Vulnerability of Oregon Hydrologic Landscapes and Streamflow to Climate Change - 5/20/2014

EPA Science Inventory

Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors. Such assessments could be particularly useful in determining hydrologic vulnerability from climate change. A...

A new multi-scale geomorphological landscape GIS for the Netherlands

NASA Astrophysics Data System (ADS)

Weerts, Henk; Kosian, Menne; Baas, Henk; Smit, Bjorn

2013-04-01

At present, the Cultural Heritage Agency of the Netherlands is developing a nationwide landscape Geographical Information System (GIS). In this new conceptual approach, the Agency puts together several multi-scale landscape classifications in a GIS. The natural physical landscapes lie at the basis of this GIS, because these landscapes provide the natural boundary conditions for anthropogenic. At the local scale a nationwide digital geomorphological GIS is available in the Netherlands. This map, that was originally mapped at 1:50,000 from the late 1970's to the 1990's, is based on geomorphometrical (observable and measurable in the field), geomorphological and, lithological and geochronological criteria. When used at a national scale, the legend of this comprehensive geomorphological map is very complex which hampers use in e.g. planning practice or predictive archaeology. At the national scale several landscape classifications have been in use in the Netherlands since the early 1950's, typically ranging in the order of 10 -15 landscape units for the entire country. A widely used regional predictive archaeological classification has 13 archaeo-landscapes. All these classifications have been defined "top-down" and their actual content and boundaries have only been broadly defined. Thus, these classifications have little or no meaning at a local scale. We have tried to combine the local scale with the national scale. To do so, we first defined national physical geographical regions based on the new 2010 national geological map 1:500,000. We also made sure there was a reference with the European LANMAP2 classification. We arrived at 20 landscape units at the national scale, based on (1) genesis, (2) large-scale geomorphology, (3) lithology of the shallow sub-surface and (4) age. These criteria that were chosen because the genesis of the landscape largely determines its (scale of) morphology and lithology that in turn determine hydrological conditions. All together, they define the natural boundary conditions for anthropogenic use. All units have been defined, mapped and described based on these criteria. This enables the link with the European LANMAP2 GIS. The unit "Till-plateau sand region" for instance runs deep into Germany and even Poland. At the local scale, the boundaries of the national units can be defined and precisely mapped by linking them to the 1:50,000 geomorphological map polygons. Each national unit consists of a typical assemblage of local geomorphological units. So, the newly developed natural physical landscape map layer can be used from the local to the European scale.

Solutions for characterising natural landscapes in New Zealand using geographical information systems.

PubMed

Brabyn, Lars

2005-07-01

This paper explores solutions for characterising naturalness in relation to visual landscapes using Geographical Information System (GIS). It is argued that planners need to identify natural landscapes and monitor changes in their extent. Just like the indices that have been developed to describe the state of the economy, indices need to be developed that monitor the state of natural landscapes. The complications in characterising natural landscapes are outlined but it is argued that there is a need to develop definitions of natural landscapes that can be operationalised with a GIS. This will have the advantages of the efficiency of the technology and that the definition will be explicit and the implementation will be independent of the operator. Several GIS solutions are provided and these are an analysis of landcover, a density analysis of roads and utilities, and an analysis of property sizes. The analysis of property sizes is sensitive to many human modifications of the landscape because many developments begin with the subdivision of properties. However, it is argued in this paper that no one definition will suffice and that all three methods provide different, yet important, insights into natural landscape character. An aggregate classification of naturalness based on the majority value of the indices is demonstrated as well as a range of techniques for expressing the uncertainty of the aggregate classification.

Chapter 3: Simulating fire hazard across landscapes through time: integrating state-and-transition models with the Fuel Characteristic Classification System

Treesearch

Jessica E. Halofsky; Stephanie K. Hart; Miles A. Hemstrom; Joshua S. Halofsky; Morris C. Johnson

2014-01-01

Information on the effects of management activities such as fuel reduction treatments and of processes such as vegetation growth and disturbance on fire hazard can help land managers prioritize treatments across a landscape to best meet management goals. State-and-transition models (STMs) allow landscape-scale simulations that incorporate effects of succession,...

Oregon Hydrologic Landscapes: An Approach for Broadscale Hydrologic Classification

EPA Science Inventory

Gaged streams represent only a small percentage of watershed hydrologic conditions throughout the Unites States and globe, but there is a growing need for hydrologic classification systems that can serve as the foundation for broad-scale assessments of the hydrologic functions of...

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Developing an ecosystem diversity framework for landscape assessment

Treesearch

Robert D. Pfister; Michael D. Sweet

2000-01-01

Ecological diversity is being addressed in various research and management efforts, but a common foundation is not explicitly defined or displayed. A formal Ecosystem Diversity Framework (EDF) would improve landscape analysis and communication across multiple scales. The EDF represents a multiple-component vegetation classification system with inherent flexibility for...

A regional perspective of the physiographic provinces of the southeastern United States

Treesearch

James H. Miller; K.S. Robinson

1995-01-01

Abstract.  A landscape classification system using defined units for physiography, landform, and soils is needed to organize ecological information and to serve as an aid for landscape management.  To assist in this effort a composite physiographic map is presented to 12 southeastern states.

Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

USDA-ARS?s Scientific Manuscript database

A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya.

PubMed

Richard, Kyalo; Abdel-Rahman, Elfatih M; Subramanian, Sevgan; Nyasani, Johnson O; Thiel, Michael; Jozani, Hosein; Borgemeister, Christian; Landmann, Tobias

2017-11-03

Cropping systems information on explicit scales is an important but rarely available variable in many crops modeling routines and of utmost importance for understanding pests and disease propagation mechanisms in agro-ecological landscapes. In this study, high spatial and temporal resolution RapidEye bio-temporal data were utilized within a novel 2-step hierarchical random forest (RF) classification approach to map areas of mono- and mixed maize cropping systems. A small-scale maize farming site in Machakos County, Kenya was used as a study site. Within the study site, field data was collected during the satellite acquisition period on general land use/land cover (LULC) and the two cropping systems. Firstly, non-cropland areas were masked out from other land use/land cover using the LULC mapping result. Subsequently an optimized RF model was applied to the cropland layer to map the two cropping systems (2nd classification step). An overall accuracy of 93% was attained for the LULC classification, while the class accuracies (PA: producer's accuracy and UA: user's accuracy) for the two cropping systems were consistently above 85%. We concluded that explicit mapping of different cropping systems is feasible in complex and highly fragmented agro-ecological landscapes if high resolution and multi-temporal satellite data such as 5 m RapidEye data is employed. Further research is needed on the feasibility of using freely available 10-20 m Sentinel-2 data for wide-area assessment of cropping systems as an important variable in numerous crop productivity models.

Classification of the visual landscape for transmission planning

Treesearch

Curtis Miller; Nargis Jetha; Rod MacDonald

1979-01-01

The Visual Landscape Type Classification method of the Route and Site Selection Division, Ontario Hydro, defines and delineates the landscape into discrete visual units using parametric and judgmental data. This qualitative and quantitative information is documented in a prescribed format to give each of the approximately 1100 Landscape Types a unique description....

Predicting plant species diversity in a longleaf pine landscape

Treesearch

L. Katherine Kirkman; P. Charles Goebel; Brian J. Palik; Larry T. West

2004-01-01

In this study, we used a hierarchical, multifactor ecological classification system to examine how spatial patterns of biodiversity develop in one of the most species-rich ecosystems in North America, the fire-maintained longleaf pine-wiregrass ecosystem and associated depressional wetlands and riparian forests. Our goal was to determine which landscape features are...

Diagnosis of streamflow prediction skills in Oregon using Hydrologic Landscape Classification

EPA Science Inventory

A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...

Where and why do models fail? Perspectives from Oregon Hydrologic Landscape classification

EPA Science Inventory

A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...

Hydrologic landscape classification evaluates streamflow vulnerability to climate change in Oregon, USA

EPA Science Inventory

Classification can allow assessments of the hydrologic functions of landscapes and their responses to stressors. Here we demonstrate the use of a hydrologic landscape (HL) approach to assess vulnerability to potential future climate change at statewide and basin scales. The HL ...

Variational and PDE-Based Methods for Big Data Analysis, Classification and Image Processing Using Graphs

DTIC Science & Technology

2015-01-01

explain the accuracy and speed increase. Exploring the underlying connections of the energy evolution of these methods and the energy landscape for the...unwanted trivial global minimizers from the energy landscape . Note that the second eigenvector of the Laplacian already provides a solution to a cut...von Brecht. Convergence and energy landscape for Cheeger cut clustering. Advances in Neural Information Processing Systems, 25:1394– 1402, 2012. [13] X

Chapter 6 - Developing the LANDFIRE Vegetation and Biophysical Settings Map Unit Classifications for the LANDFIRE Prototype Project

Treesearch

Jennifer L. Long; Melanie Miller; James P. Menakis; Robert E. Keane

2006-01-01

The Landscape Fire and Resource Management Planning Tools Prototype Project, or LANDFIRE Prototype Project, required a system for classifying vegetation composition, biophysical settings, and vegetation structure to facilitate the mapping of vegetation and wildland fuel characteristics and the simulation of vegetation dynamics using landscape modeling. We developed...

Use of hydrologic landscape classification to diagnose streamflow predictability in Oregon

EPA Science Inventory

We implement a spatially lumped rainfall-runoff model to predict daily streamflow at 88 catchments within Oregon, USA and analyze its performance within the context of Oregon Hydrologic Landscapes (OHL) classification. OHL classification is used to characterize the physio-climat...

Multifunctional energy landscape for a DNA G-quadruplex: An evolved molecular switch

NASA Astrophysics Data System (ADS)

Cragnolini, Tristan; Chakraborty, Debayan; Šponer, Jiří; Derreumaux, Philippe; Pasquali, Samuela; Wales, David J.

2017-10-01

We explore the energy landscape for a four-fold telomere repeat, obtaining interconversion pathways between six experimentally characterised G-quadruplex topologies. The results reveal a multi-funnel system, with a variety of intermediate configurations and misfolded states. This organisation is identified with the intrinsically multi-functional nature of the system, suggesting a new paradigm for the classification of such biomolecules and clarifying issues regarding apparently conflicting experimental results.

A spatially constrained ecological classification: rationale, methodology and implementation

Treesearch

Franz Mora; Louis Iverson; Louis Iverson

2002-01-01

The theory, methodology and implementation for an ecological and spatially constrained classification are presented. Ecological and spatial relationships among several landscape variables are analyzed in order to define a new approach for a landscape classification. Using ecological and geostatistical analyses, several ecological and spatial weights are derived to...

Landscape Risk Factors for Lyme Disease in the Eastern Broadleaf Forest Province of the Hudson River Valley and the Effect of Explanatory Data Classification Resolution

EPA Science Inventory

This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity)...

Travelling in the eastern Mediterranean with landscape character assessment

NASA Astrophysics Data System (ADS)

Abu Jaber, N.; Abunnasr, Y.; Abu Yahya, A.; Boulad, N.; Christou, O.; Dimitropoulos, G.; Dimopoulos, T.; Gkoltsiou, K.; Khreis, N.; Manolaki, P.; Michael, K.; Odeh, T.; Papatheodoulou, A.; Sorotou, A.; Sinno, S.; Suliman, O.; Symons, N.; Terkenli, T.; Trigkas, Vassilis; Trovato, M. G.; Victora, M.; Zomeni, M.; Vogiatzakis, I. N.

2015-06-01

Following its application in Northern Europe, Landscape Character Assessment has also been implemented in Euro-Mediterranean countries as a tool for classifying, describing and assessing landscapes. Many landscape classifications employed in the Euro-Mediterranean area are similar in philosophy and application to the ones developed in Northern Europe. However, many aspects of landform, climate, land-use and ecology, as well as socio-economic context are distinctive of Mediterranean landscapes. The paper discusses the conceptual and methodological issues faced during landscape mapping and characterisation in four East-Mediterranean countries (within the MEDSCAPES project): Cyprus, Greece, Jordan and Lebanon. The major hurdles to overcome during the first phase of methodology development include variation in availability, quality, scale and coverage of spatial datasets between countries and also terminology semantics around landscapes. For example, the concept of landscape - a well-defined term in Greek and English - did not exist in Arabic. Another issue is the use of relative terms like 'high mountains,' `uplands' `lowlands' or ' hills'. Such terms, which are regularly used in landscape description, were perceived slightly differently in the four participating countries. In addition differences exist in nomenclature and classification systems used by each country for the dominant landscape-forming factors i.e. geology, soils and land use- but also in the cultural processes shaping the landscapes - compared both to each other and to the Northern-European norms. This paper argues for the development of consistent, regionally adapted, relevant and standardised methodologies if the results and application of LCA in the eastern Mediterranean region are to be transferable and comparable between countries.

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

USGS Publications Warehouse

Wendel, Jochen; Buttenfield, Barbara P.; Stanislawski, Larry V.

2016-01-01

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

Heritage landscape structure analysis in surrounding environment of the Grand Canal Yangzhou section

NASA Astrophysics Data System (ADS)

Xu, Huan

2018-03-01

The Yangzhou section of the Grand Canal is selected for a case study in this paper. The ZY-3 satellite images of 2016 are adopted as the data source. RS and GIS are used to analyze the landscape classification of the surrounding landscape of the Grand Canal, and the classification results are precisely evaluated. Next, the overall features of the landscape pattern are analyzed. The results showed that the overall accuracy is 82.5% and the Kappa coefficient is 78.17% in the Yangzhou section. The producer’s accuracy of the water landscape is the highest, followed by that of the other landscape, farmland landscape, garden and forest landscape, architectural landscape. The user’s accuracy of different landscape types can be ranked in a descending order, as the water landscape, farmland landscape, road landscape, architectural landscape, other landscape, garden and forest landscape. The farmland landscape and the architectural landscape are the top advantageous landscape types of the heritage site. The research findings can provide basic data for landscape protection, management and sustainable development of the Grand Canal Yangzhou section.

Assessment of land use and land cover change using spatiotemporal analysis of landscape: case study in south of Tehran.

PubMed

Sabr, Abutaleb; Moeinaddini, Mazaher; Azarnivand, Hossein; Guinot, Benjamin

2016-12-01

In the recent years, dust storms originating from local abandoned agricultural lands have increasingly impacted Tehran and Karaj air quality. Designing and implementing mitigation plans are necessary to study land use/land cover change (LUCC). Land use/cover classification is particularly relevant in arid areas. This study aimed to map land use/cover by pixel- and object-based image classification methods, analyse landscape fragmentation and determine the effects of two different classification methods on landscape metrics. The same sets of ground data were used for both classification methods. Because accuracy of classification plays a key role in better understanding LUCC, both methods were employed. Land use/cover maps of the southwest area of Tehran city for the years 1985, 2000 and 2014 were obtained from Landsat digital images and classified into three categories: built-up, agricultural and barren lands. The results of our LUCC analysis showed that the most important changes in built-up agricultural land categories were observed in zone B (Shahriar, Robat Karim and Eslamshahr) between 1985 and 2014. The landscape metrics obtained for all categories pictured high landscape fragmentation in the study area. Despite no significant difference was evidenced between the two classification methods, the object-based classification led to an overall higher accuracy than using the pixel-based classification. In particular, the accuracy of the built-up category showed a marked increase. In addition, both methods showed similar trends in fragmentation metrics. One of the reasons is that the object-based classification is able to identify buildings, impervious surface and roads in dense urban areas, which produced more accurate maps.

Assessment of landscape diversity and determination of landscape hotspots - a case of Slovenia

NASA Astrophysics Data System (ADS)

Perko, Drago; Ciglič, Rok; Hrvatin, Mauro

2017-04-01

Areas with high landscape diversity can be regarded as landscape hotspots, and vice versa areas with low landscape diversity can be marked as landscape coldspots. The main purpose of this paper is to use quantitative geoinformatical approach and identify parts of our test area (the country of Slovenia) that can be described as very diverse according to natural landscapes and natural elements. We used different digital raster data of natural elements and landscape classifications and defined landscape diversity and landscape hotspots. We defined diversity for each raster pixel by counting the number of different unique types of landscape elements and types of landscapes in its neighborhood. Namely, the method was used separately to define diversity according to natural elements (types of relief forms, rocks, and vegetation) and diversity according to existing geographical landscape classifications of Slovenia (types of landscapes). In both cases one-tenth of Slovenia's surface with the highest landscape diversity was defined as landscape hotspots. The same applies to the coldspots. Additionally we tested the same method of counting different types of landscapes in certain radius also for the area of Europe in order to find areas that are more diverse at continental level. By doing so we were able to find areas that have similar level of diversity as Slovenia according to different European landscape classifications. Areas with landscape diversity may have an advantage in economic development, especially in tourism. Such areas are also important for biodiversity, habitat, and species diversity. On the other hand, localities where various natural influences mix can also be areas where it is hard to transfer best practices from one place to another because of the varying responses of the landscapes to human intervention. Thus it is important to know where areas with high landscape diversity are.

Land classification of the standing stone state forest and state park on the eastern highland rim in Tennessee: the interaction of geology, topography, and soils

Treesearch

Glendon W. Smalley; Carlie McCowan; S. David Todd; Phillip M. Morrissey; J. Andrew McBride

2013-01-01

This paper summarizes the application of a land classification system developed by the senior author to the Standing Stone State Forest and State Park (SSSF&SP) on the Eastern Highland Rim. Landtypes are the most detailed level in the hierarchical system and represent distinct units of the landscape (mapped at a scale of 1:24,000) as defined by climate, geology,...

Hydrologic Landscape Characterization for the Pacific Northwest, USA

EPA Science Inventory

Hydrologic classification can help address some of the challenges facing catchment hydrology. Wigington et al. (2013) developed a hydrologic landscape (HL) approach to classification that was applied to the state of Oregon. Several characteristics limited its applicability outs...

Accuracy of Remotely Sensed Classifications For Stratification of Forest and Nonforest Lands

Treesearch

Raymond L. Czaplewski; Paul L. Patterson

2001-01-01

We specify accuracy standards for remotely sensed classifications used by FIA to stratify landscapes into two categories: forest and nonforest. Accuracy must be highest when forest area approaches 100 percent of the landscape. If forest area is rare in a landscape, then accuracy in the nonforest stratum must be very high, even at the expense of accuracy in the forest...

ASSESSMENT OF LANDSCAPE CHARACTERISTICS ON THEMATIC IMAGE CLASSIFICATION ACCURACY

EPA Science Inventory

Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of misclassifying pixels during thematic image classification. However, there has been a lack of empirical evidence, to support these hypotheses. This...

IMPACTS OF PATCH SIZE AND LANDSCAPE HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

EPA Science Inventory

Impacts of Patch Size and Landscape Heterogeneity on Thematic Image Classification Accuracy.
Currently, most thematic accuracy assessments of classified remotely sensed images oily account for errors between the various classes employed, at particular pixels of interest, thu...

Shore zone land use and land cover: Central Atlantic Regional Ecological Test Site

USGS Publications Warehouse

Dolan, R.; Hayden, B.P.; Vincent, C.L.

1974-01-01

Anderson's 1972 United States Geological Survey classification in modified form was applied to the barrier-island coastline within the CARETS region. High-altitude, color-infrared photography of December, 1972, and January, 1973, served as the primary data base in this study. The CARETS shore zone studied was divided into six distinct geographical regions; area percentages for each class in the modified Anderson classification are presented. Similarities and differences between regions are discussed within the framework of man's modification of these landscapes. The results of this study are presented as a series of 19 maps of land-use categories. Recommendations are made for a remote-sensing system for monitoring the CARETS shore zone within the context of the dynamics of the landscapes studied.

Skylab

NASA Image and Video Library

1973-01-01

This EREP photograph of the Uncompahgre Plateau area of Colorado illustrates the land use classification using the hierarchical numbering system to depict land forms and vegetative patterns. The numerator is a three-digit number with decimal components identifying the vegetation analog or land use conditions. The denominator uses a three-component decimal system for landscape characterization.

A new landscape classification system for monitoring and assessment of pastures

USDA-ARS?s Scientific Manuscript database

Pasturelands in the United States span a broad range of climate, soils, physical sites, and management. Rather than treat each site as a unique entity, this diversity must be classified into basic units for research and management purposes. A similar system based on ecological principles is needed f...

THE EFFECTS OF HABITAT RESOLUTION ON MODELS OF AVIAN DIVERSITY AND DISTRIBUTIONS: A COMPARISON OF TWO LAND-COVER CLASSIFICATIONS

EPA Science Inventory

The quantification of pattern is a key element of landscape analyses. One aspect of this quantification of particular importance to landscape ecologists regards the classification of continuous variables to produce categorical variables such as land-cover type or elevation strat...

Analysis of landscape character for visual resource management

Treesearch

Paul F. Anderson

1979-01-01

Description, classification and delineation of visual landscape character are initial steps in developing visual resource management plans. Landscape characteristics identified as key factors in visual landscape analysis include land cover/land use and landform. Landscape types, which are combinations of landform and surface features, were delineated for management...

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

A TEST OF WATERSHED CLASSIFICATION SYSTEMS FOR ECOLOGICAL RISK ASSESSMENT

EPA Science Inventory

To facilitate extrapolation among watersheds, ecological risk assessments should be based on a model of underlying factors influencing watershed response, particularly vulnerability. We propose a conceptual model of landscape vulnerability to serve as a basis for watershed classi...

The dynamics of human-induced land cover change in miombo ecosystems of southern Africa

NASA Astrophysics Data System (ADS)

Jaiteh, Malanding Sambou

Understanding human-induced land cover change in the miombo require the consistent, geographically-referenced, data on temporal land cover characteristics as well as biophysical and socioeconomic drivers of land use, the major cause of land cover change. The overall goal of this research to examine the applications of high-resolution satellite remote sensing data in studying the dynamics of human-induced land cover change in the miombo. Specific objectives are to: (1) evaluate the applications of computer-assisted classification of Landsat Thematic Mapper (TM) data for land cover mapping in the miombo and (2) analyze spatial and temporal patterns of landscape change locations in the miombo. Stepwise Thematic Classification, STC (a hybrid supervised-unsupervised classification) procedure for classifying Landsat TM data was developed and tested using Landsat TM data. Classification accuracy results were compared to those from supervised and unsupervised classification. The STC provided the highest classification accuracy i.e., 83.9% correspondence between classified and referenced data compared to 44.2% and 34.5% for unsupervised and supervised classification respectively. Improvements in the classification process can be attributed to thematic stratification of the image data into spectrally homogenous (thematic) groups and step-by-step classification of the groups using supervised or unsupervised classification techniques. Supervised classification failed to classify 18% of the scene evidence that training data used did not adequately represent all of the variability in the data. Application of the procedure in drier miombo produced overall classification accuracy of 63%. This is much lower than that of wetter miombo. The results clearly demonstrate that digital classification of Landsat TM can be successfully implemented in the miombo without intensive fieldwork. Spatial characteristics of land cover change in agricultural and forested landscapes in central Malawi were analyzed for the period 1984 to 1995 spatial pattern analysis methods. Shifting cultivation areas, Agriculture in forested landscape, experienced highest rate of woodland cover fragmentation with mean patch size of closed woodland cover decreasing from 20ha to 7.5ha. Permanent bare (cropland and settlement) in intensive agricultural matrix landscapes increased 52% largely through the conversion of fallow areas. Protected National Park area remained fairly unchanged although closed woodland area increased by 4%, mainly from regeneration of open woodland. This study provided evidence that changes in spatial characteristics in the miombo differ with landscape. Land use change (i.e. conversion to cropland) is the primary driving force behind changes in landscape spatial patterns. Also, results revealed that exclusion of intense human use (i.e. cultivation and woodcutting) through regulations and/or fencing increased both closed woodland area (through regeneration of open woodland) and overall connectivity in the landscape. Spatial characteristics of land cover change were analyzed at locations in Malawi (wetter miombo) and Zimbabwe (drier miombo). Results indicate land cover dynamics differ both between and within case study sites. In communal areas in the Kasungu scene, land cover change is dominated by woodland fragmentation to open vegetation. Change in private commercial lands was dominantly expansion of bare (settlement and cropland) areas primarily at the expense of open vegetation (fallow land).

Geospatial analysis of lake and landscape interactions within the Toolik Lake region, North Slope of Alaska

NASA Astrophysics Data System (ADS)

Pathak, Prasad A.

The Arctic region of Alaska is experiencing severe impacts of climate change. The Arctic lakes ecosystems are bound to undergo alterations in its trophic structure and other chemical properties. However, landscape factors controlling the lake influxes were not studied till date. This research has examined the currently existing lake landscape interactions using Remote Sensing and GIS technology. The statistical modeling was carried out using Regression and CART methods. Remote sensing data was applied to derive the required landscape indices. Remote sensing in the Arctic Alaska faces many challenges including persistent cloud cover, low sun angle and limited snow free period. Tundra vegetation types are interspersed and intricate to classify unlike managed forest stands. Therefore, historical studies have remained underachieved with respect thematic accuracies. However, looking at vegetation communities at watershed level and the implementation of expert classification system achieved the accuracies up to 90%. The research has highlighted the probable role of interactions between vegetation root zones, nutrient availability within active zone, as well as importance of permafrost thawing. Multiple regression analyses and Classification Trees were developed to understand relationships between landscape factors with various chemical parameters as well as chlorophyll readings. Spatial properties of Shrubs and Riparian complexes such as complexity of individual patches at watershed level and within proximity of water channels were influential on Chlorophyll production of lakes. Till-age had significant impact on Total Nitrogen contents. Moreover, relatively young tills exhibited significantly positive correlation with concentration of various ions and conductivity of lakes. Similarly, density of patches of Heath complexes was found to be important with respect to Total Phosphorus contents in lakes. All the regression models developed in this study were significant at 95% confidence level. However, the classification trees could not achieve high predictabilities due to limited number of lakes sampled. Keywords: Landscape factors, Lake primary productivity, Arctic, Climate change, Regression, CART

Creation of a Digital Aquifer Permeability Map for the Pacific Northwest

EPA Science Inventory

Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors such as climate change. One of the greatest challenges to this effort is obtaining consistent aquifer permea...

Classification of pasture habitats by Hungarian herders in a steppe landscape (Hungary)

PubMed Central

2012-01-01

Background Landscape ethnoecology focuses on the ecological features of the landscape, how the landscape is perceived, and used by people who live in it. Though studying folk classifications of species has a long history, the comparative study of habitat classifications is just beginning. I studied the habitat classification of herders in a Hungarian steppe, and compared it to classifications of botanists and laymen. Methods For a quantitative analysis the picture sort method was used. Twenty-three pictures of 7-11 habitat types were sorted by 25 herders.’Density’ of pictures along the habitat gradient of the Hortobágy salt steppe was set as equal as possible, but pictures differed in their dominant species, wetness, season, etc. Before sorts, herders were asked to describe pictures to assure proper recognition of habitats. Results Herders classified the images into three main groups: (1) fertile habitats at the higher parts of the habitat gradient (partos, lit. on the shore); (2) saline habitats (szík, lit. salt or saline place), and (3) meadows and marshes (lapos, lit. flooded) at the lower end of the habitat gradient. Sharpness of delimitation changed along the gradient. Saline habitats were the most isolated from the rest. Botanists identified 6 groups. Laymen grouped habitats in a less coherent way. As opposed to my expectations, botanical classification was not more structured than that done by herders. I expected and found high correspondence between the classifications by herders, botanists and laymen. All tended to recognize similar main groups: wetlands, ”good grass” and dry/saline habitats. Two main factors could have been responsible for similar classifications: salient features correlated (e.g. salinity recognizable by herders and botanists but not by laymen correlated with the density of grasslands or height of vegetation recognizable also for laymen), or the same salient features were used as a basis for sorting (wetness, and abiotic stress). Conclusions Despite all the difficulties of studying habitat classifications (more implicit, more variable knowledge than knowledge on species), conducting landscape ethnoecological research will inevitably reveal a deeper human understanding of biological organization at a supraspecific level, where natural discontinuities are less sharp than at the species or population level. PMID:22853549

Temporal and spatial changes of land use and landscape in a coal mining area in Xilingol grassland

NASA Astrophysics Data System (ADS)

Guan, Chunzhu; Zhang, Baolin; Li, Jiannan; Zhao, Junling

2017-01-01

Coal mining, particularly surface mining, inevitably disturbs land. According to Landsat images acquired over Xilingol grassland in 2005, 2009 and 2015, land uses were divided into seven classes, i. e., open stope, stripping area, waste-dump area, mine industrial area, farmland, urban area and the original landscape (grassland), using supervised classification and human-computer interactive interpretation. The overall classification accuracies were 97.72 %, 98.43 % and 96.73 %, respectively; the Kappa coefficients were 0.95, 0.97 and 0.95, respectively. Analysis on LUCC (Land Use and Cover Change) showed that surface coal mining disturbed grassland ecosystem: grassland decreased by 8661.15 hm2 in 2005-2015. The area and proportion of mining operation areas (open stope, stripping area, waste-dump area, mine industrial field) increased, but those of grassland decreased continuously. Transfer matrix of land use changes showed that waste-dump had the largest impacts in mining disturbance, and that effective reclamation of waste-dump areas would mitigate eco-environment destruction, as would be of great significance to protect fragile grassland eco-system. Six landscape index showed that landscape fragmentation increased, and the influences of human activity on landscape was mainly reflected in the expansion of mining area and urban area. Remote sensing monitoring of coal surface mining in grassland would accurately demonstrate the dynamics and trend of LUCC, providing scientific supports for ecological reconstruction in surface mining area.

Variability of lotic macroinvertebrate assemblages and stream habitat characteristics across hierarchical landscape classifications.

PubMed

Mykrä, Heikki; Heino, Jani; Muotka, Timo

2004-09-01

Streams are naturally hierarchical systems, and their biota are affected by factors effective at regional to local scales. However, there have been only a few attempts to quantify variation in ecological attributes across multiple spatial scales. We examined the variation in several macroinvertebrate metrics and environmental variables at three hierarchical scales (ecoregions, drainage systems, streams) in boreal headwater streams. In nested analyses of variance, significant spatial variability was observed for most of the macroinvertebrate metrics and environmental variables examined. For most metrics, ecoregions explained more variation than did drainage systems. There was, however, much variation attributable to residuals, suggesting high among-stream variation in macroinvertebrate assemblage characteristics. Nonmetric multidimensional scaling (NMDS) and multiresponse permutation procedure (MRPP) showed that assemblage composition differed significantly among both drainage systems and ecoregions. The associated R-statistics were, however, very low, indicating wide variation among sites within the defined landscape classifications. Regional delineations explained most of the variation in stream water chemistry, ecoregions being clearly more influential than drainage systems. For physical habitat characteristics, by contrast, the among-stream component was the major source of variation. Distinct differences attributable to stream size were observed for several metrics, especially total number of taxa and abundance of algae-scraping invertebrates. Although ecoregions clearly account for a considerable amount of variation in macroinvertebrate assemblage characteristics, we suggest that a three-tiered classification system (stratification through ecoregion and habitat type, followed by assemblage prediction within these ecologically meaningful units) will be needed for effective bioassessment of boreal running waters.

Fine resolution probabilistic land cover classification of landscapes in the southeastern United States

Treesearch

Joseph St. Peter; John Hogland; Nathaniel Anderson; Jason Drake; Paul Medley

2018-01-01

Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a...

Research needs for our national landscapes

Treesearch

Elwood L. Shafer

1979-01-01

The prevailing research problem for our national landscapes is: How shall we organize, control, and coordinate public and private development so as to protect, maintain, improve, and manage those landscape features that we value most? Research questions discussed include: environmental/political conflicts, taxation and zoning, landscape classification, public...

Local soil classification and crop suitability: Implications for the historical land use and soil management in Monti di Trapani (Sicily)

NASA Astrophysics Data System (ADS)

Garcia-Vila, Margarita; Corselli, Rocco; Bonet, María Teresa; Lopapa, Giuseppe; Pillitteri, Valentina; Fereres, Elias

2017-04-01

In the past, the lack of technologies (e.g. synthetic fertilizers) to overcome biophysical limitations has played a central role in land use planning. Thus, landscape management and agronomic practices are reactions to local knowledge and perceptions on natural resources, particularly soil. In the framework of the European research project MEMOLA (FP7), the role of local farmers knowledge and perceptions on soil for the historical land use through the spatial distribution of crops and the various management practices have been assessed in three different areas of Monti di Trapani region (Sicily). The identification of the soil classification systems of farmers and the criteria on which it is based, linked to the evaluation of the farmers' ability to identify and map the different soil types, was a key step. Nevertheless, beyond the comparison of the ethnopedological classification approach versus standard soil classification systems, the study also aims at understanding local soil management and land use decisions. The applied methodology was based on an interdisciplinary approach, combining soil science methods and participatory appraisal tools, particularly: i) semi-structured interviews; ii) soil sampling and analysis; iii) discussion groups; and iv) a workshop with local edafologists and agronomists. A rich local glossary of terms associated with the soil conditions and an own soil classification system have been identified in the region. Also, a detailed soil map, including process of soil degradation and soil capability, has been generated. This traditional soil knowledge has conditioned the management and the spatial distribution of the crops, and therefore the configuration of the landscape, until the 1990s. Acknowledgements This work has been funded by the European Union project MEMOLA (Grant agreement no: 613265).

Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests

NASA Astrophysics Data System (ADS)

Wilschut, L. I.; Addink, E. A.; Heesterbeek, J. A. P.; Dubyanskiy, V. M.; Davis, S. A.; Laudisoit, A.; Begon, M.; Burdelov, L. A.; Atshabar, B. B.; de Jong, S. M.

2013-08-01

Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague.

Study on Ecological Risk Assessment of Guangxi Coastal Zone Based on 3s Technology

NASA Astrophysics Data System (ADS)

Zhong, Z.; Luo, H.; Ling, Z. Y.; Huang, Y.; Ning, W. Y.; Tang, Y. B.; Shao, G. Z.

