolina campus in Columbia, South Carolina. Each DMT workshop has been coordinated by the U.S. Geological Survey's National Geologic Map Database Project and the Association of American State Geologists (AASG). As in previous year's meetings, the objective was to foster informal discussion and exchange of technical information, principally in order to develop more efficient methods for digital mapping, cartography, GIS analysis, and information management. At this meeting, oral and poster presentations and special discussion sessions emphasized: 1) methods for creating and publishing map products (here, 'publishing' includes Web-based release); 2) field data capture software and techniques, including the use of LIDAR; 3) digital cartographic techniques; 4) migration of digital maps into ArcGIS Geodatabase format; 5) analytical GIS techniques; and 6) continued development of the National Geologic Map Database.

Determining and representing width of soil boundaries using electrical conductivity and MultiGrid

NASA Astrophysics Data System (ADS)

Greve, Mogens Humlekrog; Greve, Mette Balslev

2004-07-01

In classical soil mapping, map unit boundaries are considered crisp even though all experienced survey personnel are aware of the fact, that soil boundaries really are transition zones of varying width. However, classification of transition zone width on site is difficult in a practical survey. The objective of this study is to present a method for determining soil boundary width and a way of representing continuous soil boundaries in GIS. A survey was performed using the non-contact conductivity meter EM38 from Geonics Inc., which measures the bulk Soil Electromagnetic Conductivity (SEC). The EM38 provides an opportunity to classify the width of transition zones in an unbiased manner. By calculating the spatial rate of change in the interpolated EM38 map across the crisp map unit delineations from a classical soil mapping, a measure of transition zone width can be extracted. The map unit delineations are represented as transition zones in a GIS through a concept of multiple grid layers, a MultiGrid. Each layer corresponds to a soil type and the values in a layer represent the percentage of that soil type in each cell. As a test, the subsoil texture was mapped at the Vindum field in Denmark using both the classical mapping method with crisp representation of the boundaries and the new map with MultiGrid and continuous boundaries. These maps were then compared to an independent reference map of subsoil texture. The improvement of the prediction of subsoil texture, using continuous boundaries instead of crisp, was in the case of the Vindum field, 15%.

Research on the Application of Rapid Surveying and Mapping for Large Scare Topographic Map by Uav Aerial Photography System

NASA Astrophysics Data System (ADS)

Gao, Z.; Song, Y.; Li, C.; Zeng, F.; Wang, F.

2017-08-01

Rapid acquisition and processing method of large scale topographic map data, which relies on the Unmanned Aerial Vehicle (UAV) low-altitude aerial photogrammetry system, is studied in this paper, elaborating the main work flow. Key technologies of UAV photograph mapping is also studied, developing a rapid mapping system based on electronic plate mapping system, thus changing the traditional mapping mode and greatly improving the efficiency of the mapping. Production test and achievement precision evaluation of Digital Orth photo Map (DOM), Digital Line Graphic (DLG) and other digital production were carried out combined with the city basic topographic map update project, which provides a new techniques for large scale rapid surveying and has obvious technical advantage and good application prospect.

Remote sensing of soils, land forms, and land use in the northern great plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The fields are cultivated or the planted crop has not yet masked soil surface features. Soil limitations in 59 percent of the field of the flight line could be mapped using the above criteria. The remaining fields cannot be mapped because the vegetation or growing crops do not express features related to soil differences. This suggests that imagery from more than one year is necessary to map completely the soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations because the vegetative cover masked the soil surface and does not reflect soil differences.

Surface Rupture Map of the 2002 M7.9 Denali Fault Earthquake, Alaska: Digital Data

USGS Publications Warehouse

Haeussler, Peter J.

2009-01-01

The November 3, 2002, Mw7.9 Denali Fault earthquake produced about 340 km of surface rupture along the Susitna Glacier Thrust Fault and the right-lateral, strike-slip Denali and Totschunda Faults. Digital photogrammetric methods were primarily used to create a 1:500-scale, three-dimensional surface rupture map, and 1:6,000-scale aerial photographs were used for three-dimensional digitization in ESRI's ArcMap GIS software, using Leica's StereoAnalyst plug in. Points were digitized 4.3 m apart, on average, for the entire surface rupture. Earthquake-induced landslides, sackungen, and unruptured Holocene fault scarps on the eastern Denali Fault were also digitized where they lay within the limits of air photo coverage. This digital three-dimensional fault-trace map is superior to traditional maps in terms of relative and absolute accuracy, completeness, and detail and is used as a basis for three-dimensional visualization. Field work complements the air photo observations in locations of dense vegetation, on bedrock, or in areas where the surface trace is weakly developed. Seventeen km of the fault trace, which broke through glacier ice, were not digitized in detail due to time constraints, and air photos missed another 10 km of fault rupture through the upper Black Rapids Glacier, so that was not mapped in detail either.

Preliminary integrated geologic map databases for the United States: Digital data for the reconnaissance bedrock geologic map for the northern Alaska peninsula area, southwest Alaska

USGS Publications Warehouse

,

2006-01-01

he growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Preliminary integrated geologic map databases for the United States: Digital data for the reconnaissance geologic map of the western Aleutian Islands, Alaska

USGS Publications Warehouse

,

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO Exportfiles/ and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Preliminary integrated geologic map databases for the United States: Digital data for the generalized bedrock geologic map, Yukon Flats region, east-central Alaska

USGS Publications Warehouse

Till, Alison B.; Dumoulin, Julie A.; Phillips, Jeffrey D.; Stanley, Richard G.; Crews, Jessie

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Preliminary integrated geologic map databases for the United States: Digital data for the reconnaissance geologic map of the lower Yukon River region, Alaska

USGS Publications Warehouse

,

2006-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Spatial differences in drought vulnerability

NASA Astrophysics Data System (ADS)

Perčec Tadić, M.; Cindić, K.; Gajić-Čapka, M.; Zaninović, K.

2012-04-01

Drought causes the highest economic losses among all hydro-meteorological events in Croatia. It is the most frequent hazard, which produces the highest damages in the agricultural sector. The climate assessment in Croatia according to the aridity index (defined as the ratio of precipitation and potential evapotranspiration) shows that the susceptibility to desertification is present in the warm part of the year and it is mostly pronounced in the Adriatic region and the eastern Croatia lowland. The evidence of more frequent extreme drought events in the last decade is apparent. These facts were motivation to study the drought risk assessment in Croatia. One step in this issue is the construction of the vulnerability map. This map is a complex combination of the geomorphologic and climatological inputs (maps) that are presumed to be natural factors which modify the amount of moisture in the soil. In this study, the first version of the vulnerability map is followed by the updated one that additionally includes the soil types and the land use classes. The first input considered is the geomorphologic slope angle calculated from the digital elevation model (DEM). The SRTM DEM of 100 m resolution is used. The steeper slopes are more likely to lose water and to become dryer. The second climatological parameter, the solar irradiation map, gives for the territory of Croatia the maximum irradiation on the coast. The next meteorological parameter that influences the drought vulnerability is precipitation which is in this assessment included through the precipitation variability expressed by the coefficient of variation. Larger precipitation variability is related with the higher drought vulnerability. The preliminary results for Croatia, according to the recommended procedure in the framework of Drought Management Centre for Southeastern Europe (DMCSEE project), show the most sensitive areas to drought in the southern Adriatic coast and eastern continental lowland.

Microrelief and vegetation as the factors of spatial redistribution of nutrients in the soils of forest ecosystems

NASA Astrophysics Data System (ADS)

Chernitsova, Olga; Krechetov, Pavel

2017-04-01

The study is aimed at the identifying factors and mechanisms controlling the redistribution of nutrients in the profile of sod-podzolic soils (Umbric Albeluvisols Abruptic in WRB, 2006). The data of chemical analyzes of soil samples of soddy-pale-podzolic soils under mixed coniferous-deciduous forests, picked from the genetic horizons of 28 soil profiles up to the depth of 120-150 cm in the key area with a polygonal-block microrelief (58.39°N, 56.52°E) were used. Soil profiles were placed at the key area considering vegetation and microrelief. Samples were analyzed for humus content, available forms of N, P, K, Ca, Mg and soil texture. Published data on the capacity and the structure of biogeochemical cycling in forest phytocenoses of different ages in the southern taiga were summarized. Field sketches were used for the construction of the digital elevation model of the key area and for plotting the vegetation map showing the crowns' projections of trees and shrubs of different species. Using spatial interpolation in GIS, series of schematic maps were created that characterize the depth of the lower boundary of genetic horizons and their thickness, as well as the texture of the different soil horizons, humus content and distribution of nutrients at different depths. These schematic maps were analyzed for patterns of radial and lateral differentiation of all examined features. Pronounced textural differentiation of soils of micro-elevations and poor textural differentiation of soil of micro-depressions are revealed. It is shown that in the soils with the positions from micro-elevations through flat surfaces to micro-depressions the humus content in the upper layers (horizon A) increases 1.6-1.7 times, the content of nitrogen ‒ 1.4-1.5, phosphorus ‒ 2.6 8.4, calcium and magnesium cations ‒ 1.8-2.9 times. This differentiation in nutrients' content is coming along with the settlement of more demanding to soil fertility plants in micro-depressions. Also the bimodal distribution of the available forms of potassium, phosphorus, calcium, magnesium in the soil profile was revealed. The first maximum of nutrients content is detected in the humus-accumulative horizon A, the second - in the illuvial horizon Bt. The eluvial horizons EL are characterized by the minimum values. Considering the thickness of soil horizons, supplies of available forms of phosphorus, potassium, calcium and magnesium were estimated, which are 1.5-2.5 times higher in deeper soil horizons than in the upper ones. The complex ecological and geochemical structure of forest ecosystems is regulated by both the lateral additional supply of mobile chemical compounds by the surface and subsurface runoff, including melted snow water, as well as the peculiarities of biogeochemical cycling (the age of the forest, the penetration depth of suction roots of various species of trees, the chemical composition of the litter).

Cross-disciplinary Undergraduate Research: A Case Study in Digital Mapping, western Ireland

NASA Astrophysics Data System (ADS)

Whitmeyer, S. J.; de Paor, D. G.; Nicoletti, J.; Rivera, M.; Santangelo, B.; Daniels, J.

2008-12-01

As digital mapping technology becomes ever more advanced, field geologists spend a greater proportion of time learning digital methods relative to analyzing rocks and structures. To explore potential solutions to the time commitment implicit in learning digital field methods, we paired James Madison University (JMU) geology majors (experienced in traditional field techniques) with Worcester Polytechnic Institute (WPI) engineering students (experienced in computer applications) during a four week summer mapping project in Connemara, western Ireland. The project consisted of approximately equal parts digital field mapping (directed by the geology students), and lab-based map assembly, evaluation and formatting for virtual 3D terrains (directed by the engineering students). Students collected geologic data in the field using ruggedized handheld computers (Trimble GeoExplorer® series) with ArcPAD® software. Lab work initially focused on building geologic maps in ArcGIS® from the digital field data and then progressed to developing Google Earth-based visualizations of field data and maps. Challenges included exporting GIS data, such as locations and attributes, to KML tags for viewing in Google Earth, which we accomplished using a Linux bash script written by one of our engineers - a task outside the comfort zone of the average geology major. We also attempted to expand the scope of Google Earth by using DEMs of present-day geologically-induced landforms as representative models for paleo-geographic reconstructions of the western Ireland field area. As our integrated approach to digital field work progressed, we found that our digital field mapping produced data at a faster rate than could be effectively managed during our allotted time for lab work. This likely reflected the more developed methodology for digital field data collection, as compared with our lab-based attempts to develop new methods for 3D visualization of geologic maps. However, this experiment in cross-disciplinary undergraduate research was a big success, with an enthusiastic interchange of expertise between undergraduate geology and engineering students that produced new, cutting-edge methods for visualizing geologic data and maps.

Preparation and Presentation of Digital Maps in Raster Format

USGS Publications Warehouse

Edwards, K.; Batson, R.M.

1980-01-01

A set of algorithms has been developed at USGS Flagstaff for displaying digital map data in raster format. The set includes: FILLIN, which assigns a specified attribute code to units of a map which have been outlined on a digitizer and converted to raster format; FILBND, which removes the outlines; ZIP, which adds patterns to the map units; and COLOR, which provides a simplified process for creating color separation plates for either photographic or lithographic reproduction. - Authors

Evaluation of using digital gravity field models for zoning map creation

NASA Astrophysics Data System (ADS)

Loginov, Dmitry

2018-05-01

At the present time the digital cartographic models of geophysical fields are taking a special significance into geo-physical mapping. One of the important directions to their application is the creation of zoning maps, which allow taking into account the morphology of geophysical field in the implementation automated choice of contour intervals. The purpose of this work is the comparative evaluation of various digital models in the creation of integrated gravity field zoning map. For comparison were chosen the digital model of gravity field of Russia, created by the analog map with scale of 1 : 2 500 000, and the open global model of gravity field of the Earth - WGM2012. As a result of experimental works the four integrated gravity field zoning maps were obtained with using raw and processed data on each gravity field model. The study demonstrates the possibility of open data use to create integrated zoning maps with the condition to eliminate noise component of model by processing in specialized software systems. In this case, for solving problem of contour intervals automated choice the open digital models aren't inferior to regional models of gravity field, created for individual countries. This fact allows asserting about universality and independence of integrated zoning maps creation regardless of detail of a digital cartographic model of geo-physical fields.

Forest construction infrastructures for the prevision, suppression, and protection before and after forest fires

NASA Astrophysics Data System (ADS)

Drosos, Vasileios C.; Giannoulas, Vasileios J.; Daoutis, Christodoulos

2014-08-01

Climatic changes cause temperature rise and thus increase the risk of forest fires. In Greece the forests with the greatest risk to fire are usually those located near residential and tourist areas where there are major pressures on land use changes, while there are no currently guaranteed cadastral maps and defined title deeds because of the lack of National and Forest Cadastre. In these areas the deliberate causes of forest fires are at a percentage more than 50%. This study focuses on the forest opening up model concerning both the prevention and suppression of forest fires. The most urgent interventions that can be done after the fire destructions is also studied in relation to soil protection constructions, in order to minimize the erosion and the torrential conditions. Digital orthophotos were used in order to produce and analyze spatial data using Geographical Information Systems (GIS). Initially, Digital Elevation Models were generated, based on photogrammetry and forest areas as well as the forest road network were mapped. Road density, road distance, skidding distance and the opening up percentage were accurately measured for a forest complex. Finally, conclusions and suggestions have been drawn about the environmental compatibility of forest protection and wood harvesting works. In particular the contribution of modern technologies such as digital photogrammetry, remote sensing and Geographical Information Systems is very important, allowing reliable, effective and fast process of spatial analysis contributing to a successful planning of opening up works and fire protection.

Digital Data for the reconnaissance geologic map for Prince William Sound and the Kenai Peninsula, Alaska

USGS Publications Warehouse

Wilson, Frederic H.; Hults, Chad P.; Labay, Keith A.; Shew, Nora B.

2007-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. The files named __geol contain geologic polygons and line (contact) attributes; files named __fold contain fold axes; files named __lin contain lineaments; and files named __dike contain dikes as lines. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

Differential effects of fine root morphology on water dynamics in the root-soil interface

NASA Astrophysics Data System (ADS)

DeCarlo, K. F.; Bilheux, H.; Warren, J.

2017-12-01

Soil water uptake form plants, particularly in the rhizosphere, is a poorly understood question in the plant and soil sciences. Our study analyzed the role of belowground plant morphology on soil structural and water dynamics of 5 different plant species (juniper, grape, maize, poplar, maple), grown in sandy soils. Of these, the poplar system was extended to capture drying dynamics. Neutron radiography was used to characterize in-situ dynamics of the soil-water-plant system. A joint map of root morphology and soil moisture was created for the plant systems using digital image processing, where soil pixels were connected to associated root structures via minimum distance transforms. Results show interspecies emergent behavior - a sigmoidal relationship was observed between root diameter and bulk/rhizosphere soil water content difference. Extending this as a proxy for extent of rhizosphere development with root age, we observed a logistic growth pattern for the rhizosphere: minimal development in the early stages is superceded by rapid onset of rhizosphere formation, which then stabilizes/decays with the likely root suberization. Dynamics analysis of water content differences between the root/rhizosphere, and rhizosphere/bulk soil interface highlight the persistently higher water content in the root at all water content and root size ranges. At the rhizosphere/bulk soil interface, we observe a shift in soil water dynamics by root size: in super fine roots, we observe that water content is primarily lower in the rhizosphere under wetter conditions, which then gradually increases to a relatively higher water content under drier conditions. This shifts to a persistently higher rhizosphere water content relative to bulk soil in both wet/dry conditions with increased root size, suggesting that, by size, the finest root structures may contribute the most to total soil water uptake in plants.

Refining Landsat classification results using digital terrain data

USGS Publications Warehouse

Miller, Wayne A.; Shasby, Mark

1982-01-01

 Scientists at the U.S. Geological Survey's Earth Resources Observation systems (EROS) Data Center have recently completed two land-cover mapping projects in which digital terrain data were used to refine Landsat classification results. Digital ter rain data were incorporated into the Landsat classification process using two different procedures that required developing decision criteria either subjectively or quantitatively. The subjective procedure was used in a vegetation mapping project in Arizona, and the quantitative procedure was used in a forest-fuels mapping project in Montana. By incorporating digital terrain data into the Landsat classification process, more spatially accurate landcover maps were produced for both projects.

Digital line graphs from 1:24,000-scale maps

USGS Publications Warehouse

,

1990-01-01

The Earth Science Information Centers (ESIC) distribute digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. Digital cartographic data flles are grouped into four basic types. The first of these, called a Digital Line . Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for a number of ground positions that are usually at regularly spaced intervals. The third type is Land Use and Land Cover digital data, which provides information on nine major classes of land use such as urban, agricultural, or forest as wen as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for all known places, features, and areas in the United States identified by a proper name.

Digital line graphs from 1:100,000-scale maps

USGS Publications Warehouse

,

1989-01-01

The National Cartographic Information Center (NCIC) distributes digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. Digital cartographic data files may be grouped into four basic types. The first of these, called a Digital Line Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second form, called a Digital Elevation Model (OEM), consists of a sampled array of elevations for ground positions that are usually, but not always, at regularly spaced intervals. The third type is Land Use and Land Cover digital data, which provides information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for known places, features, and areas in the United States identified by a proper name.

STATEWIDE MAPPING OF FLORIDA SOIL RADON POTENTIALS VOLUME 2. APPENDICES A-P

EPA Science Inventory

The report gives results of a statewide mapping of Florida soil radon potentials. Statewide maps identify Florida Regions with different levels of soil radon potential. The maps provide scientific estimates of regional radon potentials that can serve as a basis for implementing r...

STATEWIDE MAPPING OF FLORIDA SOIL RADON POTENTIALS VOLUME 1. TECHNICAL REPORT

EPA Science Inventory

The report gives results of a statewide mapping of Florida soil radon potentials. Statewide maps identify Florida Regions with different levels of soil radon potential. The maps provide scientific estimates of regional radon potentials that can serve as a basis for implementing r...

Geophysical characterization of soil moisture spatial patterns in a tillage experiment

NASA Astrophysics Data System (ADS)

Martinez, G.; Vanderlinden, K.; Giráldez, J. V.; Muriel, J. L.

2009-04-01

Knowledge on the spatial soil moisture pattern can improve the characterisation of the hydrological response of either field-plots or small watersheds. Near-surface geophysical methods, such as electromagnetic induction (EMI), provide a means to map such patterns using non-invasive and non-destructive measurements of the soil apparent electrical conductivity (ECa. In this study ECa was measured using an EMI sensor and used to characterize spatially the hydrologic response of a cropped field to an intense shower. The study site is part of a long-term tillage experiment in Southern Spain in which Conventional Tillage (CT), Direct Drilling (DD) and Minimum Tillage (MT) are being evaluated since 1982. Soil ECa was measured before and after a rain event of 115 mm, near the soil surface and at deeper depth (ECas and ECad, respectively) using the EM38-DD EMI sensor. Simultaneously, elevation data were collected at each sampling point to generate a Digital Elevation Model (DEM). Soil moisture during the first survey was close to permanent wilting point and near field capacity during the second survey. For the first survey, both ECas and ECad, were higher in the CT and MT than in the DD plots. After the rain event, rill erosion appeared only in CT and MT plots were soil was uncovered, matching the drainage lines obtained from the DEM. Apparent electrical conductivity increased all over the field plot with higher increments in the DD plots. These plots showed the highest ECas and ECad values, in contrast to the spatial pattern found during the first sampling. Difference maps obtained from the two ECas and ECad samplings showed a clear difference between DD plots and CT and MT plots due to their distinct hydrologic response. Water infiltration was higher in the soil of the DD plots than in the MT and CT plots, as reflected by their ECad increment. Higher ECa increments were observed in the depressions of the terrain, where water and sediments accumulated. On the contrary, the most elevated places of the field showed lower ECa increments. When soil is wet topography dominates the hydrologic response of the field, while under drier conditions, hydraulic conductivity controls the soil water dynamics. These results show that when static soil properties, e.g. clay content, are spatially uniform, ECa can detect changes in dynamic properties like soil moisture content, characterizing their spatial pattern.

Digital data for the geology of the Southern Brooks Range, Alaska

USGS Publications Warehouse

Till, Alison B.; Dumoulin, Julie A.; Harris, Anita G.; Moore, Thomas E.; Bleick, Heather A.; Siwiec, Benjamin; Labay, Keith A.; Wilson, Frederic H.; Shew, Nora B.

2008-01-01

The growth in the use of Geographic Information Systems (GIS) has highlighted the need for digital geologic maps that have been attributed with information about age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. This report is part of a series of integrated geologic map databases that cover the entire United States. Three national-scale geologic maps that portray most or all of the United States already exist; for the conterminous U.S., King and Beikman (1974a,b) compiled a map at a scale of 1:2,500,000, Beikman (1980) compiled a map for Alaska at 1:2,500,000 scale, and for the entire U.S., Reed and others (2005a,b) compiled a map at a scale of 1:5,000,000. A digital version of the King and Beikman map was published by Schruben and others (1994). Reed and Bush (2004) produced a digital version of the Reed and others (2005a) map for the conterminous U.S. The present series of maps is intended to provide the next step in increased detail. State geologic maps that range in scale from 1:100,000 to 1:1,000,000 are available for most of the country, and digital versions of these state maps are the basis of this product. The digital geologic maps presented here are in a standardized format as ARC/INFO export files and as ArcView shape files. The files named __geol contain geologic polygons and line (contact) attributes; files named __fold contain fold axes; files named __lin contain lineaments; and files named __dike contain dikes as lines. Data tables that relate the map units to detailed lithologic and age information accompany these GIS files. The map is delivered as a set 1:250,000-scale quadrangle files. To the best of our ability, these quadrangle files are edge-matched with respect to geology. When the maps are merged, the combined attribute tables can be used directly with the merged maps to make derivative maps.

An ocean gazetteer for education and research

NASA Astrophysics Data System (ADS)

Delaney, R.; Staudigel, D.; Staudigel, H.

2003-04-01

Global travel, economy, and news coverage often challenge the student's and teacher's knowledge of the geography of the seas. The International Hydrographic Organization (IHO) has published a description of all the major seas making up earth's oceans, but there is currently no electronic tool that identifies them on a digital map. During an internship at Scripps Institution of Oceanography, we transferred the printed visual description of the seas from IHO publication 23 into a digital format. This digital map was turned into a (Flash) web application that allows a user to identify any of the IHO seas on a world map, simply by moving the computer cursor over it. In our presentation, we will describe the path taken to produce this web application and the learning process involved in this path during our internship at Scripps. The main steps in this process included the digitization of the official IHO maps, the transfer of this information onto a modern digital map by Smith and Sandwell. Adjustments were necessary due to the fact that many of the landmasses were placed incorrectly on a lat/long grid, off by as much as 100km. Boundaries between seas were often misrepresented by the IHO as straight lines on a Mercator projection. Once the digitization of the seas was completed we used the 2d animation environment Flash and we produced an interactive map environment that allows any teacher or student of ocean geography to identify an ocean by name and location. Aside from learning about the geography of the oceans, we were introduced to the use of digitizers, we learned to make maps using Generic Mapping Tools (GMT) and digital global bathymetry data sets, and we learned about map projections. We studied Flash to produce an interactive map of the oceans that displays bathymetry and topography, highlighting any particular sea the cursor moves across. The name of the selected sea in our Flash application appears in a textbox on the bottom of the map. The result of this project can be found at http://earthref.org/PACER/beta/IH023seas.

Shaping the Herders' "Mental Maps": Participatory Mapping with Pastoralists' to Understand Their Grazing Area Differentiation and Characterization

NASA Astrophysics Data System (ADS)

Wario, Hussein T.; Roba, Hassan G.; Kaufmann, Brigitte

2015-09-01

Understanding the perception of environmental resources by the users is an important element in planning its sustainable use and management. Pastoralist communities manage their vast grazing territories and exploit resource variability through strategic mobility. However, the knowledge on which pastoralists' resource management is based and their perception of the grazing areas has received limited attention. To improve this understanding and to document this knowledge in a way that can be communicated with `outsiders', we adopted a participatory mapping approach using satellite imagery to explore how Borana pastoralists of southern Ethiopia differentiated and characterized their grazing areas. The Borana herders conceptualized their grazing areas as set of distinctive grazing units each having specific names and characteristics. The precise location and the borders of each grazing unit were identified on the satellite image. In naming of the grazing units, the main differentiating criteria were landforms, vegetation types, prevalence of wildlife species, and manmade features. Based on the dominant soil type, the grazing units were aggregated into seasonal grazing areas that were described using factors such as soil drainage properties, extent of woody cover, main grass species, and prevalence of ecto-parasites. Pastoralists ranking of the seasonal grazing areas according to their suitability for cattle grazing matched with vegetation assessment results on the abundance of desirable fodder varieties. Approaching grazing area differentiation from the pastoralists' perspectives improves the understanding of rangeland characteristics that pastoralists considered important in their grazing management and visualization of their mental representation in digital maps eases communication of this knowledge.

Application of phyto-indication and radiocesium indicative methods for microrelief mapping

NASA Astrophysics Data System (ADS)

Panidi, E.; Trofimetz, L.; Sokolova, J.

2016-04-01

Remote sensing technologies are widely used for production of Digital Elevation Models (DEMs), and geomorphometry techniques are valuable tools for DEM analysis. One of the broadly used applications of these technologies and techniques is relief mapping. In the simplest case, we can identify relief structures using DEM analysis, and produce a map or map series to show the relief condition. However, traditional techniques might fail when used for mapping microrelief structures (structures below ten meters in size). In this case high microrelief dynamics lead to technological and conceptual difficulties. Moreover, erosion of microrelief structures cannot be detected at the initial evolution stage using DEM modelling and analysis only. In our study, we investigate the possibilities and specific techniques for allocation of erosion microrelief structures, and mapping techniques for the microrelief derivatives (e.g. quantitative parameters of microrelief). Our toolset includes the analysis of spatial redistribution of the soil pollutants and phyto-indication analysis, which complement the common DEM modelling and geomorphometric analysis. We use field surveys produced at the test area, which is arable territory with high erosion risks. Our main conclusion at the current stage is that the indicative methods (i.e. radiocesium and phyto-indication methods) are effective for allocation of the erosion microrelief structures. Also, these methods need to be formalized for convenient use.

Land cover mapping of the National Park Service northwest Alaska management area using Landsat multispectral and thematic mapper satellite data

USGS Publications Warehouse

Markon, C.J.; Wesser, Sara

1998-01-01

A land cover map of the National Park Service northwest Alaska management area was produced using digitally processed Landsat data. These and other environmental data were incorporated into a geographic information system to provide baseline information about the nature and extent of resources present in this northwest Alaskan environment.This report details the methodology, depicts vegetation profiles of the surrounding landscape, and describes the different vegetation types mapped. Portions of nine Landsat satellite (multispectral scanner and thematic mapper) scenes were used to produce a land cover map of the Cape Krusenstern National Monument and Noatak National Preserve and to update an existing land cover map of Kobuk Valley National Park Valley National Park. A Bayesian multivariate classifier was applied to the multispectral data sets, followed by the application of ancillary data (elevation, slope, aspect, soils, watersheds, and geology) to enhance the spectral separation of classes into more meaningful vegetation types. The resulting land cover map contains six major land cover categories (forest, shrub, herbaceous, sparse/barren, water, other) and 19 subclasses encompassing 7 million hectares. General narratives of the distribution of the subclasses throughout the project area are given along with vegetation profiles showing common relationships between topographic gradients and vegetation communities.

Quaternary Geologic Map of the Des Moines 4 Degrees x 6 Degrees Quadrangle, United States

USGS Publications Warehouse

Hallberg, George R.; Lineback, Jerry A.; Mickelson, David M.; Knox, James C.; Goebel, Joseph E.; Hobbs, Howard C.; Whitfield, John W.; Ward, Ronald A.; Boellstorff, John D.; Swinehart, James B.; Dreeszen, Vincent H.; edited and integrated by Richmond, Gerald Martin; Fullerton, David S.; Christiansen, Ann Coe

1994-01-01

The Quaternary Geologic Map of the Des Moines 4 degree x 6 degree Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1994. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files.

Quaternary Geologic Map of the Platte River 4 Degrees x 6 Degrees Quadrangle, United States

USGS Publications Warehouse

Swinehart, James B.; Dreeszen, Vincent H.; Richmond, Gerald Martin; Tipton, Merlin J.; Bretz, Richard F.; Steece, Fred V.; Hallberg, George R.; Goebel, Joseph E.; edited and integrated by Richmond, Gerald Martin

1994-01-01

The Quaternary Geologic Map of the Platte River 4 degree x 6 degree Quadrangle was mapped as part of the Quaternary Geologic Atlas of the United States. The atlas was begun as an effort to depict the areal distribution of surficial geologic deposits and other materials that accumulated or formed during the past 2+ million years, the period that includes all activities of the human species. These materials are at the surface of the earth. They make up the 'ground' on which we walk, the 'dirt' in which we dig foundations, and the 'soil' in which we grow crops. Most of our human activity is related in one way or another to these surface materials that are referred to collectively by many geologists as regolith, the mantle of fragmental and generally unconsolidated material that overlies the bedrock foundation of the continent. The maps were compiled at 1:1,000,000 scale. This map is part of the Quaternary Geologic Atlas of the United States (I-1420). It was first published as a printed edition in 1994. The geologic data have now been captured digitally and are presented here along with images of the printed map sheet and component parts as PDF files.

Remote Sensing techniques used to characterize soil erosion in southwestern Sao Paulo state. M.S. Thesis - 29 Sep. 1982; [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Pinto, S. D. A. F.

1983-01-01

Within randomly sampled squares of a 1 km x 1 km grid, rill/gullies frequency, land cover/land use type and shape of the slopes were extracted from aerial photographs of the Ribeirao Anhumas drainage basin. Mean slope gradient, stream frequency and slope length were calculated on topographic maps. Ground truth data on fine sand/coarse sand ratio and vegetation cover densities were obtained. The MSS-LANDSAT-2 data (CCTs) were analyzed using single-cell, cluster synthesis and slicer algorithms. Graphical and statistical analyses of the data indicate that different slope gradients and land cover/land use types are the most significant factors related to the soil erosion process. The digital analysis of MSS data allowed the association among gray level classes and vegetation cover classes, which defined seven classes. These gray level classes and slope gradient classes were used to rank erosion risk.

Improved spatial mapping of rainfall events with spaceborne SAR imagery

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Brisco, B.; Dobson, C.

1983-01-01

The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

Comparative evaluation of ERTS imagery for resource inventory in land use planning

NASA Technical Reports Server (NTRS)

Simonson, G. H. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Numerous previously unmapped faults in central Oregon have been distinguished on ERTS-1 imagery. Tectonic mapping of fault-controlled linears demonstrates the utility of ERTS-1 imagery as a mean of illustrating and studying the regional tectonics of the state. Soil colors observed on ERTS-1 frame 1075-18150-5 at the eastern end of the Columbia basin correlate very well with those from descriptions of soils from that area. Digital output from frame 1021-18151 has shown the enhanced ability to interpret such features as joint patterns, shadowed landslide blocks, bottomlands, and drainage patterns. Widespread use of wheat-fallow rotation in northern Umatilla County, Oregon, insures that nearly one-half of the cultivated soil is devoid of vegetation much of the time. On ERTS-1 imagery, fallow fields are only slightly darker than fields of wheat stubble at the western end of the transect. Similar climate-related contrasts in soil color are visible on ERTS-1 Imagery from several other portions of the Columbia Basin. Absence of steep topography in the area mentioned, however, minimizes the disturbing effect caused by shadows.

Spatial Digital Database for the Geology of the San Pedro River Basin in Cochise, Gila, Graham, Pima, and Pinal Counties, Arizona

USGS Publications Warehouse

Bolm, Karen S.

2002-01-01

The map area is located in southeastern Arizona. This report describes the map units, the methods used to convert the geologic map data into a digital format, and the ArcInfo GIS file structures and relationships; and it explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. See figures 2 and 3 for page-size versions of the map compilation.

Principles of soil mapping of a megalopolis with St. Petersburg as an example

NASA Astrophysics Data System (ADS)

Aparin, B. F.; Sukhacheva, E. Yu.

2014-07-01

For the first time, a soil map of St. Petersburg has been developed on a scale of 1 : 50000 using MicroStation V8i software. The legend to this map contains more than 60 mapping units. The classification of urban soils and information on the soil cover patterns are principally new elements of this legend. New concepts of the urbanized soil space and urbopedocombinations have been suggested for soil mapping of urban territories. The typification of urbopedocombinations in St. Petersburg has been performed on the basis of data on the geometry and composition of the polygons of soils and nonsoil formations. The ratio between the areas of soils and nonsoil formations and their spatial distribution patterns have been used to distinguish between six types of the urbanized soil space. The principles of classification of the soils of urban territories have been specified, and a separate order of pedo-allochthonous soils has been suggested for inclusion into the Classification and Diagnostic System of Russian Soils (2004). Six types of pedo-allochthonous soils have been distinguished on the basis of data on their humus and organic horizons and the character of the underlying mineral substrate.

Toward digital geologic map standards: a progress report

USGS Publications Warehouse

Ulrech, George E.; Reynolds, Mitchell W.; Taylor, Richard B.

1992-01-01

Establishing modern scientific and technical standards for geologic maps and their derivative map products is vital to both producers and users of such maps as we move into an age of digital cartography. Application of earth-science data in complex geographic information systems, acceleration of geologic map production, and reduction of population costs require that national standards be developed for digital geologic cartography and computer analysis. Since December 1988, under commission of the Chief Geologic of the U.S. Geological Survey and the mandate of the National Geologic Mapping Program (with added representation from the Association of American State Geologists), a committee has been designing a comprehensive set of scientific map standards. Three primary issues were: (1) selecting scientific symbology and its digital representation; (2) creating an appropriate digital coding system that characterizes geologic features with respect to their physical properties, stratigraphic and structural relations, spatial orientation, and interpreted mode of origin; and (3) developing mechanisms for reporting levels of certainty for descriptive as well as measured properties. Approximately 650 symbols for geoscience maps, including present usage of the U.S Geological Survey, state geological surveys, industry, and academia have been identified and tentatively adopted. A proposed coding system comprises four-character groupings of major and minor codes that can identify all attributes of a geologic feature. Such a coding system allows unique identification of as many as 105 geologic names and values on a given map. The new standard will track closely the latest developments of the Proposed Standard for Digital Cartographic Data soon to be submitted to the National Institute of Standards and Technology by the Federal Interagency Coordinating Committee on Digital Cartography. This standard will adhere generally to the accepted definitions and specifications for spatial data transfer. It will require separate specifications of digital cartographic quality relating to positional accuracy and ranges of measured and interpreted values such as geologic age and rock composition. Provisional digital geologic map standards will be published for trial implementation. After approximately two years, when comments on the proposed standards have been solicited and modifications made, formal adoption of the standards will be recommended. Widespread acceptance of the new standards will depend on their applicability to the broadest range of earth-science map products and their adaptability to changing cartographic technology.

The agricultural features of Nizhegorodskaya gubernia (province) in the XIX century

NASA Astrophysics Data System (ADS)

Kirillova, Vasilisa

2017-04-01

One of the main conditions for the sustainable development of any country is the food security of the population, based on the development of agriculture. This condition can be realized through the efficient use of the productive capacity of agriculture, and above all natural resources. From 1882 to 1887 in the Nizhegorodskaya gubernia (province) complex physiographic (landscape) researches were conducted by V.V. Dokuchaev and his followers. This investigation was focused on studying the relationship between the soils and the environment, having no parallel either in Russia or abroad, and received evaluation of the soils was the first experience of such a scale and nature. Reports of the expedition were presented in 14 volumes on the natural science of the study, and 11 volumes of economic statistics. Natural science volume includes descriptions of irrigation and hydrography, geology, soil and vegetation in uezds (districts). Economic volume represent a set of common data on the situation of the peasant economy, they contain information about the number of arable land, including fertilized, hayfields, forests, manure stocks, livestock, harvest volumes, proportions of cultivated crops. The aim of this research was to study the list and structure of crops cultivated in the Nizhegorodskaya gubernia in the XIX century and their compliance with the soil and climatic conditions. From the materials of the expedition reports for the eight districts of the Nizhegorodskaya gubernia was compiled a list of crops and crop area information which was introduced in the GIS (MapInfo). Geographic information systems were used to visualize the collected material in the form of maps, cartograms and charts. For the conformity assessment of soil and climatic conditions of the studied area of selected crops a map "Agricultural zoning of Russia for optimal crop growing" by I.I. Karmanov and D.S. Bulgakov (National Soil Atlas, 2011) was applied. According to this map the Nizhegorodskaya gubernia is located in three agro-climatic areas: (№9) European Southern taiga, sod-podzolic (humus soils of Opol'e), rye, barley, oat, potato and forage (corn silage), (number 11) North-steppe (ETP), gray forest soils with patches of chernozems, winter-wheat-rye, barley, oat, potato with corn silage, (№12) forest-steppe (ETP), leached and podzolized chernozems with gray forest soils , winter-wheat-rye, barley, oat, potato with sugar beet and corn for silage. Analysis of digitized information on cultivated crops of Nizhegorodskaya gubernia in the XIX century and agro-climatic characteristics of areas has shown that the list of selected crops in general corresponds to the recommendations by present-day scientists, but has its own characteristics. In reporting materials there is no information about the cultivation of crops such as winter wheat, sugar beet and corn. Potatoes and barley are cultivated in small quantities, their place is taken lentil, millet and spelt, which in today's recommendations are not mentioned.

An overview on the history of pedology and soil mapping in Italy

NASA Astrophysics Data System (ADS)

Calzolari, C.