2018-05-01

This paper takes Guangxi coastal zone as the study area, following the standards of land use type, divides the coastal zone of ecological landscape into seven kinds of natural wetland landscape types such as woodland, farmland, grassland, water, urban land and wetlands. Using TM data of 2000-2015 such 15 years, with the CART decision tree algorithm, for analysis the characteristic of types of landscape's remote sensing image and build decision tree rules of landscape classification to extract information classification. Analyzing of the evolution process of the landscape pattern in Guangxi coastal zone in nearly 15 years, we may understand the distribution characteristics and change rules. Combined with the natural disaster data, we use of landscape index and the related risk interference degree and construct ecological risk evaluation model in Guangxi coastal zone for ecological risk assessment results of Guangxi coastal zone.

Prioritizing conservation potential of arid-land montane natural springs and associated riparian areas

USGS Publications Warehouse

Thompson, B.C.; Matusik-Rowan, P. L.; Boykin, K.G.

2002-01-01

Using inventory data and input from natural resource professionals, we developed a classification system that categorizes conservation potential for montane natural springs. This system contains 18 classes based on the presence of a riparian patch, wetland species, surface water, and evidence of human activity. We measured physical and biological components of 276 montane springs in the Oscura Mountains above 1450 m and the San Andres Mountains above 1300 m in southern New Mexico. Two of the 18 classes were not represented during the inventory, indicating the system applies to conditions beyond the montane springs in our study area. The class type observed most often (73 springs) had a riparian patch, perennial surface water, and human evidence. We assessed our system in relation to 13 other wetland and riparian classification systems regarding approach, area of applicability, intended users, validation, ease of use, and examination of system response. Our classification can be used to rapidly assess priority of conservation potential for isolated riparian sites, especially springs, in arid landscapes. We recommend (1) including this classification in conservation planning, (2) removing deleterious structures from high-priority sites, and (3) assessing efficiency and use of this classification scheme elsewhere. ?? 2002 Elsevier Science Ltd.

EXTENDING AQUATIC CLASSIFICATION TO THE LANDSCAPE SCALE HYDROLOGY-BASED STRATEGIES

EPA Science Inventory

Aquatic classification of single water bodies (lakes, wetlands, estuaries) is often based on geologic origin, while stream classification has relied on multiple factors related to landform, geomorphology, and soils. We have developed an approach to aquatic classification based o...

Geomorphology Classification of Shandong Province Based on Digital Elevation Model in the 1 Arc-second Format of Shuttle Radar Topography Mission Data

NASA Astrophysics Data System (ADS)

Fu, Jundong; Zhang, Guangcheng; Wang, Lei; Xia, Nuan

2018-01-01

Based on gigital elevation model in the 1 arc-second format of shuttle radar topography mission data, using the window analysis and mean change point analysis of geographic information system (GIS) technology, programmed with python modules this, automatically extracted and calculated geomorphic elements of Shandong province. The best access to quantitatively study area relief amplitude of statistical area. According to Chinese landscape classification standard, the landscape type in Shandong province was divided into 8 types: low altitude plain, medium altitude plain, low altitude platform, medium altitude platform, low altitude hills, medium altitude hills, low relief mountain, medium relief mountain and the percentages of Shandong province’s total area are as follows: 12.72%, 0.01%, 36.38%, 0.24%, 17.26%, 15.64%, 11.1%, 6.65%. The results of landforms are basically the same as the overall terrain of Shandong Province, Shandong province’s total area, and the study can quantitatively and scientifically provide reference for the classification of landforms in Shandong province.

Characterizing fuels in treated areas.

Treesearch

Roger D. Ottmar; Clinton S. Wright

2002-01-01

Small-log utilization or thinning operations followed by a fuel treatment such as prescribed fire can be used to change the composition and structure of fuelbeds, thereby mitigating deleterious fire effects and reducing the potential for catastrophic wildfires in some forested landscapes. We are developing a national system, Fuel Characteristic Classification (FCC),...

Prospects for hydrologic classification of landscapes and watersheds

EPA Science Inventory

The ecological functions of streams and associated riparian zones are strongly influenced by the hydrological attributes of watersheds and landscapes in which they occur. Oregon hydrologic landscape regions (HLRs) have been defined based on four types of GIS data: 1) climate, 2) ...

Plant landscape design simulating natural community by using AHP method based on TWINSPAN classification

NASA Astrophysics Data System (ADS)

Wang, Li Han

2018-06-01

Taking the forest vegetation in Zijin Mountain (Purple Mountain) Area of Nanjing as the research object, based on the simulation natural and semi natural plant communities, the systematic research on the construction of Nanjing regional plant landscape is carried out by the method such as literature and theory, investigation and evaluation, discussion and reference. On the basis of TWINSPAN classification, the species composition (flora and geographical composition), community structure, species diversity, interspecific relationship and ecological niche of Zijin Mountain natural vegetation are studied and analyzed as a basis for simulation design and planting. Then, from the three levels of ornamental value, resource development and utilization potential and biological characteristics, a comprehensive evaluation system used for wild ornamental plant resources in Zijin Mountain is built. Finally, some suggestions on the planting species of deep forest vegetation in Zijin Mountain are put forward.

In Search of Effective Scales for Stream Management: Does Agroecoregion, Watershed, or Their Intersection Best Explain the Variance in Stream Macroinvertebrate Communities?

NASA Astrophysics Data System (ADS)

Dovciak, A. L.; Perry, J. A.

2002-09-01

Our lack of understanding of relationships between stream biotic communities and surrounding landscape conditions makes it difficult to determine the spatial scale at which management practices are best assessed. We investigated these relationships in the Minnesota River Basin, which is divided into major watersheds and agroecoregions which are based on soil type, geologic parent material, landscape slope steepness, and climatic factors affecting crop productivity. We collected macroinvertebrate and stream habitat data from 68 tributaries among three major watersheds and two agroecoregions. We tested the effectiveness of the two landscape classification systems (i.e., watershed, agroecoregion) in explaining variance in habitat and macroinvertebrate metrics, and analyzed the relative influence on macroinvertebrates of local habitat versus regional characteristics. Macroinvertebrate community composition was most strongly influenced by local habitat; the variance in habitat conditions was best explained at the scale of intersection of major watershed and agroecoregion (i.e., stream habitat conditions were most homogeneous within the physical regions of intersection of these two landscape classification systems). Our results are consistent with findings of other authors that most variation in macroinvertebrate community data from large agricultural catchments is attributable to local physical conditions. Our results are the first to test the hypothesis and demonstrate that the scale of intersection best explains these variances. The results suggest that management practices adjusted for both watershed and ecoregion characteristics, with the goal of improving physical habitat characteristics of local streams, may lead to better basin-wide water quality conditions and stream biological integrity.

Classification tree models for predicting distributions of michigan stream fish from landscape variables

USGS Publications Warehouse

Steen, P.J.; Zorn, T.G.; Seelbach, P.W.; Schaeffer, J.S.

2008-01-01

Traditionally, fish habitat requirements have been described from local-scale environmental variables. However, recent studies have shown that studying landscape-scale processes improves our understanding of what drives species assemblages and distribution patterns across the landscape. Our goal was to learn more about constraints on the distribution of Michigan stream fish by examining landscape-scale habitat variables. We used classification trees and landscape-scale habitat variables to create and validate presence-absence models and relative abundance models for Michigan stream fishes. We developed 93 presence-absence models that on average were 72% correct in making predictions for an independent data set, and we developed 46 relative abundance models that were 76% correct in making predictions for independent data. The models were used to create statewide predictive distribution and abundance maps that have the potential to be used for a variety of conservation and scientific purposes. ?? Copyright by the American Fisheries Society 2008.

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.

Gradient Analysis and Classification of Carolina Bay Vegetation: A Framework for Bay Wetlands Conservation and Restoration

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

Diane De Steven,Ph.D.; Maureen Tone,PhD.

1997-10-01

This report address four project objectives: (1) Gradient model of Carolina bay vegetation on the SRS--The authors use ordination analyses to identify environmental and landscape factors that are correlated with vegetation composition. Significant factors can provide a framework for site-based conservation of existing diversity, and they may also be useful site predictors for potential vegetation in bay restorations. (2) Regional analysis of Carolina bay vegetation diversity--They expand the ordination analyses to assess the degree to which SRS bays encompass the range of vegetation diversity found in the regional landscape of South Carolina's western Upper Coastal Plain. Such comparisons can indicatemore » floristic status relative to regional potentials and identify missing species or community elements that might be re-introduced or restored. (3) Classification of vegetation communities in Upper Coastal Plain bays--They use cluster analysis to identify plant community-types at the regional scale, and explore how this classification may be functional with respect to significant environmental and landscape factors. An environmentally-based classification at the whole-bay level can provide a system of templates for managing bays as individual units and for restoring bays to desired plant communities. (4) Qualitative model for bay vegetation dynamics--They analyze present-day vegetation in relation to historic land uses and disturbances. The distinctive history of SRS bays provides the possibility of assessing pathways of post-disturbance succession. They attempt to develop a coarse-scale model of vegetation shifts in response to changing site factors; such qualitative models can provide a basis for suggesting management interventions that may be needed to maintain desired vegetation in protected or restored bays.« less

Landscape risk factors for Lyme disease in the eastern broadleaf forest province of the Hudson River valley and the effect of explanatory data classification resolution.

PubMed

Messier, Kyle P; Jackson, Laura E; White, Jennifer L; Hilborn, Elizabeth D

2015-01-01

This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity) and aggregate classes (e.g., forest, developed). Percent of each landcover type, median income, and centroid coordinates were calculated by census tract. Regression results from individual and aggregate variable models were compared with the dispersion parameter-based R(2) (Rα(2)) and AIC. The maximum Rα(2) was 0.82 and 0.83 for the best aggregate and individual model, respectively. The AICs for the best models differed by less than 0.5%. The aggregate model variables included forest, developed, agriculture, agriculture-squared, y-coordinate, y-coordinate-squared, income and income-squared. The individual model variables included deciduous forest, deciduous forest-squared, developed low intensity, pasture, y-coordinate, y-coordinate-squared, income, and income-squared. Results indicate that regional landscape models for Lyme disease rate are robust to NLCD landcover classification resolution. Published by Elsevier Ltd.

Application of Piedmont Landscape Ecosystem Classification as a Reference For A Vegetation and Herpetofaunal Survey on Lake Thurmond, SC

Treesearch

Victor B. Shelburne; Lawrence R. Gering; J. Drew Lanham; Gregory P. Smith; Thomas M. Floyd; Eran S. Kilpatrick

2002-01-01

Application of a Piedmont landscape ecosystem classification methodology was used as a basis for a survey of vegetation and herpetofaunal communities on a 343 hectare (846 acre) tract on Lake Thurmond near Plum Branch, SC. The site is located in the Carolina Slate Belt of the Midlands Plateau Region of the Piedmont province. A total of 160 plots were established and 30...

Landscape metrics for three-dimension urban pattern recognition

NASA Astrophysics Data System (ADS)

Liu, M.; Hu, Y.; Zhang, W.; Li, C.

2017-12-01

Understanding how landscape pattern determines population or ecosystem dynamics is crucial for managing our landscapes. Urban areas are becoming increasingly dominant social-ecological systems, so it is important to understand patterns of urbanization. Most studies of urban landscape pattern examine land-use maps in two dimensions because the acquisition of 3-dimensional information is difficult. We used Brista software based on Quickbird images and aerial photos to interpret the height of buildings, thus incorporating a 3-dimensional approach. We estimated the feasibility and accuracy of this approach. A total of 164,345 buildings in the Liaoning central urban agglomeration of China, which included seven cities, were measured. Twelve landscape metrics were proposed or chosen to describe the urban landscape patterns in 2- and 3-dimensional scales. The ecological and social meaning of landscape metrics were analyzed with multiple correlation analysis. The results showed that classification accuracy compared with field surveys was 87.6%, which means this method for interpreting building height was acceptable. The metrics effectively reflected the urban architecture in relation to number of buildings, area, height, 3-D shape and diversity aspects. We were able to describe the urban characteristics of each city with these metrics. The metrics also captured ecological and social meanings. The proposed landscape metrics provided a new method for urban landscape analysis in three dimensions.

The Blurred Line between Form and Process: A Comparison of Stream Channel Classification Frameworks

PubMed Central

Kasprak, Alan; Hough-Snee, Nate

2016-01-01

Stream classification provides a means to understand the diversity and distribution of channels and floodplains that occur across a landscape while identifying links between geomorphic form and process. Accordingly, stream classification is frequently employed as a watershed planning, management, and restoration tool. At the same time, there has been intense debate and criticism of particular frameworks, on the grounds that these frameworks classify stream reaches based largely on their physical form, rather than direct measurements of their component hydrogeomorphic processes. Despite this debate surrounding stream classifications, and their ongoing use in watershed management, direct comparisons of channel classification frameworks are rare. Here we implement four stream classification frameworks and explore the degree to which each make inferences about hydrogeomorphic process from channel form within the Middle Fork John Day Basin, a watershed of high conservation interest within the Columbia River Basin, U.S.A. We compare the results of the River Styles Framework, Natural Channel Classification, Rosgen Classification System, and a channel form-based statistical classification at 33 field-monitored sites. We found that the four frameworks consistently classified reach types into similar groups based on each reach or segment’s dominant hydrogeomorphic elements. Where classified channel types diverged, differences could be attributed to the (a) spatial scale of input data used, (b) the requisite metrics and their order in completing a framework’s decision tree and/or, (c) whether the framework attempts to classify current or historic channel form. Divergence in framework agreement was also observed at reaches where channel planform was decoupled from valley setting. Overall, the relative agreement between frameworks indicates that criticism of individual classifications for their use of form in grouping stream channels may be overstated. These form-based criticisms may also ignore the geomorphic tenet that channel form reflects formative hydrogeomorphic processes across a given landscape. PMID:26982076

Multitemporal L- and C-Band Synthetic Aperture Radar To Highlight Differences in Water Status Among Boreal Forest and Wetland Systems in the Yukon Flats, Interior Alaska

USGS Publications Warehouse

Balser, Andrew W.; Wylie, Bruce K.

2010-01-01

Tracking landscape-scale water status in high-latitude boreal systems is indispensible to understanding the fate of stored and sequestered carbon in a climate change scenario. Spaceborne synthetic aperture radar (SAR) imagery provides critical information for water and moisture status in Alaskan boreal environments at the landscape scale. When combined with results from optical sensor analyses, a complementary picture of vegetation, biomass, and water status emerges. Whereas L-band SAR showed better inherent capacity to map water status, C-band had much more temporal coverage in this study. Analysis through the use of L- and C-band SARs combined with Landsat Enhanced Thematic Mapper Plus (ETM+) enables landscape stratification by vegetation and by seasonal and interannual hydrology. Resultant classifications are highly relevant to biogeochemistry at the landscape scale. These results enhance our understanding of ecosystem processes relevant to carbon balance and may be scaled up to inform regional carbon flux estimates and better parameterize general circulation models (GCMs).

Assessment of Landscape Fragmentation Associated With Urban Centers Using ASTER Data

NASA Astrophysics Data System (ADS)

Stefanov, W. L.

2002-12-01

The role of humans as an integral part of the environment and ecosystem processes has only recently been accepted into mainstream ecological thought. The realization that virtually all ecosystems on Earth have experienced some degree of human alteration or impact has highlighted the need to incorporate humans (and their environmental effects) into ecosystem models. A logical starting point for investigation of human ecosystem dynamics is examination of the land cover characteristics of large urban centers. Land cover and land use changes associated with urbanization are important drivers of local geological, hydrological, ecological, and climatic change. Quantification and monitoring of urban land cover/land use change is part of the primary mission of the ASTER instrument on board the NASA Terra satellite, and comprises the fundamental research objective of the Urban Environmental Monitoring (UEM) Program at Arizona State University. The UEM program seeks to acquire day/night, visible through thermal infrared data twice per year for 100 global urban centers (with an emphasis on semi-arid cities) over the nominal six-year life of the Terra mission. Data have been acquired for the majority of the target urban centers and are used to compare landscape fragmentation patterns on the basis of land cover classifications. Land cover classifications of urban centers are obtained using visible through mid-infrared reflectance and emittance spectra together with calculated vegetation index and spatial variance texture information (all derived from raw ASTER data). This information is combined within a classification matrix, using an expert system framework, to obtain final pixel classifications. Landscape fragmentation is calculated using a pixel per unit area metric for comparison between 55 urban centers with varying geographic and climatic settings including North America, South America, Europe, central and eastern Asia, and Australia. Temporal variations in land cover and landscape fragmentation are assessed for 9 urban centers (Albuquerque, New Mexico, USA; Baghdad, Iraq; Las Vegas, Nevada, USA; Lisbon, Portugal; Madrid, Spain; San Francisco, California, USA; Tokyo, Japan; and Vancouver, Canada). These data provide a useful baseline for comparison of human-dominated ecosystem land cover and associated regional landscape fragmentation. Continued collection of ASTER data throughout the duration of the Terra mission will enable further investigation of urban ecosystem trends.

Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota

USGS Publications Warehouse

Corcoran, Jennifer M.; Knight, Joseph F.; Gallant, Alisa L.

2013-01-01

Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training data, as well as the capability of measuring classification confidence. Though the random forest classifier can generate complex decision trees with a multitude of input data and still not run a high risk of over fitting, there is a great need to reduce computational and operational costs by including only key input data sets without sacrificing a significant level of accuracy. Our main questions for this study site in Northern Minnesota were: (1) how does classification accuracy and confidence of mapping wetlands compare using different remote sensing platforms and sets of input data; (2) what are the key input variables for accurate differentiation of upland, water, and wetlands, including wetland type; and (3) which datasets and seasonal imagery yield the best accuracy for wetland classification. Our results show the key input variables include terrain (elevation and curvature) and soils descriptors (hydric), along with an assortment of remotely sensed data collected in the spring (satellite visible, near infrared, and thermal bands; satellite normalized vegetation index and Tasseled Cap greenness and wetness; and horizontal-horizontal (HH) and horizontal-vertical (HV) polarization using L-band satellite radar). We undertook this exploratory analysis to inform decisions by natural resource managers charged with monitoring wetland ecosystems and to aid in designing a system for consistent operational mapping of wetlands across landscapes similar to those found in Northern Minnesota.

Accuracy of land use change detection using support vector machine and maximum likelihood techniques for open-cast coal mining areas.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-08-01

One objective of the present study was to evaluate the performance of support vector machine (SVM)-based image classification technique with the maximum likelihood classification (MLC) technique for a rapidly changing landscape of an open-cast mine. The other objective was to assess the change in land use pattern due to coal mining from 2006 to 2016. Assessing the change in land use pattern accurately is important for the development and monitoring of coalfields in conjunction with sustainable development. For the present study, Landsat 5 Thematic Mapper (TM) data of 2006 and Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) data of 2016 of a part of Jharia Coalfield, Dhanbad, India, were used. The SVM classification technique provided greater overall classification accuracy when compared to the MLC technique in classifying heterogeneous landscape with limited training dataset. SVM exceeded MLC in handling a difficult challenge of classifying features having near similar reflectance on the mean signature plot, an improvement of over 11 % was observed in classification of built-up area, and an improvement of 24 % was observed in classification of surface water using SVM; similarly, the SVM technique improved the overall land use classification accuracy by almost 6 and 3 % for Landsat 5 and Landsat 8 images, respectively. Results indicated that land degradation increased significantly from 2006 to 2016 in the study area. This study will help in quantifying the changes and can also serve as a basis for further decision support system studies aiding a variety of purposes such as planning and management of mines and environmental impact assessment.

The Landscape of long non-coding RNA classification

PubMed Central

St Laurent, Georges; Wahlestedt, Claes; Kapranov, Philipp

2015-01-01

Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. PMID:25869999

Hydrologic Landscape Regionalisation Using Deductive Classification and Random Forests

PubMed Central

Brown, Stuart C.; Lester, Rebecca E.; Versace, Vincent L.; Fawcett, Jonathon; Laurenson, Laurie

2014-01-01

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents. PMID:25396410

Hydrologic landscape regionalisation using deductive classification and random forests.

PubMed

Brown, Stuart C; Lester, Rebecca E; Versace, Vincent L; Fawcett, Jonathon; Laurenson, Laurie

2014-01-01

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Verification of hydrologic landscape derived basin-scale classifications in the Pacific Northwest

Treesearch

Keith Sawicz

2016-01-01

The interaction between the physical and climatic attributes of a basin (form) control how water is partitioned, stored, and conveyed through a catchment (function). Hydrologic Landscapes (HLs) were previously...

Development of a Digital Aquifer Permeability Map for the Pacific Southwest in Support of Hydrologic Landscape Classification: Methods

EPA Science Inventory

Researchers at the U.S. Environmental Protection Agency’s Western Ecology Division have been developing hydrologic landscape maps for selected U.S. states in an effort to create a method to identify the intrinsic watershed attributes of landscapes in regions with little dat...

THE PEAKS AND GEOMETRY OF FITNESS LANDSCAPES

PubMed Central

CRONA, KRISTINA; GREENE, DEVIN; BARLOW, MIRIAM

2012-01-01

Fitness landscapes are central in the theory of adaptation. Recent work compares global and local properties of fitness landscapes. It has been shown that multi-peaked fitness landscapes have a local property called reciprocal sign epistasis interactions. The converse is not true. We show that no condition phrased in terms of reciprocal sign epistasis interactions only, implies multiple peaks. We give a sufficient condition for multiple peaks phrased in terms of two-way interactions. This result is surprising since it has been claimed that no sufficient local condition for multiple peaks exist. We show that our result cannot be generalized to sufficient conditions for three or more peaks. Our proof depends on fitness graphs, where nodes represent genotypes and where arrows point toward more fit genotypes. We also use fitness graphs in order to give a new brief proof of the equivalent characterizations of fitness landscapes lacking genetic constraints on accessible mutational trajectories. We compare a recent geometric classification of fitness landscape based on triangulations of polytopes with qualitative aspects of gene interactions. One observation is that fitness graphs provide information not contained in the geometric classification. We argue that a qualitative perspective may help relating theory of fitness landscapes and empirical observations. PMID:23036916

An extended global Earth system data record on daily landscape freeze-thaw status determined from satellite passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Kim, Youngwook; Kimball, John S.; Glassy, Joseph; Du, Jinyang

2017-02-01

The landscape freeze-thaw (FT) signal determined from satellite microwave brightness temperature (Tb) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz Tb retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25 km grid cell resolution. The resulting FT Earth system data record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period (1979-2014) than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow- and ice-dominant and barren land, which were not represented by prior FT-ESDR versions. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily Tb variations in relation to grid-cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows respective mean annual spatial classification accuracies of 90.3 and 84.3 % for evening (PM) and morning (AM) overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing the effects of sub-grid-scale open water and terrain heterogeneity, as well as algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow- and ice-dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts, and climate anomalies from longer-term trends extending over multiple decades. The dataset is freely available online (doi:10.5067/MEASURES/CRYOSPHERE/nsidc-0477.003).

Patterns among the ashes: Exploring the relationship between landscape pattern and the emerald ash borer

Treesearch

Susan J. Crocker; Dacia M. Meneguzzo; Greg C. Liknes

2010-01-01

Landscape metrics, including host abundance and population density, were calculated using forest inventory and land cover data to assess the relationship between landscape pattern and the presence or absence of the emerald ash borer (EAB) (Agrilus planipennis Fairmaire). The Random Forests classification algorithm in the R statistical environment was...

Loss surface of XOR artificial neural networks

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; Zhao, Xiaojun; Bernal, Edgar A.; Wales, David J.

2018-05-01

Training an artificial neural network involves an optimization process over the landscape defined by the cost (loss) as a function of the network parameters. We explore these landscapes using optimization tools developed for potential energy landscapes in molecular science. The number of local minima and transition states (saddle points of index one), as well as the ratio of transition states to minima, grow rapidly with the number of nodes in the network. There is also a strong dependence on the regularization parameter, with the landscape becoming more convex (fewer minima) as the regularization term increases. We demonstrate that in our formulation, stationary points for networks with Nh hidden nodes, including the minimal network required to fit the XOR data, are also stationary points for networks with Nh+1 hidden nodes when all the weights involving the additional node are zero. Hence, smaller networks trained on XOR data are embedded in the landscapes of larger networks. Our results clarify certain aspects of the classification and sensitivity (to perturbations in the input data) of minima and saddle points for this system, and may provide insight into dropout and network compression.

Multiple-factor classification of a human-modified forest landscape in the Hsuehshan Mountain Range, Taiwan.

PubMed

Berg, Kevan J; Icyeh, Lahuy; Lin, Yih-Ren; Janz, Arnold; Newmaster, Steven G

2016-12-01

Human actions drive landscape heterogeneity, yet most ecosystem classifications omit the role of human influence. This study explores land use history to inform a classification of forestland of the Tayal Mrqwang indigenous people of Taiwan. Our objectives were to determine the extent to which human action drives landscape heterogeneity. We used interviews, field sampling, and multivariate analysis to relate vegetation patterns to environmental gradients and human modification across 76 sites. We identified eleven forest classes. In total, around 70 % of plots were at lower elevations and had a history of shifting cultivation, terrace farming, and settlement that resulted in alder, laurel, oak, pine, and bamboo stands. Higher elevation mixed conifer forests were least disturbed. Arboriculture and selective harvesting were drivers of other conspicuous forest patterns. The findings show that past land uses play a key role in shaping forests, which is important to consider when setting targets to guide forest management.

Identifying small depressional wetlands and using a topographic position index to infer hydroperiod regimes for pond-breeding amphibians

USGS Publications Warehouse

Riley, Jeffrey W.; Calhoun, Daniel L.; Barichivich, William J.; Walls, Susan C.

2017-01-01

Small, seasonal pools and temporary ponds (<4.0 ha) are the most numerous and biologically diverse wetlands in many natural landscapes. Thus, accurate determination of their numbers and spatial characteristics is beneficial for conservation and management of biodiversity associated with these freshwater systems. We examined the utility of a topographic position index (TPI) landscape classification to identify and classify depressional wetlands. We also assessed relationships between topographic characteristics and ponded duration of known wetlands to allow hydrological characteristics to be extended to non-monitored locations in similar landscapes. Our results indicate that this approach was successful at identifying wetlands, but did have higher errors of commission (10%) than omission (5%). Additionally, the TPI procedure provided a reasonable means to correlate general ponded duration characteristics (long/short) with wetland topography. Although results varied by hydrologic class, permanent/long ponded duration wetlands were more often classified correctly (80%) than were short ponded duration wetlands (67%). However, classification results were improved to 100 and 75% for permanent/long and short ponded duration wetlands, respectively, by removing wetlands occurring on an abrupt marine terrace that erroneously inflated pond topographic characteristics. Our study presents an approach for evaluating wetland suitability for species or guilds that are associated with key habitat characteristics, such as hydroperiod.

Preliminary Assessment of JERS-1 SAR to Discriminating Boreal Landscape Features for the Boreal Forest Mapping Project

NASA Technical Reports Server (NTRS)

McDonald, Kyle; Williams, Cynthia; Podest, Erika; Chapman, Bruce

1999-01-01

This paper presents an overview of the JERS-1 North American Boreal Forest Mapping Project and a preliminary assessment of JERS-1 SAR imagery for application to discriminating features applicable to boreal landscape processes. The present focus of the JERS-1 North American Boreal Forest Mapping Project is the production of continental scale wintertime and summertime SAR mosaics of the North American boreal forest for distribution to the science community. As part of this effort, JERS-1 imagery has been collected over much of Alaska and Canada during the 1997-98 winter and 1998 summer seasons. To complete the mosaics, these data will be augmented with data collected during previous years. These data will be made available to the scientific community via CD ROM containing these and similar data sets compiled from companion studies of Asia and Europe. Regional landscape classification with SAR is important for the baseline information it will provide about distribution of woodlands, positions of treeline, current forest biomass, distribution of wetlands, and extent of major rivercourses. As well as setting the stage for longer term change detection, comparisons across several years provides additional baseline information about short-term landscape change. Rapid changes, including those driven by fire, permafrost heat balance, flooding, and insect outbreaks can dominate boreal systems. We examine JERS-1 imagery covering selected sites in Alaska and Canada to assess quality and applicability to such relevant ecological and hydrological issues. The data are generally of high quality and illustrate many potential applications. A texture-based classification scheme is applied to selected regions to assess the applicability of these data for distinguishing distribution of such landcover types as wetland, tundra, woodland and forested landscapes.

Completing the land resource hierarchy

USDA-ARS?s Scientific Manuscript database

The Land Resource Hierarchy of the NRCS is a hierarchal landscape classification consisting of resource areas which represent both conceptual and spatially discrete landscape units stratifying agency programs and practices. The Land Resource Hierarchy (LRH) scales from discrete points (soil pedon an...

Landscape variation in species diversity and succession as related to topography, soils and human disturbance

Treesearch

Jeffery N. Pearcy; David M. Hix; Stacy A. Drury

1995-01-01

Three hundred and thirty-two plots have been sampled on the Wayne National Forest of southeastern Ohio, for the purpose of developing an ecological classification system (ECS). The ECS will be based on the herbaceous and woody vegetation, soils and topography of mature (80-140 year-old), relatively-undisturbed forests. Species diversity changes little across this...

Analyzing risks to protected areas using the human modification framework: a Colorado case study

Treesearch

David M. Theobald; Alisa Wade; Grant Wilcox; Nate Peterson

2010-01-01

A framework that organizes natural and protected areas is often used to help understand the potential risks to natural areas and aspects of their ecological and human dimensions. The spatial (or landscape) context of these dynamics is also a critical, but, rarely considered, factor. Common classification systems include the U.S. Geological (USGS) Gap Analysis Program...

Dynamic stratification of the landscape of Mexico: analysis of vegetation patterns observed with multitemporal remotely sensed images

Treesearch

Franz Mora; Louis R. Iverson; Louis R. Iverson

1997-01-01

Rapid deforestation in Mexico, when coupled with poor access to current and consistent ecological information across the country underscores the need for an ecological classification system that can be readily updated as new data become available. In this study, regional vegetation resources in Mexico were evaluated using remotely sensed information. Multitemporal...

Ecological Design of Fernery based on Bioregion Classification System in Ecopark Cibinong Science Center Botanic Gardens, Indonesia

NASA Astrophysics Data System (ADS)

Nafar, S.; Gunawan, A.

2017-10-01

Indonesia as mega biodiversity country has a wide variety of ferns. However, the natural habitats of ferns are currently degrading, particularly in lowlands due to the increasing level of urban-sprawl and industrial zones development. Therefore, Ecology Park (Ecopark) Cibinong Science Center-Botanic Gardens as an ex-situ conservation area is expected to be the best location to conserve the lowland ferns. The purpose of this study is to design a fernery through an ecological landscape design process. The main concept is The Journey of Fern, this concept aiming on providing users experiences in fernery by associating conservational, educational, and recreational aspects. Ecological landscape design as general is applied by the principal of reduce, reuse, and recycle (3R). Bioregion classification system is applied by grouping the plants based on the characteristics of light, water, soil, air, and temperature. The design concept is inspired by the morphology of fern and its growth patterns which is transformed into organic and geometric forms. The result of this study is a design of fernery which consist of welcome area, recreation area, service area, and conservation education area as the main area that providing 66 species of ferns.

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.

[Changes of wetland landscape pattern in Dayang River Estuary based on high-resolution remote sensing image].

PubMed

Wu, Tao; Zhao, Dong-zhi; Zhang, Feng-shou; Wei, Bao-quan

2011-07-01

Based on the comprehensive consideration of the high resolution characteristics of remote sensing data and the current situation of land cover and land use in Dayang River Estuary wetland, a classification system with different resolutions of wetland landscape in the Estuary was established. The landscape pattern indices and landscape transition matrix were calculated by using the high resolution remote sensing data, and the dynamic changes of the landscape pattern from 1984 to 2008 were analyzed. In the study period, the wetland landscape components changed drastically. Wetland landscape transferred from natural wetland into artificial wetland, and wetland core regional area decreased. Natural wetland's largest patch area index descended, and the fragmentation degree ascended; while artificial wetland area expanded, its patch number decreased, polymerization degree increased, and the maximum patch area index had an obvious increasing trend. Increasing human activities, embankment construction, and reclamation for aquaculture were the main causes for the decrease of wetland area and the degradation of the ecological functions of Dayang River Estuary. To constitute long-term scientific and reasonable development plan, establish wetland nature reserves, protect riverway, draft strict inspective regimes for aquaculture reclamation, and energetically develop resource-based tourism industry would be the main strategies for the protection of the estuarine wetland.

The fragmented nature of tundra landscape

NASA Astrophysics Data System (ADS)

Virtanen, Tarmo; Ek, Malin

2014-04-01

The vegetation and land cover structure of tundra areas is fragmented when compared to other biomes. Thus, satellite images of high resolution are required for producing land cover classifications, in order to reveal the actual distribution of land cover types across these large and remote areas. We produced and compared different land cover classifications using three satellite images (QuickBird, Aster and Landsat TM5) with different pixel sizes (2.4 m, 15 m and 30 m pixel size, respectively). The study area, in north-eastern European Russia, was visited in July 2007 to obtain ground reference data. The QuickBird image was classified using supervised segmentation techniques, while the Aster and Landsat TM5 images were classified using a pixel-based supervised classification method. The QuickBird classification showed the highest accuracy when tested against field data, while the Aster image was generally more problematic to classify than the Landsat TM5 image. Use of smaller pixel sized images distinguished much greater levels of landscape fragmentation. The overall mean patch sizes in the QuickBird, Aster, and Landsat TM5-classifications were 871 m2, 2141 m2 and 7433 m2, respectively. In the QuickBird classification, the mean patch size of all the tundra and peatland vegetation classes was smaller than one pixel of the Landsat TM5 image. Water bodies and fens in particular occur in the landscape in small or elongated patches, and thus cannot be realistically classified from larger pixel sized images. Land cover patterns vary considerably at such a fine-scale, so that a lot of information is lost if only medium resolution satellite images are used. It is crucial to know the amount and spatial distribution of different vegetation types in arctic landscapes, as carbon dynamics and other climate related physical, geological and biological processes are known to vary greatly between vegetation types.