2012-04-01

In Italy, the word pedology (pedologia) was introduced in a text book as synonym of soil science for the first time in 1904 by Vinassa de Regny. In the literature, the term cohabitates with the words agrology (agrologia), agro-geology (agro-geologia), agricultural geognostic (geognostica agraria), geopedology (geo-pedologia) used in different historical moments by differently rooted soil scientists. When early pedologists started with systematic studies of soils, their characteristics and geography, they were strongly influenced by their cultural background, mainly geology and agro-chemistry. Along the time, the soil concept evolved, as did the concept of pedology, and this is somehow witnessed by the use of different Italian words with reference to soil: suolo, terreno, terra. Differently from agro-chemists, early pedologists based the soil study on the field description of soil profile. This was firstly based on the vertical differentiation between humus rich layers and "inactive" layers and later on, as long as the discipline evolved, on the presence of genetic horizons. The first complete soil map of Italy is dated 1928. Its Author, the geologist De Angelis d'Ossat, was the president of the organising committee of the 1924 International Soil Conference of Rome, where the International Society of Soil Science was founded. The map was based on the geological map of Italy, drafted in scale 1:1,000,000 after the creation of the Kingdom of Italy in 1861. The internal disputes within the Geological Society, together with the scarce interest of most of geologists for soil, did not facilitate the birth of a central soil survey. Soil mapping was mainly conducted by universities and research institutes, and we had to wait until 1953 for a new soil map (scale 1:3,125,000) at national level to be realised by Paolo Principi, based on literature data. In 1966 a new 1:1,000,000 soil map of Italy was eventually published by a national committee, led by Fiorenzo Mancini. This was based on literature data and on field surveys, and the mapping units limits, based on geomorphology, are still the basis of the most updated European 1:1,000,000 soil map. At the end of the 80ies of the past century, soil survey and mapping were taken over by the Italian regional administrations, which set up regional soil surveys working in co-ordination among them and with the research institutions.

Soils of Walker Branch Watershed

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

Lietzke, D.A.

1994-03-01

The soil survey of Walker Branch Watershed (WBW) utilized the most up-to-date knowledge of soils, geology, and geohydrology in building the soils data base needed to reinterpret past research and to begin new research in the watershed. The soils of WBW were also compared with soils mapped elsewhere along Chestnut Ridge on the Oak Ridge Reservation to (1) establish whether knowledge obtained elsewhere could be used within the watershed, (2) determine whether there were any soils restricted to the watershed, and (3) evaluate geologic formation lateral variability. Soils, surficial geology, and geomorphology were mapped at a scale of 1:1,200 usingmore » a paper base map having 2-ft contour intervals. Most of the contours seemed to reasonably represent actual landform configurations, except for dense wooded areas. For example, the very large dolines or sinkholes were shown on the contour base map, but numerous smaller ones were not. In addition, small drainageways and gullies were often not shown. These often small but important features were located approximately as soil mapping progressed.« less

Area- and depth- weighted averages of selected SSURGO variables for the conterminous United States and District of Columbia

USGS Publications Warehouse

Wieczorek, Michael

2014-01-01

This digital data release consists of seven data files of soil attributes for the United States and the District of Columbia. The files are derived from National Resources Conservations Service’s (NRCS) Soil Survey Geographic database (SSURGO). The data files can be linked to the raster datasets of soil mapping unit identifiers (MUKEY) available through the NRCS’s Gridded Soil Survey Geographic (gSSURGO) database (http://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053628). The associated files, named DRAINAGECLASS, HYDRATING, HYDGRP, HYDRICCONDITION, LAYER, TEXT, and WTDEP are area- and depth-weighted average values for selected soil characteristics from the SSURGO database for the conterminous United States and the District of Columbia. The SSURGO tables were acquired from the NRCS on March 5, 2014. The soil characteristics in the DRAINAGE table are drainage class (DRNCLASS), which identifies the natural drainage conditions of the soil and refers to the frequency and duration of wet periods. The soil characteristics in the HYDRATING table are hydric rating (HYDRATE), a yes/no field that indicates whether or not a map unit component is classified as a "hydric soil". The soil characteristics in the HYDGRP table are the percentages for each hydrologic group per MUKEY. The soil characteristics in the HYDRICCONDITION table are hydric condition (HYDCON), which describes the natural condition of the soil component. The soil characteristics in the LAYER table are available water capacity (AVG_AWC), bulk density (AVG_BD), saturated hydraulic conductivity (AVG_KSAT), vertical saturated hydraulic conductivity (AVG_KV), soil erodibility factor (AVG_KFACT), porosity (AVG_POR), field capacity (AVG_FC), the soil fraction passing a number 4 sieve (AVG_NO4), the soil fraction passing a number 10 sieve (AVG_NO10), the soil fraction passing a number 200 sieve (AVG_NO200), and organic matter (AVG_OM). The soil characteristics in the TEXT table are percent sand, silt, and clay (AVG_SAND, AVG_SILT, and AVG_CLAY). The soil characteristics in the WTDEP table are the annual minimum water table depth (WTDEP_MIN), available water storage in the 0-25 cm soil horizon (AWS025), the minimum water table depth for the months April, May and June (WTDEPAMJ), the available water storage in the first 25 centimeters of the soil horizon (AWS25), the dominant drainage class (DRCLSD), the wettest drainage class (DRCLSWET), and the hydric classification (HYDCLASS), which is an indication of the proportion of the map unit, expressed as a class, that is "hydric", based on the hydric classification of a given MUKEY. (See Entity_Description for more detail). The tables were created with a set of arc macro language (aml) and awk (awk was created at Bell Labsin the 1970s and its name is derived from the first letters of the last names of its authors – Alfred Aho, Peter Weinberger, and Brian Kernighan) scripts. Send an email to mewieczo@usgs.gov to obtain copies of the computer code (See Process_Description.) The methods used are outlined in NRCS's "SSURGO Data Packaging and Use" (NRCS, 2011). The tables can be related or joined to the gSSURGO rasters of MUKEYs by the item 'MUKEY.' Joining or relating the tables to a MUKEY grid allows the creation of grids of area- and depth-weighted soil characteristics. A 90-meter raster of MUKEYs is provided which can be used to produce rasters of soil attributes. More detailed resolution rasters are available through NRCS via the link above.

Measuring Soil Moisture in Skeletal Soils Using a COSMOS Rover

NASA Astrophysics Data System (ADS)

Medina, C.; Neely, H.; Desilets, D.; Mohanty, B.; Moore, G. W.

2017-12-01

The presence of coarse fragments directly influences the volumetric water content of the soil. Current surface soil moisture sensors often do not account for the presence of coarse fragments, and little research has been done to calibrate these sensors under such conditions. The cosmic-ray soil moisture observation system (COSMOS) rover is a passive, non-invasive surface soil moisture sensor with a footprint greater than 100 m. Despite its potential, the COSMOS rover has yet to be validated in skeletal soils. The goal of this study was to validate measurements of surface soil moisture as taken by a COSMOS rover on a Texas skeletal soil. Data was collected for two soils, a Marfla clay loam and Chinati-Boracho-Berrend association, in West Texas. Three levels of data were collected: 1) COSMOS surveys at three different soil moistures, 2) electrical conductivity surveys within those COSMOS surveys, and 3) ground-truth measurements. Surveys with the COSMOS rover covered an 8000-h area and were taken both after large rain events (>2") and a long dry period. Within the COSMOS surveys, the EM38-MK2 was used to estimate the spatial distribution of coarse fragments in the soil around two COSMOS points. Ground truth measurements included coarse fragment mass and volume, bulk density, and water content at 3 locations within each EM38 survey. Ground-truth measurements were weighted using EM38 data, and COSMOS measurements were validated by their distance from the samples. There was a decrease in water content as the percent volume of coarse fragment increased. COSMOS estimations responded to both changes in coarse fragment percent volume and the ground-truth volumetric water content. Further research will focus on creating digital soil maps using landform data and water content estimations from the COSMOS rover.

Digitizing zone maps, using modified LARSYS program. [computer graphics and computer techniques for mapping

NASA Technical Reports Server (NTRS)

Giddings, L.; Boston, S.

1976-01-01

A method for digitizing zone maps is presented, starting with colored images and producing a final one-channel digitized tape. This method automates the work previously done interactively on the Image-100 and Data Analysis System computers of the Johnson Space Center (JSC) Earth Observations Division (EOD). A color-coded map was digitized through color filters on a scanner to form a digital tape in LARSYS-2 or JSC Universal format. The taped image was classified by the EOD LARSYS program on the basis of training fields included in the image. Numerical values were assigned to all pixels in a given class, and the resulting coded zone map was written on a LARSYS or Universal tape. A unique spatial filter option permitted zones to be made homogeneous and edges of zones to be abrupt transitions from one zone to the next. A zoom option allowed the output image to have arbitrary dimensions in terms of number of lines and number of samples on a line. Printouts of the computer program are given and the images that were digitized are shown.

Mapping broom snakeweed through image analysis of color-infrared photography and digital imagery.

PubMed

Everitt, J H; Yang, C

2007-11-01

A study was conducted on a south Texas rangeland area to evaluate aerial color-infrared (CIR) photography and CIR digital imagery combined with unsupervised image analysis techniques to map broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby]. Accuracy assessments performed on computer-classified maps of photographic images from two sites had mean producer's and user's accuracies for broom snakeweed of 98.3 and 88.3%, respectively; whereas, accuracy assessments performed on classified maps from digital images of the same two sites had mean producer's and user's accuracies for broom snakeweed of 98.3 and 92.8%, respectively. These results indicate that CIR photography and CIR digital imagery combined with image analysis techniques can be used successfully to map broom snakeweed infestations on south Texas rangelands.

Virtual Field Reconnaissance to enable multi-site collaboration in geoscience fieldwork in Chile.

NASA Astrophysics Data System (ADS)

Hughes, Leanne; Bateson, Luke; Ford, Jonathan; Napier, Bruce; Creixell, Christian; Contreras, Juan-Pablo; Vallette, Jane

2017-04-01

The unique challenges of geological mapping in remote terrains can make cross-organisation collaboration challenging. Cooperation between the British and Chilean Geological Surveys and the Chilean national mining company used the BGS digital Mapping Workflow and virtual field reconnaissance software (GeoVisionary) to undertake geological mapping in a complex area of Andean Geology. The international team undertook a pre-field evaluation using GeoVisionary to integrate massive volumes of data and interpret high resolution satellite imagery, terrain models and existing geological information to capture, manipulate and understand geological features and re-interpret existing maps. This digital interpretation was then taken into the field and verified using the BGS digital data capture system (SIGMA.mobile). This allowed the production of final geological interpretation and creation of a geological map. This presentation describes the digital mapping workflow used in Chile and highlights the key advantages of increased efficiency and communication to colleagues, stakeholders and funding bodies.

Topographically-determined soil thickening explained spatial variability of soil carbon and nitrogen in Southern California grasslands

NASA Astrophysics Data System (ADS)

Lin, Y.; Prentice, S., III; Tran, T.; Bingham, N.; King, J. Y.; Chadwick, O.

2015-12-01

At the scale of hillslopes, topography strongly regulates soil formation, affecting hillslope hydrology and biological activities. Topographic control of soil formation is particularly strong for semi-arid landscapes where soil thickening is induced by pedoturbation and soil creep. Thus, terrain attributes hold great potential for modeling full profile soil C and N stocks at the hillslope scale in these landscapes. In this study, we developed predictions of grassland soil C and N stocks using digital terrain attributes scaled to the signal of site-specific hillslope geomorphic processes. We found that soil thickness was the major control of soil organic C and N stocks and was best predicted by mean curvature. This curvature dependency of soil thickness affected prediction of organic C and N stocks because of the C and N added by taking subsoil into account. We also found that curvature was positively correlated with depth to carbonate reflecting drier soil conditions in convex hillslope positions and wetter soil conditions in concave areas. Slope aspect also had a marginal effect on soil C and N stocks; soil organic C and N stocks on the north-facing slope tended to be higher than those on the south-facing slope. We found that terrain attributes at medium resolutions (8 to 16 m) were most effective in modeling soil C and N stocks. Overall, terrain attributes explained 61% of the variation in soil thickness and 49% of the variation in soil organic C stock. Our results suggest that curvature-induced soil thickening, coupled with aspect, likely exerts a first-order control on soil organic C and N accumulation rates, and these changes occur predominantly in subsoil. Thus our data highlight the importance of subsoil in mapping soil C and N stocks and other soil properties. Our model also demonstrates how scale-driven analysis may guide soil C and N prediction in other hillslope dominated regions.

Digital Mapping Techniques '08—Workshop Proceedings, Moscow, Idaho, May 18–21, 2008

USGS Publications Warehouse

Soller, David R.

2009-01-01

The Digital Mapping Techniques '08 (DMT'08) workshop was attended by more than 100 technical experts from 40 agencies, universities, and private companies, including representatives from 24 State geological surveys. This year's meeting, the twelfth in the annual series, was hosted by the Idaho Geological Survey, from May 18-21, 2008, on the University of Idaho campus in Moscow, Idaho. Each DMT workshop has been coordinated by the U.S. Geological Survey's National Geologic Map Database Project and the Association of American State Geologists (AASG). As in previous years' meetings, the objective was to foster informal discussion and exchange of technical information, principally in order to develop more efficient methods for digital mapping, cartography, GIS analysis, and information management. At this meeting, oral and poster presentations and special discussion sessions emphasized (1) methods for creating and publishing map products (here, "publishing" includes Web-based release); (2) field data capture software and techniques, including the use of LiDAR; (3) digital cartographic techniques; (4) migration of digital maps into ArcGIS Geodatabase format; (5) analytical GIS techniques; and (6) continued development of the National Geologic Map Database.

Identifying soil landscape units at the district scale by numerically clustering remote and proximal sensed data

NASA Astrophysics Data System (ADS)

Zare, Ehsan; Huang, Jingyi; Triantafilis, John

2017-04-01

Identifying soil landscape units at a district scale is important as it allows for sustainable land-use management. However, given the large number of soil properties that need to be understood and mapped, cost-effective methods are required. In this study, we use a digital soil mapping (DSM) approach where remote and proximal sensed ancillary data collected across a farming district near Bourke, are numerical clustered (fuzzy k-means: FKM) to identify soil landscape units. The remote data was obtained from an air-borne gamma-ray spectrometer survey (i.e. potassium-K, uranium-U, thorium-Th and total counts-TC). Proximal sensed data was collected using an EM38 in the horizontal (EM38h) and vertical (EM38v) mode of operation. The FKM analysis (using Mahalanobis metric) of the kriged ancillary (i.e. common 100 m grid) data revealed a fuzziness exponent (phi) of 1.4 was suitable for further analysis and that k = 4 classes was smallest for the fuzziness performance index (FPI) and normalised classification entropy (NCE). Using laboratory measured physical (i.e. clay) and chemical (i.e. CEC, ECe and pH) properties we found k = 4 was minimized in terms of mean squared prediction error (i.e. 2p,C) when considering topsoil (0-0.3 m) clay (159.76), CEC (21.943), ECe (13.56) and pH (0.2296) and subsoil (0.9-1.2 m) clay (80.81), CEC (31.251) and ECe (16.66). These sigma2p,C are smaller than those calculated using the mapped soil landscape units identified using a traditional approach. Nevertheless, class 4A represents the Aeolian soil landscape (i.e. Nb4), while 4D, represents deep grey (CC19) self-mulching clays, and 4B and 4C yellow-grey (II1) self-mulching clays adjacent to the river and clay alluvial plain, respectively. The differences in clay and CEC reveal why 4B, 4C and 4D have been extensively developed for irrigated cotton production and also why the slightly less reactive 4B might be a source of deep drainage; evidenced by smaller topsoil (2.13 dS/m) and subsoil (3.76 dS/m) ECe. The research has implications for providing meaningful DSM of soil landscape units for farmers at districts scales where traditional methods are restrictive in terms of time and cost.

Semantic Web-based digital, field and virtual geological

NASA Astrophysics Data System (ADS)

Babaie, H. A.

2012-12-01

Digital, field and virtual Semantic Web-based education (SWBE) of geological mapping requires the construction of a set of searchable, reusable, and interoperable digital learning objects (LO) for learners, teachers, and authors. These self-contained units of learning may be text, image, or audio, describing, for example, how to calculate the true dip of a layer from two structural contours or find the apparent dip along a line of section. A collection of multi-media LOs can be integrated, through domain and task ontologies, with mapping-related learning activities and Web services, for example, to search for the description of lithostratigraphic units in an area, or plotting orientation data on stereonet. Domain ontologies (e.g., GeologicStructure, Lithostratigraphy, Rock) represent knowledge in formal languages (RDF, OWL) by explicitly specifying concepts, relations, and theories involved in geological mapping. These ontologies are used by task ontologies that formalize the semantics of computational tasks (e.g., measuring the true thickness of a formation) and activities (e.g., construction of cross section) for all actors to solve specific problems (making map, instruction, learning support, authoring). A SWBE system for geological mapping should also involve ontologies to formalize teaching strategy (pedagogical styles), learner model (e.g., for student performance, personalization of learning), interface (entry points for activities of all actors), communication (exchange of messages among different components and actors), and educational Web services (for interoperability). In this ontology-based environment, actors interact with the LOs through educational servers, that manage (reuse, edit, delete, store) ontologies, and through tools which communicate with Web services to collect resources and links to other tools. Digital geological mapping involves a location-based, spatial organization of geological elements in a set of GIS thematic layers. Each layer in the stack assembles a set of polygonal (e.g., formation, member, intrusion), linear (e.g., fault, contact), and/or point (e.g., sample or measurement site) geological elements. These feature classes, represented in domain ontologies by classes, have their own sets of property (attribute, association relation) and topological (e.g., overlap, adjacency, containment), and network (cross-cuttings; connectivity) relationships. Since geological mapping involves describing and depicting different aspects of each feature class (e.g., contact, formation, structure), the same geographic region may be investigated by different communities, for example, for its stratigraphy, rock type, structure, soil type, and isotopic and paleontological age, using sets of ontologies. These data can become interconnected applying the Semantic Web technologies, on the Linked Open Data Cloud, based on their underlying common geographic coordinates. Sets of geological data published on the Cloud will include multiple RDF links to Cloud's geospatial nodes such as GeoNames and Linked GeoData. During mapping, a device such as smartphone, laptop, or iPad, with GPS and GIS capability and a DBpedia Mobile client, can use the current position to discover and query all the geological linked data, and add new data to the thematic layers and publish them to the Cloud.

Application of remote sensing technology to land evaluation, planning utilization of land resources, and assessment of wildlife areas in eastern South Dakota

NASA Technical Reports Server (NTRS)

1975-01-01

A soils map for land evaluation in Potter County (Eastern South Dakota) was developed to demonstrate the use of remote sensing technology in the area of diverse parent materials and topography. General land use and soils maps have also been developed for land planning LANDSAT, RB-57 imagery, and USGS photographs are being evaluated for making soils and land use maps. LANDSAT fulfilled the requirements for general land use and a general soils map. RB-57 imagery supplemented by large scale black and white stereo coverage was required to provide the detail needed for the final soils map for land evaluation. Color infrared prints excelled black and white coverage for this soil mapping effort. An identification and classification key for wetland types in the Lake Dakota Plain was developed for June 1975 using color infrared imagery. Wetland types in the region are now being mapped via remote sensing techniques to provide a current inventory for development of mitigation measures.

Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watershed

NASA Astrophysics Data System (ADS)

Saran, Sameer; Sterk, Geert; Kumar, Suresh

2009-10-01

Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division into HRU's requires good-quality spatial data on land use/land cover. This paper presents different approaches to attain an optimal land use/land cover map based on remote sensing imagery for a Himalayan watershed in northern India. First digital classifications using maximum likelihood classifier (MLC) and a decision tree classifier were applied. The results obtained from the decision tree were better and even improved after post classification sorting. But the obtained land use/land cover map was not sufficient for the delineation of HRUs, since the agricultural land use/land cover class did not discriminate between the two major crops in the area i.e. paddy and maize. Subsequently the digital classification on fused data (ASAR and ASTER) were attempted to map land use/land cover classes with emphasis to delineate the paddy and maize crops but the supervised classification over fused datasets did not provide the desired accuracy and proper delineation of paddy and maize crops. Eventually, we adopted a visual classification approach on fused data. This second step with detailed classification system resulted into better classification accuracy within the 'agricultural land' class which will be further combined with topography and soil type to derive HRU's for physically-based hydrological modeling.

Geology of Point Reyes National Seashore and vicinity, California: a digital database

USGS Publications Warehouse

Clark, Jospeh C.; Brabb, Earl E.

1997-01-01

This Open-File report is a digital geologic map database. This pamphlet serves to introduce and describe the digital data. There is no paper map included in the Open-File report. The report does include, however, a PostScript plot file containing an image of the geologic map sheet with explanation, as well as the accompanying text describing the geology of the area. For those interested in a paper plot of information contained in the database or in obtaining the PostScript plot files, please see the section entitled 'For Those Who Aren't Familiar With Digital Geologic Map Databases' below. This digital map database, compiled from previously published and unpublished data and new mapping by the authors, represents the general distribution of surficial deposits and rock units in Point Reyes and surrounding areas. Together with the accompanying text file (pr-geo.txt or pr-geo.ps), it provides current information on the stratigraphy and structural geology of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:48,000 or smaller.

Staff - Jennifer E. Athey | Alaska Division of Geological & Geophysical

Science.gov Websites

multiple data management projects from digital field data collection to data compilation projects to Surveys Digital Data Series 14, http://doi.org/10.14509/photodb. http://doi.org/10.14509/29735 Athey, J.E increasing communication about digital geologic field mapping, in Soller, D.R., ed. Digital Mapping

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra.

PubMed

Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

2015-01-01

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l'Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the 'upland model' was able to more accurately predict SOC compared with the 'upland & wetland model'. However, the separately calibrated 'upland and wetland model' did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM).

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

PubMed Central

Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

2015-01-01

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the ‘upland model’ was able to more accurately predict SOC compared with the ‘upland & wetland model’. However, the separately calibrated ‘upland and wetland model’ did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM). PMID:26555071

Digital Bedrock Compilation: A Geodatabase Covering Forest Service Lands in California

NASA Astrophysics Data System (ADS)

Elder, D.; de La Fuente, J. A.; Reichert, M.

2010-12-01

This digital database contains bedrock geologic mapping for Forest Service lands within California. This compilation began in 2004 and the first version was completed in 2005. Second publication of this geodatabase was completed in 2010 and filled major gaps in the southern Sierra Nevada and Modoc/Medicine Lake/Warner Mountains areas. This digital map database was compiled from previously published and unpublished geologic mapping, with source mapping and review from California Geological Survey, the U.S. Geological Survey and others. Much of the source data was itself compilation mapping. This geodatabase is huge, containing ~107,000 polygons and ~ 280,000 arcs. Mapping was compiled from more than one thousand individual sources and covers over 41,000,000 acres (~166,000 km2). It was compiled from source maps at various scales - from ~ 1:4,000 to 1:250,000 and represents the best available geologic mapping at largest scale possible. An estimated 70-80% of the source information was digitized from geologic mapping at 1:62,500 scale or better. Forest Service ACT2 Enterprise Team compiled the bedrock mapping and developed a geodatabase to store this information. This geodatabase supports feature classes for polygons (e.g, map units), lines (e.g., contacts, boundaries, faults and structural lines) and points (e.g., orientation data, structural symbology). Lookup tables provide detailed information for feature class items. Lookup/type tables contain legal values and hierarchical groupings for geologic ages and lithologies. Type tables link coded values with descriptions for line and point attributes, such as line type, line location and point type. This digital mapping is at the core of many quantitative analyses and derivative map products. Queries of the database are used to produce maps and to quantify rock types of interest. These include the following: (1) ultramafic rocks - where hazards from naturally occurring asbestos are high, (2) granitic rocks - increased erosion hazards, (3) limestone, chert, sedimentary rocks - paleontological resources (Potential Fossil Yield Classification maps), (4) calcareous rocks (cave resources, water chemistry), and (5) lava flows - lava tubes (more caves). Map unit groupings (e.g., belts, terranes, tectonic & geomorphic provinces) can also be derived from the geodatabase. Digital geologic mapping was used in ground water modeling to predict effects of tunneling through the San Bernardino Mountains. Bedrock mapping is used in models that characterize watershed sediment regimes and quantify anthropogenic influences. When combined with digital geomorphology mapping, this geodatabase helps to assess landslide hazards.

Optical domain analog to digital conversion methods and apparatus

DOEpatents

Vawter, Gregory A

2014-05-13

Methods and apparatus for optical analog to digital conversion are disclosed. An optical signal is converted by mapping the optical analog signal onto a wavelength modulated optical beam, passing the mapped beam through interferometers to generate analog bit representation signals, and converting the analog bit representation signals into an optical digital signal. A photodiode receives an optical analog signal, a wavelength modulated laser coupled to the photodiode maps the optical analog signal to a wavelength modulated optical beam, interferometers produce an analog bit representation signal from the mapped wavelength modulated optical beam, and sample and threshold circuits corresponding to the interferometers produce a digital bit signal from the analog bit representation signal.

Introducing students to digital geological mapping: A workflow based on cheap hardware and free software

NASA Astrophysics Data System (ADS)

Vrabec, Marko; Dolžan, Erazem

2016-04-01

The undergraduate field course in Geological Mapping at the University of Ljubljana involves 20-40 students per year, which precludes the use of specialized rugged digital field equipment as the costs would be way beyond the capabilities of the Department. A different mapping area is selected each year with the aim to provide typical conditions that a professional geologist might encounter when doing fieldwork in Slovenia, which includes rugged relief, dense tree cover, and moderately-well- to poorly-exposed bedrock due to vegetation and urbanization. It is therefore mandatory that the digital tools and workflows are combined with classical methods of fieldwork, since, for example, full-time precise GNSS positioning is not viable under such circumstances. Additionally, due to the prevailing combination of complex geological structure with generally poor exposure, students cannot be expected to produce line (vector) maps of geological contacts on the go, so there is no need for such functionality in hardware and software that we use in the field. Our workflow therefore still relies on paper base maps, but is strongly complemented with digital tools to provide robust positioning, track recording, and acquisition of various point-based data. Primary field hardware are students' Android-based smartphones and optionally tablets. For our purposes, the built-in GNSS chips provide adequate positioning precision most of the time, particularly if they are GLONASS-capable. We use Oruxmaps, a powerful free offline map viewer for the Android platform, which facilitates the use of custom-made geopositioned maps. For digital base maps, which we prepare in free Windows QGIS software, we use scanned topographic maps provided by the National Geodetic Authority, but also other maps such as aerial imagery, processed Digital Elevation Models, scans of existing geological maps, etc. Point data, like important outcrop locations or structural measurements, are entered into Oruxmaps as waypoints. Students are also encouraged to directly measure structural data with specialized Android apps such as the MVE FieldMove Clino. Digital field data is exported from Oruxmaps to Windows computers primarily in the ubiquitous GPX data format and then integrated in the QGIS environment. Recorded GPX tracks are also used with the free Geosetter Windows software to geoposition and tag any digital photographs taken in the field. With minimal expenses, our workflow provides the students with basic familiarity and experience in using digital field tools and methods. The workflow is also practical enough for the prevailing field conditions of Slovenia that the faculty staff is using it in geological mapping for scientific research and consultancy work.

S-World: A high resolution global soil database for simulation modelling (Invited)

NASA Astrophysics Data System (ADS)

Stoorvogel, J. J.

2013-12-01

There is an increasing call for high resolution soil information at the global level. A good example for such a call is the Global Gridded Crop Model Intercomparison carried out within AgMIP. While local studies can make use of surveying techniques to collect additional techniques this is practically impossible at the global level. It is therefore important to rely on legacy data like the Harmonized World Soil Database. Several efforts do exist that aim at the development of global gridded soil property databases. These estimates of the variation of soil properties can be used to assess e.g., global soil carbon stocks. However, they do not allow for simulation runs with e.g., crop growth simulation models as these models require a description of the entire pedon rather than a few soil properties. This study provides the required quantitative description of pedons at a 1 km resolution for simulation modelling. It uses the Harmonized World Soil Database (HWSD) for the spatial distribution of soil types, the ISRIC-WISE soil profile database to derive information on soil properties per soil type, and a range of co-variables on topography, climate, and land cover to further disaggregate the available data. The methodology aims to take stock of these available data. The soil database is developed in five main steps. Step 1: All 148 soil types are ordered on the basis of their expected topographic position using e.g., drainage, salinization, and pedogenesis. Using the topographic ordering and combining the HWSD with a digital elevation model allows for the spatial disaggregation of the composite soil units. This results in a new soil map with homogeneous soil units. Step 2: The ranges of major soil properties for the topsoil and subsoil of each of the 148 soil types are derived from the ISRIC-WISE soil profile database. Step 3: A model of soil formation is developed that focuses on the basic conceptual question where we are within the range of a particular soil property at a particular location given a specific soil type. The soil properties are predicted for each grid cell based on the soil type, the corresponding ranges of soil properties, and the co-variables. Step 4: Standard depth profiles are developed for each of the soil types using the diagnostic criteria of the soil types and soil profile information from the ISRIC-WISE database. The standard soil profiles are combined with the the predicted values for the topsoil and subsoil yielding unique soil profiles at each location. Step 5: In a final step, additional soil properties are added to the database using averages for the soil types and pedo-transfer functions. The methodology, denominated S-World (Soils of the World), results in readily available global maps with quantitative pedon data for modelling purposes. It forms the basis for the Global Gridded Crop Model Intercomparison carried out within AgMIP.

Digital image transformation and rectification of spacecraft and radar images

NASA Technical Reports Server (NTRS)

Wu, S. S. C.

1985-01-01

The application of digital processing techniques to spacecraft television pictures and radar images is discussed. The use of digital rectification to produce contour maps from spacecraft pictures is described; images with azimuth and elevation angles are converted into point-perspective frame pictures. The digital correction of the slant angle of radar images to ground scale is examined. The development of orthophoto and stereoscopic shaded relief maps from digital terrain and digital image data is analyzed. Digital image transformations and rectifications are utilized on Viking Orbiter and Lander pictures of Mars.

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Trease, Brian; Arvidson, Raymond; Lindemann, Randel; Bennett, Keith; Zhou, Feng; Iagnemma, Karl; Senatore, Carmine; Van Dyke, Lauren

2011-01-01

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

A study of the utilization of ERTS-1 data from the Wabash River Basin. [crop identification, water resources, urban land use, soil mapping, and atmospheric modeling

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The most significant results were obtained in the water resources research, urban land use mapping, and soil association mapping projects. ERTS-1 data was used to classify water bodies to determine acreages and high agreement was obtained with USGS figures. Quantitative evaluation was achieved of urban land use classifications from ERTS-1 data and an overall test accuracy of 90.3% was observed. ERTS-1 data classifications of soil test sites were compared with soil association maps scaled to match the computer produced map and good agreement was observed. In some cases the ERTS-1 results proved to be more accurate than the soil association map.

Landscape-scale modelling of soil carbon dynamics under land use and climate change

NASA Astrophysics Data System (ADS)

Lacoste, Marine; Viaud, Valérie; Michot, Didier; Christian, Walter

2013-04-01

Soil organic carbon (SOC) sequestration is highly linked to soil use and farming practices, but also to soil redistributions, soil properties, and climate. In a global change context, landscape, farming practice and climate changes are expected; and they will most probably impact SOC dynamics. To assess their respective impacts, we modelled the SOC contents and stocks evolution at the scale of an agricultural landscape, by taking into account the soil redistribution by tillage and water processes. The simulations were conducted from 2010 to 2100 under different scenarios of landscape and climate. These scenarios combined different land uses associated to specific farming practices (mixed dairy with rotations of crops and grasslands, intensive cropping with only crops rotations or permanent grasslands), landscape managements (hedges planting or removal), and climates (business-as-usual climate and climate change, with temperature and precipitations increase). We used a spatially SOC dynamic model (adapted from RothC), coupled to a soil redistribution model (LandSoil). SOC dynamics were spatially modelled with a lateral resolution of 2-m and for soil organic layers up to 105 cm. Initial SOC stocks were described with a 2-m resolution map based on field data and produced with digital soil mapping methods. The major factor of change in SOC stocks was land use change, the second factor of importance was climate change, and finally landscape management: for the total SOC stocks (0-to-105 cm soil layer) the change of land use, climate and landscape management induced a respective mean absolute variation of 10 to 20 tC ha-1, 9 tC ha-1 and 0.4 tC ha-1. When considering the 0-to-105 cm soil layer, the different modelled landscapes showed the same sensitivity to climate change, with induced a mean decrease of 10 tC ha-1. However, the impact of climate change was found different according to the different modelled landscape when considering the 0-to-7.5 and 0-to-30 cm soil layers: the more sensitive landscapes were those of intensive cropping. This shows the importance of considering not only the plough layer, but also the vertical distribution of SOC stocks to assess the variation in SOC dynamics under land use, landscape management or climate change. Finally, rural hedgerow landscapes were proved to be quite well adapted for soil protection in a context of climate change, focusing on both carbon storage and soil erosion.

Digital Geologic Map of the Wallace 1:100,000 Quadrangle, Idaho

USGS Publications Warehouse

Lewis, Reed S.; Burmester, Russell F.; McFaddan, Mark D.; Derkey, Pamela D.; Oblad, Jon R.

1999-01-01

The geology of the Wallace 1:100,000 quadrangle, Idaho was compiled by Reed S. Lewis in 1997 primarily from published materials including 1983 data from Foster, Harrison's unpublished mapping done from 1975 to 1985, Hietenan's 1963, 1967, 1968, and 1984 mapping, Hobbs and others 1965 mapping, and Vance's 1981 mapping, supplemented by eight weeks of field mapping by Reed S. Lewis, Russell F. Burmester, and Mark D. McFaddan in 1997 and 1998. This geologic map information was inked onto a 1:100,000-scale greenline mylar of the topographic base map for input into a geographic information system (GIS). The resulting digital geologic map GIS can be queried in many ways to produce a variety of geologic maps. Digital base map data files (topography, roads, towns, rivers and lakes, etc.) are not included: they may be obtained from a variety of commercial and government sources. This database is not meant to be used or displayed at any scale larger than 1:100,000 (e.g., 1:62,500 or 1:24,000). The map area is located in north Idaho. The primary sources of map data are shown in figure 2 and additional sources are shown in figure 3. This open-file report describes the geologic map units, the methods used to convert the geologic map data into a digital format, the Arc/Info GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. Mapping and compilation was completed by the Idaho Geological Survey under contract with the U.S. Geological Survey (USGS) office in Spokane, Washington. The authors would like to acknowledge the help of the following field assistants: Josh Goodman, Yvonne Issak, Jeremy Johnson and Kevin Myer. Don Winston provided help with our ongoing study of Belt stratigraphy, and Tom Frost assisted with logistical problems and sample collection. Manuscript reviews by Steve Box, Tom Frost, and Brian White are greatly appreciated. We wish to thank Karen S. Bolm of the USGS for reviewing the digital files.

Transfer of Technology for Cadastral Mapping in Tajikistan Using High Resolution Satellite Data

NASA Astrophysics Data System (ADS)

Kaczynski, R.

2012-07-01

European Commission funded project entitled: "Support to the mapping and certification capacity of the Agency of Land Management, Geodesy and Cartography" in Tajikistan was run by FINNMAP FM-International and Human Dynamics from Nov. 2006 to June 2011. The Agency of Land Management, Geodesy and Cartography is the state agency responsible for development, implementation, monitoring and evaluation of state policies on land tenure and land management, including the on-going land reform and registration of land use rights. The specific objective was to support and strengthen the professional capacity of the "Fazo" Institute in the field of satellite geodesy, digital photogrammetry, advanced digital satellite image processing of high resolution satellite data and digital cartography. Lectures and on-the-job trainings for the personnel of "Fazo" and Agency in satellite geodesy, digital photogrammetry, cartography and the use of high resolution satellite data for cadastral mapping have been organized. Standards and Quality control system for all data and products have been elaborated and implemented in the production line. Technical expertise and trainings in geodesy, photogrammetry and satellite image processing to the World Bank project "Land Registration and Cadastre System for Sustainable Agriculture" has also been completed in Tajikistan. The new map projection was chosen and the new unclassified geodetic network has been established for all of the country in which all agricultural parcel boundaries are being mapped. IKONOS, QuickBird and WorldView1 panchromatic data have been used for orthophoto generation. Average accuracy of space triangulation of non-standard (long up to 90km) satellite images of QuickBird Pan and IKONOS Pan on ICPs: RMSEx = 0.5m and RMSEy = 0.5m have been achieved. Accuracy of digital orthophoto map is RMSExy = 1.0m. More then two and half thousands of digital orthophoto map sheets in the scale of 1:5000 with pixel size 0.5m have been produced so far by the "Fazo" Institute in Tajikistan on the basis of technology elaborated in the framework of this project. Digital cadastral maps are produced in "Fazo" and Cadastral Regional Centers in Tajikistan using ArcMap software. These digital orthophotomaps will also be used for digital mapping of water resources and other needs of the country.

Comparing Tactile Maps and Haptic Digital Representations of a Maritime Environment

ERIC Educational Resources Information Center

Simonnet, Mathieu; Vieilledent, Steephane; Jacobson, R. Daniel; Tisseau, Jacques

2011-01-01

A map exploration and representation exercise was conducted with participants who were totally blind. Representations of maritime environments were presented either with a tactile map or with a digital haptic virtual map. We assessed the knowledge of spatial configurations using a triangulation technique. The results revealed that both types of…

Mapping the spatial patterns of field traffic and traffic intensity to predict soil compaction risks at the field scale

NASA Astrophysics Data System (ADS)

Duttmann, Rainer; Kuhwald, Michael; Nolde, Michael

2015-04-01

Soil compaction is one of the main threats to cropland soils in present days. In contrast to easily visible phenomena of soil degradation, soil compaction, however, is obscured by other signals such as reduced crop yield, delayed crop growth, and the ponding of water, which makes it difficult to recognize and locate areas impacted by soil compaction directly. Although it is known that trafficking intensity is a key factor for soil compaction, until today only modest work has been concerned with the mapping of the spatially distributed patterns of field traffic and with the visual representation of the loads and pressures applied by farm traffic within single fields. A promising method for for spatial detection and mapping of soil compaction risks of individual fields is to process dGPS data, collected from vehicle-mounted GPS receivers and to compare the soil stress induced by farm machinery to the load bearing capacity derived from given soil map data. The application of position-based machinery data enables the mapping of vehicle movements over time as well as the assessment of trafficking intensity. It also facilitates the calculation of the trafficked area and the modeling of the loads and pressures applied to soil by individual vehicles. This paper focuses on the modeling and mapping of the spatial patterns of traffic intensity in silage maize fields during harvest, considering the spatio-temporal changes in wheel load and ground contact pressure along the loading sections. In addition to scenarios calculated for varying mechanical soil strengths, an example for visualizing the three-dimensional stress propagation inside the soil will be given, using the Visualization Toolkit (VTK) to construct 2D or 3D maps supporting to decision making due to sustainable field traffic management.