Remotely-Sensed Urban Wet-Landscapes AN Indicator of Coupled Effects of Human Impact and Climate Change

NASA Astrophysics Data System (ADS)

Ji, Wei

2016-06-01

This study proposes the concept of urban wet-landscapes (loosely-defined wetlands) as against dry-landscapes (mainly impervious surfaces). The study is to examine whether the dynamics of urban wet-landscapes is a sensitive indicator of the coupled effects of the two major driving forces of urban landscape change - human built-up impact and climate (precipitation) variation. Using a series of satellite images, the study was conducted in the Kansas City metropolitan area of the United States. A rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. The spatial analyses of wetland changes were implemented at the scales of metropolitan, watershed, and sub-watershed as well as based on the size of surface water bodies in order to reveal urban wetland change trends in relation to the driving forces. The study identified that wet-landscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while smaller wetlands decreased mainly due to human development activities. These findings suggest that wet-landscapes, as against the dry-landscapes, can be a more effective indicator of the coupled effects of human impact and climate change.

BATS AND BT INSECT RESISTANCE ON AGRICULTURAL LANDSCAPES

EPA Science Inventory

A landscape model that utilizes land cover classification data, insect life history, insect movement, and bat foraging pressure is developed that addresses the implementation of genetically modified crops in the Winter Garden region of Texas. The principal strategy for delaying r...

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, A.B.; McMahon, G.

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States - higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Spatial analysis of instream nitrogen loads and factors controlling nitrogen delivery to streams in the southeastern United States using spatially referenced regression on watershed attributes (SPARROW) and regional classification frameworks

USGS Publications Warehouse

Hoos, Anne B.; McMahon, Gerard

2009-01-01

Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States—higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.

Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

EPA Science Inventory

Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

RS- and GIS-based study on landscape pattern change in the Poyang Lake wetland area, China

NASA Astrophysics Data System (ADS)

Chen, Xiaoling; Li, Hui; Bao, Shuming; Wu, Zhongyi; Fu, Weijuan; Cai, Xiaobin; Zhao, Hongmei; Guo, Peng

2006-10-01

As wetland has been recognized as an important component of ecosystem, it is received ever-increasing attention worldwide. Poyang Lake wetlands, the international wetlands and the largest bird habitat in Asia, play an important role in biodiversity and ecologic protection. However, with the rapid economic growth and urbanization, landscape patterns in the wetlands have dramatically changed in the past three decades. To better understand the wetland landscape dynamics, remote sensing, geographic information system technologies, and the FRAGSTATS landscape analysis program were used to measure landscape patterns. Statistical approach was employed to illustrate the driving forces. In this study, Landsat images (TM and ETM+) from 1989 and 2000 were acquired for the wetland area. The landscapes in the wetland area were classified as agricultural land, urban, wetland, forest, grassland, unused land, and water body using a combination of supervised and unsupervised classification techniques integrated with Digital Elevation Model (DEM). Landscape indices, which are popular for the quantitative analysis of landscape pattern, were then employed to analyze the landscape pattern changes between the two dates in a GIS. From this analysis an understanding of the spatial-temporal patterns of landscape evolution was generated. The results show that wetland area was reduced while fragmentation was increased over the study period. Further investigation was made to examine the relationship between landscape metrics and some other parameters such as urbanization to address the driving forces for those changes. The urban was chosen as center to conduct buffer analysis in a GIS to study the impact of human-induced activities on landscape pattern dynamics. It was found that the selected parameters were significantly correlated with the landscape metrics, which may well indicate the impact of human-induced activities on the wetland landscape pattern dynamics and account for the driving forces.

Landscape ecological security assessment based on projection pursuit in Pearl River Delta.

PubMed

Gao, Yang; Wu, Zhifeng; Lou, Quansheng; Huang, Huamei; Cheng, Jiong; Chen, Zhangli

2012-04-01

Regional landscape ecological security is an important issue for ecological security, and has a great influence on national security and social sustainable development. The Pearl River Delta (PRD) in southern China has experienced rapid economic development and intensive human activities in recent years. This study, based on landscape analysis, provides a method to discover the alteration of character among different landscape types and to understand the landscape ecological security status. Based on remotely sensed products of the Landsat 5 TM images in 1990 and the Landsat 7 ETM+ images in 2005, landscape classification maps of nine cities in the PRD were compiled by implementing Remote Sensing and Geographic Information System technology. Several indices, including aggregation, crush index, landscape shape index, Shannon's diversity index, landscape fragile index, and landscape security adjacent index, were applied to analyze spatial-temporal characteristics of landscape patterns in the PRD. A landscape ecological security index based on these outcomes was calculated by projection pursuit using genetic algorithm. The landscape ecological security of nine cities in the PRD was thus evaluated. The main results of this research are listed as follows: (1) from 1990 to 2005, the aggregation index, crush index, landscape shape index, and Shannon's diversity index of nine cities changed little in the PRD, while the landscape fragile index and landscape security adjacent index changed obviously. The landscape fragile index of nine cities showed a decreasing trend; however, the landscape security adjacent index has been increasing; (2) from 1990 to 2005, landscape ecology of the cities of Zhuhai and Huizhou maintained a good security situation. However, there was a relatively low value of ecological security in the cities of Dongguan and Foshan. Except for Foshan and Guangzhou, whose landscape ecological security situation were slightly improved, the cities had reduced values in landscape ecological security, with the most decreased number 0.52 in Zhaoqing. Results of this study offer important information for regional eco-construction and natural resource exploitation.

First steps towards a novel European forest fuel classification systems and a European forest fuel map

NASA Astrophysics Data System (ADS)

Sebastián-López, Ana; Urbieta, Itziar R.; de La Fuente Blanco, David; García Mateo, Rubén.; Moreno Rodríguez, José Manuel; Eftichidis, George; Varela, Vassiliki; Cesari, Véronique; Mário Ribeiro, Luís.; Viegas, Domingos Xavier; Lanorte, Antonio; Lasaponara, Rosa; Camia, Andrea; San Miguel, Jesús

2010-05-01

Forest fires burn at the local scale, but their massive occurrence causes effects which have global dimensions. Furthermore climate change projections associate global warming to a significant increase in forest fire activity. Warmer and drier conditions are expected to increase the frequency, duration and intensity of fires, and greater amounts of fuel associated with forest areas in decline may cause more frequent and larger fires. These facts create the need for establishing strategies for harmonizing fire danger rating, fire risk assessment, and fire prevention policies at a supranational level. Albeit forest fires are a permanent threat for European ecosystems, particularly in the south, there is no commonly accepted fuel classification scheme adopted for operational use by the Member States of the EU. The European Commission (EC) DG Environment and JRC have launched a set of studies following a resolution of the European Parliament on the further development and enhancement of the European Forest Fire Information System (EFFIS), the EC focal point for information on forest fires in Europe. One of the studies that are being funded is the FUELMAP project. The objective of FUELMAP is to develop a novel fuel classification system and a new European fuel map that will be based on a comprehensive classification of fuel complexes representing the various vegetation types across EU27, plus Switzerland, Croatia and Turkey. The overall work plan is grounded on a throughout knowledge of European forest landscapes and the key features of fuel situations occurring in natural areas. The method makes extended use of existing databases available in the Member States and European Institutions. Specifically, our proposed classification combines relevant information on ecoregions, land cover and uses, potential and actual vegetation, and stand structure. GIS techniques are used in order to define the geographic extent of the classification units and for identifying the main driving factors that determine the spatial distribution of the resulting fuel complexes. Furthermore, relevant parameters influencing fire potential and effects such as fuel load, live/dead ratio, and fuels' size classes' distribution are considered. National- and local-scale datasets (vegetation maps, forest inventory plots, fuel maps...) will be also studied and compared. Local ground- truth data will be used to assess the accuracy of the classification and will contribute, along with literature values and experts' opinion, to characterize the fuels' physical properties. The resulting classification aims to support the characterization of the fire potential, serve as input in fire emissions models, and be used to assess the expected impact of fire in the European landscapes. The work plan includes the development of a GIS software tool to automatically update the fuel map from modified (up-to-date) input data layers. The fuel map of Europe is mainly intended to support the implementation of the EFFIS modules that can be enhanced by the use of improved information on forest fuel properties and spatial distribution, though it is also envisaged that the results of the project might be useful for other relevant applications at different spatial scales. To this purpose, the classification will be designed with a hierarchical and flexible structure for describing heterogeneous landscapes. The work is on-going and this presentation shows the first results towards the envisaged European fuel map.

Verification of Hydrologic Landscape Derived Basin-Scale Classifications in the Pacific Northwest

EPA Science Inventory

The interaction between the physical properties of a catchment (form) and climatic forcing of precipitation and energy control how water is partitioned, stored, and conveyed through a catchment (function). Hydrologic Landscapes (HLs) were previously developed across Oregon and de...

Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA.

PubMed

Veselka, Walter; Rentch, James S; Grafton, William N; Kordek, Walter S; Anderson, James T

2010-11-01

Bioassessment methods for wetlands, and other bodies of water, have been developed worldwide to measure and quantify changes in "biological integrity." These assessments are based on a classification system, meant to ensure appropriate comparisons between wetland types. Using a local site-specific disturbance gradient, we built vegetation indices of biological integrity (Veg-IBIs) based on two commonly used wetland classification systems in the USA: One based on vegetative structure and the other based on a wetland's position in a landscape and sources of water. The resulting class-specific Veg-IBIs were comprised of 1-5 metrics that varied in their sensitivity to the disturbance gradient (R2=0.14-0.65). Moreover, the sensitivity to the disturbance gradient increased as metrics from each of the two classification schemes were combined (added). Using this information to monitor natural and created wetlands will help natural resource managers track changes in biological integrity of wetlands in response to anthropogenic disturbance and allows the use of vegetative communities to set ecological performance standards for mitigation banks.

Hydrological resiliency in the Western Boreal Plains: classification of hydrological responses using wavelet analysis to assess landscape resilience

NASA Astrophysics Data System (ADS)

Probert, Samantha; Kettridge, Nicholas; Devito, Kevin; Hannah, David; Parkin, Geoff

2017-04-01

The Boreal represents a system of substantial resilience to climate change, with minimal ecological change over the past 6000 years. However, unprecedented climatic warming, coupled with catchment disturbances could exceed thresholds of hydrological function in the Western Boreal Plains. Knowledge of ecohydrological and climatic feedbacks that shape the resilience of boreal forests has advanced significantly in recent years, but this knowledge is yet to be applied and understood at landscape scales. Hydrological modelling at the landscape scale is challenging in the WBP due to diverse, non-topographically driven hydrology across the mosaic of terrestrial and aquatic ecosystems. This study functionally divides the geologic and ecological components of the landscape into Hydrologic Response Areas (HRAs) and wetland, forestland, interface and pond Hydrologic Units (HUs) to accurately characterise water storage and infer transmission at multiple spatial and temporal scales. Wavelet analysis is applied to pond and groundwater levels to describe the patterns of water storage in response to climate signals; to isolate dominant controls on hydrological responses and to assess the relative importance of physical controls between wet and dry climates. This identifies which components of the landscape exhibit greater magnitude and frequency of variability to wetting and drying trends, further to testing the hierarchical framework for hydrological storage controls of: climate, bedrock geology, surficial geology, soil, vegetation, and topography. Classifying HRA and HU hydrological function is essential to understand and predict water storage and redistribution through drought cycles and wet periods. This work recognises which landscape components are most sensitive under climate change and disturbance and also creates scope for hydrological resiliency research in Boreal systems by recognising critical landscape components and their role in landscape collapse or catastrophic shift in ecosystem function under future climatic scenarios.

Radiation Induced Vaccination to Breast Cancer

DTIC Science & Technology

2016-12-01

in supporting a memory CD8 T cell response and decreased MDSCs but in reality the small patient numbers and the relatively short survival times...ABSTRACT Inhibiting TGFβ in the context of focal irradiation seems to create a favorable systemic immune landscape that drives T cell memory ...differentiation while limiting myeloid suppression. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES

RESEARCH AREA 7.1: Exploring the Systematics of Controlling Quantum Phenomena

DTIC Science & Technology

2016-10-05

the bottom to the top of the landscape. Computational analyses for simple model quantum systems are performed to ascertain the relative abundance of...SECURITY CLASSIFICATION OF: This research is concerned with the theoretical and experimental control quantum dynamics phenomena. Advances include new...algorithms to accelerate quantum control as well as provide physical insights into the controlled dynamics. The latter research includes the

Integration of Landscape Ecosystem Classification and Historic Land Records in the Francis Marion National Forest

Treesearch

Peter U. Kennedy; Victor B. Shelburne

2002-01-01

Geographic Information Systems (GIS) data and historical plats ranging from 1716 to 1894 in the Coastal Flatwoods Region of South Carolina were used to quantify changes on a temporal scale. Combining the historic plats and associated witness trees (trees marking the boundaries of historic plats) with an existing database of the soils and other attributes was the basis...

Applicability of Hydrologic Landscapes for Model Calibration at the Watershed Scale in the Pacific Northwest

EPA Science Inventory

The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of tec...

Linking fecal bacteria in rivers to landscape, geochemical, and hydrologic factors and sources at the basin scale

PubMed Central

Verhougstraete, Marc P.; Martin, Sherry L.; Kendall, Anthony D.; Hyndman, David W.; Rose, Joan B.

2015-01-01

Linking fecal indicator bacteria concentrations in large mixed-use watersheds back to diffuse human sources, such as septic systems, has met limited success. In this study, 64 rivers that drain 84% of Michigan’s Lower Peninsula were sampled under baseflow conditions for Escherichia coli, Bacteroides thetaiotaomicron (a human source-tracking marker), landscape characteristics, and geochemical and hydrologic variables. E. coli and B. thetaiotaomicron were routinely detected in sampled rivers and an E. coli reference level was defined (1.4 log10 most probable number⋅100 mL−1). Using classification and regression tree analysis and demographic estimates of wastewater treatments per watershed, septic systems seem to be the primary driver of fecal bacteria levels. In particular, watersheds with more than 1,621 septic systems exhibited significantly higher concentrations of B. thetaiotaomicron. This information is vital for evaluating water quality and health implications, determining the impacts of septic systems on watersheds, and improving management decisions for locating, constructing, and maintaining on-site wastewater treatment systems. PMID:26240328

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.

Columbia River Estuary ecosystem classification—Concept and application

USGS Publications Warehouse

Simenstad, Charles A.; Burke, Jennifer L.; O'Connor, Jim E.; Cannon, Charles; Heatwole, Danelle W.; Ramirez, Mary F.; Waite, Ian R.; Counihan, Timothy D.; Jones, Krista L.

2011-01-01

This document describes the concept, organization, and application of a hierarchical ecosystem classification that integrates saline and tidal freshwater reaches of estuaries in order to characterize the ecosystems of large flood plain rivers that are strongly influenced by riverine and estuarine hydrology. We illustrate the classification by applying it to the Columbia River estuary (Oregon-Washington, USA), a system that extends about 233 river kilometers (rkm) inland from the Pacific Ocean. More than three-quarters of this length is tidal freshwater. The Columbia River Estuary Ecosystem Classification ("Classification") is based on six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. We define and map Levels 1-3 for the entire Columbia River estuary with existing geospatial datasets, and provide examples of Levels 4-6 for one hydrogeomorphic reach. In particular, three levels of the Classification capture the scales and categories of ecosystem structure and processes that are most tractable to estuarine research, monitoring, and management. These three levels are the (1) eight hydrogeomorphic reaches that embody the formative geologic and tectonic processes that created the existing estuarine landscape and encompass the influence of the resulting physiography on interactions between fluvial and tidal hydrology and geomorphology across 230 kilometers (km) of estuary, (2) more than 15 ecosystem complexes composed of broad landforms created predominantly by geologic processes during the Holocene, and (3) more than 25 geomorphic catenae embedded within ecosystem complexes that represent distinct geomorphic landforms, structures, ecosystems, and habitats, and components of the estuarine landscape most likely to change over short time periods.

On the Usefulness of Hydrologic Landscapes for Hydrologic Modeling and Water Management

EPA Science Inventory

Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

On the Usefulness of Hydrologic Landscapes on Hydrologic Model calibration and Selection

EPA Science Inventory

Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

Using hydrologic landscape classification to assess streamflow vulnerability to changes in climate

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

An assessment of streamflow vulnerability to climate using Hydrologic Landscape classification

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management.

PubMed

Williams, Bradley S; D'Amico, Ellen; Kastens, Jude H; Thorp, James H; Flotemersch, Joseph E; Thoms, Martin C

2013-09-01

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.

Assessing the habitat suitability of agricultural landscapes for characteristic breeding bird guilds using landscape metrics.

PubMed

Borges, Friederike; Glemnitz, Michael; Schultz, Alfred; Stachow, Ulrich

2017-04-01

Many of the processes behind the decline of farmland birds can be related to modifications in landscape structure (composition and configuration), which can partly be expressed quantitatively with measurable or computable indices, i.e. landscape metrics. This paper aims to identify statistical relationships between the occurrence of birds and the landscape structure. We present a method that combines two comprehensive procedures: the "landscape-centred approach" and "guild classification". Our study is based on more than 20,000 individual bird observations based on a 4-year bird monitoring approach in a typical agricultural area in the north-eastern German lowlands. Five characteristic bird guilds, each with three characteristic species, are defined for the typical habitat types of that area: farmland, grassland, hedgerow, forest and settlement. The suitability of each sample plot for each guild is indicated by the level of persistence (LOP) of occurrence of three respective species. Thus, the sample plots can be classified as "preferred" or "less preferred" depending on the lower and upper quartiles of the LOP values. The landscape structure is characterized by 16 different landscape metrics expressing various aspects of landscape composition and configuration. For each guild, the three landscape metrics with the strongest rank correlation with the LOP values and that are not mutually dependent were identified. For four of the bird guilds, the classification success was better than 80%, compared with only 66% for the grassland bird guild. A subset of six landscape metrics proved to be the most meaningful and sufficiently classified the sample areas with respect to bird guild suitability. In addition, derived logistic functions allowed the production of guild-specific habitat suitability maps for the whole landscape. The analytical results show that the proposed approach is appropriate to assess the habitat suitability of agricultural landscapes for characteristic bird guilds.

Exploring indigenous landscape classification across different dimensions: a case study from the Bolivian Amazon.

PubMed

Riu-Bosoms, Carles; Vidal-Amat, Teresa; Duane, Andrea; Fernandez-Llamazares, Alvaro; Guèze, Maximilien; Luz, Ana C; Macía, Manuel J; Paneque-Gálvez, Jaime; Reyes-García, Victoria

Decisions on landscape management are often dictated by government officials based on their own understandings of how landscape should be used and managed, but rarely considering local peoples' understandings of the landscape they inhabit. We use data collected through free listings, field transects, and interviews to describe how an Amazonian group of hunter-horticulturalists, the Tsimane', classify and perceive the importance of different elements of the landscape across the ecological, socioeconomic, and spiritual dimensions. The Tsimane' recognize nine folk ecotopes (i.e., culturally-recognized landscape units) and use a variety of criteria (including geomorphological features and landscape uses) to differentiate ecotopes from one another. The Tsimane' rank different folk ecotopes in accordance with their perceived ecological, socioeconomic, and spiritual importance. Understanding how local people perceive their landscape contributes towards a landscape management planning paradigm that acknowledges the continuing contributions to management of landscape inhabitants, as well as their cultural and land use rights.

An analysis of historic and projected climate scenarios in the Western United States using hydrologic landscape classification.

EPA Science Inventory

: Identifying areas of similar hydrology within the United States and its regions (hydrologic landscapes - HLs) is an active area of research. HLs are being used to construct spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, a...

An analysis of historic and projected climate scenarios in the Western united States using hydrologic landscape classification

EPA Science Inventory

Identifying areas of similar hydrology within the United States and its regions (Hydrologic landscapes - HLs) is an active area of research. HLs have been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the ...

Using Hydrologic Landscape Classification to Evaluate the Hydrologic Effects of Climate in the Southwestern United States

EPA Science Inventory

Hydrologic landscapes (HLs) have been an active area of research at regional and national scales in the United States. The concept has been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the Pacific Northwe...

Industrial Landscapes: Perception and Classification as Learning Activities

ERIC Educational Resources Information Center

Peters, Gary; Larkin, Robert P.

1977-01-01

Suggests a high school or college level program of subjective perception and evaluation of industrial landscapes. Slides of local or national industrial sites can be rated and classified as pleasing or unpleasing in terms of variables such as architectural style of building, smokestacks, age, and visible pollution. (AV)

Gradient modeling of conifer species using random forests

Treesearch

Jeffrey S. Evans; Samuel A. Cushman

2009-01-01

Landscape ecology often adopts a patch mosaic model of ecological patterns. However, many ecological attributes are inherently continuous and classification of species composition into vegetation communities and discrete patches provides an overly simplistic view of the landscape. If one adopts a nichebased, individualistic concept of biotic communities then it may...

Seri Landscape Classification and Spatial Reference

ERIC Educational Resources Information Center

O'Meara, Carolyn

2010-01-01

This thesis contributes to the growing field of ethnophysiography, a new subfield of cognitive anthropology that aims to determine the universals and variation in the categorization of landscape objects across cultures. More specifically, this work looks at the case of the Seri people of Sonora, Mexico to investigate the way they categorize…

Regional landscape ecosystems of Michigan, Minnesota and Wisconsin: a working map and classification.

Treesearch

Dennis A. Albert

1995-01-01

Describes the landscape ecosystems (ecoregions) of Michigan, Minnesota, and Wisconsin and includes maps of all three states. Regional descriptions include climate, bedrock geology, landforms, lakes and streams, soils, presettlement vegetation, natural disturbance, present vegetation and land use, rare biota, natural areas, public land managers, and conservation...

Assessing connectivity in salmonid fishes with DNA microsatellite markers

Treesearch

Helen Neville; Jason Dunham; Mary Peacock

2006-01-01

Connectivity is a key consideration for the management and conservation of any species, but empirical characterizations of connectivity can be extremely challenging. Assessments of connectivity require biologically realistic classifications of landscape structure (Kotliar and Wiens 1990), and an understanding of how landscape structure affects migration, dispersal, and...

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Echols, D.; Sapkota, S.K.

2002-01-01

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LM-NRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments.

PubMed

Ramsey, Elijah W; Nelson, Gene A; Echols, Darrell; Sapkota, Sijan K

2002-05-01

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LMNRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

Use of Binary Partition Tree and energy minimization for object-based classification of urban land cover

NASA Astrophysics Data System (ADS)

Li, Mengmeng; Bijker, Wietske; Stein, Alfred

2015-04-01

Two main challenges are faced when classifying urban land cover from very high resolution satellite images: obtaining an optimal image segmentation and distinguishing buildings from other man-made objects. For optimal segmentation, this work proposes a hierarchical representation of an image by means of a Binary Partition Tree (BPT) and an unsupervised evaluation of image segmentations by energy minimization. For building extraction, we apply fuzzy sets to create a fuzzy landscape of shadows which in turn involves a two-step procedure. The first step is a preliminarily image classification at a fine segmentation level to generate vegetation and shadow information. The second step models the directional relationship between building and shadow objects to extract building information at the optimal segmentation level. We conducted the experiments on two datasets of Pléiades images from Wuhan City, China. To demonstrate its performance, the proposed classification is compared at the optimal segmentation level with Maximum Likelihood Classification and Support Vector Machine classification. The results show that the proposed classification produced the highest overall accuracies and kappa coefficients, and the smallest over-classification and under-classification geometric errors. We conclude first that integrating BPT with energy minimization offers an effective means for image segmentation. Second, we conclude that the directional relationship between building and shadow objects represented by a fuzzy landscape is important for building extraction.

IMPACTS OF PATCH SIZE AND LAND COVER HETEROGENEITY ON THEMATIC IMAGE CLASSIFICATION ACCURACY

EPA Science Inventory

Landscape characteristics such as small patch size and land cover heterogeneity have been hypothesized to increase the likelihood of miss-classifying pixels during thematic image classification. However, there has been a lack of empirical evidence to support these hypotheses,...

Neighbourhood-Scale Urban Forest Ecosystem Classification

Treesearch

James W.N. Steenberg; Andrew A. Millward; Peter N. Duinker; David J. Nowak; Pamela J. Robinson

2015-01-01

Urban forests are now recognized as essential components of sustainable cities, but there remains uncertainty concerning how to stratify and classify urban landscapes into units of ecological significance at spatial scales appropriate for management. Ecosystem classification is an approach that entails quantifying the social and ecological processes that shape...

Landscape habitats [Chapter 2

Treesearch

C. L. Simmons

1994-01-01

This landscape habitat description is based on a ground reconnaissance of the Lost Lake, West Glacier Lake, and East Glacier Lake portions of GLEES conducted during 10 days in July-September 1986 and on subsequent photo interpretation of 1:6000 scale color-infrared photographs. A ground check was conducted in July-August 1987. The classification used is a physiognomic...

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

EPA Science Inventory

Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

Appendix E: Research papers. Use of remote sensing in landscape stratification for environmental impact assessment

NASA Technical Reports Server (NTRS)

Stanturf, J. A.; Heimbuch, D. G.

1980-01-01

A refinement to the matrix approach to environmental impact assessment is to use landscape units in place of separate environmental elements in the analysis. Landscape units can be delineated by integrating remotely sensed data and available single-factor data. A remote sensing approach to landscape stratification is described and the conditions under which it is superior to other approaches that require single-factor maps are indicated. Flowcharts show the steps necessary to develop classification criteria, delineate units and a map legend, and use the landscape units in impact assessment. Application of the approach to assessing impacts of a transmission line in Montana is presented to illustrate the method.

Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities

USGS Publications Warehouse

McKenna, James E.; Schaeffer, Jeffrey S.; Stewart, Jana S.; Slattery, Michael T.

2015-01-01

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.

Water balances of two Piedmont headwater catchments: implications for regional hydrologic landscape classification

Treesearch

C. Dreps; G. Sun; J. Boggs

2014-01-01

In the Piedmont of North Carolina, a traditionally water-rich region, reservoirs that serve over 1 million people are under increasing pressure due to naturally occurring droughts and increasing land development. Innovative development approaches aim to maintain hydrologic conditions of the undisturbed landscape, but are based on insufficient target information. This...

Monitoring Wildlife Interactions with Their Environment: An Interdisciplinary Approach

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

Charles-Smith, Lauren E.; Domnguez, Ignacio X.; Fornaro, Robert J.

In a rapidly changing world, wildlife ecologists strive to correctly model and predict complex relationships between animals and their environment, which facilitates management decisions impacting public policy to conserve and protect delicate ecosystems. Recent advances in monitoring systems span scientific domains, including animal and weather monitoring devices and landscape classification mapping techniques. The current challenge is how to combine and use detailed output from various sources to address questions spanning multiple disciplines. WolfScout wildlife and weather tracking system is a software tool capable of filling this niche. WolfScout automates integration of the latest technological advances in wildlife GPS collars, weathermore » stations, drought conditions, and severe weather reports, and animal demographic information. The WolfScout database stores a variety of classified landscape maps including natural and manmade features. Additionally, WolfScout’s spatial database management system allows users to calculate distances between animals’ location and landscape characteristics, which are linked to the best approximation of environmental conditions at the animal’s location during the interaction. Through a secure website, data are exported in formats compatible with multiple software programs including R and ArcGIS. The WolfScout design promotes interoperability in data, between researchers, and software applications while standardizing analyses of animal interactions with their environment.« less

Equivalent Diagnostic Classification Models

ERIC Educational Resources Information Center

Maris, Gunter; Bechger, Timo

2009-01-01

Rupp and Templin (2008) do a good job at describing the ever expanding landscape of Diagnostic Classification Models (DCM). In many ways, their review article clearly points to some of the questions that need to be answered before DCMs can become part of the psychometric practitioners toolkit. Apart from the issues mentioned in this article that…

Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests

Treesearch

Brian J. Palik; Richard Buech; Leanne Egeland

2003-01-01

Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...

Using aerial images for establishing a workflow for the quantification of water management measures

NASA Astrophysics Data System (ADS)

Leuschner, Annette; Merz, Christoph; van Gasselt, Stephan; Steidl, Jörg

2017-04-01

Quantified landscape characteristics, such as morphology, land use or hydrological conditions, play an important role for hydrological investigations as landscape parameters directly control the overall water balance. A powerful assimilation and geospatial analysis of remote sensing datasets in combination with hydrological modeling allows to quantify landscape parameters and water balances efficiently. This study focuses on the development of a workflow to extract hydrologically relevant data from aerial image datasets and derived products in order to allow an effective parametrization of a hydrological model. Consistent and self-contained data source are indispensable for achieving reasonable modeling results. In order to minimize uncertainties and inconsistencies, input parameters for modeling should be extracted from one remote-sensing dataset mainly if possbile. Here, aerial images have been chosen because of their high spatial and spectral resolution that permits the extraction of various model relevant parameters, like morphology, land-use or artificial drainage-systems. The methodological repertoire to extract environmental parameters range from analyses of digital terrain models, multispectral classification and segmentation of land use distribution maps and mapping of artificial drainage-systems based on spectral and visual inspection. The workflow has been tested for a mesoscale catchment area which forms a characteristic hydrological system of a young moraine landscape located in the state of Brandenburg, Germany. These dataset were used as input-dataset for multi-temporal hydrological modelling of water balances to detect and quantify anthropogenic and meteorological impacts. ArcSWAT, as a GIS-implemented extension and graphical user input interface for the Soil Water Assessment Tool (SWAT) was chosen. The results of this modeling approach provide the basis for anticipating future development of the hydrological system, and regarding system changes for the adaption of water resource management decisions.

Pond Identification, Classification, and Inundation Dynamics at St. Marks National Wildlife Refuge in northwest Florida, USA

NASA Astrophysics Data System (ADS)

Riley, J. W.; Calhoun, D.; Barichivich, J.

2012-12-01

The persistence and resilience of amphibian communities is largely dependent on adequate breeding habitat. This is especially important for threatened and endangered species that may often exist as isolated populations and have specific requirements for breeding. A study currently being conducted by the U.S. Geological Survey is investigating the feasibility of a repatriation effort of the Striped Newt (Notophthalmus perstriatus), a federal candidate species, within the St. Marks National Wildlife Refuge (SMNWR) in northwest Florida. This amphibian species requires ponds that are free of fishes and, for this reason, generally chooses ephemeral ponds as breeding sites. The delineation of potential breeding habitat is a first step in selecting candidate areas for repatriation. To achieve this, a LIDAR (Light Detection and Ranging) derived digital elevation model (DEM) and a topographic position index (TPI) classification scheme was used to identify and classify isolated depressions across the landscape. The TPI evaluates the difference in elevation from a central DEM cell to the mean elevation of a neighborhood of surrounding DEM cells and is a robust tool for locating depressional features within a landscape. These candidate depression features were then screened to remove large perennial ponds and smaller connected ponds from further consideration. In addition, the perimeters of twenty-two field identified ephemeral ponds were surveyed with a high precision RTK GPS (Real Time Kinematic Global Positioning System) unit to provide a calibration dataset to evaluate the performance of the feature identification method. This set of ponds was also instrumented with water-level recorders to investigate inundation dynamics across a wide range of hydrologic conditions. We anticipate being able to classify pond hydroperiod—thus each pond's potential as breeding habitat—at the monitored locations through this combination of approaches. Using estimates of pond size, morphology, and landscape position derived from the DEM, the classifications will be extended to other ponds on the refuge.

Human preference for ecological units: patterns of dispersed campsites within landtype associations on the Chippewa National Forest

Treesearch

Lisa Whitcomb; Dennis Parker; Bob Carr; Paul Gobster; Herb Schroeder

2002-01-01

Forest Service landscape architects sought a method for determining if people showed a preference for certain landscape-scale ecosystems and if ecological classification units could be used in visual resource management. A study was conducted on the Chippewa National Forest to test whether there was a systematic relationship between dispersed campsite locations and...

Applicability of Hydrologic Landscapes for Model Calibration ...

EPA Pesticide Factsheets

The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of techniques were applied to the HL assessment unit composition in watersheds across the Pacific Northwest to aggregate the hydrologic behavior of the Hydrologic Landscapes from the assessment unit scale to the watershed scale. This non-trivial solution both emphasizes HL classifications within the watershed that provide that majority of moisture surplus/deficit and considers the relative position (upstream vs. downstream) of these HL classifications. A clustering algorithm was applied to the HL-based characterization of assessment units within 185 watersheds to help organize watersheds into nine classes hypothesized to have similar hydrologic behavior. The HL-based classes were used to organize and describe hydrologic behavior information about watershed classes and both predictions and validations were independently performed with regard to the general magnitude of six hydroclimatic signature values. A second cluster analysis was then performed using the independently calculated signature values as similarity metrics, and it was found that the six signature clusters showed substantial overlap in watershed class membership to those in the HL-based classes. One hypothesis set forward from thi

BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

NASA Technical Reports Server (NTRS)

Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

NASA Astrophysics Data System (ADS)

Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

2014-12-01

Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery. Caribbean Journal of Science. 44(2):175-198.

Treesearch

E.H. Helmer; T.A. Kennaway; D.H. Pedreros; M.L. Clark; H. Marcano-Vega; L.L. Tieszen; S.R. Schill; C.M.S. Carrington

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius...

[Landscape character assessment framework in rural area: A case study in Qiaokou, Chang-sha, China].

PubMed

Zhang, Qian; Liu, Wen-ping; Yu, Zhen-rong

2015-05-01

Based on the concept and methods of landscape character assessment (LCA) in England, this paper applied a complete process of landscape character assessment with a case study in Qiaokou Town, which is located in a typical southern paddy fields area in Changsha City. We drew the landscape character map of Qiaokou Town through desk classification and field survey, identified and compared the key characters of each character area, and proposed suggestions on the improvement and stewardship of landscape characters. The results showed that Qiaokou could be divided into 2 landscape character types and 7 landscape character areas with the main differences in cropland and vegetation pattern as well as aesthetic characters. The case study indicated that LCA could be a critical tool to identify the characteristics in rural area, and provide helpful guidance to protect, restore and maintain the unique culture and characters of rural landscape, which is useful for targeted rural landscape development. In the future, we suggested that the assessment on the effects of landscape construction measures on the ecosystem services should be incorporated in LCA research as well.

Repetitive element signature-based visualization, distance computation, and classification of 1766 microbial genomes.

PubMed

Lee, Kang-Hoon; Shin, Kyung-Seop; Lim, Debora; Kim, Woo-Chan; Chung, Byung Chang; Han, Gyu-Bum; Roh, Jeongkyu; Cho, Dong-Ho; Cho, Kiho

2015-07-01

The genomes of living organisms are populated with pleomorphic repetitive elements (REs) of varying densities. Our hypothesis that genomic RE landscapes are species/strain/individual-specific was implemented into the Genome Signature Imaging system to visualize and compute the RE-based signatures of any genome. Following the occurrence profiling of 5-nucleotide REs/words, the information from top-50 frequency words was transformed into a genome-specific signature and visualized as Genome Signature Images (GSIs), using a CMYK scheme. An algorithm for computing distances among GSIs was formulated using the GSIs' variables (word identity, frequency, and frequency order). The utility of the GSI-distance computation system was demonstrated with control genomes. GSI-based computation of genome-relatedness among 1766 microbes (117 archaea and 1649 bacteria) identified their clustering patterns; although the majority paralleled the established classification, some did not. The Genome Signature Imaging system, with its visualization and distance computation functions, enables genome-scale evolutionary studies involving numerous genomes with varying sizes. Copyright © 2015 Elsevier Inc. All rights reserved.

Natural Resources Inventory and Land Evaluation in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. A system was developed to operationally map and measure the areal extent of various land use categories for updating existing and producing new and actual thematic maps showing the latest state of rural and urban landscapes and its changes. The processing system includes: (1) preprocessing steps for radiometric and geometric corrections; (2) classification of the data by a multivariate procedure, using a stepwise linear discriminant analysis based on carefully selected training cells; and (3) output in form of color maps by printing black and white theme overlays of a selected scale with photomation system and its coloring and combination into a color composite.

Forest land cover change (1975-2000) in the Greater Border Lakes region

Treesearch

Peter T. Wolter; Brian R. Sturtevant; Brian R. Miranda; Sue M. Lietz; Phillip A. Townsend; John Pastor

2012-01-01

This document and accompanying maps describe land cover classifications and change detection for a 13.8 million ha landscape straddling the border between Minnesota, and Ontario, Canada (greater Border Lakes Region). Land cover classifications focus on discerning Anderson Level II forest and nonforest cover to track spatiotemporal changes in forest cover. Multi-...

Evaluating the statistical performance of less applied algorithms in classification of worldview-3 imagery data in an urbanized landscape

NASA Astrophysics Data System (ADS)

Ranaie, Mehrdad; Soffianian, Alireza; Pourmanafi, Saeid; Mirghaffari, Noorollah; Tarkesh, Mostafa

2018-03-01

In recent decade, analyzing the remotely sensed imagery is considered as one of the most common and widely used procedures in the environmental studies. In this case, supervised image classification techniques play a central role. Hence, taking a high resolution Worldview-3 over a mixed urbanized landscape in Iran, three less applied image classification methods including Bagged CART, Stochastic gradient boosting model and Neural network with feature extraction were tested and compared with two prevalent methods: random forest and support vector machine with linear kernel. To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data. Moreover, using ANOVA and Tukey test, statistical difference significance between the classification methods was significantly surveyed. In general, the results showed that random forest with marginal difference compared to Bagged CART and stochastic gradient boosting model is the best performing method whilst based on independent validation there was no significant difference between the performances of classification methods. It should be finally noted that neural network with feature extraction and linear support vector machine had better processing speed than other.

Environmental mapping and monitoring of Iceland by remote sensing (EMMIRS)

NASA Astrophysics Data System (ADS)

Pedersen, Gro B. M.; Vilmundardóttir, Olga K.; Falco, Nicola; Sigurmundsson, Friðþór S.; Rustowicz, Rose; Belart, Joaquin M.-C.; Gísladóttir, Gudrun; Benediktsson, Jón A.

2016-04-01

Iceland is exposed to rapid and dynamic landscape changes caused by natural processes and man-made activities, which impact and challenge the country. Fast and reliable mapping and monitoring techniques are needed on a big spatial scale. However, currently there is lack of operational advanced information processing techniques, which are needed for end-users to incorporate remote sensing (RS) data from multiple data sources. Hence, the full potential of the recent RS data explosion is not being fully exploited. The project Environmental Mapping and Monitoring of Iceland by Remote Sensing (EMMIRS) bridges the gap between advanced information processing capabilities and end-user mapping of the Icelandic environment. This is done by a multidisciplinary assessment of two selected remote sensing super sites, Hekla and Öræfajökull, which encompass many of the rapid natural and man-made landscape changes that Iceland is exposed to. An open-access benchmark repository of the two remote sensing supersites is under construction, providing high-resolution LIDAR topography and hyperspectral data for land-cover and landform classification. Furthermore, a multi-temporal and multi-source archive stretching back to 1945 allows a decadal evaluation of landscape and ecological changes for the two remote sensing super sites by the development of automated change detection techniques. The development of innovative pattern recognition and machine learning-based approaches to image classification and change detection is one of the main tasks of the EMMIRS project, aiming to extract and compute earth observation variables as automatically as possible. Ground reference data collected through a field campaign will be used to validate the implemented methods, which outputs are then inferred with geological and vegetation models. Here, preliminary results of an automatic land-cover classification based on hyperspectral image analysis are reported. Furthermore, the EMMIRS project investigates the complex landscape dynamics between geological and ecological processes. This is done through cross-correlation of mapping results and implementation of modelling techniques that simulate geological and ecological processes in order to extrapolate the landscape evolution

Microtopographic characterization of ice-wedge polygon landscape in Barrow, Alaska: a digital map of troughs, rims, centers derived from high resolution (0.25 m) LiDAR data

DOE Data Explorer

Gangodagamage, Chandana; Wullschleger, Stan

2014-07-03

The dataset represents microtopographic characterization of the ice-wedge polygon landscape in Barrow, Alaska. Three microtopographic features are delineated using 0.25 m high resolution digital elevation dataset derived from LiDAR. The troughs, rims, and centers are the three categories in this classification scheme. The polygon troughs are the surface expression of the ice-wedges that are in lower elevations than the interior polygon. The elevated shoulders of the polygon interior immediately adjacent to the polygon troughs are the polygon rims for the low center polygons. In case of high center polygons, these features are the topographic highs. In this classification scheme, both topographic highs and rims are considered as polygon rims. The next version of the dataset will include more refined classification scheme including separate classes for rims ad topographic highs. The interior part of the polygon just adjacent to the polygon rims are the polygon centers.

Relationship between tourism development and vegetated landscapes in Luya Mountain Nature Reserve, Shanxi, China.

PubMed

Cheng, Zhan-Hong; Zhang, Jin-Tun

2005-09-01

The relationship between tourism development and vegetated landscapes is analyzed for the Luya Mountain Nature Reserve (LMNR), Shanxi, China, in this study. Indices such as Sensitive Level (SL), Landscape Importance Value (LIV), information index of biodiversity (H'), Shade-tolerant Species Proportion (SSP), and Tourism Influencing Index (TII) are used to characterize vegetated landscapes, the impact of tourism, and their relationship. Their relationship is studied by Two-Way Indicator Species Analysis (TWINSPAN) and Detrended Correspondence Analysis (DCA). TWINSPAN gives correct and rapid partition to the classification, and DCA ordination shows the changing tendency of all vegetation types based on tourism development. These results reflect the ecological relationship between tourism development and vegetated landscapes. In Luya Mountain Nature Reserve, most plant communities are in good or medium condition, which shows that these vegetated landscapes can support more tourism. However, the occurrence of the bad condition shows that there is a severe contradiction between tourism development and vegetated landscapes.

Landscape object-based analysis of wetland plant functional types: the effects of spatial scale, vegetation classes and classifier methods

NASA Astrophysics Data System (ADS)

Dronova, I.; Gong, P.; Wang, L.; Clinton, N.; Fu, W.; Qi, S.

2011-12-01

Remote sensing-based vegetation classifications representing plant function such as photosynthesis and productivity are challenging in wetlands with complex cover and difficult field access. Recent advances in object-based image analysis (OBIA) and machine-learning algorithms offer new classification tools; however, few comparisons of different algorithms and spatial scales have been discussed to date. We applied OBIA to delineate wetland plant functional types (PFTs) for Poyang Lake, the largest freshwater lake in China and Ramsar wetland conservation site, from 30-m Landsat TM scene at the peak of spring growing season. We targeted major PFTs (C3 grasses, C3 forbs and different types of C4 grasses and aquatic vegetation) that are both key players in system's biogeochemical cycles and critical providers of waterbird habitat. Classification results were compared among: a) several object segmentation scales (with average object sizes 900-9000 m2); b) several families of statistical classifiers (including Bayesian, Logistic, Neural Network, Decision Trees and Support Vector Machines) and c) two hierarchical levels of vegetation classification, a generalized 3-class set and more detailed 6-class set. We found that classification benefited from object-based approach which allowed including object shape, texture and context descriptors in classification. While a number of classifiers achieved high accuracy at the finest pixel-equivalent segmentation scale, the highest accuracies and best agreement among algorithms occurred at coarser object scales. No single classifier was consistently superior across all scales, although selected algorithms of Neural Network, Logistic and K-Nearest Neighbors families frequently provided the best discrimination of classes at different scales. The choice of vegetation categories also affected classification accuracy. The 6-class set allowed for higher individual class accuracies but lower overall accuracies than the 3-class set because individual classes differed in scales at which they were best discriminated from others. Main classification challenges included a) presence of C3 grasses in C4-grass areas, particularly following harvesting of C4 reeds and b) mixtures of emergent, floating and submerged aquatic plants at sub-object and sub-pixel scales. We conclude that OBIA with advanced statistical classifiers offers useful instruments for landscape vegetation analyses, and that spatial scale considerations are critical in mapping PFTs, while multi-scale comparisons can be used to guide class selection. Future work will further apply fuzzy classification and field-collected spectral data for PFT analysis and compare results with MODIS PFT products.

A global view of shifting cultivation: Recent, current, and future extent

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

Heinimann, Andreas; Mertz, Ole; Frolking, Steve

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing-based land cover and land use classifications, as these are unable to adequately capture such landscapes' dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation atmore » a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21 st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation$-$the majority in the Americas (41%) and Africa (37%)$-$this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation.« less

A global view of shifting cultivation: Recent, current, and future extent

DOE PAGES

Heinimann, Andreas; Mertz, Ole; Frolking, Steve; ...

2017-09-08

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing-based land cover and land use classifications, as these are unable to adequately capture such landscapes' dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation atmore » a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21 st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation$-$the majority in the Americas (41%) and Africa (37%)$-$this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation.« less

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID:29016604

Classification of vegetation in an open landscape using full-waveform airborne laser scanner data

NASA Astrophysics Data System (ADS)

Alexander, Cici; Deák, Balázs; Kania, Adam; Mücke, Werner; Heilmeier, Hermann

2015-09-01

Airborne laser scanning (ALS) is increasingly being used for the mapping of vegetation, although the focus so far has been on woody vegetation, and ALS data have only rarely been used for the classification of grassland vegetation. In this study, we classified the vegetation of an open alkali landscape, characterized by two Natura 2000 habitat types: Pannonic salt steppes and salt marshes and Pannonic loess steppic grasslands. We generated 18 variables from an ALS dataset collected in the growing (leaf-on) season. Elevation is a key factor determining the patterns of vegetation types in the landscape, and hence 3 additional variables were based on a digital terrain model (DTM) generated from an ALS dataset collected in the dormant (leaf-off) season. We classified the vegetation into 24 classes based on these 21 variables, at a pixel size of 1 m. Two groups of variables with and without the DTM-based variables were used in a Random Forest classifier, to estimate the influence of elevation, on the accuracy of the classification. The resulting classes at Level 4, based on associations, were aggregated at three levels - Level 3 (11 classes), Level 2 (8 classes) and Level 1 (5 classes) - based on species pool, site conditions and structure, and the accuracies were assessed. The classes were also aggregated based on Natura 2000 habitat types to assess the accuracy of the classification, and its usefulness for the monitoring of habitat quality. The vegetation could be classified into dry grasslands, wetlands, weeds, woody species and man-made features, at Level 1, with an accuracy of 0.79 (Cohen's kappa coefficient, κ). The accuracies at Levels 2-4 and the classification based on the Natura 2000 habitat types were κ: 0.76, 0.61, 0.51 and 0.69, respectively. Levels 1 and 2 provide suitable information for nature conservationists and land managers, while Levels 3 and 4 are especially useful for ecologists, geologists and soil scientists as they provide high resolution data on species distribution, vegetation patterns, soil properties and on their correlations. Including the DTM-based variables increased the accuracy (κ) from 0.73 to 0.79 for Level 1. These findings show that the structural and spectral attributes of ALS echoes can be used for the classification of open landscapes, especially those where vegetation is influenced by elevation, such as coastal salt marshes, sand dunes, karst or alluvial areas; in these cases, ALS has a distinct advantage over other remotely sensed data.

Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

NASA Astrophysics Data System (ADS)

Karakacan Kuzucu, A.; Bektas Balcik, F.

2017-11-01

Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

An Investigation of Automatic Change Detection for Topographic Map Updating

NASA Astrophysics Data System (ADS)

Duncan, P.; Smit, J.

2012-08-01

Changes to the landscape are constantly occurring and it is essential for geospatial and mapping organisations that these changes are regularly detected and captured, so that map databases can be updated to reflect the current status of the landscape. The Chief Directorate of National Geospatial Information (CD: NGI), South Africa's national mapping agency, currently relies on manual methods of detecting changes and capturing these changes. These manual methods are time consuming and labour intensive, and rely on the skills and interpretation of the operator. It is therefore necessary to move towards more automated methods in the production process at CD: NGI. The aim of this research is to do an investigation into a methodology for automatic or semi-automatic change detection for the purpose of updating topographic databases. The method investigated for detecting changes is through image classification as well as spatial analysis and is focussed on urban landscapes. The major data input into this study is high resolution aerial imagery and existing topographic vector data. Initial results indicate the traditional pixel-based image classification approaches are unsatisfactory for large scale land-use mapping and that object-orientated approaches hold more promise. Even in the instance of object-oriented image classification generalization of techniques on a broad-scale has provided inconsistent results. A solution may lie with a hybrid approach of pixel and object-oriented techniques.

The ecological classification of coastal wet longleaf pine (pinus palustris) of Florida from reference conditions

Treesearch

George L. McCaskill; Jose. Shibu

2012-01-01

Tropical storms, fire, and urbanization have produced a heavily fragmented forested landscape along Florida’s Gulf coast. The longleaf pine forest, one of the most threatened ecosystems in the US, makes up a major part of this fragmented landscape. These three disturbance regimes have produced a mosaic of differently-aged pine patches of single or two cohort structures...

Research and Application of Remote Sensing Monitoring Method for Desertification Land Under Time and Space Constraints

NASA Astrophysics Data System (ADS)

Zhang, Nannnan; Wang, Rongbao; Zhang, Feng

2018-04-01

Serious land desertification and sandified threaten the urban ecological security and the sustainable economic and social development. In recent years, a large number of mobile sand dunes in Horqin sandy land flow into the northwest of Liaoning Province under the monsoon, make local agriculture suffer serious harm. According to the characteristics of desertification land in northwestern Liaoning, based on the First National Geographical Survey data, the Second National Land Survey data and the 1984-2014 Landsat satellite long time sequence data and other multi-source data, we constructed a remote sensing monitoring index system of desertification land in Northwest Liaoning. Through the analysis of space-time-spectral characteristics of desertification land, a method for multi-spectral remote sensing image recognition of desertification land under time-space constraints is proposed. This method was used to identify and extract the distribution and classification of desertification land of Chaoyang City (a typical citie of desertification in northwestern Liaoning) in 2008 and 2014, and monitored the changes and transfers of desertification land from 2008 to 2014. Sandification information was added to the analysis of traditional landscape changes, improved the analysis model of desertification land landscape index, and the characteristics and laws of landscape dynamics and landscape pattern change of desertification land from 2008 to 2014 were analyzed and revealed.

Integration of visual quality considerations in development of Israeli vegetation management policy.

PubMed

Misgav, A; Amir, S

2001-06-01

This article deals with the visual quality of Mediterranean vegetation groups in northern Israel, the public's preference of these groups as a visual resource, and the policy options for their management. The study is based on a sample of 44 Mediterranean vegetation groups and three population groups of local residents, who were interviewed using a questionnaire and photographs of the vegetation groups. The results of the research showed that plant classification methods based on flora composition, habitat, and external appearance were found to be suitable for visual plant classification and for the evaluation of visual preference of vegetation groups by the interviewed public. The vegetation groups of planted pine forests and olive groves, characterizing a cultured vegetation landscape, were preferred over typical Mediterranean landscapes such as scrub and grassed scrub. The researchers noted a marked difference between the two products of vegetation management policy, one that proposes the conservation and restoration of the variety of native Mediterranean vegetation landscape, and a second that advanced the development of the cultured landscape of planted olive groves and pines forests, which were highly preferred by the public. The authors suggested the development of an integrated vegetation management policy that would combine both needs and thus reduce the gap between the policy proposed by planners and the local population's visual preference.

The edge-preservation multi-classifier relearning framework for the classification of high-resolution remotely sensed imagery

NASA Astrophysics Data System (ADS)

Han, Xiaopeng; Huang, Xin; Li, Jiayi; Li, Yansheng; Yang, Michael Ying; Gong, Jianya

2018-04-01

In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy.

Modern landscape processes affecting archaeological sites along the Colorado River corridor downstream of Glen Canyon Dam, Glen Canyon National Recreation Area, Arizona

USGS Publications Warehouse

East, Amy E.; Sankey, Joel B.; Fairley, Helen C.; Caster, Joshua J.; Kasprak, Alan

2017-08-29

The landscape of the Colorado River through Glen Canyon National Recreation Area formed over many thousands of years and was modified substantially after the completion of Glen Canyon Dam in 1963. Changes to river flow, sediment supply, channel base level, lateral extent of sedimentary terraces, and vegetation in the post-dam era have modified the river-corridor landscape and have altered the effects of geologic processes that continue to shape the landscape and its cultural resources. The Glen Canyon reach of the Colorado River downstream of Glen Canyon Dam hosts many archaeological sites that are prone to erosion in this changing landscape. This study uses field evaluations from 2016 and aerial photographs from 1952, 1973, 1984, and 1996 to characterize changes in potential windblown sand supply and drainage configuration that have occurred over more than six decades at 54 archaeological sites in Glen Canyon and uppermost Marble Canyon. To assess landscape change at these sites, we use two complementary geomorphic classification systems. The first evaluates the potential for aeolian (windblown) transport of river-derived sand from the active river channel to higher elevation archaeological sites. The second identifies whether rills, gullies, or arroyos (that is, overland drainages that erode the ground surface) exist at the archaeological sites as well as the geomorphic surface, and therefore the relative base level, to which those flow paths drain. Results of these assessments are intended to aid in the management of irreplaceable archaeological resources by the National Park Service and stakeholders of the Glen Canyon Dam Adaptive Management Program.

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function

PubMed Central

Groenendyk, Derek G.; Ferré, Ty P.A.; Thorp, Kelly R.; Rice, Amy K.

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth’s surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function. PMID:26121466

Hydrologic-Process-Based Soil Texture Classifications for Improved Visualization of Landscape Function.

PubMed

Groenendyk, Derek G; Ferré, Ty P A; Thorp, Kelly R; Rice, Amy K

2015-01-01

Soils lie at the interface between the atmosphere and the subsurface and are a key component that control ecosystem services, food production, and many other processes at the Earth's surface. There is a long-established convention for identifying and mapping soils by texture. These readily available, georeferenced soil maps and databases are used widely in environmental sciences. Here, we show that these traditional soil classifications can be inappropriate, contributing to bias and uncertainty in applications from slope stability to water resource management. We suggest a new approach to soil classification, with a detailed example from the science of hydrology. Hydrologic simulations based on common meteorological conditions were performed using HYDRUS-1D, spanning textures identified by the United States Department of Agriculture soil texture triangle. We consider these common conditions to be: drainage from saturation, infiltration onto a drained soil, and combined infiltration and drainage events. Using a k-means clustering algorithm, we created soil classifications based on the modeled hydrologic responses of these soils. The hydrologic-process-based classifications were compared to those based on soil texture and a single hydraulic property, Ks. Differences in classifications based on hydrologic response versus soil texture demonstrate that traditional soil texture classification is a poor predictor of hydrologic response. We then developed a QGIS plugin to construct soil maps combining a classification with georeferenced soil data from the Natural Resource Conservation Service. The spatial patterns of hydrologic response were more immediately informative, much simpler, and less ambiguous, for use in applications ranging from trafficability to irrigation management to flood control. The ease with which hydrologic-process-based classifications can be made, along with the improved quantitative predictions of soil responses and visualization of landscape function, suggest that hydrologic-process-based classifications should be incorporated into environmental process models and can be used to define application-specific maps of hydrologic function.

Is Nigeria losing its natural vegetation and landscape? Assessing the landuse-landcover change trajectories and effects in Onitsha using remote sensing and GIS

NASA Astrophysics Data System (ADS)

Nwaogu, Chukwudi; Okeke, Onyedikachi J.; Fadipe, Olusola O.; Bashiru, Kehinde A.; Pechanec, Vilém

2017-12-01

Onitsha is one of the largest commercial cities in Africa with its population growth rate increasing arithmetically for the past two decades. This situation has direct and indirect effects on the natural resources including vegetation and water. The study aimed at assessing land use-land cover (LULC) change and its effects on the vegetation and landscape from 1987 to 2015 using geoinformatics. Supervised and unsupervised classifications including maximum likelihood algorithm were performed using ENVI 4.7 and ArcGIS 10.1 versions. The LULC was classified into 7 classes: built-up areas (settlement), waterbody, thick vegetation, light vegetation, riparian vegetation, sand deposit (bare soil) and floodplain. The result revealed that all the three vegetation types decreased in areas throughout the study period while, settlement, sand deposit and floodplain areas have remarkable increase of about 100% in 2015 when compared with the total in 1987. Number of dominant plant species decreased continuously during the study. The overall classification accuracies in 1987, 2002 and 2015 was 90.7%, 92.9% and 95.5% respectively. The overall kappa coefficient of the image classification for 1987, 2002 and 2015 was 0.98, 0.93 and 0.96 respectively. In general, the average classification was above 90%, a proof that the classification was reliable and acceptable.

Soil quality and soil degradation in agricultural loess soils in Central Europe - impacts of traditional small-scale and modernized large-scale agriculture

NASA Astrophysics Data System (ADS)

Schneider, Christian

2017-04-01

The study analyzes the impact of different farming systems on soil quality and soil degradation in European loess landscapes. The analyses are based on geo-chemical soil properties, landscape metrics and geomorphological indicators. The German Middle Saxonian Loess Region represents loess landscapes whose ecological functions were shaped by land consolidation measures resulting in large-scale high-input farming systems. The Polish Proszowice Plateau is still characterized by a traditional small-scale peasant agriculture. The research areas were analyzed on different scale levels combining GIS, field, and laboratory methods. A digital terrain classification was used to identify representative catchment basins for detailed pedological studies which were focused on soil properties that responded to soil management within several years, like pH-value, total carbon (TC), total nitrogen (TN), inorganic carbon (IC), soil organic carbon (TOC=TC-IC), hot-water extractable carbon (HWC), hot-water extractable nitrogen (HWN), total phosphorus, plant-available phosphorus (P), plant-available potassium (K) and the potential cation exchange capacity (CEC). The study has shown that significant differences in major soil properties can be observed because of different fertilizer inputs and partly because of different cultivation techniques. Also the traditional system increases soil heterogeneity. Contrary to expectations the study has shown that the small-scale peasant farming system resulted in similar mean soil organic carbon and phosphorus contents like the industrialized high-input farming system. A further study could include investigations of the effects of soil amendments like herbicides and pesticide on soil degradation.

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California: year-1 progress

USGS Publications Warehouse

Forney, William; Raumann, Christian G.; Minor, T.B.; Smith, J. LaRue; Vogel, John; Vitales, Robert

2002-01-01

As part of the requirements for the Geographic Research and Applications Prospectus grants, this Open-File Report is the second of two that resulted from the first year of the project. The first Open-File Report (OFR 01-418) introduced the project, reviewed the existing body of literature, and outlined the research approach. This document will present an update of the research approach and offer some preliminary results from multiple efforts, specifically, the production of historical digital orthophoto quadrangles, the development of the land use/land cover (LULC) classification system, the development of a temporal transportation layer, the classification of anthropogenic cover types from the IKONOS imagery, a preliminary evaluation of landscape ecology metrics (quantification of spatial and temporal patterns of ecosystem structure and function with appropriate indices) and their utility in comparing two LULC systems, and a new initiative in community-based science and facilitation.

Advances in the molecular genetics of gliomas - implications for classification and therapy.

PubMed

Reifenberger, Guido; Wirsching, Hans-Georg; Knobbe-Thomsen, Christiane B; Weller, Michael

2017-07-01

Genome-wide molecular-profiling studies have revealed the characteristic genetic alterations and epigenetic profiles associated with different types of gliomas. These molecular characteristics can be used to refine glioma classification, to improve prediction of patient outcomes, and to guide individualized treatment. Thus, the WHO Classification of Tumours of the Central Nervous System was revised in 2016 to incorporate molecular biomarkers - together with classic histological features - in an integrated diagnosis, in order to define distinct glioma entities as precisely as possible. This paradigm shift is markedly changing how glioma is diagnosed, and has important implications for future clinical trials and patient management in daily practice. Herein, we highlight the developments in our understanding of the molecular genetics of gliomas, and review the current landscape of clinically relevant molecular biomarkers for use in classification of the disease subtypes. Novel approaches to the genetic characterization of gliomas based on large-scale DNA-methylation profiling and next-generation sequencing are also discussed. In addition, we illustrate how advances in the molecular genetics of gliomas can promote the development and clinical translation of novel pathogenesis-based therapeutic approaches, thereby paving the way towards precision medicine in neuro-oncology.

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Assessment of Acacia koa forest health across environmental gradients in Hawai'i using fine resolution remote sensing and GIS.

PubMed

Morales, Rodolfo Martinez; Idol, Travis; Friday, James B

2011-01-01

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai'ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600-1,000 m asl in the island of Kaua'i, which correspond to gradients of temperature and rainfall ranging from 17-20 °C mean annual temperature and 750-1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai'i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species.

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics.

PubMed

Esbah, Hayriye; Deniz, Bulent; Kara, Baris; Kesgin, Birsen

2010-06-01

Bafa Lake Nature Park is one of Turkey's most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural-natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.

Hydrogeomorphic Classification of Wetlands on Mt. Desert Island, Maine, Including Hydrologic Susceptibility Factors for Wetlands in Acadia National Park

USGS Publications Warehouse

Nielsen, Martha G.

2006-01-01

The U.S. Geological Survey, in cooperation with the National Park Service, developed a hydrogeomorphic (HGM) classification system for wetlands greater than 0.4 hectares (ha) on Mt. Desert Island, Maine, and applied this classification using map-scale data to more than 1,200 mapped wetland units on the island. In addition, two hydrologic susceptibility factors were defined for a subset of these wetlands, using 11 variables derived from landscape-scale characteristics of the catchment areas of these wetlands. The hydrologic susceptibility factors, one related to the potential hydrologic pathways for contaminants and the other to the susceptibility of wetlands to disruptions in water supply from projected future changes in climate, were used to indicate which wetlands (greater than 1 ha) in Acadia National Park (ANP) may warrant further investigation or monitoring. The HGM classification system consists of 13 categories: Riverine-Upper Perennial, Riverine-Nonperennial, Riverine- Tidal, Depressional-Closed, Depressional-Semiclosed, Depressional-Open, Depressional-No Ground-Water Input, Mineral Soil Flat, Organic Soil Flat, Tidal Fringe, Lacustrine Fringe, Slope, and Hilltop/Upper Hillslope. A dichotomous key was developed to aid in the classification of wetlands. The National Wetland Inventory maps produced by the U.S. Fish and Wildlife Service provided the wetland mapping units used for this classification. On the basis of topographic map information and geographic information system (GIS) layers at a scale of 1:24,000 or larger, 1,202 wetland units were assigned a preliminary HGM classification. Two of the 13 HGM classes (Riverine-Tidal and Depressional-No Ground-Water Input) were not assigned to any wetlands because criteria for determining those classes are not available at that map scale, and must be determined by more site-specific information. Of the 1,202 wetland polygons classified, which cover 1,830 ha in ANP, 327 were classified as Slope, 258 were Depressional (Open, Semiclosed, and Closed), 231 were Riverine (Upper Perennial and Nonperennial), 210 were Soil Flat (Mineral and Organic), 68 were Lacustrine Fringe, 51 were Tidal Fringe, 22 were Hilltop/Upper Hillslope, and another 35 were small open water bodies. Most small, isolated wetlands classified on the island are Slope wetlands. The least common, Hilltop/Upper Hillslope wetlands, only occur on a few hilltops and shoulders of hills and mountains. Large wetland complexes generally consist of groups of Depressional wetlands and Mineral Soil Flat or Organic Soil Flat wetlands, often with fringing Slope wetlands at their edges and Riverine wetlands near streams flowing through them. The two analyses of wetland hydrologic susceptibility on Mt. Desert Island were applied to 186 wetlands located partially or entirely within ANP. These analyses were conducted using individually mapped catchments for each wetland. The 186 wetlands were aggregated from the original 1,202 mapped wetland polygons on the basis of their HGM classes. Landscape-level hydrologic, geomorphic, and soil variables were defined for the catchments of the wetlands, and transformed into scaled scores from 0 to 10 for each variable. The variables included area of the wetland, area of the catchment, area of the wetland divided by the area of the catchment, the average topographic slope of the catchment, the amount of the catchment where bedrock crops out with no soil cover or excessively thin soil cover, the amount of storage (in lakes and wetlands) in the catchment, the topographic relief of the catchment, the amount of clay-rich soil in the catchment, the amount of manmade impervious surface, whether the wetland had a stream inflow, and whether the wetland had a hydraulic connection to a lake or estuary. These data were determined using a GIS and data layers mapped at a scale of 1:24,000 or larger. These landscape variables were combined in different ways for the two hydrologic susceptibility fact

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.

Using Imaging Spectroscopy to Map Changing Distributions of Dominant Species in Oil-Contaminated Salt Marshes of Louisiana

NASA Astrophysics Data System (ADS)

Beland, M. C.; Roberts, D. A.; Peterson, S.; Biggs, T. W.; Kokaly, R. F.; Piazza, S.; Roth, K. L.; Khanna, S.; Ustin, S.

2016-12-01

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes. Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010-2012 for oiled and non-oiled shorelines. CDA discriminated dominant species with a high level of accuracy (overall accuracy = 82%, kappa = 0.78) and consistency over three imaging dates (overall2010 = 82%, overall2011 = 82%, overall2012 = 88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (≤ 28m from shore) for all three dates (2010 = 79%, 2011 = 61%, 2012 = 63%), followed by Juncus roemerianus (2010 = 11%, 2011 = 19%, 2012 = 17%) and Distichlis spicata (2010 = 4%, 2011 = 10%, 2012 = 7%). Marshes that were heavily contaminated with oil exhibited variable responses from 2010-2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only Spartina alterniflora dominated marshes were extensively degraded, losing 15% (354,604 m2) cover in oiled shoreline zones, suggesting that Spartina alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position.

Classification-Assisted Memetic Algorithms for Equality-Constrained Optimization Problems

NASA Astrophysics Data System (ADS)

Handoko, Stephanus Daniel; Kwoh, Chee Keong; Ong, Yew Soon

Regressions has successfully been incorporated into memetic algorithm (MA) to build surrogate models for the objective or constraint landscape of optimization problems. This helps to alleviate the needs for expensive fitness function evaluations by performing local refinements on the approximated landscape. Classifications can alternatively be used to assist MA on the choice of individuals that would experience refinements. Support-vector-assisted MA were recently proposed to alleviate needs for function evaluations in the inequality-constrained optimization problems by distinguishing regions of feasible solutions from those of the infeasible ones based on some past solutions such that search efforts can be focussed on some potential regions only. For problems having equality constraints, however, the feasible space would obviously be extremely small. It is thus extremely difficult for the global search component of the MA to produce feasible solutions. Hence, the classification of feasible and infeasible space would become ineffective. In this paper, a novel strategy to overcome such limitation is proposed, particularly for problems having one and only one equality constraint. The raw constraint value of an individual, instead of its feasibility class, is utilized in this work.

Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

NASA Technical Reports Server (NTRS)

Fagan, Matthew E.; Defries, Ruth S.; Sesnie, Steven E.; Arroyo-Mora, J. Pablo; Soto, Carlomagno; Singh, Aditya; Townsend, Philip A.; Chazdon, Robin L.

2015-01-01

An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

Impact of CO2 emissions on the geoecological state of landscapes of the British Isles: carbon footprint versus the assimilation potential

NASA Astrophysics Data System (ADS)

Romanova, Emma; Bulokhov, Anton; Arshinova, Marina

2017-04-01

The geoecological state of landscapes is determined by the type and intensity of anthropogenic impacts, the ability of geosystems to sustain them and the number of population living within a particular landscape unit. The main sources of CO2 emissions are thermal power plants, industrial facilities, transport and waste utilization. In Great Britain 163 enterprises produce 254.7 MMT CO2Eq. and 20 enterprises in Ireland - 17.8 MMT CO2Eq. Total transport emissions are 122 MMT CO2Eq. Utilization of solid wastes collected on the British Isles produces about 4.2 MMT CO2Eq. The spatial pattern of CO2 sources within the landscapes is particularly mosaic. Among the indicators which characterize the capacity of landscapes to neutralize wastes the assimilation potential (AP) is particularly important. The neutralization is based on the process of sequestration of gaseous substances, i.e. their accumulation in leaves, branches and stocks during respiration and growth of trees and in water bodies by aquatic organisms. Thus the AP is calculated basing on the area of forests and wetlands which perform the regulating services in landscapes. Total absorbing capacity of forests of the British Isles is 6.805 MMT CO2Eq. Inland waters cover 0.01% of the territory and their assimilating role is minor. The evaluation procedure includes several analytical steps: 1) inventory of the volumes of CO2 emissions by all anthropogenic sources within the borders of natural geosystems; 2) calculation of the area of CO2 assimilation in landscapes and the maximum possible volumes of CO2 sequestration; 3) comparison of the volumes of emissions and the assimilation potential of each landscape, classification of landscapes into debtors (with the deficit of AP) and creditors (with surplus AP); 4) calculation of population in each landscape; 5) risk assessment for the inhabitants living within landscapes-debtors; 6) classification and mapping of landscapes according to their geoecological state. The assimilation potential of landscapes-creditors is higher, than it is necessary for the neutralization of CO2 emissions; they are capable of the positive biotic regulation of carbon cycle. But the most landscapes in England are debtors - their AP is sometimes well below the amount of CO2 emissions, so they cannot neutralize wastes completely any more. Such geosystems reach critical thresholds of environmental services exploitation, their biota turns from a carbon pool into a source of its drain, thus endangering the regulatory abilities of landscapes. The geoecological situation in these geocomplexes creates the risk of serious diseases for inhabitants, and such landscapes are considered as unfavorable for living. According to the calculations to neutralize all CO2 emissions produced within the British Isles they need an area 16 times larger than the available one. Hence the transition to a low-carbon energy regime to mitigate CO2 emission within landscapes-debtors is a most actual challenge.