Digital terrain tapes: user guide

USGS Publications Warehouse

,

1980-01-01

DMATC's digital terrain tapes are a by-product of the agency's efforts to streamline the production of raised-relief maps. In the early 1960's DMATC developed the Digital Graphics Recorder (DGR) system that introduced new digitizing techniques and processing methods into the field of three-dimensional mapping. The DGR system consisted of an automatic digitizing table and a computer system that recorded a grid of terrain elevations from traces of the contour lines on standard topographic maps. A sequence of computer accuracy checks was performed and then the elevations of grid points not intersected by contour lines were interpolated. The DGR system produced computer magnetic tapes which controlled the carving of plaster forms used to mold raised-relief maps. It was realized almost immediately that this relatively simple tool for carving plaster molds had enormous potential for storing, manipulating, and selectively displaying (either graphically or numerically) a vast number of terrain elevations. As the demand for the digital terrain tapes increased, DMATC began developing increasingly advanced digitizing systems and now operates the Digital Topographic Data Collection System (DTDCS). With DTDCS, two types of data elevations as contour lines and points, and stream and ridge lines are sorted, matched, and resorted to obtain a grid of elevation values for every 0.01 inch on each map (approximately 200 feet on the ground). Undefined points on the grid are found by either linear or or planar interpolation.

Cokriging of Electromagnetic Induction Soil Electrical Conductivity Measurements and Soil Textural Properties to Demarcate Sub-field Management Zones for Precision Irrigation.

NASA Astrophysics Data System (ADS)

Ding, R.; Cruz, L.; Whitney, J.; Telenko, D.; Oware, E. K.

2017-12-01

There is the growing need for the development of efficient irrigation management practices due to increasing irrigation water scarcity as a result of growing population and changing climate. Soil texture primarily controls the water-holding capacity of soils, which determines the amount of irrigation water that will be available to the plant. However, while there are significant variabilities in the textural properties of the soil across a field, conventional irrigation practices ignore the underlying variability in the soil properties, resulting in over- or under-irrigation. Over-irrigation leaches plant nutrients beyond the root-zone leading to fertilizer, energy, and water wastages with dire environmental consequences. Under-irrigation, in contrast, causes water stress of the plant, thereby reducing plant quality and yield. The goal of this project is to leverage soil textural map of a field to create water management zones (MZs) to guide site-specific precision irrigation. There is increasing application of electromagnetic induction methods to rapidly and inexpensively map spatially continuous soil properties in terms of the apparent electrical conductivity (ECa) of the soil. ECa is a measure of the bulk soil properties, including soil texture, moisture, salinity, and cation exchange capacity, making an ECa map a pseudo-soil map. Data for the project were collected from a farm site at Eden, NY. The objective is to leverage high-resolution ECa map to predict spatially dense soil textural properties from limited measurements of soil texture. Thus, after performing ECa mapping, we conducted particle-size analysis of soil samples to determine the textural properties of soils at selected locations across the field. We cokriged the high-resolution ECa measurements with the sparse soil textural data to estimate a soil texture map for the field. We conducted irrigation experiments at selected locations to calibrate representative water-holding capacities of each estimated soil textural unit. Estimated soil units with similar water-holding characteristics were merged to create sub-field water MZs to guide precision irrigation of each MZ, instructed by each MZ's calibrated water-holding properties.

Soil mapping and process modeling for sustainable land use management: a brief historical review

NASA Astrophysics Data System (ADS)

Brevik, Eric C.; Pereira, Paulo; Muñoz-Rojas, Miriam; Miller, Bradley A.; Cerdà, Artemi; Parras-Alcántara, Luis; Lozano-García, Beatriz

2017-04-01

Basic soil management goes back to the earliest days of agricultural practices, approximately 9,000 BCE. Through time humans developed soil management techniques of ever increasing complexity, including plows, contour tillage, terracing, and irrigation. Spatial soil patterns were being recognized as early as 3,000 BCE, but the first soil maps didn't appear until the 1700s and the first soil models finally arrived in the 1880s (Brevik et al., in press). The beginning of the 20th century saw an increase in standardization in many soil science methods and wide-spread soil mapping in many parts of the world, particularly in developed countries. However, the classification systems used, mapping scale, and national coverage varied considerably from country to country. Major advances were made in pedologic modeling starting in the 1940s, and in erosion modeling starting in the 1950s. In the 1970s and 1980s advances in computing power, remote and proximal sensing, geographic information systems (GIS), global positioning systems (GPS), and statistics and spatial statistics among other numerical techniques significantly enhanced our ability to map and model soils (Brevik et al., 2016). These types of advances positioned soil science to make meaningful contributions to sustainable land use management as we moved into the 21st century. References Brevik, E., Pereira, P., Muñoz-Rojas, M., Miller, B., Cerda, A., Parras-Alcantara, L., Lozano-Garcia, B. Historical perspectives on soil mapping and process modelling for sustainable land use management. In: Pereira, P., Brevik, E., Muñoz-Rojas, M., Miller, B. (eds) Soil mapping and process modelling for sustainable land use management (In press). Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. 2016. Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274.

Digital geologic map database of the Nevada Test Site area, Nevada

USGS Publications Warehouse

Wahl, R.R.; Sawyer, D.A.; Minor, S.A.; Carr, M.D.; Cole, J.C.; Swadley, W.C.; Laczniak, R.J.; Warren, R.G.; Green, K.S.; Engle, C.M.

1997-01-01

Forty years of geologic investigations at the Nevada Test Site (NTS) have been digitized. These data include all geologic information that: (1) has been collected, and (2) can be represented on a map within the map borders at the map scale is included in the map digital coverages. The following coverages are included with this dataset: Coverage Type Description geolpoly Polygon Geologic outcrops geolflts line Fault traces geolatts Point Bedding attitudes, etc. geolcald line Caldera boundaries geollins line Interpreted lineaments geolmeta line Metamorphic gradients The above coverages are attributed with numeric values and interpreted information. The entity files documented below show the data associated with each coverage.

Land use and land cover digital data from 1:250,000- and 1:100,000- scale maps

USGS Publications Warehouse

,

1990-01-01

The Earth Science Information Centers (ESIC) distribute digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. The data files are grouped into four basic types. The first type, called a Digital Line Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for ground positions that are usually at regularly spaced intervals. The third type, Land Use and Land Cover digital data, provide information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for known places, features, and areas in the United States identified by a proper name.

Digital mono- and 3D stereo-photogrammetry for geological and geomorphological mapping

NASA Astrophysics Data System (ADS)

Scapozza, Cristian; Schenker, Filippo Luca; Castelletti, Claudio; Bozzini, Claudio; Ambrosi, Christian

2016-04-01

The generalization of application of digital tools for managing, mapping and updating geological data have become widely accepted in the last decennia. Despite the increasing quality and availability of digital topographical maps, orthorectified aerial photographs (orthophotos) and high resolution (5 up to 0.5 m) Digital Elevation Models (DEMs), a correct recognition of the kind, the nature and the boundaries of geological formations and geomophological landforms, unconsolidated sedimentary deposits or slope instabilities is often very difficult on conventional two-dimensional (2D) products, in particular in steep zones (rock walls and talus slopes), under the forest cover, for a very complex topography and in deeply urbanised zones. In many cases, photo-interpretative maps drawn only by 2D data sets must be improved by field verifications or, at least, by field oblique photographs. This is logical, because our natural perception of the real world is three-dimensional (3D), which is partially disabled by the application of 2D visualization techniques. Here we present some examples of application of digital mapping based on a 3D visualization (for aerial and satellite images photo-interpretation) or on a terrestrial perception by digital mono-photogrammetry (for oblique photographs). The 3D digital mapping was performed thanks to an extension of the software ESRI® ArcGIS™ called ArcGDS™. This methodology was also applied on historical aerial photographs (normally analysed by optical stereo-photogrammetry), which were digitized by scanning and then oriented and aero-triangulated thanks to the ArcGDS™ software, allowing the 3D visualisation and the mapping in a GIS environment (Ambrosi and Scapozza, 2015). The mono-photogrammetry (or monoplotting) is the technique of photogrammetrical georeferentiation of single oblique unrectified photographs, which are related to a DEM. In other words, the monoplotting allows relating each pixel of the photograph to the corresponding real world pixel on the DEM, and then extract georeferenced vector data and orthorectified raster data from terrestrial photographs (Bozzini et al., 2012; Scapozza et al., 2014). Through some case studies, we show (1) how 3D digital stereo-photogrammetry makes it possible the production of Quaternary geological and geomorphological maps, (2) how digital mono-photogrammetry is a powerful tool for supporting geological mapping in very steep zones and (3) how the combination of these two digital tools permits diachronical mapping of phenomena evolution (such as landslides or rockglaciers) during the entire twentieth century. Ambrosi C. and Scapozza C. 2015. Improvements in 3-D digital mapping for geomorphological and Quaternary geological cartography. Geographica Helvetica 70: 121-133. doi: 10.5194/gh-70-121-2015 Bozzini C., Conedera M. and Krebs P. 2012. A new monoplotting tool to extract georeferenced vector data and orthorectified raster data from oblique non-metric photographs. International Journal of Heritage in the Digital Era 1: 499-518. doi: 10.1260/2047-4970.1.3.499 Scapozza C., Lambiel C., Bozzini C., Mari S. and Conedera M. 2014. Assessing the rock glacier kinematics on three different timescales: a case study from the southern Swiss Alps. Earth Surface Processes and Landforms 39: 2056-2069. doi: 10.1002/esp.3599

LANDSAT-1 data, its use in a soil survey program

NASA Technical Reports Server (NTRS)

Westin, F. C.; Frazee, C. J.

1975-01-01

The following applications of LANDSAT imagery were investigated: assistance in recognizing soil survey boundaries, low intensity soil surveys, and preparation of a base map for publishing thematic soils maps. The following characteristics of LANDSAT imagery were tested as they apply to the recognition of soil boundaries in South Dakota and western Minnesota: synoptic views due to the large areas covered, near-orthography and lack of distortion, flexibility of selecting the proper season, data recording in four parts of the spectrum, and the use of computer compatible tapes. A low intensity soil survey of Pennington County, South Dakota was completed in 1974. Low intensity inexpensive soil surveys can provide the data needed to evaluate agricultural land for the remaining counties until detailed soil surveys are completed. In using LANDSAT imagery as a base map for publishing thematic soil maps, the first step was to prepare a mosaic with 20 LANDSAT scenes from several late spring passes in 1973.

ERTS-1 MSS imagery: Its use in delineating soil associations and as a base map for publishing soils information. [South Dakota

NASA Technical Reports Server (NTRS)

Westin, F. C.

1974-01-01

ERTS 1 imagery is a useful tool in the identification and refinement of soil association areas and an excellent base map upon which soil association information can be published. Prints of bands 5 and 7 were found to be most useful to help delineate major soil and vegetation areas. After delineating major soil areas, over 4800 land sale prices covering a period of 1967-72 were located in the soil areas and averaged. The soil association then were described as soil association value areas and published on a 1:1,000,000 scale ERTS mosaic of South Dakota constructed using negative prints of band 7. The map is intended for use by state and county revenue officers, by individual buyers and sellers of land and lending institutions, and as a reference map by those planning road routes and cable lines and pipelines.

Integrated geomorphologic and GIS analysis for the assessment of erosion zones and its relationship with hazardous zones in the Zacatecas and Guadalupe quadrangles, Mexico

NASA Astrophysics Data System (ADS)

Escalona-Alcázar, F. d. J.; Escobedo-Arellano, B.; Castillo-Félix, B.; Carrillo-Castillo, C.; García-Sandoval, P.; Gurrola-Menchaca, L. L.; Núñez-Peña, E. P.; Esparza-Martínez, A.; Bluhm-Gutiérrez, J.; Guijarro-Rodríguez, C. J.

2012-04-01

The morphology of the Zacatecas and Guadalupe quadrangles is composed to the West by a NNE-SSW fault bounded range and to the East a valley cut by minor hills. The most important and fast growing cities in the state are located in that range. However, in urban development plans variables such as the geology and geomorphologic processes, as well as the land cover characteristics, are poorly taken into consideration. Due to the landscape modification the erosion agents, mainly water, removes loose materials that are either natural or artificial. The effects on the buildings and roads are fractures, slope instability, and rock falling. In this study we present a model that considers the detailed geologic mapping, the geomorphology, land use, vegetation, and the digital slope model scale 1:50 000. The geomorphologic parameters considered were: relief energy, dissection density, general dissection density, and maximum dissection depth. The location and internal characteristics of mapped talus deposits were the basis to define the erosion criteria. High erosion zones are located in slopes over 20° where the talus deposits initiate due to the relative abundance of loose debris. Medium erosion areas are located in slopes over 10° that downslope has progressive accumulation of sediments. While the low erosion zones are located in slopes ranging from 5° to 20° with almost flat lying beds. These parameters were analyzed in ArcGIS together with the digital slope model, detailed geology mapping, the land use cover, and the soil information. The results where verified in the range where the city has been growing in recent years. The soils all over the range are lithosols which are only 10 to 15 cm thick; while the vegetation is composed mainly of bushes and nopals. Even though both, vegetation and soil are not modified, the erosion effects in them are very slow regardless of their location. The faults located in high erosion zones facilitate rock falling mainly during the rainy season; whereas in medium erosion zones it occurs if the road cuts or cliffs are steep. The rocks varying from loose to moderately consolidated, as well as the artificial fillings and talus deposits, are easily or difficultly eroded according with the erosion zones proposed in our model. The effects observed are fractured roads and house walls, removal of soil underneath the buildings, gullies formation, and slope instability. The model defines areas where the erosion effects can be related to the development of hazardous zones. This model gives criteria for land use planning and urban development.

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete.

PubMed

Karydas, Christos G; Sekuloska, Tijana; Silleos, Georgios N

2009-02-01

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.

Soil mapping and processes modelling for sustainable land management: a review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

2017-04-01

Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

National Soil Information System in Turkey

NASA Astrophysics Data System (ADS)

Emrah Erdogan, Hakki; Sahin, Mehmet; Sahin, Yuksel

2013-04-01

Land consolidation (LC) represents complexity if management, legal, economic and technical procedures realized in order to adjust the land structure according to actual human preferences and needs. It includes changes in ownership rights to land and other real estate property, exchange of parcels among owners, changes in parcel borders, parcel size and shape, joining and dividing of parcels, changes in land use, construction works as roads, bridges, water changes etc.. Since the subject of LC is agricultural lands, the quality of consolidation depends on the quality of soil data. General Directorate of Agrarian Reform (GDAR) is the responsible institution on land consolidation whole of Turkey. Under GDAR, National Soil Information System (NSIS) has been build up with base soil data in relevant scale (1:5000). NSIS contain detailed information on soil chemical and physical properties, current land use, parent material, land capability class, Storie Index Values. SI were used on land consolidation, land use planning and farm development services. LCC was used for land distribution, rental land; define of village settlement, consolidation, expropriation, reconstruction, reclamation, non-agricultural usage. LCC were also specified to subclasses in four different limited factors as i) flow and erosion risk ii) requirement of drainage and soil moisture iii) Limits of soil tillage and root (shallow soils, low water retention capacity, stony, salty .etc) iv) climatic limits. In this study, digital soil survey and mapping project located in Yumurtalik, Adana is presented as an example of NSIS data structure. The project cover an area of 45709 ha that include crop lands as an area of 28528 ha and other land use (urban, roads..etc) as an area of 17181 ha. Soil profiles were described in 45 different points and totally 1279 soil samples were collected in field study and the check bore hole were made in 3170 points.

Quantifying soil burn severity for hydrologic modeling to assess post-fire effects on sediment delivery

NASA Astrophysics Data System (ADS)

Dobre, Mariana; Brooks, Erin; Lew, Roger; Kolden, Crystal; Quinn, Dylan; Elliot, William; Robichaud, Pete

2017-04-01

Soil erosion is a secondary fire effect with great implications for many ecosystem resources. Depending on the burn severity, topography, and the weather immediately after the fire, soil erosion can impact municipal water supplies, degrade water quality, and reduce reservoirs' storage capacity. Scientists and managers use field and remotely sensed data to quickly assess post-fire burn severity in ecologically-sensitive areas. From these assessments, mitigation activities are implemented to minimize post-fire flood and soil erosion and to facilitate post-fire vegetation recovery. Alternatively, land managers can use fire behavior and spread models (e.g. FlamMap, FARSITE, FOFEM, or CONSUME) to identify sensitive areas a priori, and apply strategies such as fuel reduction treatments to proactively minimize the risk of wildfire spread and increased burn severity. There is a growing interest in linking fire behavior and spread models with hydrology-based soil erosion models to provide site-specific assessment of mitigation treatments on post-fire runoff and erosion. The challenge remains, however, that many burn severity mapping and modeling products quantify vegetation loss rather than measuring soil burn severity. Wildfire burn severity is spatially heterogeneous and depends on the pre-fire vegetation cover, fuel load, topography, and weather. Severities also differ depending on the variable of interest (e.g. soil, vegetation). In the United States, Burned Area Reflectance Classification (BARC) maps, derived from Landsat satellite images, are used as an initial burn severity assessment. BARC maps are classified from either a Normalized Burn Ratio (NBR) or differenced Normalized Burned Ratio (dNBR) scene into four classes (Unburned, Low, Moderate, and High severity). The development of soil burn severity maps requires further manual field validation efforts to transform the BARC maps into a product more applicable for post-fire soil rehabilitation activities. Alternative spectral indices and modeled output approaches may prove better predictors of soil burn severity and hydrologic effects, but these have not yet been assessed in a model framework. In this project we compare field-verified soil burn severity maps to satellite-derived and modeled burn severity maps. We quantify the extent to which there are systematic differences in these mapping products. We then use the Water Erosion Prediction Project (WEPP) hydrologic soil erosion model to assess sediment delivery from these fires using the predicted and observed soil burn severity maps. Finally, we discuss differences in observed and predicted soil burn severity maps and application to watersheds in the Pacific Northwest to estimate post-fire sediment delivery.

A digital version of the 1970 U.S. Geological Survey topographic map of the San Francisco Bay region, three sheets, 1:125,000

USGS Publications Warehouse

Aitken, Douglas S.

1997-01-01

This Open-File report is a digital topographic map database. It contains a digital version of the 1970 U.S. Geological Survey topographic map of the San Francisco Bay Region (3 sheets), at a scale of 1:125,000. These ARC/INFO coverages are in vector format. The vectorization process has distorted characters representing letters and numbers, as well as some road and other symbols, making them difficult to read in some instances. This pamphlet serves to introduce and describe the digital data. There is no paper map included in the Open-File report. The content and character of the database and methods of obtaining it are described herein.