A field guide for the assessment of erosion, sediment transport, and deposition in incised channels of the southwestern United States

USGS Publications Warehouse

Parker, John T.C.

2000-01-01

Deeply incised channels, commonly called arroyos, are a typical feature of the dry alluvium-filled valleys of the southwestern United States. Unlike many geological processes that operate over millions of years, the formation of many miles of arroyos is one that took place in a little more than a century. Most arroyos in the region began to form in the late 19th century. Because dry landscapes change so quickly, they present society with special problems. Rapid expansion of channels by headcut migration, deepening, and widening causes loss of productive agricultural and commercial lands and threatens infrastructure such as roads, bridges, and buildings. High rates of sedimentation shorten the life of reservoirs, clog culverts, and fill stream channels to the extent that they can no longer contain streamflow within their banks. This report presents an explanation of erosional and depositional processes in desert landscapes, especially those characterized by incised channels, for the use of those who use, manage, and live on such lands. The basic principles of erosion, sediment transport, and deposition are presented including the formation of sediment, the forces that erode and transport it, the forces that resist its erosion and transport, and the conditions that cause it to be deposited. The peculiarities of sedimentation processes in the Southwest include the infrequent and variable precipitation, the geological setting, and the sparseness of vegetation. A classification system for incised channels that is intended for users who do not necessarily have a background in fluvial hydrology has been developed and is presented in this report. The classification system is intended to enable a user to classify a reach of channel quickly on the basis of field observations. The system is based on the shape and condition of channels and on the sedimentation processes that are predominantly responsible for those conditions. Because those processes are controlled by environmental factors operating on the entire drainage basin, classification of channels can provide land managers and users with an understanding of what areas are likely to be most susceptible to erosion or the effects of high sedimentation rates and under what conditions they are most likely to occur.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

Ecosystem services classification: A systems ecology perspective of the cascade framework.

PubMed

La Notte, Alessandra; D'Amato, Dalia; Mäkinen, Hanna; Paracchini, Maria Luisa; Liquete, Camino; Egoh, Benis; Geneletti, Davide; Crossman, Neville D

2017-03-01

Ecosystem services research faces several challenges stemming from the plurality of interpretations of classifications and terminologies. In this paper we identify two main challenges with current ecosystem services classification systems: i) the inconsistency across concepts, terminology and definitions, and; ii) the mix up of processes and end-state benefits, or flows and assets. Although different ecosystem service definitions and interpretations can be valuable for enriching the research landscape, it is necessary to address the existing ambiguity to improve comparability among ecosystem-service-based approaches. Using the cascade framework as a reference, and Systems Ecology as a theoretical underpinning, we aim to address the ambiguity across typologies. The cascade framework links ecological processes with elements of human well-being following a pattern similar to a production chain. Systems Ecology is a long-established discipline which provides insight into complex relationships between people and the environment. We present a refreshed conceptualization of ecosystem services which can support ecosystem service assessment techniques and measurement. We combine the notions of biomass, information and interaction from system ecology, with the ecosystem services conceptualization to improve definitions and clarify terminology. We argue that ecosystem services should be defined as the interactions (i.e. processes) of the ecosystem that produce a change in human well-being, while ecosystem components or goods, i.e. countable as biomass units, are only proxies in the assessment of such changes. Furthermore, Systems Ecology can support a re-interpretation of the ecosystem services conceptualization and related applied research, where more emphasis is needed on the underpinning complexity of the ecological system.

Land cover heterogeneity and soil respiration in a west Greenland tundra landscape

NASA Astrophysics Data System (ADS)

Bradley-Cook, J. I.; Burzynski, A.; Hammond, C. R.; Virginia, R. A.

2011-12-01

Multiple direct and indirect pathways underlie the association between land cover classification, temperature and soil respiration. Temperature is a main control of the biological processes that constitute soil respiration, yet the effect of changing atmospheric temperatures on soil carbon flux is unresolved. This study examines associations amongst land cover, soil carbon characteristics, soil respiration, and temperature in an Arctic tundra landscape in western Greenland. We used a 1.34 meter resolution multi-spectral WorldView2 satellite image to conduct an unsupervised multi-staged ISODATA classification to characterize land cover heterogeneity. The four band image was taken on July 10th, 2010, and captures an 18 km by 15 km area in the vicinity of Kangerlussuaq. The four major terrestrial land cover classes identified were: shrub-dominated, graminoid-dominated, mixed vegetation, and bare soil. The bare soil class was comprised of patches where surface soil has been deflated by wind and ridge-top fellfield. We hypothesize that soil respiration and soil carbon storage are associated with land cover classification and temperature. We set up a hierarchical field sampling design to directly observe spatial variation between and within land cover classes along a 20 km temperature gradient extending west from Russell Glacier on the margin of the Greenland Ice Sheet. We used the land cover classification map and ground verification to select nine sites, each containing patches of the four land cover classes. Within each patch we collected soil samples from a 50 cm pit, quantified vegetation, measured active layer depth and determined landscape characteristics. From a subset of field sites we collected additional 10 cm surface soil samples to estimate soil heterogeneity within patches and measured soil respiration using a LiCor 8100 Infrared Gas Analyzer. Soil respiration rates varied with land cover classes, with values ranging from 0.2 mg C/m^2/hr in the bare soil class to over 5 mg C/m^2/hr in the graminoid-dominated class. These findings suggest that shifts in land cover vegetation types, especially soil and vegetation loss (e.g. from wind deflation), can alter landscape soil respiration. We relate soil respiration measurements to soil, vegetation, and permafrost characteristics to understand how ecosystem properties and processes vary at the landscape scale. A long-term goal of this research is to develop a spatially explicit model of soil organic matter, soil respiration, and temperature sensitivity of soil carbon dynamics for a western Greenland permafrost tundra ecosystems.

`Hardcastle Hollows' in loess landforms: Closed depressions in aeolian landscapes - in a geoheritage context

NASA Astrophysics Data System (ADS)

Fagg, Roger; Smalley, Ian

2018-04-01

Loess landscapes sometimes contain isolated depressed areas, which often appear as lakes. The outline shape (and distribution) of these depressions could be controlled by random processes, particularly if the depressions are caused by loess hydroconsolidation and ground subsidence. By applying the Zingg system of shape classification it is possible to propose a mean random shape for the closed depressions. A Zingg rectangle with a side ratio of about 2:1 is produced by a very simple Monte Carlo method, which had been used previously to calculate the mean random shape of a loess particle. The Zingg rectangle indicates the basic shape of the mean closed depression. A simple four stage process for the formation of the depressions is proposed. They might be called `Hardcastle Hollows' in honour of John Hardcastle who first reported them, in New Zealand. Studies on Ukrainian deposits suggest that there might be some stratigraphic value in the observation of closed depressions; they are often not superimposed in successive depositions of loess. Hydroconsolidation is important in landscape processes. The hollows provide interesting habitats and enlarge the ecological interest of loess deposits; the geoheritage scene is enhanced.

Wetland Hydrological Connectivity: A Classification Approach and Continental Assessment

EPA Science Inventory

Connectivity has become a major focus of hydrological and ecological studies. Connectivity influences fluxes between landscape elements, while isolation reduces flows between elements. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrolo...

Multivariate classification of small order watersheds in the Quabbin Reservoir Basin, Massachusetts

USGS Publications Warehouse

Lent, R.M.; Waldron, M.C.; Rader, J.C.

1998-01-01

A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wetland density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.A multivariate approach was used to analyze hydrologic, geologic, geographic, and water-chemistry data from small order watersheds in the Quabbin Reservoir Basin in central Massachusetts. Eighty three small order watersheds were delineated and landscape attributes defining hydrologic, geologic, and geographic features of the watersheds were compiled from geographic information system data layers. Principal components analysis was used to evaluate 11 chemical constituents collected bi-weekly for 1 year at 15 surface-water stations in order to subdivide the basin into subbasins comprised of watersheds with similar water quality characteristics. Three principal components accounted for about 90 percent of the variance in water chemistry data. The principal components were defined as a biogeochemical variable related to wetland density, an acid-neutralization variable, and a road-salt variable related to density of primary roads. Three subbasins were identified. Analysis of variance and multiple comparisons of means were used to identify significant differences in stream water chemistry and landscape attributes among subbasins. All stream water constituents were significantly different among subbasins. Multiple regression techniques were used to relate stream water chemistry to landscape attributes. Important differences in landscape attributes were related to wetlands, slope, and soil type.

Analysis of Patent Databases Using VxInsight

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

BOYACK,KEVIN W.; WYLIE,BRIAN N.; DAVIDSON,GEORGE S.

2000-12-12

We present the application of a new knowledge visualization tool, VxInsight, to the mapping and analysis of patent databases. Patent data are mined and placed in a database, relationships between the patents are identified, primarily using the citation and classification structures, then the patents are clustered using a proprietary force-directed placement algorithm. Related patents cluster together to produce a 3-D landscape view of the tens of thousands of patents. The user can navigate the landscape by zooming into or out of regions of interest. Querying the underlying database places a colored marker on each patent matching the query. Automatically generatedmore » labels, showing landscape content, update continually upon zooming. Optionally, citation links between patents may be shown on the landscape. The combination of these features enables powerful analyses of patent databases.« less

Wetland Hydrological Connectivity: A Classification Approach and United States Assessment

EPA Science Inventory

Connectivity has become a major focus of hydrological and ecological studies. Connectivity influences fluxes between landscape elements, while isolation reduces flows between elements. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrolo...

Land use classification in Bolivia

NASA Technical Reports Server (NTRS)

Brockmann, C. E.; Brooner, W. G.

1975-01-01

The Bolivian LANDSAT Program is an integrated, multidisciplinary project designed to provide thematic analysis of LANDSAT, Skylab, and other remotely sensed data for natural resource management and development in Bolivia, is discussed. Among the first requirements in the program is the development of a legend, and appropriate methodologies, for the analysis and classification of present land use based on landscape cover. The land use legend for Bolivia consists of approximately 80 categories in a hierarchical organization which may be collapsed for generalization, or expanded for greater detail. The categories, and their definitions, provide for both a graphic and textual description of the complex and diverse landscapes found in Bolivia, and are designed for analysis from LANDSAT and other remotely sensed data at scales of 1:1,000,000 and 1:250,000. Procedures and example products developed are described and illustrated, for the systematic analysis and mapping of present land use for all of Bolivia.

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Genomic landscape of gastric cancer: molecular classification and potential targets.

PubMed

Guo, Jiawei; Yu, Weiwei; Su, Hui; Pang, Xiufeng

2017-02-01

Gastric cancer imposes a considerable health burden worldwide, and its mortality ranks as the second highest for all types of cancers. The limited knowledge of the molecular mechanisms underlying gastric cancer tumorigenesis hinders the development of therapeutic strategies. However, ongoing collaborative sequencing efforts facilitate molecular classification and unveil the genomic landscape of gastric cancer. Several new drivers and tumorigenic pathways in gastric cancer, including chromatin remodeling genes, RhoA-related pathways, TP53 dysregulation, activation of receptor tyrosine kinases, stem cell pathways and abnormal DNA methylation, have been revealed. These newly identified genomic alterations await translation into clinical diagnosis and targeted therapies. Considering that loss-of-function mutations are intractable, synthetic lethality could be employed when discussing feasible therapeutic strategies. Although many challenges remain to be tackled, we are optimistic regarding improvements in the prognosis and treatment of gastric cancer in the near future.

Effects of Tree-crop Farming on Land-cover Transitions in a Mosaic Landscape in the Eastern Region of Ghana.

PubMed

Asubonteng, Kwabena; Pfeffer, Karin; Ros-Tonen, Mirjam; Verbesselt, Jan; Baud, Isa

2018-05-11

Tree crops such as cocoa and oil palm are important to smallholders' livelihoods and national economies of tropical producer countries. Governments seek to expand tree-crop acreages and improve yields. Existing literature has analyzed socioeconomic and environmental effects of tree-crop expansion, but its spatial effects on the landscape are yet to be explored. This study aims to assess the effects of tree-crop farming on the composition and the extent of land-cover transitions in a mixed cocoa/oil palm landscape in Ghana. Land-cover maps of 1986 and 2015 produced through ISODATA, and maximum likelihood classification were validated with field reference, Google Earth data, and key respondent interviews. Post-classification change detection was conducted and the transition matrix analyzed using intensity analysis. Cocoa and oil palm areas have increased in extent by 8.9% and 11.2%, respectively, mainly at the expense of food-crop land and forest. The intensity of forest loss to both tree crops is at a lower intensity than the loss of food-crop land. There were transitions between cocoa and oil palm, but the gains in oil palm outweigh those of cocoa. Cocoa and oil palm have increased in area and dominance. The main cover types converted to tree-crop areas are food-crop land and off-reserve forest. This is beginning to have serious implications for food security and livelihood options that depend on ecosystem services provided by the mosaic landscape. Tree-crop policies should take account of the geographical distribution of tree-commodity production at landscape level and its implications for food production and ecosystems services.

Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes

EPA Science Inventory

Wetland ecosystems straddle both terrestrial and aquatic habitats, performing many ecological functions directly and indirectly benefitting humans. However, global wetland losses are substantial. Satellite remote sensing and classification informs wise wetland management and moni...

Wetland Hydrologic Connectivity to Downstream Waters: A Classification Approach and National Assessment

EPA Science Inventory

Connectivity has become a major focus of hydrological and ecological studies. Connectivity influences fluxes between landscape elements, while isolation reduces flows between elements. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrolo...

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.

Assessment of geostatistical features for object-based image classification of contrasted landscape vegetation cover

NASA Astrophysics Data System (ADS)

de Oliveira Silveira, Eduarda Martiniano; de Menezes, Michele Duarte; Acerbi Júnior, Fausto Weimar; Castro Nunes Santos Terra, Marcela; de Mello, José Márcio

2017-07-01

Accurate mapping and monitoring of savanna and semiarid woodland biomes are needed to support the selection of areas of conservation, to provide sustainable land use, and to improve the understanding of vegetation. The potential of geostatistical features, derived from medium spatial resolution satellite imagery, to characterize contrasted landscape vegetation cover and improve object-based image classification is studied. The study site in Brazil includes cerrado sensu stricto, deciduous forest, and palm swamp vegetation cover. Sentinel 2 and Landsat 8 images were acquired and divided into objects, for each of which a semivariogram was calculated using near-infrared (NIR) and normalized difference vegetation index (NDVI) to extract the set of geostatistical features. The features selected by principal component analysis were used as input data to train a random forest algorithm. Tests were conducted, combining spectral and geostatistical features. Change detection evaluation was performed using a confusion matrix and its accuracies. The semivariogram curves were efficient to characterize spatial heterogeneity, with similar results using NIR and NDVI from Sentinel 2 and Landsat 8. Accuracy was significantly greater when combining geostatistical features with spectral data, suggesting that this method can improve image classification results.

Delineation, characterization, and classification of topographic eminences

NASA Astrophysics Data System (ADS)

Sinha, Gaurav

Topographic eminences are defined as upwardly rising, convex shaped topographic landforms that are noticeably distinct in their immediate surroundings. As opposed to everyday objects, the properties of a topographic eminence are dependent not only on how it is conceptualized, but is also intrinsically related to its spatial extent and its relative location in the landscape. In this thesis, a system for automated detection, delineation and characterization of topographic eminences based on an analysis of digital elevation models is proposed. Research has shown that conceptualization of eminences (and other landforms) is linked to the cultural and linguistic backgrounds of people. However, the perception of stimuli from our physical environment is not subject to cultural or linguistic bias. Hence, perceptually salient morphological and spatial properties of the natural landscape can form the basis for generically applicable detection and delineation of topographic eminences. Six principles of cognitive eminence modeling are introduced to develop the philosophical foundation of this research regarding eminence delineation and characterization. The first step in delineating eminences is to automatically detect their presence within digital elevation models. This is achieved by the use of quantitative geomorphometric parameters (e.g., elevation, slope and curvature) and qualitative geomorphometric features (e.g., peaks, passes, pits, ridgelines, and valley lines). The process of eminence delineation follows that of eminence detection. It is posited that eminences may be perceived either as monolithic terrain objects, or as composites of morphological parts (e.g., top, bottom, slope). Individual eminences may also simultaneously be conceived as comprising larger, higher order eminence complexes (e.g., mountain ranges). Multiple algorithms are presented for the delineation of simple and complex eminences, and the morphological parts of eminences. The proposed eminence detection and delineation methods are amenable to intuitive parameterization such that they can easily capture the multitude of eminence conceptualizations that people develop due to differences in terrain type and cultural and linguistic backgrounds. Eminence delineation is an important step in object based modeling of the natural landscape. However, mere 'geocoding' of eminences is not sufficient for modeling how people intuitively perceive and reason about eminences. Therefore, a comprehensive eminence parameterization system for characterizing the perceptual properties of eminences is also proposed in this thesis. Over 40 parameters are suggested for measuring the commonly perceived properties of eminences: size, shape, topology, proximity, and visibility. The proposed parameters describe different aspects of naive eminence perception. Quantitative analysis of eminence parameters using cluster analysis, confirms that not only can eminences be parameterized as individual terrain objects, but that eminence (dis)similarities can be exploited to develop intuitive eminence classification systems. Eminence parameters are also shown to be essential for exploring the relationships between extracted eminences and natural language terms (e.g., hill, mount, mountain, peak) used commonly to refer to different types of eminences. The results from this research confirm that object based modeling of the landscape is not only useful for terrain information system design, but is also essential for understanding how people commonly conceptualize their observations of and interactions with the natural landscape.

A hierarchical approach to forest landscape pattern characterization.

PubMed

Wang, Jialing; Yang, Xiaojun

2012-01-01

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.

History of Soil Survey and Evolution of the Brazilian Soil Classification System - SiBCS

NASA Astrophysics Data System (ADS)

Cunha dos Anjos, Lúcia Helena; Csekö Nolasco de Carvalho, Claudia; Homem Antunes, Mauro Antonio; Muggler, Cristine Carole

2014-05-01

In Brazil soil surveys started around 1940 and the first map with soil information of São Paulo State was published in 1943. The Committee of Soils of the National Service for Agronomic Research was created in 1947 by the Agriculture Ministry and became an historical landmark for soil survey in Brazil. In 1953, the National Program of soil survey was approved and the first soil map and report of Rio de Janeiro State was released in 1958, followed by São Paulo State in 1960. This is also the origin of Embrapa Soil Research institution. Other milestones were the soil surveys published by the Agronomic Institute of Campinas (IAC) and the natural resources studies published within the RADAMBRASIL Project, initially planned for the Amazon region and later covering the whole country. Many soil studies followed and a comprehensive knowledge of tropical soils was achieved resulting in successful technologies for agriculture production, in lands considered by many as of "low fertility and acid soils with limited or no agricultural potential". However, detailed soil surveys are still lacking; only 5% of the country soils are mapped in 1:25.000 scales, and 15-20% in 1:100.000. In the first soil survey reports of Rio de Janeiro (1958) and São Paulo (1960), soil classes were defined according to Baldwin, Kellog & Thorp (Yearbook of Agriculture for 1938), and Thorp & Smith (Soil Science, 67, 1949) publications. It was already clear that the existing classification systems were not adequate to represent the highly weathered tropical soils of the large old landscapes in the cerrado (savanna like) region, or the soils formed on recent hydromorphic conditions at the Amazon Basin and Pantanal region. A national classification system to embody the country's large territory and environmental variation from tropical to subtropical and semiarid conditions, as well as the diversity of soil forming processes in old and new landscapes had to be developed. In 1964, the first attempt of a national soil classification was presented by Marcelo Camargo (Embrapa Soils) and Jacob Bennema (FAO adviser). When Soil Taxonomy was first published in 1975, a field workshop was held in Brazil, and the system was not accepted by the country scientists; one main reason was the usage of climate as a main attribute for suborders. In 1978, the first national soil field correlation meeting was held with the goal of developing the national system, giving origin to the Brazilian Soil Classification System (SiBCS). In 1980, a working group was created by Embrapa Soils and other institutes resulting in four approximations of the system. In 1999, the first edition of the SiBCS was released, followed by a second edition in 2006 and the third in 2013. The SiBCS is a hierarchic system, based on morphogenetic soil attributes, with six categorical levels: order, suborder, great group, subgroup, family, and series. It has 13 soil orders, and it is structured as a key down to subgroup level. Many soil attributes are based on concepts adopted by the Soil Taxonomy (United States) and by the World Reference Base for Soil Resources (WRB - FAO). The development of the SiBCS is supervised by a national executive committee, and information is available at http://www.cnps.embrapa.br/sibcs (in Portuguese).

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

Hollingsworth, LaWen T.; Kurth, Laurie,; Parresol, Bernard, R.

Landscape-scale fire behavior analyses are important to inform decisions on resource management projects that meet land management objectives and protect values from adverse consequences of fire. Deterministic and probabilistic geospatial fire behavior analyses are conducted with various modeling systems including FARSITE, FlamMap, FSPro, and Large Fire Simulation System. The fundamental fire intensity algorithms in these systems require surface fire behavior fuel models and canopy cover to model surface fire behavior. Canopy base height, stand height, and canopy bulk density are required in addition to surface fire behavior fuel models and canopy cover to model crown fire activity. Several surface fuelmore » and canopy classification efforts have used various remote sensing and ecological relationships as core methods to develop the spatial layers. All of these methods depend upon consistent and temporally constant interpretations of crown attributes and their ecological conditions to estimate surface fuel conditions. This study evaluates modeled fire behavior for an 80,000 ha tract of land in the Atlantic Coastal Plain of the southeastern US using three different data sources. The Fuel Characteristic Classification System (FCCS) was used to build fuelbeds from intensive field sampling of 629 plots. Custom fire behavior fuel models were derived from these fuelbeds. LANDFIRE developed surface fire behavior fuel models and canopy attributes for the US using satellite imagery informed by field data. The Southern Wildfire Risk Assessment (SWRA) developed surface fire behavior fuel models and canopy cover for the southeastern US using satellite imagery. Differences in modeled fire behavior, data development, and data utility are summarized to assist in determining which data source may be most applicable for various land management activities and required analyses. Characterizing fire behavior under different fuel relationships provides insights for natural ecological processes, management strategies for fire mitigation, and positive and negative features of different modeling systems. A comparison of flame length, rate of spread, crown fire activity, and burn probabilities modeled with FlamMap shows some similar patterns across the landscape from all three data sources, but there are potentially important differences. All data sources showed an expected range of fire behavior. Average flame lengths ranged between 1 and 1.4 m. Rate of spread varied the greatest with a range of 2.4-5.7 m min{sup -1}. Passive crown fire was predicted for 5% of the study area using FCCS and LANDFIRE while passive crown fire was not predicted using SWRA data. No active crown fire was predicted regardless of the data source. Burn probability patterns across the landscape were similar but probability was highest using SWRA and lowest using FCCS.« less

Modeling urban land development as a continuum to address fine-grained habitat heterogeneity

Treesearch

P.N. Manley; S.A. Parks; Lori Campbell; M.D. Schlesinger

2009-01-01

Natural landscapes are increasingly subjected to impacts associated with urbanization, resulting in loss and degradation of native ecosystems and biodiversity. Traditional classification approaches to the characterization of urbanization may prove inadequate in some human-modified...

Determination of critical habitat for the endangered Nelson's bighorn sheep in southern California

USGS Publications Warehouse

Turner, J.C.; Douglas, C.L.; Hallum, C.R.; Krausman, P.R.; Ramey, R.R.

2004-01-01

The United States Fish and Wildlife Service's (USFWS) designation of critical habitat for the endangered Nelson's bighorn sheep (Ovis canadensis nelsoni) in the Peninsular Ranges of southern California has been controversial because of an absence of a quantitative, repeatable scientific approach to the designation of critical habitat. We used 12,411 locations of Nelson's bighorn sheep collected from 1984-1998 to evaluate habitat use within 398 km2 of the USFWS-designated critical habitat in the northern Santa Rosa Mountains, Riverside County, California. We developed a multiple logistic regression model to evaluate and predict the probability of bighorn use versus non-use of native landscapes. Habitat predictor variables included elevation, slope, ruggedness, slope aspect, proximity to water, and distance from minimum expanses of escape habitat. We used Earth Resources Data Analysis System Geographic Information System (ERDAS-GIS) software to view, retrieve, and format predictor values for input to the Statistical Analysis Systems (SAS) software. To adequately account for habitat landscape diversity, we carried out an unsupervised classification at the outset of data inquiry using a maximum-likelihood clustering scheme implemented in ERDAS. We used the strata resulting from the unsupervised classification in a stratified random sampling scheme to minimize data loads required for model development. Based on 5 predictor variables, the habitat model correctly classified >96% of observed bighorn sheep locations. Proximity to perennial water was the best predictor variable. Ninety-seven percent of the observations were within 3 km of perennial water. Exercising the model over the northern Santa Rosa Mountain study area provided probabilities of bighorn use at a 30 x 30-m2 pixel level. Within the 398 km 2 of USFWS-designated critical habitat, only 34% had a graded probability of bighorn use to non-use ranging from ???1:1 to 6,044:1. The remaining 66% of the study area had odds of having bighorn use <1:1 or it was more likely not to be used by bighorn sheep. The USFWS designation of critical habitat included areas (45 km2) of importance (2.5 to ???40 observations per km2 per year) to Nelson's bighorn sheep and large landscapes (353 km2) that do not appear to be used (<1 observation per km2 per year).

Spring distributions and relationships with land cover and hydrogeologic strata in a karst landscape in Winona County, Minnesota, USA

USGS Publications Warehouse

Williams, M.A.; Vondracek, B.

2010-01-01

Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota USA, a karst landscape. Nearestneighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology. ?? 2010 Springer-Verlag.

Spring distribution in Winona County, Minnesota, USA and the relationship with geologic strata in a karst landscape

USGS Publications Warehouse

Vondracek, Bruce C.; Williams, Mary A.

2010-01-01

Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota, USA, a karst landscape. Nearest-neighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology.

The ITE Land classification: Providing an environmental stratification of Great Britain.

PubMed

Bunce, R G; Barr, C J; Gillespie, M K; Howard, D C

1996-01-01

The surface of Great Britain (GB) varies continuously in land cover from one area to another. The objective of any environmentally based land classification is to produce classes that match the patterns that are present by helping to define clear boundaries. The more appropriate the analysis and data used, the better the classes will fit the natural patterns. The observation of inter-correlations between ecological factors is the basis for interpreting ecological patterns in the field, and the Institute of Terrestrial Ecology (ITE) Land Classification formalises such subjective ideas. The data inevitably comprise a large number of factors in order to describe the environment adequately. Single factors, such as altitude, would only be useful on a national basis if they were the only dominant causative agent of ecological variation.The ITE Land Classification has defined 32 environmental categories called 'land classes', initially based on a sample of 1-km squares in Great Britain but subsequently extended to all 240 000 1-km squares. The original classification was produced using multivariate analysis of 75 environmental variables. The extension to all squares in GB was performed using a combination of logistic discrimination and discriminant functions. The classes have provided a stratification for successive ecological surveys, the results of which have characterised the classes in terms of botanical, zoological and landscape features.The classification has also been applied to integrate diverse datasets including satellite imagery, soils and socio-economic information. A variety of models have used the structure of the classification, for example to show potential land use change under different economic conditions. The principal data sets relevant for planning purposes have been incorporated into a user-friendly computer package, called the 'Countryside Information System'.

Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy

USGS Publications Warehouse

Beland, Michael; Roberts, Dar A.; Peterson, Seth H.; Biggs, Trent W.; Kokaly, Raymond F.; Piazza, Sarai; Roth, Keely L.; Khanna, Shruti; Ustin, Susan L.

2016-01-01

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes.Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines.CDA discriminated dominant species with a high level of accuracy (overall accuracy = 82%, kappa = 0.78) and consistency over three imaging dates (overall2010 = 82%, overall2011 = 82%, overall2012 = 88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (≤ 28 m from shore) for all three dates (2010 = 79%, 2011 = 61%, 2012 = 63%), followed by Juncus roemerianus (2010 = 11%, 2011 = 19%, 2012 = 17%) and Distichlis spicata (2010 = 4%, 2011 = 10%, 2012 = 7%).Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604 m2) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position.

Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: "The Forest Pulse".

PubMed

Olivero, Jesús; Ferri, Francisco; Acevedo, Pelayo; Lobo, Jorge M; Fa, John E; Farfán, Miguel Á; Romero, David; Real, Raimundo

2016-12-01

Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as "The Forest Pulse". These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a consequence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing, overall hunting, and more specifically the hunting of primates, Mazama americana, Dasyprocta fuliginosa, and Tayassu pecari. Our results showed that TEK-based approaches can serve as a basis for validating the livelihood relevance of landscapes in high-value conservation areas, which can form the basis for furthering the management of natural resources in these regions.

Identifying socio-ecological networks in rural-urban gradients: Diagnosis of a changing cultural landscape.

PubMed

Arnaiz-Schmitz, C; Schmitz, M F; Herrero-Jáuregui, C; Gutiérrez-Angonese, J; Pineda, F D; Montes, C

2018-01-15

Socio-ecological systems maintain reciprocal interactions between biophysical and socioeconomic structures. As a result of these interactions key essential services for society emerge. Urban expansion is a direct driver of land change and cause serious shifts in socio-ecological relationships and the associated lifestyles. The framework of rural-urban gradients has proved to be a powerful tool for ecological research about urban influences on ecosystems and on sociological issues related to social welfare. However, to date there has not been an attempt to achieve a classification of municipalities in rural-urban gradients based on socio-ecological interactions. In this paper, we developed a methodological approach that allows identifying and classifying a set of socio-ecological network configurations in the Region of Madrid, a highly dynamic cultural landscape considered one of the European hotspots in urban development. According to their socio-ecological links, the integrated model detects four groups of municipalities, ordered along a rural-urban gradient, characterized by their degree of biophysical and socioeconomic coupling and different indicators of landscape structure and social welfare. We propose the developed model as a useful tool to improve environmental management schemes and land planning from a socio-ecological perspective, especially in territories subject to intense urban transformations and loss of rurality. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a Digital Aquifer Permeability Map for the ...

EPA Pesticide Factsheets

Researchers at the U.S. Environmental Protection Agency’s Western Ecology Division have been developing hydrologic landscape maps for selected U.S. states in an effort to create a method to identify the intrinsic watershed attributes of landscapes in regions with little data. Each hydrologic landscape unit is assigned a categorical value from five key indices of macro-scale hydrologic behavior, including annual climate, climate seasonality, aquifer permeability, terrain, and soil permeability. The aquifer permeability index requires creation of a from-scratch dataset for each state. The permeability index for the Pacific Southwest (California, Nevada, and Arizona) expands and modifies the permeability index for the Pacific Northwest (Oregon, Washington, and Idaho), which preceded it. The permeability index was created by assigning geologic map units to one of 18 categories with presumed similar values of permeability to create a hydrolithologic map. The hydrolithologies were then further categorized into permeability index classifications of high, low, unknown and surface water. Unconsolidated, carbonate, volcanic, and undifferentiated units are classified more conservatively to better address uncertainty in source data. High vs. low permeability classifications are assigned qualitatively but follow a threshold guideline of 8.5x10-2 m/day hydraulic conductivity. Estimates of permeability from surface lithology is the current best practice for broad-sca

Estimating greenhouse gas emissions at the soil-atmosphere interface in forested watersheds of the US Northeast.

PubMed

Gomez, Joshua; Vidon, Philippe; Gross, Jordan; Beier, Colin; Caputo, Jesse; Mitchell, Myron

2016-05-01

Although anthropogenic emissions of greenhouse gases (GHG: CO2, CH4, N2O) are unequivocally tied to climate change, natural systems such as forests have the potential to affect GHG concentration in the atmosphere. Our study reports GHG emissions as CO2, CH4, N2O, and CO2eq fluxes across a range of landscape hydrogeomorphic classes (wetlands, riparian areas, lower hillslopes, upper hillslopes) in a forested watershed of the Northeastern USA and assesses the usability of the topographic wetness index (TWI) as a tool to identify distinct landscape geomorphic classes to aid in the development of GHG budgets at the soil atmosphere interface at the watershed scale. Wetlands were hot spots of GHG production (in CO2eq) in the landscape owing to large CH4 emission. However, on an areal basis, the lower hillslope class had the greatest influence on the net watershed CO2eq efflux, mainly because it encompassed the largest proportion of the study watershed (54 %) and had high CO2 fluxes relative to other land classes. On an annual basis, summer, fall, winter, and spring accounted for 40, 27, 9, and 24 % of total CO2eq emissions, respectively. When compared to other approaches (e.g., random or systematic sampling design), the TWI landscape classification method was successful in identifying dominant landscape hydrogeomorphic classes and offered the possibility of systematically accounting for small areas of the watershed (e.g., wetlands) that have a disproportionate effect on total GHG emissions. Overall, results indicate that soil CO2eq efflux in the Archer Creek Watershed may exceed C uptake by live trees under current conditions.

Impacts of Landscape Context on Patterns of Wind Downfall Damage in a Fragmented Amazonian Landscape

NASA Astrophysics Data System (ADS)

Schwartz, N.; Uriarte, M.; DeFries, R. S.; Gutierrez-Velez, V. H.; Fernandes, K.; Pinedo-Vasquez, M.

2015-12-01

Wind is a major disturbance in the Amazon and has both short-term impacts and lasting legacies in tropical forests. Observed patterns of damage across landscapes result from differences in wind exposure and stand characteristics, such as tree stature, species traits, successional age, and fragmentation. Wind disturbance has important consequences for biomass dynamics in Amazonian forests, and understanding the spatial distribution and size of impacts is necessary to quantify the effects on carbon dynamics. In November 2013, a mesoscale convective system was observed over the study area in Ucayali, Peru, a highly human modified and fragmented forest landscape. We mapped downfall damage associated with the storm in order to ask: how does the severity of damage vary within forest patches, and across forest patches of different sizes and successional ages? We applied spectral mixture analysis to Landsat images from 2013 and 2014 to calculate the change in non-photosynthetic vegetation fraction after the storm, and combined it with C-band SAR data from the Sentinel-1 satellite to predict downfall damage measured in 30 field plots using random forest regression. We then applied this model to map damage in forests across the study area. Using a land cover classification developed in a previous study, we mapped secondary and mature forest, and compared the severity of damage in the two. We found that damage was on average higher in secondary forests, but patterns varied spatially. This study demonstrates the utility of using multiple sources of satellite data for mapping wind disturbance, and adds to our understanding of the sources of variation in wind-related damage. Ultimately, an improved ability to map wind impacts and a better understanding of their spatial patterns can contribute to better quantification of carbon dynamics in Amazonian landscapes.

Field Guide to the Plant Community Types of Voyageurs National Park

USGS Publications Warehouse

Faber-Langendoen, Don; Aaseng, Norman; Hop, Kevin; Lew-Smith, Michael

2007-01-01

INTRODUCTION The objective of the U.S. Geological Survey-National Park Service Vegetation Mapping Program is to classify, describe, and map vegetation for most of the park units within the National Park Service (NPS). The program was created in response to the NPS Natural Resources Inventory and Monitoring Guidelines issued in 1992. Products for each park include digital files of the vegetation map and field data, keys and descriptions to the plant communities, reports, metadata, map accuracy verification summaries, and aerial photographs. Interagency teams work in each park and, following standardized mapping and field sampling protocols, develop products and vegetation classification standards that document the various vegetation types found in a given park. The use of a standard national vegetation classification system and mapping protocol facilitate effective resource stewardship by ensuring compatibility and widespread use of the information throughout the NPS as well as by other Federal and state agencies. These vegetation classifications and maps and associated information support a wide variety of resource assessment, park management, and planning needs, and provide a structure for framing and answering critical scientific questions about plant communities and their relation to environmental processes across the landscape. This field guide is intended to make the classification accessible to park visitors and researchers at Voyageurs National Park, allowing them to identify any stand of natural vegetation and showing how the classification can be used in conjunction with the vegetation map (Hop and others, 2001).

Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird.

PubMed

Khimoun, Aurélie; Peterman, William; Eraud, Cyril; Faivre, Bruno; Navarro, Nicolas; Garnier, Stéphane

2017-10-01

Within the framework of landscape genetics, resistance surface modelling is particularly relevant to explicitly test competing hypotheses about landscape effects on gene flow. To investigate how fragmentation of tropical forest affects population connectivity in a forest specialist bird species, we optimized resistance surfaces without a priori specification, using least-cost (LCP) or resistance (IBR) distances. We implemented a two-step procedure in order (i) to objectively define the landscape thematic resolution (level of detail in classification scheme to describe landscape variables) and spatial extent (area within the landscape boundaries) and then (ii) to test the relative role of several landscape features (elevation, roads, land cover) in genetic differentiation in the Plumbeous Warbler (Setophaga plumbea). We detected a small-scale reduction of gene flow mainly driven by land cover, with a negative impact of the nonforest matrix on landscape functional connectivity. However, matrix components did not equally constrain gene flow, as their conductivity increased with increasing structural similarity with forest habitat: urban areas and meadows had the highest resistance values whereas agricultural areas had intermediate resistance values. Our results revealed a higher performance of IBR compared to LCP in explaining gene flow, reflecting suboptimal movements across this human-modified landscape, challenging the common use of LCP to design habitat corridors and advocating for a broader use of circuit theory modelling. Finally, our results emphasize the need for an objective definition of landscape scales (landscape extent and thematic resolution) and highlight potential pitfalls associated with parameterization of resistance surfaces. © 2017 John Wiley & Sons Ltd.

Image Classification for Web Genre Identification

DTIC Science & Technology

2012-01-01

recognition and landscape detection using the computer vision toolkit OpenCV1. For facial recognition , we researched the possibilities of using the...method for connecting these names with a face/personal photo and logo respectively. [2] METHODOLOGY For this project, we focused primarily on facial

State-and-transition models for heterogeneous landscapes: A strategy for development and application

USDA-ARS?s Scientific Manuscript database

Interpretation of assessment and monitoring data requires information about reference conditions and ecological resilience. Reference conditions used as benchmarks can be specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially obser...

EFFECTS OF LANDSCAPE CHARACTERISTICS ON LAND-COVER CLASS ACCURACY

EPA Science Inventory

Utilizing land-cover data gathered as part of the National Land-Cover Data (NLCD) set accuracy assessment, several logistic regression models were formulated to analyze the effects of patch size and land-cover heterogeneity on classification accuracy. Specific land-cover ...

Profile of a city: characterizing and classifying urban soils in the city of Ghent

NASA Astrophysics Data System (ADS)

Delbecque, Nele; Verdoodt, Ann

2017-04-01

Worldwide, urban lands are expanding rapidly. Conversion of agricultural and natural landscapes to urban fabric can strongly influence soil properties through soil sealing, excavation, leveling, contamination, waste disposal and land management. Urban lands, often characterized by intensive use, need to deliver many production, ecological and cultural ecosystem services. To safeguard this natural capital for future generations, an improved understanding of biogeochemical characteristics, processes and functions of urban soils in time and space is essential. Additionally, existing (inter)national soil classification systems, based on the identification of soil genetic horizons, do not always allow a functional classification of urban soils. This research aims (1) to gain insight into urban soils and their properties in the city of Ghent (Belgium), and (2) to develop a procedure to functionally incorporate urban soils into existing (inter)national soil classification systems. Undisturbed soil cores (depth up to 1.25 m) are collected at 15 locations in Ghent with different times since development and land uses. Geotek MSCL-scans are taken to determine magnetic susceptibility and gamma density and to obtain high resolution images. Physico-chemical characterization of the soil cores is performed by means of detailed soil profile descriptions, traditional lab analyses, as well as proximal soil sensing techniques (XRF). The first results of this research will be presented and critically discussed to improve future efforts to characterize, classify and evaluate urban soils and their ecosystem services.

Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China.

PubMed

Yang, Qiquan; Huang, Xin; Li, Jiayi

2017-08-24

The urban heat island (UHI) effect exerts a great influence on the Earth's environment and human health and has been the subject of considerable attention. Landscape patterns are among the most important factors relevant to surface UHIs (SUHIs); however, the relationship between SUHIs and landscape patterns is poorly understood over large areas. In this study, the surface UHI intensity (SUHII) is defined as the temperature difference between urban and suburban areas, and the landscape patterns are quantified by the urban-suburban differences in several typical landscape metrics (ΔLMs). Temperature and land-cover classification datasets based on satellite observations were applied to analyze the relationship between SUHII and ΔLMs in 332 cities/city agglomerations distributed in different climatic zones of China. The results indicate that SUHII and its correlations with ΔLMs are profoundly influenced by seasonal, diurnal, and climatic factors. The impacts of different land-cover types on SUHIs are different, and the landscape patterns of the built-up and vegetation (including forest, grassland, and cultivated land) classes have the most significant effects on SUHIs. The results of this study will help us to gain a deeper understanding of the relationship between the SUHI effect and landscape patterns.

Land use changing and land use optimization of Lake Baikal basin on the example of two key areas

NASA Astrophysics Data System (ADS)

Solodyankina, S.

2012-04-01

Lake Baikal contains roughly 20% of the world's unfrozen surface fresh water. It was declared a UNESCO World Heritage Site in 1996. Today levels of urbanization and economic stress on environmental resources is increasing on the shorts of the lake Baikal. The potential of economic development (industry, local tourism, and mining) of the Severobaykalsky and Sludyansky districts is rather high although they are characterized not only by beneficial features for local economy but also by considerable disadvantages for nature of this world valuable territory. This investigation show human-caused landscape changes during economic development of the two key areas in Baikal water catchment basin during 10 years (point of reference is 2000 year). Key areas are 1) the Baikalo-Patomskoe highland in the north of the Baikal catchment basin (Severobaykalsky district, Republic of Buryatia); 2) Khamar-Daban mountain system in the south of the Baikal catchment basin (Sludyansky districy, Irkutsk region). Since 2000 year land use of the territory has changed. Areas of agriculture were reduced but recreation activity on the bank of the lake was increased. Methods of GIS analysis and local statistic analysis of landscape characteristic were used. Nature, rural and urban areas ratio are estimated. Vegetation and soil condition assessment were made. The essence of this research is in helping to make decisions linked to upcoming problems: situation identification, evaluation and forecasting of the potential landscape condition, optimization of land use, mitigation of impact and mapping of territories and nature resources which have a high ecological value or endangered by industrial impact. For this purpose landscape maps of the territories on the base of the remote sensing information and field investigations were created. They used to calculate potential landscape functions of the territory without taking into account present impact of anthropogenic actions. Land use maps for years 2000 and 2010 were created to show: 1) how many landscape functions (ecosystem services) have been missed in time period of 2000-2010 years; 2) trends of land use changing. The nature-anthropogenic landscapes classification is developed, where natural and anthropogenic factors are taken into account in one system. It used to considerate of cumulative impacts of anthropogenic actions for each relevant resource, and to analyse of all past, present, and reasonably foreseeable future condition of whole landscape and its components (parent rock, surface and ground water, soil, flora and fauna, air).

Toward a Rapid Synthesis of Field and Desktop Data for Classifying Streams in the Pacific Northwest: Guiding the Sampling and Management of Salmonid Habitat

NASA Astrophysics Data System (ADS)

Kasprak, A.; Wheaton, J. M.; Bouwes, N.; Weber, N. P.; Trahan, N. C.; Jordan, C. E.

2012-12-01

River managers often seek to understand habitat availability and quality for riverine organisms within the physical template provided by their landscape. Yet the large amount of natural heterogeneity in landscapes gives rise to stream systems which are highly variable over small spatial scales, potentially complicating site selection for surveying aquatic habitat while simultaneously making a simple, wide-reaching management strategy elusive. This is particularly true in the rugged John Day River Basin of northern Oregon, where efforts as part of the Columbia Habitat Monitoring Program to conduct site-based surveys of physical habitat for endangered steelhead salmon (Oncorhynchus mykiss) are underway. As a complete understanding of the type and distribution of habitat available to these fish would require visits to all streams in the basin (impractical due to its large size), here we develop an approach for classifying channel types which combines remote desktop GIS analyses with rapid field-based stream and landscape surveys. At the core of this method, we build off of the River Styles Framework, an open-ended and process-based approach for classifying streams and informing management decisions. This framework is combined with on-the-ground fluvial audits, which aim to quickly and continuously map sediment dynamics and channel behavior along selected channels. Validation of this classification method is completed by on-the-ground stream surveys using a digital iPad platform and by rapid small aircraft overflights to confirm or refine predictions. We further compare this method with existing channel classification approaches for the region (e.g. Beechie, Montgomery and Buffington). The results of this study will help guide both the refinement of site stratification and selection for salmonid habitat monitoring within the basin, and will be vital in designing and prioritizing restoration and management strategies tailored to the distribution of river styles found across the region.

Assessment of Acacia Koa Forest Health across Environmental Gradients in Hawai‘i Using Fine Resolution Remote Sensing and GIS

PubMed Central

Morales, Rodolfo Martinez; Idol, Travis; Friday, James B.

2011-01-01

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai‘ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600–1,000 m asl in the island of Kaua‘i, which correspond to gradients of temperature and rainfall ranging from 17–20 °C mean annual temperature and 750–1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai‘i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species. PMID:22163920

A global view of shifting cultivation: Recent, current, and future extent

PubMed Central

Mertz, Ole; Frolking, Steve; Egelund Christensen, Andreas; Hurni, Kaspar; Sedano, Fernando; Parsons Chini, Louise; Sahajpal, Ritvik; Hansen, Matthew; Hurtt, George

2017-01-01

Mosaic landscapes under shifting cultivation, with their dynamic mix of managed and natural land covers, often fall through the cracks in remote sensing–based land cover and land use classifications, as these are unable to adequately capture such landscapes’ dynamic nature and complex spectral and spatial signatures. But information about such landscapes is urgently needed to improve the outcomes of global earth system modelling and large-scale carbon and greenhouse gas accounting. This study combines existing global Landsat-based deforestation data covering the years 2000 to 2014 with very high-resolution satellite imagery to visually detect the specific spatio-temporal pattern of shifting cultivation at a one-degree cell resolution worldwide. The accuracy levels of our classification were high with an overall accuracy above 87%. We estimate the current global extent of shifting cultivation and compare it to other current global mapping endeavors as well as results of literature searches. Based on an expert survey, we make a first attempt at estimating past trends as well as possible future trends in the global distribution of shifting cultivation until the end of the 21st century. With 62% of the investigated one-degree cells in the humid and sub-humid tropics currently showing signs of shifting cultivation—the majority in the Americas (41%) and Africa (37%)—this form of cultivation remains widespread, and it would be wrong to speak of its general global demise in the last decades. We estimate that shifting cultivation landscapes currently cover roughly 280 million hectares worldwide, including both cultivated fields and fallows. While only an approximation, this estimate is clearly smaller than the areas mentioned in the literature which range up to 1,000 million hectares. Based on our expert survey and historical trends we estimate a possible strong decrease in shifting cultivation over the next decades, raising issues of livelihood security and resilience among people currently depending on shifting cultivation. PMID:28886132

Enhanced-Resolution Satellite Microwave Brightness Temperature Records for Mapping Boreal-Arctic Landscape Freeze-Thaw Heterogeneity

NASA Astrophysics Data System (ADS)

Kim, Y.; Du, J.; Kimball, J. S.

2017-12-01

The landscape freeze-thaw (FT) status derived from satellite microwave remote sensing is closely linked to vegetation phenology and productivity, surface energy exchange, evapotranspiration, snow/ice melt dynamics, and trace gas fluxes over land areas affected by seasonally frozen temperatures. A long-term global satellite microwave Earth System Data Record of daily landscape freeze-thaw status (FT-ESDR) was developed using similar calibrated 37GHz, vertically-polarized (V-pol) brightness temperatures (Tb) from SMMR, SSM/I, and SSMIS sensors. The FT-ESDR shows mean annual spatial classification accuracies of 90.3 and 84.3 % for PM and AM overpass retrievals relative surface air temperature (SAT) measurement based FT estimates from global weather stations. However, the coarse FT-ESDR gridding (25-km) is insufficient to distinguish finer scale FT heterogeneity. In this study, we tested alternative finer scale FT estimates derived from two enhanced polar-grid (3.125-km and 6-km resolution), 36.5 GHz V-pol Tb records derived from calibrated AMSR-E and AMSR2 sensor observations. The daily FT estimates are derived using a modified seasonal threshold algorithm that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using ERA-Interim reanalysis based SAT, downscaled using a digital terrain map and estimated temperature lapse rates. The resulting polar-grid FT records for a selected study year (2004) show mean annual spatial classification accuracies of 90.1% (84.2%) and 93.1% (85.8%) for respective PM (AM) 3.125km and 6-km Tb retrievals relative to in situ SAT measurement based FT estimates from regional weather stations. Areas with enhanced FT accuracy include water-land boundaries and mountainous terrain. Differences in FT patterns and relative accuracy obtained from the enhanced grid Tb records were attributed to several factors, including different noise contributions from underlying Tb processing and spatial mismatches between Tb retrievals and SAT calibrated FT thresholds.

Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape

NASA Astrophysics Data System (ADS)

Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis

2011-11-01

The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing

NASA Astrophysics Data System (ADS)

O'Connell, Jerome; Bradter, Ute; Benton, Tim G.

2015-11-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ˜22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.

Identification and characterization of agro-ecological infrastructures by remote sensing

NASA Astrophysics Data System (ADS)

Ducrot, D.; Duthoit, S.; d'Abzac, A.; Marais-Sicre, C.; Chéret, V.; Sausse, C.

2015-10-01

Agro-Ecological Infrastructures (AEIs) include many semi-natural habitats (hedgerows, grass strips, grasslands, thickets…) and play a key role in biodiversity preservation, water quality and erosion control. Indirect biodiversity indicators based on AEISs are used in many national and European public policies to analyze ecological processes. The identification of these landscape features is difficult and expensive and limits their use. Remote sensing has a great potential to solve this problem. In this study, we propose an operational tool for the identification and characterization of AEISs. The method is based on segmentation, contextual classification and fusion of temporal classifications. Experiments were carried out on various temporal and spatial resolution satellite data (20-m, 10-m, 5-m, 2.5-m, 50-cm), on three French regions southwest landscape (hilly, plain, wooded, cultivated), north (open-field) and Brittany (farmland closed by hedges). The results give a good idea of the potential of remote sensing image processing methods to map fine agro-ecological objects. At 20-m spatial resolution, only larger hedgerows and riparian forests are apparent. Classification results show that 10-m resolution is well suited for agricultural and AEIs applications, most hedges, forest edges, thickets can be detected. Results highlight the multi-temporal data importance. The future Sentinel satellites with a very high temporal resolution and a 10-m spatial resolution should be an answer to AEIs detection. 2.50-m resolution is more precise with more details. But treatments are more complicated. At 50-cm resolution, accuracy level of details is even higher; this amplifies the difficulties previously reported. The results obtained allow calculation of statistics and metrics describing landscape structures.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing.

PubMed

O'Connell, Jerome; Bradter, Ute; Benton, Tim G

2015-11-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer ( Emberiza citronella ), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m 2 . The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.

Combined use of SAR and optical data for environmental assessments around refugee camps in semiarid landscapes

NASA Astrophysics Data System (ADS)

Braun, A.; Hochschild, V.

2015-04-01

Over 15 million people were officially considered as refugees in the year 2012 and another 28 million as internally displaced people (IDPs). Natural disasters, climatic and environmental changes, violent regional conflicts and population growth force people to migrate in all parts of this world. This trend is likely to continue in the near future, as political instabilities increase and land degradation progresses. EO4HumEn aims at developing operational services to support humanitarian operations during crisis situations by means of dedicated geo-spatial information products derived from Earth observation and GIS data. The goal is to develop robust, automated methods of image analysis routines for population estimation, identification of potential groundwater extraction sites and monitoring the environmental impact of refugee/IDP camps. This study investigates the combination of satellite SAR data with optical sensors and elevation information for the assessment of the environmental conditions around refugee camps. In order to estimate their impact on land degradation, land cover classifications are required which target dynamic landscapes. We performed a land use / land cover classification based on a random forest algorithm and 39 input prediction rasters based on Landsat 8 data and additional layers generated from radar texture and elevation information. The overall accuracy was 92.9 %, while optical data had the highest impact on the final classification. By analysing all combinations of the three input datasets we additionally estimated their impact on single classification outcomes and land cover classes.

GIS interpolations of witness tree records (1839-1866) for northern Wisconsin at multiple scales

USGS Publications Warehouse

He, H.S.; Mladenoff, D.J.; Sickley, T.A.; Guntenspergen, G.R.

2000-01-01

To construct forest landscape of pre-European settlement periods, we developed a GIS interpolation approach to convert witness tree records of the U.S. General Land Office (GLO) survey from point to polygon data, which better described continuously distributed vegetation. The witness tree records (1839-1866) were processed for a 3-million ha landscape in northern Wisconsin, U.S.A. at different scales. We provided implications of processing results at each scale. Compared with traditional GLO mapping that has fixed mapping scales and generalized classifications, our approach allows presettlement forest landscapes to be analysed at the individual species level and reconstructed under various classifications. We calculated vegetation indices including relative density, dominance, and importance value for each species, and quantitatively described the possible outcomes when GLO records are analysed at three different scales (resolution). The 1 x 1-section resolution preserved spatial information but derived the most conservative estimates of species distributions measured in percentage area, which increased at coarser resolutions. Such increases under the 2 x 2-section resolution were in the order of three to four times for the least common species, two to three times for the medium to most common species, and one to two times for the most common or highly contagious species. We marred the distributions of hemlock and sugar maple from the pre-European settlement period based on their witness tree locations and reconstructed presettlement forest landscapes based on species importance values derived for all species. The results provide a unique basis to further study land cover changes occurring after European settlement.

Predicting and quantifying soil processes using “geomorphon” landform Classification

USDA-ARS?s Scientific Manuscript database

Soil development and behavior vary spatially at multiple observation scales. Predicting and quantifying soil properties and processes via a catena integrates predictable landscape scale variation relevant to both management decisions and soil survey. Soil maps generally convey variation as a set of ...

Can ecological land classification increase the utility of vegetation monitoring data

USDA-ARS?s Scientific Manuscript database

Vegetation dynamics in rangelands and other ecosystems are known to be mediated by topoedaphic properties. Vegetation monitoring programs, however, often do not consider the impact of soils and other sources of landscape heterogeneity on the temporal patterns observed. Ecological sites (ES) comprise...

The 20th-Century Topographic Survey as Source Data for Long-Term Landscape Studies at Local and Regional Scales

USGS Publications Warehouse

Varanka, Dalia

2006-01-01

Historical topographic maps are the only systematically collected data resource covering the entire nation for long-term landscape change studies over the 20th century for geographical and environmental research. The paper discusses aspects of the historical U.S. Geological Survey topographic maps that present constraints on the design of a database for such studies. Problems involved in this approach include locating the required maps, understanding land feature classification differences between topographic vs. land use/land cover maps, the approximation of error between different map editions of the same area, and the identification of true changes on the landscape between time periods. Suggested approaches to these issues are illustrated using an example of such a study by the author.

Impact of atmospheric correction and image filtering on hyperspectral classification of tree species using support vector machine

NASA Astrophysics Data System (ADS)

Shahriari Nia, Morteza; Wang, Daisy Zhe; Bohlman, Stephanie Ann; Gader, Paul; Graves, Sarah J.; Petrovic, Milenko

2015-01-01

Hyperspectral images can be used to identify savannah tree species at the landscape scale, which is a key step in measuring biomass and carbon, and tracking changes in species distributions, including invasive species, in these ecosystems. Before automated species mapping can be performed, image processing and atmospheric correction is often performed, which can potentially affect the performance of classification algorithms. We determine how three processing and correction techniques (atmospheric correction, Gaussian filters, and shade/green vegetation filters) affect the prediction accuracy of classification of tree species at pixel level from airborne visible/infrared imaging spectrometer imagery of longleaf pine savanna in Central Florida, United States. Species classification using fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) atmospheric correction outperformed ATCOR in the majority of cases. Green vegetation (normalized difference vegetation index) and shade (near-infrared) filters did not increase classification accuracy when applied to large and continuous patches of specific species. Finally, applying a Gaussian filter reduces interband noise and increases species classification accuracy. Using the optimal preprocessing steps, our classification accuracy of six species classes is about 75%.

Mapping vegetation communities using statistical data fusion in the Ozark National Scenic Riverways, Missouri, USA

USGS Publications Warehouse

Chastain, R.A.; Struckhoff, M.A.; He, H.S.; Larsen, D.R.

2008-01-01

A vegetation community map was produced for the Ozark National Scenic Riverways consistent with the association level of the National Vegetation Classification System. Vegetation communities were differentiated using a large array of variables derived from remote sensing and topographic data, which were fused into independent mathematical functions using a discriminant analysis classification approach. Remote sensing data provided variables that discriminated vegetation communities based on differences in color, spectral reflectance, greenness, brightness, and texture. Topographic data facilitated differentiation of vegetation communities based on indirect gradients (e.g., landform position, slope, aspect), which relate to variations in resource and disturbance gradients. Variables derived from these data sources represent both actual and potential vegetation community patterns on the landscape. A hybrid combination of statistical and photointerpretation methods was used to obtain an overall accuracy of 63 percent for a map with 49 vegetation community and land-cover classes, and 78 percent for a 33-class map of the study area.

A hydrologically explicit, spatially exact, classification of landforms for Canada at 1:500,000 scale.

NASA Astrophysics Data System (ADS)

MacMillan, Robert A.; Geng, Xiaoyuan; Smith, Scott; Zawadzka, Joanna; Hengl, Tom

2016-04-01

A new approach for classifying landform types has been developed and applied to all of Canada using a 250 m DEM. The resulting LandMapR classification has been designed to provide a stable and consistent spatial fabric to act as initial proto-polygons to be used in updating the current 1:1 M scale Soil Landscapes of Canada map to 1:500,000 scale. There is a desire to make the current SLC polygon fabric more consistent across the country, more correctly aligned to observable hydrological and landscape features, more spatially exact, more detailed and more interpretable. The approach is essentially a modification of the Hammond (1954) criteria for classifying macro landform types as implemented for computerized analysis by Dikau (1989, 1991) and Brabyn (1998). The major modification is that the key input variables of local relief and relative position in the landscape are computed for specific hillslopes that occur between individual, explicitly defined, channels and divides. While most approaches, including Dikau et al., (1991) and SOTER (Dobos et al., 2005) compute relative relief and landscape position within a neighborhood analysis window (NAW) of some fixed size (9,600 m and 1 km respectively) the LandMapR method assesses these variables based on explicit analysis of flow paths between locally defined divides and channels (or lakes). We have modified the Hammond criteria by splitting the lowest relief class of 0-30 m into 4 classes of 0-0 m, 0-1 m, 1-10 m and 10-30 m) in order to be able to better differentiate subtle landform features in areas of low relief. Essentially this enables recognition of lakes and open water (0 relief and 0 slope), shorelines and littoral zones (0-1 m), nearly flat, low-relief landforms (1-10 m) and low relief undulating plains (10-30 m). We also modified the Hammond approach for separating upper versus lower landform positions used to differentiate flat areas in uplands from flat lowlands. We instead differentiate 3 relative slope positions of channel valley, toe slope and upper slope consistently and exhaustively and so can identify any flat areas that occur in any of these three landform positions. We did not find it necessary to use slope gradient as a criteria for defining and delineating classes because relief acts as a surrogate for slope and each relief class exhibits a narrow and definable range of slope gradients. Dominant slope gradient (or other attributes) can be computed, post classification, for each defined polygon, if there is a need to further classify by slope or other attribute. This simplifies classification and also reduces pixilation in the classification arising from considering too many local criteria in the class definitions. The resulting polygons provide an extremely detailed classification of relief and landform position at the level of individual hillslopes across all of Canada. The polygon boundaries explicitly follow major identifiable drainage networks and work their way upslope to delineate interfluves that occupy upslope positions at all levels of relief. The detailed LandMapR polygon classifications nest consistently within more general regions defined by the original Hammond-Dikau procedures. Initial visual analysis reveals a strong and consistent spatial relationship between observable changes in slope, vegetation and drainage regime and LandMapR landform polygon boundaries. More detailed quantitative assessment of the accuracy and utility of the LandMapR polygon classes is planned.

High spatial resolution mapping of land cover types in a priority area for conservation in the Brazilian savanna

NASA Astrophysics Data System (ADS)

Ribeiro, F.; Roberts, D. A.; Hess, L. L.; Davis, F. W.; Caylor, K. K.; Nackoney, J.; Antunes Daldegan, G.

2017-12-01

Savannas are heterogeneous landscapes consisting of highly mixed land cover types that lack clear distinct boundaries. The Brazilian Cerrado is a Neotropical savanna considered a biodiversity hotspot for conservation due to its biodiversity richness and rapid transformation of its landscape by crop and pasture activities. The Cerrado is one of the most threatened Brazilian biomes and only 2.2% of its original extent is strictly protected. Accurate mapping and monitoring of its ecosystems and adjacent land use are important to select areas for conservation and to improve our understanding of the dynamics in this biome. Land cover mapping of savannas is difficult due to spectral similarity between land cover types resulting from similar vegetation structure, floristically similar components, generalization of land cover classes, and heterogeneity usually expressed as small patch sizes within the natural landscape. These factors are the major contributor to misclassification and low map accuracies among remote sensing studies in savannas. Specific challenges to map the Cerrado's land cover types are related to the spectral similarity between classes of land use and natural vegetation, such as natural grassland vs. cultivated pasture, and forest ecosystem vs. crops. This study seeks to classify and evaluate the land cover patterns across an area ranked as having extremely high priority for future conservation in the Cerrado. The main objective of this study is to identify the representativeness of each vegetation type across the landscape using high to moderate spatial resolution imagery using an automated scheme. A combination of pixel-based and object-based approaches were tested using RapidEye 3A imagery (5m spatial resolution) to classify the Cerrado's major land cover types. The random forest classifier was used to map the major ecosystems present across the area, and demonstrated to have an effective result with 68% of overall accuracy. Post-classification modification was performed to refine information to the major physiognomic groups of each ecosystem type. In this step, we used segmentation in eCognition, considering the random forest classification as input as well as other environmental layers (e.g. slope, soil types), which improved the overall classification to 75%.

Understanding Student Language: An Unsupervised Dialogue Act Classification Approach

ERIC Educational Resources Information Center

Ezen-Can, Aysu; Boyer, Kristy Elizabeth

2015-01-01

Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…

Mapping regional livelihood benefits from local ecosystem services assessments in rural Sahel

PubMed Central

Sinare, Hanna; Enfors Kautsky, Elin; Ouedraogo, Issa; Gordon, Line J.

2018-01-01

Most current approaches to landscape scale ecosystem service assessments rely on detailed secondary data. This type of data is seldom available in regions with high levels of poverty and strong local dependence on provisioning ecosystem services for livelihoods. We develop a method to extrapolate results from a previously published village scale ecosystem services assessment to a higher administrative level, relevant for land use decision making. The method combines remote sensing (using a hybrid classification method) and interviews with community members. The resulting landscape scale maps show the spatial distribution of five different livelihood benefits (nutritional diversity, income, insurance/saving, material assets and energy, and crops for consumption) that illustrate the strong multifunctionality of the Sahelian landscapes. The maps highlight the importance of a diverse set of sub-units of the landscape in supporting Sahelian livelihoods. We see a large potential in using the resulting type of livelihood benefit maps for guiding future land use decisions in the Sahel. PMID:29389965

Mapping regional livelihood benefits from local ecosystem services assessments in rural Sahel.

PubMed

Malmborg, Katja; Sinare, Hanna; Enfors Kautsky, Elin; Ouedraogo, Issa; Gordon, Line J

2018-01-01

Most current approaches to landscape scale ecosystem service assessments rely on detailed secondary data. This type of data is seldom available in regions with high levels of poverty and strong local dependence on provisioning ecosystem services for livelihoods. We develop a method to extrapolate results from a previously published village scale ecosystem services assessment to a higher administrative level, relevant for land use decision making. The method combines remote sensing (using a hybrid classification method) and interviews with community members. The resulting landscape scale maps show the spatial distribution of five different livelihood benefits (nutritional diversity, income, insurance/saving, material assets and energy, and crops for consumption) that illustrate the strong multifunctionality of the Sahelian landscapes. The maps highlight the importance of a diverse set of sub-units of the landscape in supporting Sahelian livelihoods. We see a large potential in using the resulting type of livelihood benefit maps for guiding future land use decisions in the Sahel.

Colony-level variation in pollen collection and foraging preferences among wild-caught bumble bees (Hymenoptera: Apidae).

PubMed

Saifuddin, Mustafa; Jha, Shalene

2014-04-01

Given that many pollinators have exhibited dramatic declines related to habitat destruction, an improved understanding of pollinator resource collection across human-altered landscapes is essential to conservation efforts. Despite the importance of bumble bees (Bombus spp.) as global pollinators, little is known regarding how pollen collection patterns vary between individuals, colonies, and landscapes. In this study, Vosnesensky bumble bees (Bombus vosnesenskii Radoszkowski) were collected from a range of human-altered and natural landscapes in northern California. Extensive vegetation surveys and Geographic Information System (GIS)-based habitat classifications were conducted at each site, bees were genotyped to identify colony mates, and pollen loads were examined to identify visited plants. In contrast to predictions based on strong competitive interactions, pollen load composition was significantly more similar for bees captured in a shared study region compared with bees throughout the research area but was not significantly more similar for colony mates. Preference analyses revealed that pollen loads were not composed of the most abundant plant species per study region. The majority of ranked pollen preference lists were significantly correlated for pairwise comparisons of colony mates and individuals within a study region, whereas the majority of pairwise comparisons of ranked pollen preference lists between individuals located at separate study regions were uncorrelated. Results suggest that pollen load composition and foraging preferences are similar for bees throughout a shared landscape regardless of colony membership. The importance of native plant species in pollen collection is illustrated through preference analyses, and we suggest prioritization of specific rare native plant species for enhanced bumble bee pollen collection.

A new approach to the identification of Landscape Quality Objectives (LQOs) as a set of indicators.

PubMed

Sowińska-Świerkosz, Barbara Natalia; Chmielewski, Tadeusz J

2016-12-15

The objective of the paper is threefold: (1) to introduce Landscape Quality Objectives (LQOs) as a set of indicators; (2) to present a method of linking social and expert opinion in the process of the formulation of landscape indicators; and (3) to present a methodological framework for the identification of LQOs. The implementation of these goals adopted a six-stage procedure based on the use of landscape units: (1) GIS analysis; (2) classification; (3) social survey; (4) expert value judgement; (5) quality assessment; and (6) guidelines formulation. The essence of the research was the presentation of features that determine landscape quality according to public opinion as a set of indicators. The results showed that 80 such indicators were identified, of both a qualitative (49) and a quantitative character (31). Among the analysed units, 60% (18 objects) featured socially expected (and confirmed by experts) levels of landscape quality, and 20% (6 objects) required overall quality improvement in terms of both public and expert opinion. The adopted procedure provides a new tool for integrating social responsibility into environmental management. The advantage of the presented method is the possibility of its application in the territories of various European countries. It is flexible enough to be based on cartographic studies, landscape research methods, and environmental quality standards existing in a given country. Copyright © 2016 Elsevier Ltd. All rights reserved.