Determination of Soil Erosion Risk in the Mustafakemalpasa River Basin, Turkey, Using the Revised Universal Soil Loss Equation, Geographic Information System, and Remote Sensing

NASA Astrophysics Data System (ADS)

Ozsoy, Gokhan; Aksoy, Ertugrul; Dirim, M. Sabri; Tumsavas, Zeynal

2012-10-01

Sediment transport from steep slopes and agricultural lands into the Uluabat Lake (a RAMSAR site) by the Mustafakemalpasa (MKP) River is a serious problem within the river basin. Predictive erosion models are useful tools for evaluating soil erosion and establishing soil erosion management plans. The Revised Universal Soil Loss Equation (RUSLE) function is a commonly used erosion model for this purpose in Turkey and the rest of the world. This research integrates the RUSLE within a geographic information system environment to investigate the spatial distribution of annual soil loss potential in the MKP River Basin. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index: The topographic factor was developed from a digital elevation model; the K factor was determined from a combination of the soil map and the geological map; and the land cover factor was generated from Landsat-7 Enhanced Thematic Mapper (ETM) images. According to the model, the total soil loss potential of the MKP River Basin from erosion by water was 11,296,063 Mg year-1 with an average soil loss of 11.2 Mg year-1. The RUSLE produces only local erosion values and cannot be used to estimate the sediment yield for a watershed. To estimate the sediment yield, sediment-delivery ratio equations were used and compared with the sediment-monitoring reports of the Dolluk stream gauging station on the MKP River, which collected data for >41 years (1964-2005). This station observes the overall efficiency of the sediment yield coming from the Orhaneli and Emet Rivers. The measured sediment in the Emet and Orhaneli sub-basins is 1,082,010 Mg year-1 and was estimated to be 1,640,947 Mg year-1 for the same two sub-basins. The measured sediment yield of the gauge station is 127.6 Mg km-2 year-1 but was estimated to be 170.2 Mg km-2 year-1. The close match between the sediment amounts estimated using the RUSLE-geographic information system (GIS) combination and the measured values from the Dolluk sediment gauge station shows that the potential soil erosion risk of the MKP River Basin can be estimated correctly and reliably using the RUSLE function generated in a GIS environment.

The digital geologic map of Colorado in ARC/INFO format, Part A. Documentation

USGS Publications Warehouse

Green, Gregory N.

1992-01-01

This geologic map was prepared as a part of a study of digital methods and techniques as applied to complex geologic maps. The geologic map was digitized from the original scribe sheets used to prepare the published Geologic Map of Colorado (Tweto 1979). Consequently the digital version is at 1:500,000 scale using the Lambert Conformal Conic map projection parameters of the state base map. Stable base contact prints of the scribe sheets were scanned on a Tektronix 4991 digital scanner. The scanner automatically converts the scanned image to an ASCII vector format. These vectors were transferred to a VAX minicomputer, where they were then loaded into ARC/INFO. Each vector and polygon was given attributes derived from the original 1979 geologic map. This database was developed on a MicroVAX computer system using VAX V 5.4 nd ARC/INFO 5.0 software. UPDATE: April 1995, The update was done solely for the purpose of adding the abilitly to plot to an HP650c plotter. Two new ARC/INFO plot AMLs along with a lineset and shadeset for the HP650C design jet printer have been included. These new files are COLORADO.650, INDEX.650, TWETOLIN.E00 and TWETOSHD.E00. These files were created on a UNIX platform with ARC/INFO 6.1.2. Updated versions of INDEX.E00, CONTACT.E00, LINE.E00, DECO.E00 and BORDER.E00 files that included the newly defined HP650c items are also included. * Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Descriptors: The Digital Geologic Map of Colorado in ARC/INFO Format Open-File Report 92-050

The digital geologic map of Colorado in ARC/INFO format, Part B. Common files

USGS Publications Warehouse

Green, Gregory N.

1992-01-01

This geologic map was prepared as a part of a study of digital methods and techniques as applied to complex geologic maps. The geologic map was digitized from the original scribe sheets used to prepare the published Geologic Map of Colorado (Tweto 1979). Consequently the digital version is at 1:500,000 scale using the Lambert Conformal Conic map projection parameters of the state base map. Stable base contact prints of the scribe sheets were scanned on a Tektronix 4991 digital scanner. The scanner automatically converts the scanned image to an ASCII vector format. These vectors were transferred to a VAX minicomputer, where they were then loaded into ARC/INFO. Each vector and polygon was given attributes derived from the original 1979 geologic map. This database was developed on a MicroVAX computer system using VAX V 5.4 nd ARC/INFO 5.0 software. UPDATE: April 1995, The update was done solely for the purpose of adding the abilitly to plot to an HP650c plotter. Two new ARC/INFO plot AMLs along with a lineset and shadeset for the HP650C design jet printer have been included. These new files are COLORADO.650, INDEX.650, TWETOLIN.E00 and TWETOSHD.E00. These files were created on a UNIX platform with ARC/INFO 6.1.2. Updated versions of INDEX.E00, CONTACT.E00, LINE.E00, DECO.E00 and BORDER.E00 files that included the newly defined HP650c items are also included. * Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Descriptors: The Digital Geologic Map of Colorado in ARC/INFO Format Open-File Report 92-050

A simplified close range photogrammetry method for soil erosion assessment

USDA-ARS?s Scientific Manuscript database

With the increased affordability of consumer grade cameras and the development of powerful image processing software, digital photogrammetry offers a competitive advantage as a tool for soil erosion estimation compared to other technologies. One bottleneck of digital photogrammetry is its dependency...

Digital image analysis techniques for fiber and soil mixtures : technical summary.

DOT National Transportation Integrated Search

1999-05-01

This project used to innovative technologies of digital image analysis for the characterization of a material currently being considered for broad use at DOTD. The material under consideration is a mixture of fiber and soil for use in the stabilizati...

Map showing geologic terranes of the Hailey 1 degree x 2 degrees quadrangle and the western part of the Idaho Falls 1 degree x 2 degrees quadrangle, south-central Idaho

USGS Publications Warehouse

Worl, R.G.; Johnson, K.M.

1995-01-01

The paper version of Map Showing Geologic Terranes of the Hailey 1x2 Quadrangle and the western part of the Idaho Falls 1x2 Quadrangle, south-central Idaho was compiled by Ron Worl and Kate Johnson in 1995. The plate was compiled on a 1:250,000 scale topographic base map. TechniGraphic System, Inc. of Fort Collins Colorado digitized this map under contract for N.Shock. G.Green edited and prepared the digital version for publication as a geographic information system database. The digital geologic map database can be queried in many ways to produce a variety of geologic maps.

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

Signal digitizing system and method based on amplitude-to-time optical mapping

DOEpatents

Chou, Jason; Bennett, Corey V; Hernandez, Vince

2015-01-13

A signal digitizing system and method based on analog-to-time optical mapping, optically maps amplitude information of an analog signal of interest first into wavelength information using an amplitude tunable filter (ATF) to impress spectral changes induced by the amplitude of the analog signal onto a carrier signal, i.e. a train of optical pulses, and next from wavelength information to temporal information using a dispersive element so that temporal information representing the amplitude information is encoded in the time domain in the carrier signal. Optical-to-electrical conversion of the optical pulses into voltage waveforms and subsequently digitizing the voltage waveforms into a digital image enables the temporal information to be resolved and quantized in the time domain. The digital image may them be digital signal processed to digitally reconstruct the analog signal based on the temporal information with high fidelity.

Quaternary Geology and Liquefaction Susceptibility, San Francisco, California 1:100,000 Quadrangle: A Digital Database

USGS Publications Warehouse

Knudsen, Keith L.; Noller, Jay S.; Sowers, Janet M.; Lettis, William R.

1997-01-01

This Open-File report is a digital geologic map database. This pamphlet serves to introduce and describe the digital data. There are no paper maps included in the Open-File report. The report does include, however, PostScript plot files containing the images of the geologic map sheets with explanations, as well as the accompanying text describing the geology of the area. For those interested in a paper plot of information contained in the database or in obtaining the PostScript plot files, please see the section entitled 'For Those Who Aren't Familiar With Digital Geologic Map Databases' below. This digital map database, compiled from previously unpublished data, and new mapping by the authors, represents the general distribution of surficial deposits in the San Francisco bay region. Together with the accompanying text file (sf_geo.txt or sf_geo.pdf), it provides current information on Quaternary geology and liquefaction susceptibility of the San Francisco, California, 1:100,000 quadrangle. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:100,000 or smaller. The content and character of the database, as well as three methods of obtaining the database, are described below.

Hydrologic Reconnaissance of Wetland-Bird Habitat in Areas With Potential to be Influenced by Water Produced During Coalbed Methane Production in the Northern Powder River Basin, MT

NASA Astrophysics Data System (ADS)

Custer, S. G.; Sojda, R. S.

2003-12-01

The removal and disposal of ground water during production of coalbed methane has the potential to influence wetland-bird habitat in the Powder River Basin. Office analysis of wetland areas was conducted on National Wetland Inventory maps and Digital Orthophoto Quadrangles along the Tongue and Powder rivers in the northern Powder River Basin, Montana. Selected sites were palustrine emergent, large enough to be important to waterbirds, part of a wetland complex, not dependent on artificial water regimes, in an area with high potential for coalbed methane production, and judged to be accessible in the field. Several promising wetland areas were selected for field examination. Field investigation suggests that the most promising wetlands in oxbow cutoffs would not be productive sites. Only facultative not obligate wetland plants were observed, the topographic position of the wetlands suggested that flooding would be infrequent, and the stream flow would likely dilute the effect of produced water adjacent to these rivers. Fortuitously wetland-bird habitat not recognized on the National Wetland Inventory maps and Digital Orthophoto Quadrangles was observed along Rosebud Creek during the field reconnaissance. This habitat is not continuous. The lack of continuity is reflected in the soil surveys as well as in the reconnaissance field nvestigation. The Alluvial Land soil series corresponds to observed wetland areas but the extent of the wetland-bird habitat varies substantially within the soil unit. When the Korchea series is present, extensive wetland-bird habitat is not observed. Field and aerial photo analysis suggests that the presence of the habitat may be controlled by beaver, and/or by stratigraphic and structural elements that influence stream erosion. Human modification of the stream for irrigation purposes may impact habitat continuity in some areas. The "Rosebud" type wetland-bird habitat may have the potential to be influenced by coalbed methane water production and warrants further more detailed investigation to determine the areal extent of the habitat, to determine the factors that control the distribution of intermittent wetland-bird-habitat areas, and to better model whether and how water produced during coalbed methane development might influence wetland-bird habitat.

Petrographic characterization of lunar soils: Application of x ray digital-imaging to quantitative and automated analysis

NASA Technical Reports Server (NTRS)

Higgins, Stefan J.; Patchen, Allan; Chambers, John G.; Taylor, Lawrence A.; Mckay, David S.

1994-01-01

The rocks and soils of the moon will be the raw materials for various engineering needs at a lunar base, such as sources of hydrogen, oxygen, metals, etc. The material of choice for most of the bulk needs is the regolith and its less than 1 cm fraction, the soil. For specific mineral resources it may be necessary to concentrate minerals from either rocks or soils. Therefore, quantitative characterizations of these rocks and soils are necessary in order to better define their mineral resource potential. However, using standard point-counting microscopic procedures, it is difficult to quantitatively determine mineral abundances and virtually impossible to obtain data on mineral distributions within grains. As a start to fulfilling these needs, Taylor et al. and Chambers et al. have developed a procedure for characterization of crushed lunar rocks using x ray digital imaging. The development of a similar digital imaging procedure for lunar soils as obtained from a spectrometer is described.

Watershed boundaries and digital elevation model of Oklahoma derived from 1:100,000-scale digital topographic maps

USGS Publications Warehouse

Cederstrand, J.R.; Rea, A.H.

1995-01-01

This document provides a general description of the procedures used to develop the data sets included on this compact disc. This compact disc contains watershed boundaries for Oklahoma, a digital elevation model, and other data sets derived from the digital elevation model. The digital elevation model was produced using the ANUDEM software package, written by Michael Hutchinson and licensed from the Centre for Resource and Environmental Studies at The Australian National University. Elevation data (hypsography) and streams (hydrography) from digital versions of the U.S. Geological Survey 1:100,000-scale topographic maps were used by the ANUDEM package to produce a hydrologically conditioned digital elevation model with a 60-meter cell size. This digital elevation model is well suited for drainage-basin delineation using automated techniques. Additional data sets include flow-direction, flow-accumulation, and shaded-relief grids, all derived from the digital elevation model, and the hydrography data set used in producing the digital elevation model. The watershed boundaries derived from the digital elevation model have been edited to be consistent with contours and streams from the U.S. Geological Survey 1:100,000-scale topographic maps. The watershed data set includes boundaries for 11-digit Hydrologic Unit Codes (watersheds) within Oklahoma, and 8-digit Hydrologic Unit Codes (cataloging units) outside Oklahoma. Cataloging-unit boundaries based on 1:250,000-scale maps outside Oklahoma for the Arkansas, Red, and White River basins are included. The other data sets cover Oklahoma, and where available, portions of 1:100,000-scale quadrangles adjoining Oklahoma.

Digital database of the geologic map of the island of Hawai'i [Hawaii

USGS Publications Warehouse

Trusdell, Frank A.; Wolfe, Edward W.; Morris, Jean

2006-01-01

This online publication (DS 144) provides the digital database for the printed map by Edward W. Wolfe and Jean Morris (I-2524-A; 1996). This digital database contains all the information used to publish U.S. Geological Survey Geologic Investigations Series I-2524-A (available only in paper form; see http://pubs.er.usgs.gov/pubs/i/i2524A). The database contains the distribution and relationships of volcanic and surficial-sedimentary deposits on the island of Hawai‘i. This dataset represents the geologic history for the five volcanoes that comprise the Island of Hawai'i. The volcanoes are Kohala, Mauna Kea, Hualalai, Mauna Loa and Kīlauea.This database of the geologic map contributes to understanding the geologic history of the Island of Hawai‘i and provides the basis for understanding long-term volcanic processes in an intra-plate ocean island volcanic system. In addition the database also serves as a basis for producing volcanic hazards assessment for the island of Hawai‘i. Furthermore it serves as a base layer to be used for interdisciplinary research.This online publication consists of a digital database of the geologic map, an explanatory pamphlet, description of map units, correlation of map units diagram, and images for plotting. Geologic mapping was compiled at a scale of 1:100,000 for the entire mapping area. The geologic mapping was compiled as a digital geologic database in ArcInfo GIS format.

DEVELOPMENT OF LAND COVER AND TERRAIN DATA BASES FOR THE INNOKO NATIONAL WILDLIFE REFUGE, ALASKA, USING LANDSAT AND DIGITAL TERRAIN DATA.

USGS Publications Warehouse

Markon, Carl J.; Talbot, Stephen

1986-01-01

Landsat-derived land cover maps and associated elevation, slope, and aspect class maps were produced for the Innoko National Wildlife Refuge (3,850,000 acres; 1,555,095 hectares) in northwestern Alaska. These maps and associated digital data products are being used by the U. S. Fish and Wildlife Service for wildlife management, research, and comprehensive conservation planning. Portions of two Landsat Multispectral Scanner (MSS) scenes and digital terrain data were used to produce 1:250,000 scale land cover and terrain maps. Prints of summer and winter Landsat MSS scenes were used to manually interpret broad physiographic strata. These strata were transferred to U. S. Geological Survey 1:250,000-scale topographic maps and digitized. Seven major land cover classes and 23 subclasses were identified. The major land cover classes include: forest, scrub, dwarf scrub and related types, herbaceous, scarcely vegetated areas, water, and shadow.

3D silicon breast surface mapping via structured light profilometry

NASA Astrophysics Data System (ADS)

Vairavan, R.; Ong, N. R.; Sauli, Z.; Kirtsaeng, S.; Sakuntasathien, S.; Shahimin, M. M.; Alcain, J. B.; Lai, S. L.; Paitong, P.; Retnasamy, V.

2017-09-01

Digital fringe projection technique is one of the promising optical methods for 3D surface imaging as it demonstrates non contact and non invasive characteristics. The potential of this technique matches the requirement for human body evaluation, as it is vital for disease diagnosis and for treatment option selection. Thus, the digital fringe projection has addressed this requirement with its wide clinical related application and studies. However, the application of this technique for 3D surface mapping of the breast is very minimal. Hence, in this work, the application of digital fringe projection for 3D breast surface mapping is reported. Phase shift fringe projection technique was utilized to perform the 3D breast surface mapping. Maiden results have confirmed the feasibility of using the digital fringe projection method for 3D surface mapping of the breast and it can be extended for breast cancer detection.

Method for the visualization of landform by mapping using low altitude UAV application

NASA Astrophysics Data System (ADS)

Sharan Kumar, N.; Ashraf Mohamad Ismail, Mohd; Sukor, Nur Sabahiah Abdul; Cheang, William

2018-05-01

Unmanned Aerial Vehicle (UAV) and Digital Photogrammetry are evolving drastically in mapping technology. The significance and necessity for digital landform mapping are developing with years. In this study, a mapping workflow is applied to obtain two different input data sets which are the orthophoto and DSM. A fine flying technology is used to capture Low Altitude Aerial Photography (LAAP). Low altitude UAV (Drone) with the fixed advanced camera was utilized for imagery while computerized photogrammetry handling using Photo Scan was applied for cartographic information accumulation. The data processing through photogrammetry and orthomosaic processes is the main applications. High imagery quality is essential for the effectiveness and nature of normal mapping output such as 3D model, Digital Elevation Model (DEM), Digital Surface Model (DSM) and Ortho Images. The exactitude of Ground Control Points (GCP), flight altitude and the resolution of the camera are essential for good quality DEM and Orthophoto.

Geologic Communications | Alaska Division of Geological & Geophysical

Science.gov Websites

improves a database for the Division's digital and map-based geological, geophysical, and geochemical data interfaces DGGS metadata and digital data distribution - Geospatial datasets published by DGGS are designed to be compatible with a broad variety of digital mapping software, to present DGGS's geospatial data

Evaluating RGB photogrammetry and multi-temporal digital surface models for detecting soil erosion

NASA Astrophysics Data System (ADS)

Anders, Niels; Keesstra, Saskia; Seeger, Manuel

2013-04-01

Photogrammetry is a widely used tool for generating high-resolution digital surface models. Unmanned Aerial Vehicles (UAVs), equipped with a Red Green Blue (RGB) camera, have great potential in quickly acquiring multi-temporal high-resolution orthophotos and surface models. Such datasets would ease the monitoring of geomorphological processes, such as local soil erosion and rill formation after heavy rainfall events. In this study we test a photogrammetric setup to determine data requirements for soil erosion studies with UAVs. We used a rainfall simulator (5 m2) and above a rig with attached a Panasonic GX1 16 megapixel digital camera and 20mm lens. The soil material in the simulator consisted of loamy sand at an angle of 5 degrees. Stereo pair images were taken before and after rainfall simulation with 75-85% overlap. Acquired images were automatically mosaicked to create high-resolution orthorectified images and digital surface models (DSM). We resampled the DSM to different spatial resolutions to analyze the effect of cell size to the accuracy of measured rill depth and soil loss estimations, and determined an optimal cell size (thus flight altitude). Furthermore, the high spatial accuracy of the acquired surface models allows further analysis of rill formation and channel initiation related to e.g. surface roughness. We suggest implementing near-infrared and temperature sensors to combine soil moisture and soil physical properties with surface morphology for future investigations.

Digital geomorphological landslide hazard mapping of the Alpago area, Italy

NASA Astrophysics Data System (ADS)

van Westen, Cees J.; Soeters, Rob; Sijmons, Koert

Large-scale geomorphological maps of mountainous areas are traditionally made using complex symbol-based legends. They can serve as excellent "geomorphological databases", from which an experienced geomorphologist can extract a large amount of information for hazard mapping. However, these maps are not designed to be used in combination with a GIS, due to their complex cartographic structure. In this paper, two methods are presented for digital geomorphological mapping at large scales using GIS and digital cartographic software. The methods are applied to an area with a complex geomorphological setting on the Borsoia catchment, located in the Alpago region, near Belluno in the Italian Alps. The GIS database set-up is presented with an overview of the data layers that have been generated and how they are interrelated. The GIS database was also converted into a paper map, using a digital cartographic package. The resulting largescale geomorphological hazard map is attached. The resulting GIS database and cartographic product can be used to analyse the hazard type and hazard degree for each polygon, and to find the reasons for the hazard classification.