Monitoring Ecological and Environmental Changes in Coastal Wetlands in the Yellow River Delta from 1987 to 2010 Using Remote Sensing Techniques

NASA Astrophysics Data System (ADS)

Shang, Kun; Zhao, Dong; Gan, Fuping; Xiao, Chenchao

2016-04-01

Many wetlands in the world have degraded rapidly in recent years, especially in China. The Yellow River Delta (YRD) is one of the largest deltas in China. The YRD Nature Reserve is one of China's most complete, broadest, and youngest wetland ecological systems in the warm-temperate zone. Most previous studies have placed particular emphasis on ecological environment or landscape of the YRD based on the distribution of wetlands. In recent years, with the rapid development of the city of Dongying, located in the YRD, the impacts of human activities are increasingly significant, so that monitoring changes in the wetlands has become especially important. In this research, we applied an improved Support Vector Machine (SVM) approach to wetland classification based on feature band set construction and optimization using seven Landsat images. By extracting waterlines, classifying wetlands and deriving landscape parameters, we have achieved high-frequency comprehensive monitoring of the wetlands in the YRD over a relatively long period. It offers a better estimate of wetland change trends than certain previous studies. From 1987 to 2010, the natural waterline primarily experienced erosion due to precipitation abnormalities, as well as coastal exploitation, as the co-analyzed meteorological data suggest. Meanwhile, the artificial waterline barely changed. The wetland area decreased rapidly from approximately 4,607 km2 to 2,714 km2 between 1987 and 2000. Ecological resilience and landscape diversity also decreased significantly during this period. The major impact factors were most likely urbanization, population expansion and the exploitation of the wetlands. After 2000, ecological resilience exhibited a positive trend. However, because newly built aquatic farms and salt works caused serious damages and threatened the natural beach landscape, the landscape fragmentation of muddy and sandy beaches increased after 2000. According to the results, more effective policies and laws for wetland protection are urgently needed, and the water sources of these wetlands should be guaranteed in the future. In particular, there is an urgent need to establish a complete dynamic monitoring system of the land use/cover change in the YRD.

Energy dissipation for flat-sloped stepped spillways using new inception point relationship

USDA-ARS?s Scientific Manuscript database

Transforming from a rural to an urban landscape has created a change in hazard classification for many earthen embankments. As a result, these facilities provide inadequate spillway capacity for the upgraded hazard rating. To bring these dams into compliance with state and federal dam safety regul...

CLASSIFYING OREGON ESTUARIES BY HABITAT: ANALYSIS OF EXISTING DATA AND A PROPOSAL FOR A PILOT STUDY

EPA Science Inventory

Because many estuarine resources are linked to benthic habitats, classification of estuaries by habitat types may prove a relevant approach for grouping estuaries with similar ecological values and vulnerability to landscape alterations. As a first step, we evaluated whether pub...

Cases of Coastal Zone Change and Land Use/Land Cover Change: a learning module that goes beyond the "how" of doing image processing and change detection to asking the "why" about what are the "driving forces" of global change.

NASA Astrophysics Data System (ADS)

Ford, R. E.

2006-12-01

In 2006 the Loma Linda University ESSE21 Mesoamerican Project (Earth System Science Education for the 21st Century) along with partners such as the University of Redlands and California State University, Pomona, produced an online learning module that is designed to help students learn critical remote sensing skills-- specifically: ecosystem characterization, i.e. doing a supervised or unsupervised classification of satellite imagery in a tropical coastal environment. And, it would teach how to measure land use / land cover change (LULC) over time and then encourage students to use that data to assess the Human Dimensions of Global Change (HDGC). Specific objectives include: 1. Learn where to find remote sensing data and practice downloading, pre-processing, and "cleaning" the data for image analysis. 2. Use Leica-Geosystems ERDAS Imagine or IDRISI Kilimanjaro to analyze and display the data. 3. Do an unsupervised classification of a LANDSAT image of a protected area in Honduras, i.e. Cuero y Salado, Pico Bonito, or Isla del Tigre. 4. Virtually participate in a ground-validation exercise that would allow one to re-classify the image into a supervised classification using the FAO Global Land Cover Network (GLCN) classification system. 5. Learn more about each protected area's landscape, history, livelihood patterns and "sustainability" issues via virtual online tours that provide ground and space photos of different sites. This will help students in identifying potential "training sites" for doing a supervised classification. 6. Study other global, US, Canadian, and European land use/land cover classification systems and compare their advantages and disadvantages over the FAO/GLCN system. 7. Learn to appreciate the advantages and disadvantages of existing LULC classification schemes and adapt them to local-level user needs. 8. Carry out a change detection exercise that shows how land use and/or land cover has changed over time for the protected area of your choice. The presenter will demonstrate the module, assess the collaborative process which created it, and describe how it has been used so far by users in the US as well as in Honduras and elsewhere via a series joint workshops held in Mesoamerica. Suggestions for improvement will be requested. See the module and related content resources at: http://resweb.llu.edu/rford/ESSE21/LUCCModule/

Land Cover and Hydrologic Variability in Residential Watersheds: Drivers of N Loss in Sacramento CA

NASA Astrophysics Data System (ADS)

McConaghie, J. B.; Zhou, W.; Cadenasso, M. L.

2011-12-01

A key aspect to understanding N loss from urban systems is the link between landscape heterogeneity and variability in non-point source (NPS) nitrogen (N) flux. Because water transports N across the landscape and into receiving streams as runoff, understanding how landscape heterogeneity influences water quantity and movement is also needed. High variability in N loss has been documented from urban systems. However, typical NPS studies characterize landscape heterogeneity by land use and only weakly explain variability in stream N. Focusing on land cover, rather than land use, may better explain observed variability in N loss because land cover elements may better indicate major drivers of N loss. Also, most studies have been conducted in temperate urban systems with stream flow year round. In semi-arid urban systems, storm flow accounts for the majority of stream discharges, and residential irrigation contributes significantly to flows in the dry season. To address how landscape heterogeneity affects variability in water quantity and quality in urban streams, we examined how land cover influences stream flows and N loss in residential streams of metropolitan Sacramento, CA. We analyzed fine-scale variation in land cover and stream N during base flow and storm events in 4 residential watersheds which differ substantially in land cover. We classified land cover using HERCULES (High Ecological Resolution Classification for Urban Landscapes and Environmental Systems) which was developed specifically for urban systems. HERCULES classifies high-resolution aerial photographs into 5 elements: buildings, pavement, herbaceous and woody vegetation, and bare soil. Streams were sampled for discharge, NO3, and Total N using auto samplers during storms in the 2010-2011 rainy season and monthly in the dry season. Partial correlation analysis and multivariate models describe the relationships between land cover elements, water retention, and stream N in these watersheds. We found an early season flush of N from streams during the first storms, and N levels diminished through progressive storms. Also, N concentrations were higher during the rainy season compared to the dry season. High proportion of impervious cover was associated with greater flow rates overall, while high proportion of herbaceous cover was associated with reduced flow rates during storms. The proportion of pavement in the watersheds, a commonly used indicator of urban intensity, did not strongly correlate with increased levels of stream N except during the flush, but did correlate with the magnitude and timing of flows during storms. However, high proportions of building cover, e.g. residential homes, did correlate with higher N fluxes. The use of fertilizers or enhanced N cycling through vegetation management near residential buildings is a possible source of increased N. Management to reduce aquatic enrichment of N from urban ecosystems may be best directed toward identifying N sources and sinks associated with specific land covers. Management must also account for seasonal dynamics, such as annual hydrologic patterns, which drive the loss of N.

Monitoring changes in landscape pattern: use of Ikonos and Quickbird images.

PubMed

Alphan, Hakan; Çelik, Nil

2016-02-01

This paper aimed to analyze short-term changes in landscape pattern that primarily results from building development in the east coast of Mersin Province (Turkey). Three sites were selected. Ikonos (2003) and Quickbird (2009) images for these sites were classified, and land cover transformations were quantitatively analyzed using cross-tabulation of classification results. Changes in landscape structure were assessed by comparing the calculated values of area/edge and shape metrics for the earlier and later dates. Area/edge metrics included percentage of land and edge density, while shape metrics included perimeter-area ratio, fractal dimension, and related circumscribing circle (RCC) metrics. Orchards and buildings were dominating land cover classes. Variations in patch edge, size, and shapes were also analyzed and discussed. Degradation of prime agricultural areas due to building development and implications of such development on habitat fragmentation were highlighted.

Pedodiversity and Its Significance in the Context of Modern Soil Geography

NASA Astrophysics Data System (ADS)

Krasilnikov, P. V.; Gerasimova, M. I.; Golovanov, D. L.; Konyushkova, M. V.; Sidorova, V. A.; Sorokin, A. S.

2018-01-01

Methodological basics of the study and quantitative assessment of pedodiversity are discussed. It is shown that the application of various indices and models of pedodiversity can be feasible for solving three major issues in pedology: a comparative geographical analysis of different territories, a comparative historical analysis of soil development in the course of landscape evolution, and the analysis of relationships between biodiversity and pedodiversity. Analogous geographic concepts of geodiversity and landscape diversity are also discussed. Certain limitations in the use of quantitative estimates of pedodiversity related to their linkage to the particular soil classification systems and with the initial soil maps are considered. Problems of the interpretation of the results of pedodiversity assessments are emphasized. It is shown that scientific explanations of biodiversity cannot be adequately applied in soil studies. Promising directions of further studies of pedodiversity are outlined. They include the assessment of the functional diversity of soils on the basis of data on their properties, integration with geostatistical methods of evaluation of soil variability, and assessment of pedodiversity on different scales.

Distribution of global fallouts cesium-137 in taiga and tundra catenae at the Ob River basin

NASA Astrophysics Data System (ADS)

Semenkov, I. N.; Usacheva, A. A.; Miroshnikov, A. Yu.

2015-03-01

The classification of soil catenae at the Ob River basin is developed and applied. This classification reflects the diverse geochemical conditions that led to the formation of certain soil bodies, their combinations and the migration fields of chemical elements. The soil and geochemical diversity of the Ob River basin catenae was analyzed. The vertical and lateral distribution of global fallouts cesium-137 was studied using the example of the four most common catenae types in Western Siberia tundra and taiga. In landscapes of dwarf birches and dark coniferous forests on gleysols, cryosols, podzols, and cryic-stagnosols, the highest 137Cs activity density and specific activity are characteristic of the upper soil layer of over 30% ash, while the moss-grass-shrub cover is characterized by low 137Cs activity density and specific activity. In landscapes of dwarf birches and pine woods on podzols, the maximum specific activity of cesium-137 is typical for moss-grass-shrub cover, while the maximum reserves are concentrated in the upper soil layer of over 30% ash. Bog landscapes and moss-grass-shrub cover are characterized by a minimum activity of 137Cs, and its reserves in soil generally decrease exponentially with depth. The cesium-137 penetration depth increases in oligotrophic histosols from northern to middle taiga landscapes from 10-15 to 40 cm. 137Cs is accumulated in oligotrophic histosols for increases in pH from 3.3 to 4.0 and in concretionary interlayers of pisoplinthic-cryic-histic-stagnosols. Cryogenic movement, on the one hand, leads to burying organic layers enriched in 137Cs and, on the other hand, to deducing specific activity when mixed with low-active material from lower soil layers.

Multitemporal analysis of Landsat images to detect land use land cover changes for monitoring soil sealing in the Nola area (Naples, Italy)

NASA Astrophysics Data System (ADS)

De Giglio, Michaela; Allocca, Maria; Franci, Francesca

2016-10-01

Land Use Land Cover Changes (LULCC) data provide objective information to support environmental policy, urban planning purposes and sustainable land development. Understanding of past land use/cover practices and current landscape patterns is critical to assess the effects of LULCC on the Earth system. Within the framework of soil sealing in Italy, the present study aims to assess the LULCC of the Nola area (Naples metropolitan area, Italy), relating to a thirty year period from 1984 to 2015. The urban sprawl affects this area causing the impervious surface increase, the loss in rural areas and landscape fragmentation. Located near Vesuvio volcano and crossed by artificial filled rivers, the study area is subject to landslide, hydraulic and volcanic risks. Landsat time series has been processed by means of the supervised per-pixel classification in order to produce multitemporal Land Use Land Cover maps. Then, post-classification comparison approach has been applied to quantify the changes occurring between 1984 and 2015, also analyzing the intermediate variations in 1999, namely every fifteen years. The results confirm the urban sprawl. The increase of the built-up areas mainly causes the habitat fragmentation and the agricultural land conversion of the Nola area that is already damaged by unauthorized disposal of urban waste. Moreover, considering the local risk maps, it was verified that some of the new urban areas were built over known hazardous sites. In order to limit the soil sealing, urgent measures and sustainable urban planning are required.

Distinctive fingerprints of erosional regimes in terrestrial channel networks

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.

2017-12-01

Satellite imagery and digital elevation maps capture the large scale morphology of channel networks attributed to long term erosional processes, such as fluvial, glacial, groundwater sapping and subglacial erosion. Characteristic morphologies associated with each of these styles of erosion have been studied in detail, but there exists a knowledge gap related to their parameterization and quantification. This knowledge gap prevents a rigorous analysis of the dominant processes that shaped a particular landscape, and a comparison across styles of erosion. To address this gap, we use previous morphological descriptions of glaciers, rivers, sapping valleys and tunnel valleys to identify and measure quantitative metrics diagnostic of these distinctive styles of erosion. From digital elevation models, we identify four geometric metrics: The minimum channel width, channel aspect ratio (longest length to channel width at the outlet), presence of undulating longitudinal profiles, and tributary junction angle. We also parameterize channel network complexity in terms of its stream order and fractal dimension. We then perform a statistical classification of the channel networks using a Principal Component Analysis on measurements of these six metrics on a dataset of 70 channelized systems. We show that rivers, glaciers, groundwater seepage and subglacial meltwater erode the landscape in rigorously distinguishable ways. Our methodology can more generally be applied to identify the contributions of different processes involved in carving a channel network. In particular, we are able to identify transitions from fluvial to glaciated landscapes or vice-versa.

[Object-oriented remote sensing image classification in epidemiological studies of visceral leishmaniasis in urban areas].

PubMed

Almeida, Andréa Sobral de; Werneck, Guilherme Loureiro; Resendes, Ana Paula da Costa

2014-08-01

This study explored the use of object-oriented classification of remote sensing imagery in epidemiological studies of visceral leishmaniasis (VL) in urban areas. To obtain temperature and environmental information, an object-oriented classification approach was applied to Landsat 5 TM scenes from the city of Teresina, Piauí State, Brazil. For 1993-1996, VL incidence rates correlated positively with census tracts covered by dense vegetation, grass/pasture, and bare soil and negatively with areas covered by water and densely populated areas. In 2001-2006, positive correlations were found with dense vegetation, grass/pasture, bare soil, and densely populated areas and negative correlations with occupied urban areas with some vegetation. Land surface temperature correlated negatively with VL incidence in both periods. Object-oriented classification can be useful to characterize landscape features associated with VL in urban areas and to help identify risk areas in order to prioritize interventions.

Landscape sensitivity in a dynamic environment

NASA Astrophysics Data System (ADS)

Lin, Jiun-Chuan; Jen, Chia-Horn

2010-05-01

Landscape sensitivity at different scales and topics is presented in this study. Methodological approach composed most of this paper. According to the environmental records in the south eastern Asia, the environment change is highly related with five factors, such as scale of influence area, background of environment characters, magnitude and frequency of events, thresholds of occurring hazards and influence by time factor. This paper tries to demonstrate above five points from historical and present data. It is found that landscape sensitivity is highly related to the degree of vulnerability of the land and the processes which put on the ground including human activities. The scale of sensitivity and evaluation of sensitivities is demonstrated in this paper by the data around east Asia. The methods of classification are mainly from the analysis of environmental data and the records of hazards. From the trend of rainfall records, rainfall intensity and change of temperature, the magnitude and frequency of earthquake, dust storm, days of draught, number of hazards, there are many coincidence on these factors with landscape sensitivities. In conclusion, the landscape sensitivities could be classified as four groups: physical stable, physical unstable, unstable, extremely unstable. This paper explain the difference.

Identification of environmental covariates of West Nile virus vector mosquito population abundance.

PubMed

Trawinski, Patricia R; Mackay, D Scott

2010-06-01

The rapid spread of West Nile virus (WNv) in North America is a major public health concern. Culex pipiens-restuans is the principle mosquito vector of WNv in the northeastern United States while Aedes vexans is an important bridge vector of the virus in this region. Vector mosquito abundance is directly dependent on physical environmental factors that provide mosquito habitats. The objective of this research is to determine landscape elements that explain the population abundance and distribution of WNv vector mosquitoes using stepwise linear regression. We developed a novel approach for examining a large set of landscape variables based on a land use and land cover classification by selecting variables in stages to minimize multicollinearity. We also investigated the distance at which landscape elements influence abundance of vector populations using buffer distances of 200, 400, and 1000 m. Results show landscape effects have a significant impact on Cx. pipiens-estuans population distribution while the effects of landscape features are less important for prediction of Ae. vexans population distributions. Cx. pipiens-restuans population abundance is positively correlated with human population density, housing unit density, and urban land use and land cover classes and negatively correlated with age of dwellings and amount of forested land.

A comparative interregional analysis of selected data from LANDSAT-1 and EREP for the inventory and monitoring of natural ecosystems

NASA Technical Reports Server (NTRS)

Poulton, C. E.

1975-01-01

Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.

Vegetation fire proneness in Europe

NASA Astrophysics Data System (ADS)

Pereira, Mário; Aranha, José; Amraoui, Malik

2015-04-01

Fire selectivity has been studied for vegetation classes in terms of fire frequency and fire size in a few European regions. This analysis is often performed along with other landscape variables such as topography, distance to roads and towns. These studies aims to assess the landscape sensitivity to forest fires in peri-urban areas and land cover changes, to define landscape management guidelines and policies based on the relationships between landscape and fires in the Mediterranean region. Therefore, the objectives of this study includes the: (i) analysis of the spatial and temporal variability statistics within Europe; and, (ii) the identification and characterization of the vegetated land cover classes affected by fires; and, (iii) to propose a fire proneness index. The datasets used in the present study comprises: Corine Land Cover (CLC) maps for 2000 and 2006 (CLC2000, CLC2006) and burned area (BA) perimeters, from 2000 to 2013 in Europe, provided by the European Forest Fire Information System (EFFIS). The CLC is a part of the European Commission programme to COoRdinate INformation on the Environment (Corine) and it provides consistent, reliable and comparable information on land cover across Europe. Both the CLC and EFFIS datasets were combined using geostatistics and Geographical Information System (GIS) techniques to access the spatial and temporal evolution of the types of shrubs and forest affected by fires. Obtained results confirms the usefulness and efficiency of the land cover classification scheme and fire proneness index which allows to quantify and to compare the propensity of vegetation classes and countries to fire. As expected, differences between northern and southern Europe are notorious in what concern to land cover distribution, fire incidence and fire proneness of vegetation cover classes. This work was supported by national funds by FCT - Portuguese Foundation for Science and Technology, under the project PEst-OE/AGR/UI4033/2014 and by the project SUSTAINSYS: Environmental Sustainable Agro-Forestry Systems (NORTE-07-0124-FEDER-000044), financed by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework (QREN), through the European Regional Development Fund (FEDER), as well as by National Funds (PIDDAC) through the Portuguese Foundation for Science and Technology (FCT/MEC).

National Program for Inspection of Non-Federal Dams. Batterson Park Pond Dam (CT 00262), Connecticut River Basin, Farmington/New Britain, Connecticut. Phase I Inspection Report.

DTIC Science & Technology

1978-12-01

Division to inspect and report on selected dams in the State of Connecticut. Authorization and notice to proceed were issued to Storch Engineers under a...operable however. c. Size Classification - The size classification of I the dam is intermediate. The storage (2,520 acre-feet) governs the...Landscape Architects Planners - Environental Consultants 13ATFRMN ?ARtK P*Nr3 DAm CAPAC MlY CUR~VE ELEV .DP/ R AvJQ ATkrp oi .V0i 30-70 31 F q * .7 CO

Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

NASA Astrophysics Data System (ADS)

Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

2016-12-01

Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted towards areas where the methods disagree, highlighting how each technique should be properly weighted over these areas to increase the classification accuracy of water. The conclusions and techniques developed in this study are applicable to other areas where similar environmental conditions and data availability exist.

A simple approach for a spatial terrestrial exposure assessment of the insecticide fenoxycarb, based on a high-resolution landscape analysis.

PubMed

Thomas, Kai; Resseler, Herbert; Spatz, Robert; Hendley, Paul; Sweeney, Paul; Urban, Martin; Kubiak, Roland

2016-11-01

The objective was to refine the standard regulatory exposure scenario used in plant protection product authorisations by developing a more realistic landscape-related GIS-based exposure assessment for terrestrial non-target arthropods. We quantified the proportion of adjacent off-target area in agricultural landscapes potentially exposed to insecticide drift from applications of the active substance fenoxycarb. High-resolution imagery, landscape classification and subsequent stepwise analysis of a whole landscape using drift and interception functions were applied to selected areas in representative fruit-producing regions in Germany. Even under worst-case assumptions regarding treated area, use rate and drift, less than 12% of the non-agricultural habitat area would potentially be exposed to fenoxycarb drift above regulatory acceptable concentrations. Additionally, if the filtering effect of tall vegetation were taken into account, this number would decrease to 6.6%. Further refinements to landscape elements and application conditions indicate that less than 5% of the habitat area might be exposed above regulatory acceptable concentrations, meaning that 95% of the non-agricultural habitat area will be unimpacted (i.e. no unacceptable effects) and can serve as refuge for recolonisation. Approaches and tools are proposed for standardisable and transparent refinements in regulatory risk assessments on the landscape level. © 2016 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2016 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Role of small oligomers on the amyloidogenic aggregation free-energy landscape.

PubMed

He, Xianglan; Giurleo, Jason T; Talaga, David S

2010-01-08

We combine atomic-force-microscopy particle-size-distribution measurements with earlier measurements on 1-anilino-8-naphthalene sulfonate, thioflavin T, and dynamic light scattering to develop a quantitative kinetic model for the aggregation of beta-lactoglobulin into amyloid. We directly compare our simulations to the population distributions provided by dynamic light scattering and atomic force microscopy. We combine species in the simulation according to structural type for comparison with fluorescence fingerprint results. The kinetic model of amyloidogenesis leads to an aggregation free-energy landscape. We define the roles of and propose a classification scheme for different oligomeric species based on their location in the aggregation free-energy landscape. We relate the different types of oligomers to the amyloid cascade hypothesis and the toxic oligomer hypothesis for amyloid-related diseases. We discuss existing kinetic mechanisms in terms of the different types of oligomers. We provide a possible resolution to the toxic oligomer-amyloid coincidence.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing

PubMed Central

O’Connell, Jerome; Bradter, Ute; Benton, Tim G.

2015-01-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability. PMID:26664131

Mapping Deforestation area in North Korea Using Phenology-based Multi-Index and Random Forest

NASA Astrophysics Data System (ADS)

Jin, Y.; Sung, S.; Lee, D. K.; Jeong, S.

2016-12-01

Forest ecosystem provides ecological benefits to both humans and wildlife. Growing global demand for food and fiber is accelerating the pressure on the forest ecosystem in whole world from agriculture and logging. In recently, North Korea lost almost 40 % of its forests to crop fields for food production and cut-down of forest for fuel woods between 1990 and 2015. It led to the increased damage caused by natural disasters and is known to be one of the most forest degraded areas in the world. The characteristic of forest landscape in North Korea is complex and heterogeneous, the major landscape types in the forest are hillside farm, unstocked forest, natural forest and plateau vegetation. Remote sensing can be used for the forest degradation mapping of a dynamic landscape at a broad scale of detail and spatial distribution. Confusion mostly occurred between hillside farmland and unstocked forest, but also between unstocked forest and forest. Most previous forest degradation that used focused on the classification of broad types such as deforests area and sand from the perspective of land cover classification. The objective of this study is using random forest for mapping degraded forest in North Korea by phenological based vegetation index derived from MODIS products, which has various environmental factors such as vegetation, soil and water at a regional scale for improving accuracy. The model created by random forest resulted in an overall accuracy was 91.44%. Class user's accuracy of hillside farmland and unstocked forest were 97.2% and 84%%, which indicate the degraded forest. Unstocked forest had relative low user accuracy due to misclassified hillside farmland and forest samples. Producer's accuracy of hillside farmland and unstocked forest were 85.2% and 93.3%, repectly. In this case hillside farmland had lower produce accuracy mainly due to confusion with field, unstocked forest and forest. Such a classification of degraded forest could supply essential information to decide the priority of forest management and restoration in degraded forest area.

Analysis of the Degree of Artificialization of the Cities of Itapema and Balneário Camboriú - Santa Catarina ( Brazil )

NASA Astrophysics Data System (ADS)

Piatto, L.; Polette, M.

2010-12-01

Artificialization is a dynamic process of change of the natural landscape in a given amount of time. Is the natural landscape change for the artificial one. This process always takes place when humans alter a space in accordance with their needs and resources availability. The fast population growth of coastal areas is speeding the artificialization process of coastal zones, turning these ecosystems into the most urbanized ones in the world. Although the coastline is a just a small portion of the coastal zone, it is the link between the terrestrial and sea lives. This feature is not only attractive to the rich biodiversity which it is formed by, but also to humans. Therefore, coastlines must primarily be ordered and regulated in order to ensure sustainable development, avoiding the exhaustion of its capacity. Thus, this work studies two relevant areas of the mid-north coast of the State of Santa Catarina , in South Brazil , where it is possible to find a deep artificialization process: Itapema and Balneario Camboriu. The objective of this project is to make a quantitative analysis of the degree of artificialization of both these cities as well as analyzing land use by vectorization using satellite images, which allows for greater detail and definition of the different levels of artificialization. For this purpose, the cities were divided into landscape units and subdivided into zones, and, then, classified into four levels of artificialization: Natural, Semi-natural, Semi-artificial, and Artificial. Then, a databank of each city was created, quantifying the distinct categories of occupation and distribution of the different degrees of artificialization in each area. One artificial and two semi-natural units were found in Balneario Camboriu. The artificial area is at its occupation limit, compromising the future of the semi-natural areas, which may become targets of the real estate and civil construction industries. More critical values were found in Itapema, with two units classified as artificial. This result reflects the intense densification of the coastline, where occupation conflicts with the capacity of supporting its already-over-exploited resources. After this quantitative classification, we compared the method used in this work and that used by Project "Orla" (a public policy program held by the Federal Government and supervised by the State and Municipal Coastal Management Programs), which qualitatively classified the same areas by means of visual identification of the units. The comparison showed that the quantitative system of classification of the coastline was more efficient and can complement the analyses of Project "Orla", validating its qualitative classification with concrete percentages of occupation. The method of visual analysis of high-definition images proved to be a good tool for land use classification. Thus, it is interesting to note that the present method is relatively cheap, which can be used both in coastline projects, such as Project "Orla", as well as in urban planning projects by any city government.

Integrating landscape system and meta-ecosystem frameworks to advance the understanding of ecosystem function in heterogeneous landscapes: An analysis on the carbon fluxes in the Northern Highlands Lake District (NHLD) of Wisconsin and Michigan.

PubMed

Yang, Haile; Chen, Jiakuan

2018-01-01

The successful integration of ecosystem ecology with landscape ecology would be conducive to understanding how landscapes function. There have been several attempts at this, with two main approaches: (1) an ecosystem-based approach, such as the meta-ecosystem framework and (2) a landscape-based approach, such as the landscape system framework. These two frameworks are currently disconnected. To integrate these two frameworks, we introduce a protocol, and then demonstrate application of the protocol using a case study. The protocol includes four steps: 1) delineating landscape systems; 2) classifying landscape systems; 3) adjusting landscape systems to meta-ecosystems and 4) integrating landscape system and meta-ecosystem frameworks through meta-ecosystems. The case study is the analyzing of the carbon fluxes in the Northern Highlands Lake District (NHLD) of Wisconsin and Michigan using this protocol. The application of this protocol revealed that one could follow this protocol to construct a meta-ecosystem and analyze it using the integrative framework of landscape system and meta-ecosystem frameworks. That is, one could (1) appropriately describe and analyze the spatial heterogeneity of the meta-ecosystem; (2) understand the emergent properties arising from spatial coupling of local ecosystems in the meta-ecosystem. In conclusion, this protocol is a useful approach for integrating the meta-ecosystem framework and the landscape system framework, which advances the describing and analyzing of the spatial heterogeneity and ecosystem function of interconnected ecosystems.

Integrating landscape system and meta-ecosystem frameworks to advance the understanding of ecosystem function in heterogeneous landscapes: An analysis on the carbon fluxes in the Northern Highlands Lake District (NHLD) of Wisconsin and Michigan

PubMed Central

Chen, Jiakuan

2018-01-01

The successful integration of ecosystem ecology with landscape ecology would be conducive to understanding how landscapes function. There have been several attempts at this, with two main approaches: (1) an ecosystem-based approach, such as the meta-ecosystem framework and (2) a landscape-based approach, such as the landscape system framework. These two frameworks are currently disconnected. To integrate these two frameworks, we introduce a protocol, and then demonstrate application of the protocol using a case study. The protocol includes four steps: 1) delineating landscape systems; 2) classifying landscape systems; 3) adjusting landscape systems to meta-ecosystems and 4) integrating landscape system and meta-ecosystem frameworks through meta-ecosystems. The case study is the analyzing of the carbon fluxes in the Northern Highlands Lake District (NHLD) of Wisconsin and Michigan using this protocol. The application of this protocol revealed that one could follow this protocol to construct a meta-ecosystem and analyze it using the integrative framework of landscape system and meta-ecosystem frameworks. That is, one could (1) appropriately describe and analyze the spatial heterogeneity of the meta-ecosystem; (2) understand the emergent properties arising from spatial coupling of local ecosystems in the meta-ecosystem. In conclusion, this protocol is a useful approach for integrating the meta-ecosystem framework and the landscape system framework, which advances the describing and analyzing of the spatial heterogeneity and ecosystem function of interconnected ecosystems. PMID:29415066

Decadal Trend in Agricultural Abandonment and Woodland Expansion in an Agro-Pastoral Transition Band in Northern China.

PubMed

Wang, Chao; Gao, Qiong; Wang, Xian; Yu, Mei

2015-01-01

Land use land cover (LULC) changes frequently in ecotones due to the large climate and soil gradients, and complex landscape composition and configuration. Accurate mapping of LULC changes in ecotones is of great importance for assessment of ecosystem functions/services and policy-decision support. Decadal or sub-decadal mapping of LULC provides scenarios for modeling biogeochemical processes and their feedbacks to climate, and evaluating effectiveness of land-use policies, e.g. forest conversion. However, it remains a great challenge to produce reliable LULC maps in moderate resolution and to evaluate their uncertainties over large areas with complex landscapes. In this study we developed a robust LULC classification system using multiple classifiers based on MODIS (Moderate Resolution Imaging Spectroradiometer) data and posterior data fusion. Not only does the system create LULC maps with high statistical accuracy, but also it provides pixel-level uncertainties that are essential for subsequent analyses and applications. We applied the classification system to the Agro-pasture transition band in northern China (APTBNC) to detect the decadal changes in LULC during 2003-2013 and evaluated the effectiveness of the implementation of major Key Forestry Programs (KFPs). In our study, the random forest (RF), support vector machine (SVM), and weighted k-nearest neighbors (WKNN) classifiers outperformed the artificial neural networks (ANN) and naive Bayes (NB) in terms of high classification accuracy and low sensitivity to training sample size. The Bayesian-average data fusion based on the results of RF, SVM, and WKNN achieved the 87.5% Kappa statistics, higher than any individual classifiers and the majority-vote integration. The pixel-level uncertainty map agreed with the traditional accuracy assessment. However, it conveys spatial variation of uncertainty. Specifically, it pinpoints the southwestern area of APTBNC has higher uncertainty than other part of the region, and the open shrubland is likely to be misclassified to the bare ground in some locations. Forests, closed shrublands, and grasslands in APTBNC expanded by 23%, 50%, and 9%, respectively, during 2003-2013. The expansion of these land cover types is compensated with the shrinkages in croplands (20%), bare ground (15%), and open shrublands (30%). The significant decline in agricultural lands is primarily attributed to the KFPs implemented in the end of last century and the nationwide urbanization in recent decade. The increased coverage of grass and woody plants would largely reduce soil erosion, improve mitigation of climate change, and enhance carbon sequestration in this region.

Quantifying the Availability of Tidewater Glacial Ice as Habitat for Harbor Seals in a Tidewater Glacial Fjord in Alaska Using Object-Based Image Analysis of Airborne Visible Imagery

NASA Astrophysics Data System (ADS)

Prakash, A.; Haselwimmer, C. E.; Gens, R.; Womble, J. N.; Ver Hoef, J.

2013-12-01

Tidewater glaciers are prominent landscape features that play a significant role in landscape and ecosystem processes along the southeastern and southcentral coasts of Alaska. Tidewater glaciers calve large icebergs that serve as an important substrate for harbor seals (Phoca vitulina richardii) for resting, pupping, nursing young, molting, and avoiding predators. Many of the tidewater glaciers in Alaska are retreating, which may influence harbor seal populations. Our objectives are to investigate the relationship between ice conditions and harbor seal distributions, which are poorly understood, in John's Hopkins Inlet, Glacier Bay National Park, Alaska, using a combination of airborne remote sensing and statistical modeling techniques. We present an overview of some results from Object-Based Image Analysis (OBIA) for classification of a time series of very high spatial resolution (4 cm pixels) airborne imagery acquired over John's Hopkins Inlet during the harbor seal pupping season in June and during the molting season in August from 2007 - 2012. Using OBIA we have developed a workflow to automate processing of the large volumes (~1250 images/survey) of airborne visible imagery for 1) classification of ice products (e.g. percent ice cover, percent brash ice, percent ice bergs) at a range of scales, and 2) quantitative determination of ice morphological properties such as iceberg size, roundness, and texture that are not found in traditional per-pixel classification approaches. These ice classifications and morphological variables are then used in statistical models to assess relationships with harbor seal abundance and distribution. Ultimately, understanding these relationships may provide novel perspectives on the spatial and temporal variation of harbor seals in tidewater glacial fjords.