Maps of averaged spectral deviations from soil lines and their comparison with traditional soil maps

NASA Astrophysics Data System (ADS)

Rukhovich, D. I.; Rukhovich, A. D.; Rukhovich, D. D.; Simakova, M. S.; Kulyanitsa, A. L.; Bryzzhev, A. V.; Koroleva, P. V.

2016-07-01

The analysis of 34 cloudless fragments of Landsat 5, 7, and 8 images (1985-2014) on the territory of Plavsk, Arsen'evsk, and Chern districts of Tula oblast has been performed. It is shown that bare soil surface on the RED-NIR plots derived from the images cannot be described in the form of a sector of spectral plane as it can be done for the NDVI values. The notion of spectral neighborhood of soil line (SNSL) is suggested. It is defined as the sum of points of the RED-NIR spectral space, which are characterized by spectral characteristics of the bare soil applied for constructing soil lines. The way of the SNSL separation along the line of the lowest concentration density of points on the RED-NIR spectral space is suggested. This line separates bare soil surface from vegetating plants. The SNSL has been applied to construct soil line (SL) for each of the 34 images and to delineate bare soil surface on them. Distances from the points with averaged RED-NIR coordinates to the SL have been calculated using the method of moving window. These distances can be referred to as averaged spectral deviations (ASDs). The calculations have been performed strictly for the SNSL areas. As a result, 34 maps of ASDs have been created. These maps contain ASD values for 6036 points of a grid used in the study. Then, the integral map of normalized ASD values has been built with due account for the number of points participating in the calculation (i.e., lying in the SNSL) within the moving window. The integral map of ASD values has been compared with four traditional soil maps on the studied territory. It is shown that this integral map can be interpreted in terms of soil taxa: the areas of seven soil subtypes (soddy moderately podzolic, soddy slightly podzolic, light gray forest. gray forest, dark gray forest, podzolized chernozems, and leached chernozems) belonging to three soil types (soddy-podzolic, gray forest, and chernozemic soils) can be delineated on it.

Representative Elementary Area Determinations through Digital Photography, Image Analysis, and Soil Color

USDA-ARS?s Scientific Manuscript database

Photography has been a welcome tool in assisting to document and convey qualitative soil information. Greater availability of digital cameras with increased information storage capabilities has promoted novel uses of this technology in investigations of water movement patterns, organic matter conte...

A simplified close range photogrammetric technique for soil erosion assessment

USDA-ARS?s Scientific Manuscript database

Surface reconstruction using digital photogrammetry offers a great advantage for soil erosion research. The technology can be cumbersome for field application as it relies on the accurate measurement of control points often using a survey grade instruments. Also, even though digital photogrammetry h...

Application of Ifsar Technology in Topographic Mapping: JUPEM's Experience

NASA Astrophysics Data System (ADS)

Zakaria, Ahamad

2018-05-01

The application of Interferometric Synthetic Aperture Radar (IFSAR) in topographic mapping has increased during the past decades. This is due to the advantages that IFSAR technology offers in solving data acquisition problems in tropical regions. Unlike aerial photography, radar technology offers wave penetration through cloud cover, fog and haze. As a consequence, images can be made free of any natural phenomenon defects. In Malaysia, Department of Survey and Mapping Malaysia (JUPEM) has been utilizing the IFSAR products since 2009 to update topographic maps at 1 : 50,000 map scales. Orthorectified radar imagery (ORI), Digital Surface Models (DSM) and Digital Terrain Models (DTM) procured under the project have been further processed before the products are ingested into a revamped mapping workflow consisting of stereo and mono digitizing processes. The paper will highlight the experience of Department of Survey and Mapping Malaysia (DSMM)/ JUPEM in using such technology in order to speed up mapping production.

Soil, water, and vegetation conditions in south Texas. [Hildago County, Texas

NASA Technical Reports Server (NTRS)

Wiegand, C. L.; Gausman, H. W.; Leamer, R. W.; Richardson, A. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. To distinguish dead from live vegetation, spectrophotometrically measured infinite reflectance of dead and live corn (Zea mays L.) leaves were compared over the 0.5 to 2.5 micron waveband. Dead leaf reflectance was reached over the entire 0.5 to 2.5 micron waveband by stacking only two to three leaves. Live leaf reflectance was attained by stacking two leaves for the 0.5 to 0.75 micron waveband (chlorophyll absorption region), eight leaves for the 0.75 to 1.35 micron waveband (near infrared region), and three leaves for the 1.35 to 2.5 micron waveband (water absorption region). LANDSAT-1 MSS digital data for 11 December 1973 overpass were used to estimate the sugar cane acreage in Hidalgo County. The computer aided estimate was 22,100 acres compared with the Texas Crop and Livestock Reporting Service estimate of 20,500 acres for the 1973-'74 crop year. Although there were errors of omission from harvested fields that were identified as bare soil and some citrus and native vegetation that were mistakenly identified as sugar cane, the mapped location of sugar cane fields in the county compared favorably with their location on the thematic map generated by the computer.

Standard for the U.S. Geological Survey Historical Topographic Map Collection

USGS Publications Warehouse

Allord, Gregory J.; Fishburn, Kristin A.; Walter, Jennifer L.

2014-01-01

This document defines the digital map product of the U.S. Geological Survey (USGS) Historical Topographic Map Collection (HTMC). The HTMC is a digital archive of about 190,000 printed topographic quadrangle maps published by the USGS from the inception of the topographic mapping program in 1884 until the last paper topographic map using lithographic printing technology was published in 2006. The HTMC provides a comprehensive digital repository of all scales and all editions of USGS printed topographic maps that is easily discovered, browsed, and downloaded by the public at no cost. Each printed topographic map is scanned “as is” and captures the content and condition of each map. The HTMC provides ready access to maps that are no longer available for distribution in print. A new generation of topographic maps called “US Topo” was defined in 2009. US Topo maps, though modeled on the legacy 7.5-minute topographic maps, conform to different standards. For more information on the HTMC, see the project Web site at: http://nationalmap.gov/historical/.

Topographic map of the western region of Dao Vallis in Hellas Planitia, Mars; MTM 500k -40/082E OMKT

USGS Publications Warehouse

Rosiek, Mark R.; Redding, Bonnie L.; Galuszka, Donna M.

2006-01-01

This map, compiled photogrammetrically from Viking Orbiter stereo image pairs, is part of a series of topographic maps of areas of special scientific interest on Mars. Contours were derived from a digital terrain model (DTM) compiled on a digital photogrammetric workstation using Viking Orbiter stereo image pairs with orientation parameters derived from an analytic aerotriangulation. The image base for this map employs Viking Orbiter images from orbits 406 and 363. An orthophotomosaic was created on the digital photogrammetric workstation using the DTM compiled from stereo models.

Fine-Scale Relief in the Amazon Drives Large Scale Ecohydrological Processes

NASA Astrophysics Data System (ADS)

Nobre, A. D.; Cuartas, A.; Hodnett, M.; Saleska, S. R.

2014-12-01

Access to soil water by roots is a key ecophysiological factor for plant productivity in natural systems. Periodically during dry seasons or critically during episodic climate droughts, shortage of water supply can reduce or severely impair plant life. At the other extreme persistent soil waterlogging will limit root respiration and restrict local establishment to adapted species, usually leading to stunted and less productive communities. Soil-water availability is therefore a very important climate variable controlling plant physiology and ecosystem dynamics. Terra-firme, the non-seasonally floodable terrain that covers 82% of the landscape in Amazonia,[1] supports the most massive part of the rainforest ecosystem. The availability of soil water data for terra-firme is scant and very coarse. This lack of data has hampered observational and modeling studies aiming to develop a large-scale integrative ecohydrological picture of Amazonia and its vulnerability to climate change. We have mapped the Amazon basin with a new terrain model developed in our group (HAND, Height Above the Nearest drainage[2]), delineating soil water environments using topographical data from the SRTM digital elevation model (250 m horizontal interpolated resolution). The preliminary results show that more than 50% of Terra-firme has the water table very close to the surface (up to 2 m deep), while the remainder of the upland landscape has variable degree of dependence on non-saturated soil (vadose layer). The mapping also shows extremely heterogeneous patterns of fine-scale relief across the basin, which implies complex ecohydrological regional forcing on the forest physiology. Ecoclimate studies should therefore take into account fine-scale relief and its implications for soil-water availability to plant processes. [1] Melack, J. M., & Hess, L. L. (2011). Remote sensing of the distribution and extent of wetlands in the Amazon basin. In W. J. Junk & M. Piedade (Eds.), Amazonian floodplain forests: Ecophysiology, ecology, biodiversity and sustainable management (pp. 1-28). Ecological Studies-Springer. [2] Nobre, A. D., Cuartas, L. A., Hodnett, M., … Saleska, S. (2011). Height Above the Nearest Drainage - a hydrologically relevant new terrain model. Journal of Hydrology, 404(1-2), 13-29

Semi-automatic handling of meteorological ground measurements using WeatherProg: prospects and practical implications

NASA Astrophysics Data System (ADS)

Langella, Giuliano; Basile, Angelo; Bonfante, Antonello; De Mascellis, Roberto; Manna, Piero; Terribile, Fabio

2016-04-01

WeatherProg is a computer program for the semi-automatic handling of data measured at ground stations within a climatic network. The program performs a set of tasks ranging from gathering raw point-based sensors measurements to the production of digital climatic maps. Originally the program was developed as the baseline asynchronous engine for the weather records management within the SOILCONSWEB Project (LIFE08 ENV/IT/000408), in which daily and hourly data where used to run water balance in the soil-plant-atmosphere continuum or pest simulation models. WeatherProg can be configured to automatically perform the following main operations: 1) data retrieval; 2) data decoding and ingestion into a database (e.g. SQL based); 3) data checking to recognize missing and anomalous values (using a set of differently combined checks including logical, climatological, spatial, temporal and persistence checks); 4) infilling of data flagged as missing or anomalous (deterministic or statistical methods); 5) spatial interpolation based on alternative/comparative methods such as inverse distance weighting, iterative regression kriging, and a weighted least squares regression (based on physiography), using an approach similar to PRISM. 6) data ingestion into a geodatabase (e.g. PostgreSQL+PostGIS or rasdaman). There is an increasing demand for digital climatic maps both for research and development (there is a gap between the major of scientific modelling approaches that requires digital climate maps and the gauged measurements) and for practical applications (e.g. the need to improve the management of weather records which in turn raises the support provided to farmers). The demand is particularly burdensome considering the requirement to handle climatic data at the daily (e.g. in the soil hydrological modelling) or even at the hourly time step (e.g. risk modelling in phytopathology). The key advantage of WeatherProg is the ability to perform all the required operations and calculations in an automatic fashion, except the need of a human interaction upon specific issues (such as the decision whether a measurement is an anomaly or not according to the detected temporal and spatial variations with contiguous points). The presented computer program runs from command line and shows peculiar characteristics in the cascade modelling within different contexts belonging to agriculture, phytopathology and environment. In particular, it can be a powerful tool to set up cutting-edge regional web services based on weather information. Indeed, it can support territorial agencies in charge of meteorological and phytopathological bulletins.

Rapid assessment and mapping of tree cover in southern African savanna woodlands using a new iPhone App and Landsat 8 imagery

NASA Astrophysics Data System (ADS)

Fuller, D. O.

2016-12-01

Tree cover is a key parameter in climate modeling. It strongly influences CO2 exchanges between the land surface and atmosphere and surface energy balance. We measured percent woody canopy cover (PWCC) in the savanna woodlands of eastern Zambia over a 10-day period in May 2016 using a new iPhone App (CanopyApp) and related these field measurements to Landsat 8 (L8) Band 4 (red) imagery acquired approximately the same time. We then used parameters from the band 4 digital numbers (DNs)-PWCC linear regression to derive a new map of PWCC for the entire L8 scene. Consistent with theory and previous empirical studies, we found that the relationship between L8 band 4 DNs- PWCC was negative and linear (r2 = 0.61, p < 0.05). Interestingly, the relationship between PWCC and L8 band 4 surface reflectance was weaker (r2 = 0.46, p < 0.05) than that for DNs. This suggests that the scene model used in L8 atmospheric correction may not account well for within-pixel shadowing effects and other spatial inhomogeneities from variable soil and background reflectance. Our PWCC map agreed qualitatively with similar percent tree-cover maps based on Landsat level 1 products and past field studies in the area conducted using a hemispherical lens. Our results also compared favorably with other remote sensing studies that have used complex multivariate approaches to estimate tree cover, which suggests that use of a single L8 band 4 is sufficient to estimate PWCC when spectral contrast exists between the grass, soil and tree layers during the austral fall period in southern African savannas.

Digital recovery, modification, and analysis of Tetra Tech seismic horizon mapping, National Petroleum Reserve Alaska (NPRA), northern Alaska

USGS Publications Warehouse

Saltus, R.W.; Kulander, Christopher S.; Potter, Christopher J.

2002-01-01

We have digitized, modified, and analyzed seismic interpretation maps of 12 subsurface stratigraphic horizons spanning portions of the National Petroleum Reserve in Alaska (NPRA). These original maps were prepared by Tetra Tech, Inc., based on about 15,000 miles of seismic data collected from 1974 to 1981. We have also digitized interpreted faults and seismic velocities from Tetra Tech maps. The seismic surfaces were digitized as two-way travel time horizons and converted to depth using Tetra Tech seismic velocities. The depth surfaces were then modified by long-wavelength corrections based on recent USGS seismic re-interpretation along regional seismic lines. We have developed and executed an algorithm to identify and calculate statistics on the area, volume, height, and depth of closed structures based on these seismic horizons. These closure statistics are tabulated and have been used as input to oil and gas assessment calculations for the region. Directories accompanying this report contain basic digitized data, processed data, maps, tabulations of closure statistics, and software relating to this project.

Mapping Soil Salinity/Sodicity by using Landsat OLI Imagery and PLSR Algorithm over Semiarid West Jilin Province, China

PubMed Central

Liu, Mingyue; Du, Baojia; Zhang, Bai

2018-01-01

Soil salinity and sodicity can significantly reduce the value and the productivity of affected lands, posing degradation, and threats to sustainable development of natural resources on earth. This research attempted to map soil salinity/sodicity via disentangling the relationships between Landsat 8 Operational Land Imager (OLI) imagery and in-situ measurements (EC, pH) over the west Jilin of China. We established the retrieval models for soil salinity and sodicity using Partial Least Square Regression (PLSR). Spatial distribution of the soils that were subjected to hybridized salinity and sodicity (HSS) was obtained by overlay analysis using maps of soil salinity and sodicity in geographical information system (GIS) environment. We analyzed the severity and occurring sizes of soil salinity, sodicity, and HSS with regard to specified soil types and land cover. Results indicated that the models’ accuracy was improved by combining the reflectance bands and spectral indices that were mathematically transformed. Therefore, our results stipulated that the OLI imagery and PLSR method applied to mapping soil salinity and sodicity in the region. The mapping results revealed that the areas of soil salinity, sodicity, and HSS were 1.61 × 106 hm2, 1.46 × 106 hm2, and 1.36 × 106 hm2, respectively. Also, the occurring area of moderate and intensive sodicity was larger than that of salinity. This research may underpin efficiently mapping regional salinity/sodicity occurrences, understanding the linkages between spectral reflectance and ground measurements of soil salinity and sodicity, and provide tools for soil salinity monitoring and the sustainable utilization of land resources. PMID:29614727

Recovery and archiving key Arctic Alaska vegetation map and plot data for the Arctic-Boreal Vulnerability Field Experiment (ABoVE)

NASA Astrophysics Data System (ADS)

Walker, D. A.; Breen, A. L.; Broderson, D.; Epstein, H. E.; Fisher, W.; Grunblatt, J.; Heinrichs, T.; Raynolds, M. K.; Walker, M. D.; Wirth, L.

2013-12-01

Abundant ground-based information will be needed to inform remote-sensing and modeling studies of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE). A large body of plot and map data collected by the Alaska Geobotany Center (AGC) and collaborators from the Arctic regions of Alaska and the circumpolar Arctic over the past several decades is being archived and made accessible to scientists and the public via the Geographic Information Network of Alaska's (GINA's) 'Catalog' display and portal system. We are building two main types of data archives: Vegetation Plot Archive: For the plot information we use a Turboveg database to construct the Alaska portion of the international Arctic Vegetation Archive (AVA) http://www.geobotany.uaf.edu/ava/. High quality plot data and non-digital legacy datasets in danger of being lost have highest priority for entry into the archive. A key aspect of the database is the PanArctic Species List (PASL-1), developed specifically for the AVA to provide a standard of species nomenclature for the entire Arctic biome. A wide variety of reports, documents, and ancillary data are linked to each plot's geographic location. Geoecological Map Archive: This database includes maps and remote sensing products and links to other relevant data associated with the maps, mainly those produced by the Alaska Geobotany Center. Map data include GIS shape files of vegetation, land-cover, soils, landforms and other categorical variables and digital raster data of elevation, multispectral satellite-derived data, and data products and metadata associated with these. The map archive will contain all the information that is currently in the hierarchical Toolik-Arctic Geobotanical Atlas (T-AGA) in Alaska http://www.arcticatlas.org, plus several additions that are in the process of development and will be combined with GINA's already substantial holdings of spatial data from northern Alaska. The Geoecological Atlas Portal uses GINA's Catalog tool to develop a web interface to view and access the plot and map data. The mapping portal allows visualization of GIS data, sample-point locations and imagery and access to the map data. Catalog facilitates the discovery and dissemination of science-based information products in support of analysis and decision-making concerned with development and climate change and is currently used by GINA in several similar archive/distribution portals.

Potential of EnMAP spaceborne imaging spectroscopy for the prediction of common surface soil properties and expected accuracy

NASA Astrophysics Data System (ADS)

Chabrillat, Sabine; Foerster, Saskia; Steinberg, Andreas; Stevens, Antoine; Segl, Karl

2016-04-01

There is a renewed awareness of the finite nature of the world's soil resources, growing concern about soil security, and significant uncertainties about the carrying capacity of the planet. As a consequence, soil scientists are being challenged to provide regular assessments of soil conditions from local through to global scales. However, only a few countries have the necessary survey and monitoring programs to meet these new needs and existing global data sets are out-of-date. A particular issue is the clear demand for a new area-wide regional to global coverage with accurate, up-to-date, and spatially referenced soil information as expressed by the modeling scientific community, farmers and land users, and policy and decision makers. Soil spectroscopy from remote sensing observations based on studies from the laboratory scale to the airborne scale has been shown to be a proven method for the quantitative prediction of key soil surface properties in local areas for exposed soils in appropriate surface conditions such as low vegetation cover and low water content. With the upcoming launch of the next generation of hyperspectral satellite sensors in the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. Nevertheless, the capabilities to extend the soil properties current spectral modeling from local to regional scales are still to be demonstrated using robust methods. In particular, three central questions are at the forefront of research nowadays: a) methodological developments toward improved algorithms and operational tools for the extraction of soil properties, b) up scaling from the laboratory into space domain, and c) demonstration of the potential of upcoming satellite systems and expected accuracy of soil maps. In this study, airborne imaging spectroscopy data from several test sites are used to simulate EnMAP satellite images at 30 m scale. Then, different soil algorithms are examined based on the analyses of chemical-physical features from the soil spectral reflectance and/or multivariate established techniques such as Partial-Least Squares PLS, Support-Vector Machine SVM, to determine common surface soil properties, in particular soil organic carbon (SOC), clay and iron oxide content. Results show that EnMAP is able to predict clay, free iron oxide, and SOC with an RV2 between 0.53 and 0.67 compared to airborne imagery with RV2 between 0.64 and 0.74. The correlation between EnMAP and airborne imagery prediction results is high (Pearson coefficients between 0.84 and 0.91). Furthermore, spatial distribution is coherent between the airborne mapping and simulated EnMAP mapping as shown with a spatial structure analysis. In general, this paper demonstrates the high potential of upcoming spaceborne hyperspectral missions for soil science studies but also shows the need for future adapted strategies to fulfill the entire potential of soil spectroscopy for orbital utilization.

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Hyperspectral Soil Mapper (HYSOMA) software interface: Review and future plans

NASA Astrophysics Data System (ADS)

Chabrillat, Sabine; Guillaso, Stephane; Eisele, Andreas; Rogass, Christian

2014-05-01

With the upcoming launch of the next generation of hyperspectral satellites that will routinely deliver high spectral resolution images for the entire globe (e.g. EnMAP, HISUI, HyspIRI, HypXIM, PRISMA), an increasing demand for the availability/accessibility of hyperspectral soil products is coming from the geoscience community. Indeed, many robust methods for the prediction of soil properties based on imaging spectroscopy already exist and have been successfully used for a wide range of soil mapping airborne applications. Nevertheless, these methods require expert know-how and fine-tuning, which makes them used sparingly. More developments are needed toward easy-to-access soil toolboxes as a major step toward the operational use of hyperspectral soil products for Earth's surface processes monitoring and modelling, to allow non-experienced users to obtain new information based on non-expensive software packages where repeatability of the results is an important prerequisite. In this frame, based on the EU-FP7 EUFAR (European Facility for Airborne Research) project and EnMAP satellite science program, higher performing soil algorithms were developed at the GFZ German Research Center for Geosciences as demonstrators for end-to-end processing chains with harmonized quality measures. The algorithms were built-in into the HYSOMA (Hyperspectral SOil MApper) software interface, providing an experimental platform for soil mapping applications of hyperspectral imagery that gives the choice of multiple algorithms for each soil parameter. The software interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. Additionally, a field calibration option calculates fully quantitative soil maps provided ground truth soil data are available. Implemented soil algorithms have been tested and validated using extensive in-situ ground truth data sets. The source of the HYSOMA code was developed as standalone IDL software to allow easy implementation in the hyperspectral and non-hyperspectral communities. Indeed, within the hyperspectral community, IDL language is very widely used, and for non-expert users that do not have an ENVI license, such software can be executed as a binary version using the free IDL virtual machine under various operating systems. Based on the growing interest of users in the software interface, the experimental software was adapted for public release version in 2012, and since then ~80 users of hyperspectral soil products downloaded the soil algorithms at www.gfz-potsdam.de/hysoma. The software interface was distributed for free as IDL plug-ins under the IDL-virtual machine. Up-to-now distribution of HYSOMA was based on a close source license model, for non-commercial and educational purposes. Currently, the HYSOMA is being under further development in the context of the EnMAP satellite mission, for extension and implementation in the EnMAP Box as EnSoMAP (EnMAP SOil MAPper). The EnMAP Box is a freely available, platform-independent software distributed under an open source license. In the presentation we will focus on an update of the HYSOMA software interface status and upcoming implementation in the EnMAP Box. Scientific software validation, associated publication record and users responses as well as software management and transition to open source will be discussed.

Oxygen-17 anomaly in soil nitrate: A new precipitation proxy for desert landscapes

NASA Astrophysics Data System (ADS)

Wang, Fan; Ge, Wensheng; Luo, Hao; Seo, Ji-Hye; Michalski, Greg

2016-03-01

The nitrogen cycle in desert soil ecosystems is particularly sensitive to changes in precipitation, even of relatively small magnitude and short duration, because it is already under water stress. This suggests that desert soils may have preserved past evidence of small variations in continental precipitation. We have measured nitrate (NO3-) concentrations in soils from the Atacama (Chile), Kumtag (China), Mojave (US), and Thar (India) deserts, and stable nitrogen and oxygen isotope (15N, 17O, and 18O) abundances of the soil NO3-. 17O anomalies (Δ17O), the deviations from the mass-independent isotopic fractionation, were detected in soil NO3- from almost all sites of these four deserts. There was a strong negative correlation between the mean annual precipitation (MAP) and soil NO3- Δ17O values (Δ

Application of laboratory reflectance spectroscopy to target and map expansive soils: example of the western Loiret, France

NASA Astrophysics Data System (ADS)

Hohmann, Audrey; Dufréchou, Grégory; Grandjean, Gilles; Bourguignon, Anne

2014-05-01

Swelling soils contain clay minerals that change volume with water content and cause extensive and expensive damage on infrastructures. Based on spatial distribution of infrastructure damages and existing geological maps, the Bureau de Recherches Géologiques et Minières (BRGM, i.e. the French Geological Survey) published in 2010 a 1:50 000 swelling hazard map of France, indexing the territory to low, moderate, or high swelling risk. This study aims to use SWIR (1100-2500 nm) reflectance spectra of soils acquired under laboratory controlled conditions to estimate the swelling potential of soils and improve the swelling risk map of France. 332 samples were collected at the W of Orléans (France) in various geological formations and swelling risk areas. Comparisons of swelling potential of soil samples and swelling risk areas of the map show several inconsistent associations that confirm the necessity to redraw the actual swelling risk map of France. New swelling risk maps of the sampling area were produce from soil samples using three interpolation methods. Maps produce using kriging and Natural neighbour interpolation methods did not permit to show discrete lithological units, introduced unsupported swelling risk zones, and did not appear useful to refine swelling risk map of France. Voronoi polygon was also used to produce map where swelling potential estimated from each samples were extrapolated to a polygon and all polygons were thus supported by field information. From methods tested here, Voronoi polygon appears thus the most adapted method to produce expansive soils maps. However, size of polygon is highly dependent of the samples spacing and samples may not be representative of the entire polygon. More samples are thus needed to provide reliable map at the scale of the sampling area. Soils were also sampled along two sections with a sampling interval of ca. 260 m and ca. 50 m. Sample interval of 50 m appears more adapted for mapping of smallest lithological units. The presence of several samples close to themselves indicating the same swelling potential is a good indication of the presence of a zone with constant swelling potential. Combination of Voronoi method and sampling interval of ca. 50 m appear adapted to produce local swelling potential maps in areas where doubt remain or where infrastructure damages attributed to expansive soils are knew.

Highly spatially- and seasonally-resolved predictive contamination maps for persistent organic pollutants: development and validation.

PubMed

Ballabio, Cristiano; Guazzoni, Niccoló; Comolli, Roberto; Tremolada, Paolo

2013-08-01

A reliable spatial assessment of the POPs contamination in soils is essential for burden studies and flux evaluations. Soil characteristics and properties vary enormously even within small spatial scale and over time; therefore soil capacity of accumulating POPs varies greatly. In order to include this very high spatial and temporal variability, models can be used for assessing soil accumulation capacity in a specific time and space and, from it, the spatial distribution and temporal trends of POPs concentrations. In this work, predictive contamination maps of the accumulation capacity of soils were developed at a space resolution of 1×1m with a time frame of one day, in a study area located in the central Alps. Physical algorithms for temperature and organic carbon estimation along the soil profile and across the year were fitted to estimate the horizontal, vertical and seasonal distribution of the contamination potential for PCBs in soil (Ksa maps). The resulting maps were cross-validated with an independent set of PCB contamination data, showing very good agreement (e.g. for CB-153, R(2)=0.80, p-value≤2.2·10(-06)). Slopes of the regression between predicted Ksa and experimental concentrations were used to map the soil contamination for the whole area, taking into account soil characteristics and temperature conditions. These maps offer the opportunity to evaluate burden (concentration maps) and fluxes (emission maps) with highly resolved temporal and spatial detail. In addition, in order to explain the observed low autumn PCB concentrations in soil related to the high Ksa values of this period, a dynamic model of seasonal variation of soil concentrations was developed basing on rate parameters fitted on measured concentrations. The model was able to describe, at least partially, the observed different behavior between the quite rapid discharge phase in summer and the slow recharge phase in autumn. Copyright © 2013 Elsevier B.V. All rights reserved.

The Circumpolar Arctic vegetation map

USGS Publications Warehouse

Walker, Donald A.; Raynolds, Martha K.; Daniels, F.J.A.; Einarsson, E.; Elvebakk, A.; Gould, W.A.; Katenin, A.E.; Kholod, S.S.; Markon, C.J.; Melnikov, E.S.; Moskalenko, N.G.; Talbot, S. S.; Yurtsev, B.A.; Bliss, L.C.; Edlund, S.A.; Zoltai, S.C.; Wilhelm, M.; Bay, C.; Gudjonsson, G.; Ananjeva, G.V.; Drozdov, D.S.; Konchenko, L.A.; Korostelev, Y.V.; Ponomareva, O.E.; Matveyeva, N.V.; Safranova, I.N.; Shelkunova, R.; Polezhaev, A.N.; Johansen, B.E.; Maier, H.A.; Murray, D.F.; Fleming, Michael D.; Trahan, N.G.; Charron, T.M.; Lauritzen, S.M.; Vairin, B.A.

2005-01-01

Question: What are the major vegetation units in the Arctic, what is their composition, and how are they distributed among major bioclimate subzones and countries? Location: The Arctic tundra region, north of the tree line. Methods: A photo-interpretive approach was used to delineate the vegetation onto an Advanced Very High Resolution Radiometer (AVHRR) base image. Mapping experts within nine Arctic regions prepared draft maps using geographic information technology (ArcInfo) of their portion of the Arctic, and these were later synthesized to make the final map. Area analysis of the map was done according to bioclimate subzones, and country. The integrated mapping procedures resulted in other maps of vegetation, topography, soils, landscapes, lake cover, substrate pH, and above-ground biomass. Results: The final map was published at 1:7 500 000 scale map. Within the Arctic (total area = 7.11 x 106 km 2), about 5.05 ?? 106 km2 is vegetated. The remainder is ice covered. The map legend generally portrays the zonal vegetation within each map polygon. About 26% of the vegetated area is erect shrublands, 18% peaty graminoid tundras, 13% mountain complexes, 12% barrens, 11% mineral graminoid tundras, 11% prostrate-shrub tundras, and 7% wetlands. Canada has by far the most terrain in the High Arctic mostly associated with abundant barren types and prostrate dwarf-shrub tundra, whereas Russia has the largest area in the Low Arctic, predominantly low-shrub tundra. Conclusions: The CAVM is the first vegetation map of an entire global biome at a comparable resolution. The consistent treatment of the vegetation across the circumpolar Arctic, abundant ancillary material, and digital database should promote the application to numerous land-use, and climate-change applications and will make updating the map relatively easy. ?? IAVS; Opulus Press.

Mapping, Charting, and Geodesy Division Abstracts of Publications, Presentations and Transitions: 1991

DTIC Science & Technology

1992-05-01

Clark, T.H. Fay, Multispectral I Bathymetry Programs: A Users Guide, NTN 95. Myrick, S., M. Lohrenz, Data Base Design Document for the Digital Map...Computer1 Software in the A-12 Digital Map Set, NTN 162. Myrick, S., M. Lohrenz, P. Wischow, M. Trenchard, S. Tyskiewicz, J. Kaufman, MDFF I HELP...Shaw, K, D. Byman, S. Carter, M. Kalcic, M. Clawson, M. Harris, A Summary of the i Collected Data from a Survey of Navy Digital MC&G Requirements

Evaluation of LANDSAT-4 Thematic Mapper Data as Applied to Geologic Exploration: Summary of Results. [Death Valley, California, Cement-Velma, Oklahoma; Big Horn and Wind River Basins, Wyoming; Spanish Peaks, Colorado; and the Four Corners area (Paradox Basin of Utah and Colorado)

NASA Technical Reports Server (NTRS)

Dykstra, J. D.; Sheffield, C. A.; Everett, J. R.

1984-01-01

As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.

VARIABLE RATE APPLICATION OF SOIL HERBICIDES IN ARABLE CROPS: FROM THEORY TO PRACTICE.

PubMed

Heijting, S; Kempenaar, C

2014-01-01

Soil herbicides are applied around crop emergence and kill germinating weeds in the surface layer of the soil. These herbicides play an important role in the chemical management of weeds in major arable crops. From an environmental point of view there is a clear need for smarter application of these chemicals. This paper presents research done in The Netherlands on Variable Rate Application (VRA) of soil herbicides by taking into account spatial variation of the soil. Herbicides adsorbed to soil parameters such as clay or organic matter are not available for herbicidal activity. Decision Support Rules (DSR) describe the relation between the soil parameter and herbicide dosage needed for effectively controlling weeds. Research methods such as greenhouse trials, models and on farm research to develop DSR are discussed and results are presented. Another important ingredient for VRA of soil herbicides is an accurate soil map of the field. Sampling and subsequent interpolation is costly. Soil scans measuring a proxy that is subsequently translated into soil properties such as clay fraction and soil organic matter content offer a quicker way to achieve such maps but validation is needed. DSR is applied to the soil map to get the variable dosage map. The farmer combines this map with the routing, spray volume and spray boom width in the Farm Management Information System (FMIS), resulting in a task file. This task file can subsequently be read by the board computer resulting in a VRA spray map. Reduction in soil herbicide depends on the DSR, the spatial variation and pattern of the soil, the spatial configuration of the routing and the technical advances of the spray equipment. Recently, within the framework the Programma Precisie Landbouw, first steps were made to test and implement this in practice. Currently, theory and practice of VRA of soil herbicides is developed within the research program IJKakker in close cooperation with pioneering farmers in The Netherlands.

A semester-long soil mapping project for an undergraduate pedology course

NASA Astrophysics Data System (ADS)

Brown, David J.

2015-04-01

Most students taking a pedology course will never work as soil mappers. But many will use soil maps at some point in their careers. At Montana State University, students spent 3 "lab" hours a week, complementing two lectures a week, in the field learning how to study soils literally from the ground up. The only prerequisites for enrollment were completion of an introductory soil science class and 3rd year standing at the university. The area to be mapped, just a km from campus, included a steep mountain backslope, and a complex footslope-toeslope area with diverse soils. Students were divided into teams of 3-4, with approximately 40 students altogether split over two sections that overlapped in the field by one hour. In the first lab session, groups completed a very basic description of just one soil profile. In subsequent weeks, they rotated through multiple pits excavated in a small area, and expanded their soil profile descriptions and interpretations. As students developed proficiency, they were assigned more dispersed locations to study, working for the most part independently as I hiked between pits. Throughout this process, every pit was geolocated using a GPS unit, and every profile description was copied and retained in a designated class file. Student groups delineated map units using stereo air photography, then used these delineations to guide the selection of their final locations to describe. At the end of the course, groups used all of the combined and georeferenced profile descriptions to construct a soil map of the study area complete with map unit descriptions. Most students struggled to make sense of the substantial variability within their map units, but through this struggle -- and their semester of field work -- they gained an appreciation for the value and limitations of a soil map that could not be obtained from even the most entertaining lecture. Both the class and particularly the field sessions received consistently high student reviews during the four years I had students map soils at Montanta State University.

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Trease, Brian

2011-01-01

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting system, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction System), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using Adams dynamic modeling software. The external library was built in Fortran and called by Adams to model the wheel-soil interactions include the rut-formation effect of deformable soils, lateral and longitudinal forces, bull-dozing effects, and applied wheel torque. The paper presents the details and implementation of the system. To validate the developed system, one study case is presented from a realistic drive on Mars of the Opportunity rover. The simulation results match well from the measurement of on-board telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

Determination of representative elementary areas for soil redoximorphic features by digital image processing

USDA-ARS?s Scientific Manuscript database

Photography has been a welcome tool in documenting and conveying qualitative soil information. When coupled with image analysis software, the usefulness of digital cameras can be increased to advance the field of micropedology. The determination of a Representative Elementary Area (REA) still rema...

Combining land use data acquired from Landsat with soil map data

NASA Technical Reports Server (NTRS)

Westin, F. C.; Brandner, T. M.

1981-01-01

A method currently used to derive agrophysical units (APUs), i.e., geographical areas having definable/comparable agronomic and physical parameters which reflect a range in agricultural use and management, is discussed with reference to results obtained for South Dakota and an area in China. The method consists of combining agricultural land use data acquired from Landsat with soil map data. The resulting map units are soil associations characterized by cropland use intensity, and they can be used to identify major cropland areas and to develop a rating reflecting the relative potential of the soils in the delineated area for crop production, as well as to update small-scale soil maps.

Climate and atmospheric modeling studies. Climate applications of Earth and planetary observations. Chemistry of Earth and environment

NASA Technical Reports Server (NTRS)

1990-01-01

The research conducted during the past year in the climate and atmospheric modeling programs concentrated on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three-dimensional global climate model, and an upper ocean model. Principal applications have been the study of the impact of CO2, aerosols and the solar 'constant' on climate. Progress was made in the 3-D model development towards physically realistic treatment of these processes. In particular, a map of soil classifications on 1 degree x 1 degree resolution has been digitized, and soil properties have been assigned to each soil type. Using this information about soil properties, a method was developed to simulate the hydraulic behavior of soils of the world. This improved treatment of soil hydrology, together with the seasonally varying vegetation cover, will provide a more realistic study of the role of the terrestrial biota in climate change. A new version of the climate model was created which follows the isotopes of water and sources of water (or colored water) throughout the planet. Each isotope or colored water source is a fraction of the climate model's water. It participates in condensation and surface evaporation at different fractionation rates and is transported by the dynamics. A major benefit of this project has been to improve the programming techniques and physical simulation of the water vapor budget of the climate model.

On-the-go mapping of soil mechanical resistance using a linear depth effect model.

USDA-ARS?s Scientific Manuscript database

An instrumented blade sensor was developed to map soil mechanical resistance as well as its change with depth. The sensor has become a part of the Integrated Soil Physical Properties Mapping System (ISPPMS), which also includes an optical and a capacitor-based sensor. The instrumented blade of the...

Alaska Interim Land Cover Mapping Program; final report

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine; Doughty, E.F.; Shasby, Mark; Benjamin, Susan

1989-01-01

In 1985, the U.S. Geological Survey initiated a research project to develop an interim land cover data base for Alaska as an alternative to the nationwide Land Use and Land Cover Mapping Program. The Alaska Interim Land Cover Mapping Program was subsequently created to develop methods for producing a series of land cover maps that utilized the existing Landsat digital land cover classifications produced by and for the major land management agencies for mapping the vegetation of Alaska. The program was successful in producing digital land cover classifications and statistical summaries using a common statewide classification and in reformatting these data to produce l:250,000-scale quadrangle-based maps directly from the Scitex laser plotter. A Federal and State agency review of these products found considerable user support for the maps. Presently the Geological Survey is committed to digital processing of six to eight quadrangles each year.

7 CFR 12.31 - On-site wetland identification criteria.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CONSERVATION Wetland Conservation § 12.31 On-site wetland identification criteria. (a) Hydric soils. (1) NRCS shall identify hydric soils through the use of published soil maps which reflect soil surveys completed by NRCS or through the use of on-site reviews. If a published soil map is unavailable for a given...