A Forest Landscape Visualization System

Treesearch

Tim McDonald; Bryce Stokes

1998-01-01

A forest landscape visualization system was developed and used in creating realistic images depicting how an area might appear if harvested. The system uses a ray-tracing renderer to draw model trees on a virtual landscape. The system includes components to create landscape surfaces from digital elevation data, populate/cut trees within (polygonal) areas, and convert...

[Molecular Genetics as Best Evidence in Glioma Diagnostics].

PubMed

Masui, Kenta; Komori, Takashi

2016-03-01

The development of a genomic landscape of gliomas has led to the internally consistent, molecularly-based classifiers. However, development of a biologically insightful classification to guide therapy is still ongoing. Further, tumors are heterogeneous, and they change and adapt in response to drugs. The challenge of developing molecular classifiers that provide meaningful ways to stratify patients for therapy remains a major challenge for the field. Therefore, by incorporating molecular markers into the new World Health Organization (WHO) classification of tumors of the central nervous system, the traditional principle of diagnosis based on histologic criteria will be replaced by a multilayered approach combining histologic features and molecular information in an "integrated diagnosis", to define tumor entities as narrowly as possible. We herein review the current status of diagnostic molecular markers for gliomas, focusing on IDH mutation, ATRX mutation, 1p/19q co-deletion, and TERT promoter mutation in adult tumors, as well as BRAF and H3F3A aberrations in pediatric gliomas, the combination of which will be a promising endeavor to render molecular genetics as a best evidence in the glioma diagnositics.

Using ontology-based annotation to profile disease research

PubMed Central

Coulet, Adrien; LePendu, Paea; Shah, Nigam H

2012-01-01

Background Profiling the allocation and trend of research activity is of interest to funding agencies, administrators, and researchers. However, the lack of a common classification system hinders the comprehensive and systematic profiling of research activities. This study introduces ontology-based annotation as a method to overcome this difficulty. Analyzing over a decade of funding data and publication data, the trends of disease research are profiled across topics, across institutions, and over time. Results This study introduces and explores the notions of research sponsorship and allocation and shows that leaders of research activity can be identified within specific disease areas of interest, such as those with high mortality or high sponsorship. The funding profiles of disease topics readily cluster themselves in agreement with the ontology hierarchy and closely mirror the funding agency priorities. Finally, four temporal trends are identified among research topics. Conclusions This work utilizes disease ontology (DO)-based annotation to profile effectively the landscape of biomedical research activity. By using DO in this manner a use-case driven mechanism is also proposed to evaluate the utility of classification hierarchies. PMID:22494789

Channel Classification across Arid West Landscapes in Support of OHW Delineation

DTIC Science & Technology

2013-01-01

8 Figure 5. National Hydrography Dataset for Chinle Creek, AZ...the OHW boundary is determined by observing recent physical evidence subsequent to flow. Channel morphology and physical features associated with the...data from the National Hydrography Dataset (NHD) (USGS 2010). The NHD digital ERDC/CRREL TR-13-3 9 stream data were downloaded as a line

Global synthesis of the classifications, distributions, benefits and issues of terracing

Treesearch

Wei Wei; Die Chen; Lixin Wang; Stefani Daryanto; Liding Chen; Yang Yu; Yonglong Lu; Ge Sun; Tianjiao Feng

2016-01-01

For thousands of years, humans have created different types of terraces in different sloping conditions, meant to mitigate flood risks, reduce soil erosion and conserve water. These anthropogenic landscapes can be found in tropical and subtropical rainforests, deserts, and arid and semiarid mountains across the globe. Despite the long history, the roles of and the...

Landscape scale mapping of forest inventory data by nearest neighbor classification

Treesearch

Andrew Lister

2009-01-01

One of the goals of the Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program is large-area mapping. FIA scientists have tried many methods in the past, including geostatistical methods, linear modeling, nonlinear modeling, and simple choropleth and dot maps. Mapping methods that require individual model-based maps to be...

Classification and spatial analysis of eastern hemlock health using remote sensing and GIS

Treesearch

Laurent R. Bonneau; Kathleen S. Shields; Daniel L. Civco; David R. Mikus

2000-01-01

Over the past decade hemlock stands in southern Connecticut have undergone significant decline coincident with the arrival in 1985 of an exotic insect pest, the hemlock woolly adelgid (Adelges tsugae Annand). The objective of this study was to evaluate image enhancement techniques for rating the health of hemlocks at the landscape level using...

Post-fire tree establishment patterns at the alpine treeline ecotone: Mount Rainier National Park, Washington, USA

Treesearch

Kirk M. Stueve; Dawna L. Cerney; Regina M. Rochefort; Laurie L. Kurth

2009-01-01

We performed classification analysis of 1970 satellite imagery and 2003 aerial photography to delineate establishment. Local site conditions were calculated from a LIDAR-based DEM, ancillary climate data, and 1970 tree locations in a GIS. We used logistic regression on a spatially weighted landscape matrix to rank variables.

Comparison of statistical and theoretical habitat models for conservation planning: the benefit of ensemble prediction

Treesearch

D. Todd Jones-Farrand; Todd M. Fearer; Wayne E. Thogmartin; Frank R. Thompson; Mark D. Nelson; John M. Tirpak

2011-01-01

Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and...

Preliminary fuel characterization of the chauga ridges region of the Southern Appalachian Mountains

Treesearch

Aaron D. Stottlemyer; Victor B. Shelburne; Thomas A. Waldrop; Sandra Rideout-Hanzak; William C. Bridges

2006-01-01

Many areas of the southern Appalachian Mountains contain large amounts of dead and/or ericaceous fuel. Fuel information critical in modeling fire behavior and its effects is not available to forest managers in the southern Appalachian Mountains, and direct measurement is often impractical due to steep, remote topography. An existing landscape ecosystem classification (...

Methods for improving accuracy and extending results beyond periods covered by traditional ground-truth in remote sensing classification of a complex landscape

USDA-ARS?s Scientific Manuscript database

Successful development of approaches to quantify impacts of diverse landuse and associated agricultural management practices on ecosystem services is frequently limited by lack of historical and contemporary landuse data. We hypothesized that recent ground truth data could be used to extrapolate pre...

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

USGS Publications Warehouse

Wallace, C.S.A.; Marsh, S.E.

2005-01-01

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

High-resolution mapping of ecosystem carbon storage and potential effects of permafrost thaw in periglacial terrain, European Russian Arctic

NASA Astrophysics Data System (ADS)

Hugelius, Gustaf; Virtanen, Tarmo; Kaverin, Dmitry; Pastukhov, Alexander; Rivkin, Felix; Marchenko, Sergey; Romanovsky, Vladimir; Kuhry, Peter

2011-09-01

This study describes detailed partitioning of phytomass carbon (C) and soil organic carbon (SOC) for four study areas in discontinuous permafrost terrain, Northeast European Russia. The mean aboveground phytomass C storage is 0.7 kg C m-2. Estimated landscape SOC storage in the four areas varies between 34.5 and 47.0 kg C m-2 with LCC (land cover classification) upscaling and 32.5-49.0 kg C m-2 with soil map upscaling. A nested upscaling approach using a Landsat thematic mapper land cover classification for the surrounding region provides estimates within 5 ± 5% of the local high-resolution estimates. Permafrost peat plateaus hold the majority of total and frozen SOC, especially in the more southern study areas. Burying of SOC through cryoturbation of O- or A-horizons contributes between 1% and 16% (mean 5%) of total landscape SOC. The effect of active layer deepening and thermokarst expansion on SOC remobilization is modeled for one of the four areas. The active layer thickness dynamics from 1980 to 2099 is modeled using a transient spatially distributed permafrost model and lateral expansion of peat plateau thermokarst lakes is simulated using geographic information system analyses. Active layer deepening is expected to increase the proportion of SOC affected by seasonal thawing from 29% to 58%. A lateral expansion of 30 m would increase the amount of SOC stored in thermokarst lakes/fens from 2% to 22% of all SOC. By the end of this century, active layer deepening will likely affect more SOC than thermokarst expansion, but the SOC stores vulnerable to thermokarst are less decomposed.

Integrating machine learning techniques and high-resolution imagery to generate GIS-ready information for urban water consumption studies

NASA Astrophysics Data System (ADS)

Wolf, Nils; Hof, Angela

2012-10-01

Urban sprawl driven by shifts in tourism development produces new suburban landscapes of water consumption on Mediterranean coasts. Golf courses, ornamental, 'Atlantic' gardens and swimming pools are the most striking artefacts of this transformation, threatening the local water supply systems and exacerbating water scarcity. In the face of climate change, urban landscape irrigation is becoming increasingly important from a resource management point of view. This paper adopts urban remote sensing towards a targeted mapping approach using machine learning techniques and highresolution satellite imagery (WorldView-2) to generate GIS-ready information for urban water consumption studies. Swimming pools, vegetation and - as a subgroup of vegetation - turf grass are extracted as important determinants of water consumption. For image analysis, the complex nature of urban environments suggests spatial-spectral classification, i.e. the complementary use of the spectral signature and spatial descriptors. Multiscale image segmentation provides means to extract the spatial descriptors - namely object feature layers - which can be concatenated at pixel level to the spectral signature. This study assesses the value of object features using different machine learning techniques and amounts of labeled information for learning. The results indicate the benefit of the spatial-spectral approach if combined with appropriate classifiers like tree-based ensembles or support vector machines, which can handle high dimensionality. Finally, a Random Forest classifier was chosen to deliver the classified input data for the estimation of evaporative water loss and net landscape irrigation requirements.

Carbon, fire, and fuels: The importance of fuels and fuel characterization and the status of wildland fire fuels data for the United States

NASA Astrophysics Data System (ADS)

French, N. H. F.; Prichard, S.; McKenzie, D.; Kennedy, M. C.; Billmire, M.; Ottmar, R. D.; Kasischke, E. S.

2016-12-01

Quantification of emissions of carbon during combustion relies on knowing three general variables: how much landscape is impacted by fire (burn area), how much carbon is in that landscape (fuel loading), and fuel properties that determine the fraction that is consumed (fuel condition). These variables also determine how much carbon remains at the site in the form of unburned organic material or char, and therefore drive post-fire carbon dynamics and pools. In this presentation we review the importance of understanding fuel type, fuel loading, and fuel condition for quantifying carbon dynamics properly during burning and for measuring and mapping fuels across landscapes, regions, and continents. Variability in fuels has been shown to be a major driver of uncertainty in fire emissions, but has had little attention until recently. We review the current state of fuel characterization for fire management and carbon accounting, and present a new approach to quantifying fuel loading for use in fire-emissions mapping and for improving fire-effects assessment. The latest results of a study funded by the Joint Fire Science Program (JFSP) are presented, where a fuel loading database is being built to quantify variation in fuel loadings, as represented in the Fuel Characteristic Classification System (FCCS), across the conterminous US and Alaska. Statistical assessments of these data at multiple spatial scales will improve tools used by fire managers and scientists to quantify fire's impact on the land, atmosphere, and carbon cycle.

The ERTS-1 investigation (ER-600). Volume 5: ERTS-1 urban land use analysis

NASA Technical Reports Server (NTRS)

Erb, R. B.

1974-01-01

The Urban Land Use Team conducted a year's investigation of ERTS-1 MSS data to determine the number of Land Use categories in the Houston, Texas, area. They discovered unusually low classification accuracies occurred when a spectrally complex urban scene was classified with extensive rural areas containing spectrally homogeneous features. Separate computer processing of only data in the urbanized area increased classification accuracies of certain urban land use categories. Even so, accuracies of urban landscape were in the 40-70 percent range compared to 70-90 percent for the land use categories containing more homogeneous features (agriculture, forest, water, etc.) in the nonurban areas.

Geomorphology applied to landscape analysis for planning and management of natural spaces. Case study: Las Batuecas-S. de Francia and Quilamas natural parks, (Salamanca, Spain).

PubMed

Martínez-Graña, A M; Silva, P G; Goy, J L; Elez, J; Valdés, V; Zazo, C

2017-04-15

Geomorphology is fundamental to landscape analysis, as it represents the main parameter that determines the land spatial configuration and facilitates reliefs classification. The goal of this article is the elaboration of thematic maps that enable the determination of different landscape units and elaboration of quality and vulnerability synthetic maps for landscape fragility assessment prior to planning human activities. For two natural spaces, the final synthetic maps were created with direct (visual-perceptual features) and indirect (cartographic models and 3D simulations) methods from thematic maps with GIS technique. This enabled the creation of intrinsic and extrinsic landscape quality maps showing sectors needing most preservation, as well as intrinsic and extrinsic landscape fragility maps (environment response capacity or vulnerability towards human actions). The resulting map shows absorption capacity for areas of maximum and/or minimum human intervention. Sectors of high absorption capacity (minimum need for preservation) are found where the incidence of human intervention is minimum: escarpment bottoms, fitted rivers, sinuous high lands with thick vegetation coverage and valley interiors, or those areas with high landscape quality, low fragility and high absorption capacity, whose average values are found across lower hillsides of some valleys, and sectors with low absorption capacity (areas needing most preservation) found mainly in the inner parts of natural spaces: peaks and upper hillsides, synclines flanks and scattered areas. For the integral analysis of landscape, a mapping methodology has been set. It comprises a valid criterion for rational and sustainable planning, management and protection of natural spaces. Copyright © 2017 Elsevier B.V. All rights reserved.

Learnings from Opportunistic Wetlands: The Role of Substrate and Landscape Position on Reconstructed Landforms in a Sub-humid Climate

NASA Astrophysics Data System (ADS)

Little-Devito, M.; Chasmer, L.; Devito, K.; Kettridge, N.; Lukenbach, M. C.; Mendoza, C. A.

2017-12-01

Wetlands are important features in large-scale reclamation projects, and are integral to sustaining landscape eco-hydrological function and meeting reclamation goals. Despite a sub-humid climate, opportunistic wetlands are appearing on reconstructed landforms, and present an opportunity to understand the requirements for wetland construction, relative wetland succession, and their role in functioning landscapes. The relative importance and relationship between local and landscape-scale factors in determining initial wetland formation, as well as the relative occurrence and wetland type found on newly reclaimed landscapes was studied using both field and active (LiDAR) remote sensing methods. A random transect survey approach was used to characterize vegetation communities, soil and hydrologic characteristics, and local and landscape physiographic position across reconstructed landforms. Transects were also used to validate a broader area LiDAR-based classification. Preliminary findings suggest a higher frequency of opportunistic wetlands than anticipated. Soil texture of constructed landforms was important in determining the significance of local and landscape factors. On fine-textured constructed landforms, regardless of landscape position, wetlands formed on flat areas and in shallow depressions where soils had low water storage that promoted frequent surface saturation. Wetlands were less frequent on coarse-textured landforms and their location was controlled by landscape-scale factors, being restricted to the toes of slopes and areas intersecting the groundwater table. Wetlands found across all material types were predominantly Salix sp. and Carex sp. swamps with Typha sp. marsh complexes. This may indicate a potential initial phase of wetland succession and paludification in the Boreal Plains. These findings have important implications for understanding general wetland development, the initial phase of wetland paludification, and will aid the development of a geomorphic framework to better inform wetland construction and promote sustainable forest-wetland complexes similar to those found in natural landscapes.

A new approach for assessing integrated potential conditions of soil and climate for the cultivation of vines in the Azores Islands

NASA Astrophysics Data System (ADS)

Madruga, João; Azevedo, Eduardo; Reis, Francisco; Sampaio, João; Pinheiro, Jorge; Madeira, Manuel

2014-05-01

Being fairly common belief that the particular soil conditions are of great importance in defining the characteristics and qualities of the wine as the final product, it is also recognized the difficulty of establishing and interpreting this relationship clearly. The geological diversity seems to correlate with the characteristics defined in accordance with the classification system employed in France Appellation d' Origine Contrôlée (AOC), suggesting that, in addition to the variety and climate, geology and soil play an important role the properties and characteristics of the grapes produced in a given geographical location. Moreover, although it is known that the vine is tailored to a wide diversity of soil types, it appears also that many of the world's most famous vineyards are installed in poor and rocky terrain where no other crop would be grown in favorable conditions. Such is the case almost extreme implanted in the land of "cracker " and " Lagido " which are the traditional names in the archipelago of the Azores to the cracked surfaces of basaltic lava fields of heterogeneous size ranging from gravel to blocks of Azorean vineyards, whose vines manage to substrate cracks survival and production, albeit in modest yields. Apart from this traditional model of Azorean "terroir" of recognized cultural and landscape value where some interesting wines have been produced and quality recognized, there are significant areas in the islands whose soil and climate and physiographic characteristics suggest a potential for wine production that deserves to be the object of careful assessment, with a view to a possible study of integrated experimental basis. We refer specifically to landscape units of the lower area of some islands, in many cases presently devoted to pasture during the summer where productivity tends to be marginal, because strongly affected by water stress. Such areas preferably South exposed and of gentle slopes providing moderate exposure to the mechanization of farming operations, comprise weakly weathered vitric soils from pyroclastic materials, well drained, mainly over pomice deposits but also of basaltic "lapilli" which, according to the Soil Taxonomy classification generally fall in the greatgroup of Udivitrands. In this preliminary study, the edaphic, climatic and physiographic characteristics of the landscape are considered based on GIS tools, in order to define the distribution of the most representative landscape units with the greatest apparent potential for wine production in some islands of the Azores.

A 3D convolutional neural network approach to land cover classification using LiDAR and multi-temporal Landsat imagery

NASA Astrophysics Data System (ADS)

Xu, Z.; Guan, K.; Peng, B.; Casler, N. P.; Wang, S. W.

2017-12-01

Landscape has complex three-dimensional features. These 3D features are difficult to extract using conventional methods. Small-footprint LiDAR provides an ideal way for capturing these features. Existing approaches, however, have been relegated to raster or metric-based (two-dimensional) feature extraction from the upper or bottom layer, and thus are not suitable for resolving morphological and intensity features that could be important to fine-scale land cover mapping. Therefore, this research combines airborne LiDAR and multi-temporal Landsat imagery to classify land cover types of Williamson County, Illinois that has diverse and mixed landscape features. Specifically, we applied a 3D convolutional neural network (CNN) method to extract features from LiDAR point clouds by (1) creating occupancy grid, intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into a 3D CNN feature extractor for many epochs of learning. The learned features (e.g., morphological features, intensity features, etc) were combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. We used photo interpretation for training and testing data generation. The classification results show that our approach outperforms traditional methods using LiDAR derived feature maps, and promises to serve as an effective methodology for creating high-quality land cover maps through fusion of complementary types of remote sensing data.

Fifty-year spatiotemporal analysis of landscape changes in the Mont Saint-Hilaire UNESCO Biosphere Reserve (Quebec, Canada).

PubMed

Béliveau, Marc; Germain, Daniel; Ianăş, Ana-Neli

2017-05-01

Diachronic analysis with a GIS-based classification of land-use changes based on aerial photographs, orthophotos, topographic maps, geotechnical reports, urban plans, and using landscape metrics has permitted insight into the driving forces responsible for landscape fragmentation in the Mont Saint-Hilaire (MSH) Biosphere Reserve over the period 1958-2015. Although the occurrence of exogenous factors, such as extreme weather and fires, can have a significant influence on the fragmentation of the territory in time and space, the accelerated development of the built environment (+470%) is nevertheless found to be primarily responsible for landscape fragmentation and the loss of areas formerly occupied by orchards, agriculture, and woodlands. The landscape metrics used corroborate these results, with a simplification of the shape of polygons, and once again reveal the difficulties of harmonizing different land uses. MSH has become somewhat of a forest island in a sea of residential development and agriculture. To counter this isolation of fragmented habitat components, forest corridors have been proposed and developed for the Biosphere Reserve and particularly for the core area. Two corridors, to the north and south, are used to connect the protected area and other wooded areas at the regional scale, in order to promote genetic exchange between populations of various species. In that regard, the forest buffer zone around the hill continues to play a key role and has great ecological value for species and ecological preservation and conservation. However, appropriate management and landscape preservation actions should recognize and focus on landscape composition and the associated geographical configuration.

Mediterranean Land Use and Land Cover Classification Assessment Using High Spatial Resolution Data

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Boteva, Silvena

2016-10-01

Landscape fragmentation is noticeably practiced in Mediterranean regions and imposes substantial complications in several satellite image classification methods. To some extent, high spatial resolution data were able to overcome such complications. For better classification performances in Land Use Land Cover (LULC) mapping, the current research adopts different classification methods comparison for LULC mapping using Sentinel-2 satellite as a source of high spatial resolution. Both of pixel-based and an object-based classification algorithms were assessed; the pixel-based approach employs Maximum Likelihood (ML), Artificial Neural Network (ANN) algorithms, Support Vector Machine (SVM), and, the object-based classification uses the Nearest Neighbour (NN) classifier. Stratified Masking Process (SMP) that integrates a ranking process within the classes based on spectral fluctuation of the sum of the training and testing sites was implemented. An analysis of the overall and individual accuracy of the classification results of all four methods reveals that the SVM classifier was the most efficient overall by distinguishing most of the classes with the highest accuracy. NN succeeded to deal with artificial surface classes in general while agriculture area classes, and forest and semi-natural area classes were segregated successfully with SVM. Furthermore, a comparative analysis indicates that the conventional classification method yielded better accuracy results than the SMP method overall with both classifiers used, ML and SVM.

Remote sensing of landscape-level coastal environmental indicators.

PubMed

Klemas, V V

2001-01-01

Advances in technology and decreases in cost are making remote sensing (RS) and geographic information systems (GIS) practical and attractive for use in coastal resource management. They are also allowing researchers and managers to take a broader view of ecological patterns and processes. Landscape-level environmental indicators that can be detected by Landsat Thematic Mapper (TM) and other remote sensors are available to provide quantitative estimates of coastal and estuarine habitat conditions and trends. Such indicators include watershed land cover, riparian buffers, shoreline and wetland changes, among others. With the launch of Landsat 7, the cost of TM imagery has dropped by nearly a factor of 10, decreasing the cost of monitoring large coastal areas and estuaries. New satellites, carrying sensors with much finer spatial (1-5 m) and spectral (200 narrow bands) resolutions are being launched, providing a capability to more accurately detect changes in coastal habitat and wetland health. Advances in the application of GIS help incorporate ancillary data layers to improve the accuracy of satellite land-cover classification. When these techniques for generating, organizing, storing, and analyzing spatial information are combined with mathematical models, coastal planners and managers have a means for assessing the impacts of alternative management practices.

Wetland Hydrological Connectivity: A Classification Approach ...

EPA Pesticide Factsheets

Connectivity has become a major focus of hydrological and ecological studies. Connectivity influences fluxes between landscape elements, while isolation reduces flows between elements. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrologic connectivity is particularly significant, since movement of chemical constituents and biota flows are often associated with water flow. While wetlands have many important on-site functions, the degree to which they are connected to other ecosystems is a controlling influence on the effect these waters have on the larger landscape. Specifically, wetlands with high connectivity can serve as sources (e.g., net exporters of dissolved carbon), while those with low connectivity can function as sinks (e.g., net importers of suspended sediments). Here we focus on so-called “geographically isolated wetlands” (GIWs), or wetlands that are completely surrounded by uplands. While these wetlands normally lack surface water connections, they can be hydrologically connected to downstream waters through intermittent surface flow or groundwater. To help quantify connectivity of GIWs with downstream waters, we developed a system to classify GIWs based on type, magnitude, and frequency of hydrologic connectivity. We determine type (overland, shallow groundwater, or deep groundwater connectivity) by considering soil and bedrock permeability. For magnitude, we developed indices to repre

Mapping the Natchez Trace Parkway

USGS Publications Warehouse

Rangoonwala, Amina; Bannister, Terri; Ramsey, Elijah W.

2011-01-01

Based on a National Park Service (NPS) landcover classification, a landcover map of the 715-km (444-mile) NPS Natchez Trace Parkway (hereafter referred to as the "Parkway") was created. The NPS landcover classification followed National Vegetation Classification (NVC) protocols. The landcover map, which extended the initial landcover classification to the entire Parkway, was based on color-infrared photography converted to 1-m raster-based digital orthophoto quarter quadrangles, according to U.S. Geological Survey mapping standards. Our goal was to include as many alliance classes as possible in the Parkway landcover map. To reach this goal while maintaining a consistent and quantifiable map product throughout the Parkway extent, a mapping strategy was implemented based on the migration of class-based spectral textural signatures and the congruent progressive refinement of those class signatures along the Parkway. Progressive refinement provided consistent mapping by evaluating the spectral textural distinctiveness of the alliance-association classes, and where necessary, introducing new map classes along the Parkway. By following this mapping strategy, the use of raster-based image processing and geographic information system analyses for the map production provided a quantitative and reproducible product. Although field-site classification data were severely limited, the combination of spectral migration of class membership along the Parkway and the progressive classification strategy produced an organization of alliances that was internally highly consistent. The organization resulted from the natural patterns or alignments of spectral variance and the determination of those spectral patterns that were compositionally similar in the dominant species as NVC alliances. Overall, the mapped landcovers represented the existent spectral textural patterns that defined and encompassed the complex variety of compositional alliances and associations of the Parkway. Based on that mapped representation, forests dominate the Parkway landscape. Grass is the second largest Parkway land cover, followed by scrub-shrub and shrubland classes and pine plantations. The map provides a good representation of the landcover patterns and their changes over the extent of the Parkway, south to north.

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

USGS Publications Warehouse

Smith, Kathryn E.L.; Nayegandhi, Amar; Brock, John C.

2010-01-01

INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

Geologic research in support of sustainable agriculture

USGS Publications Warehouse

Gough, L.P.; Herring, J.R.

1993-01-01

The importance and role of the geosciences in studies of sustainable agriculture include such traditional research areas as, agromineral resource assessments, the mapping and classification of soils and soil amendments, and the evaluation of landscapes for their vulnerability to physical and chemical degradation. Less traditional areas of study, that are increasing in societal importance because of environmental concerns and research into sustainable systems in general, include regional geochemical studies of plant and animal trace element deficiencies and toxicities, broad-scale water quality investigations, agricultural chemicals and the hydrogeologic interface, and minimally processed and ion-exchange agrominerals. We discuss the importance and future of phosphate in the US and world based on human population growth, projected agromineral demands in general, and the unavailability of new, high-quality agricultural lands. We also present examples of studies that relate geochemistry and the hydrogeologic characteristics of a region to the bioavailability and cycling of trace elements important to sustainable agricultural systems. ?? 1993.

The development of quick, robust, quantitative phenotypic assays for describing the host–nonhost landscape to stripe rust

PubMed Central

Dawson, Andrew M.; Bettgenhaeuser, Jan; Gardiner, Matthew; Green, Phon; Hernández-Pinzón, Inmaculada; Hubbard, Amelia; Moscou, Matthew J.

2015-01-01

Nonhost resistance is often conceptualized as a qualitative separation from host resistance. Classification into these two states is generally facile, as they fail to fully describe the range of states that exist in the transition from host to nonhost. This poses a problem when studying pathosystems that cannot be classified as either host or nonhost due to their intermediate status relative to these two extremes. In this study, we investigate the efficacy of the Poaceae-stripe rust (Puccinia striiformis Westend.) interaction for describing the host–nonhost landscape. First, using barley (Hordeum vulgare L.) and Brachypodium distachyon (L.) P. Beauv. We observed that macroscopic symptoms of chlorosis and leaf browning were associated with hyphal colonization by P. striiformis f. sp. tritici, respectively. This prompted us to adapt a protocol for visualizing fungal structures into a phenotypic assay that estimates the percent of leaf colonized. Use of this assay in intermediate host and intermediate nonhost systems found the frequency of infection decreases with evolutionary divergence from the host species. Similarly, we observed that the pathogen’s ability to complete its life cycle decreased faster than its ability to colonize leaf tissue, with no incidence of pustules observed in the intermediate nonhost system and significantly reduced pustule formation in the intermediate host system as compared to the host system, barley-P. striiformis f. sp. hordei. By leveraging the stripe rust pathosystem in conjunction with macroscopic and microscopic phenotypic assays, we now hope to dissect the genetic architecture of intermediate host and intermediate nonhost resistance using structured populations in barley and B. distachyon. PMID:26579142

Multi-scale curvature for automated identification of glaciated mountain landscapes

NASA Astrophysics Data System (ADS)

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2014-03-01

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes.

Fuel characterization in the southern Appalachian Mountains: an application of landscape ecosystem classification

Treesearch

Aaron D. Stottlemeyer; Victor B. Shelburne; Thomas A. Waldrop; Sandra Rideout-Hanzak; William C. Bridges

2009-01-01

Prescribed fire has been widely used in the south-eastern United States to meet forest management objectives, but has only recently been reintroduced to the southern Appalachian Mountains. Fuel information is not available to forest managers in this region and direct measurement is often impractical owing to steep, remote topography. The objective of the present study...

Testing and classification of individual plants for fire behaviour: plant selection for the wildland–urban interface

Treesearch

Robert H. White; Wayne C. Zipperer

2010-01-01

Knowledge of how species differ in their flammability characteristics is needed to develop more reliable lists of plants recommended for landscaping homes in the wildland–urban interface (WUI). As indicated by conflicting advice in such lists, such characterisation is not without difficulties and disagreements. The flammability of vegetation is often described as...

Nebraska Vocational Agribusiness Curriculum for City Schools. Horticulture. Agricultural Mechanics. A Curriculum Guide. 11th Grade.

ERIC Educational Resources Information Center

Nebraska Univ., Lincoln. Dept. of Agricultural Education.

Designed for use with high school juniors, this agribusiness curriculum for city schools contains thirty-two units of instruction in the areas of horticulture and agricultural mechanics. Among the units included in the curriculum are (1) Planting Media, (2) Fertilizer, (3) Plant Classification, (4) Turf Grass Management, (5) Landscape Design, (6)…

Hierarchical subdivisions of the Columbia Plateau and Blue Mountains ecoregions, Oregon and Washington.

Treesearch

Sharon E. Clarke; Sandra A. Bryce

1997-01-01

This document presents two spatial scales of a hierarchical, ecoregional framework and provides a connection to both larger and smaller scale ecological classifications. The two spatial scales are subregions (1:250,000) and landscape-level ecoregions (1:100,000), or Level IV and Level V ecoregions. Level IV ecoregions were developed by the Environmental Protection...

Monitoring urban tree cover using object-based image analysis and public domain remotely sensed data

Treesearch

L. Monika Moskal; Diane M. Styers; Meghan Halabisky

2011-01-01

Urban forest ecosystems provide a range of social and ecological services, but due to the heterogeneity of these canopies their spatial extent is difficult to quantify and monitor. Traditional per-pixel classification methods have been used to map urban canopies, however, such techniques are not generally appropriate for assessing these highly variable landscapes....

Do We Need a New Definition of Soil?

NASA Astrophysics Data System (ADS)

Arnold, Richard W.; Brevik, Eric C.

2014-05-01

Effective communication is really desirable to better relate with politicians, an interested lay public, and others not involved in soil science. Soil survey programs are intended to help people understand how soils function in their landscapes to make ecosystems operate better without damaging the environment and to indicate different kinds of suitability for various purposes. The properties of soils as recognized, described, and mapped at detailed scales form the basis for developing diagnostics for a systematic taxonomy that enables scientists to interact with other. In the USA mapping done at scales of 1:15,840± made it possible to define and use so-called "soil series", initially as soil map units, but later as central concepts of a set of soils which could be segregated using phases to indicate important features, primarily for farming. Detailed soil surveys published using a standard format helps maintain uniformity across the country. Soil series are recognized as the basic units of soils within the evolving hierarchical soil taxonomy and diagnostic properties are defined, measured and used to update and modify the scientific classification. Concepts like soil quality and soil function are considered to be "attributes" and not basic properties of soils. They are the collective interpretation of the combination of properties thought to be relevant for communicating important aspects of using, managing, restoring, and protecting the lands of any locality, region, or country. A famous example in the US was the land capability system with classes and subclasses of suitability for agricultural land uses. An updated soil survey in California contains over 500 pages providing details about classes of 30 different functional soil classifications for 155 map units. Over the years soil extension agents were the interpreters of the science to the lay folks and could help them form mental pictures of soils and soil landscapes locally They were the early leaders of what we think of as "field guides to natural resources" such as trees, flowers, birds, and so forth. There were not such books to identify soils but the basics have always been there waiting for proper attention, preparation, and use. At smaller scales the map units are always combinations of the basic units, and now it is possible to use some higher category classes to indicate the central concepts of larger areas. Every year soil scientists around the world observe and describe features and properties of soils in landscapes that are getting more attention than previously. Soil genesis studies help us to better understand the complexity of landscape and soil evolution. Often they indicate that current soils are commonly being formed from parts of previous soils. We do not need a new definition of soil. We do need to work on developing and testing complete interpretive classifications of soils to better meet the needs of societies today. This means "soil quality", "soil functions", and other attributes of soils require more attention, now and in the near future to permit politicians and lay publics to better understand the significance of soils to the future of civilization. "After all is said and done, more is said than done" Aesop, Greek storyteller

Mapping Human-Dominated Landscapes: the Distribution and Yield of Major Crops of the World

NASA Astrophysics Data System (ADS)

Monfreda, C.; Ramankutty, N.; Foley, J. A.

2005-12-01

Croplands cover 18 million km2, an area the size of South America, and provide ecosystem goods and services essential to human well-being. Most global land-cover classifications group the diversity of croplands into a single or very few categories, thereby excluding critical information to answer key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information on land-use practices is even more limited. The relative lack of information about agricultural landscapes results partly from difficulties in using satellite data to identify individual crop types and land-use practices at a global scale. We address limitations common to remote-sensing classifications by distributing national, state, and county level statistics across a recently updated global dataset of cropland cover at 5 minute resolution. The resulting datasets depict the fractional harvested area and yield of twenty distinct crop types: maize, wheat, rice, sorghum, millet, barley, oats, soybeans, sunflower, rapeseed/canola, pulses, groundnuts/peanuts, oil palm, cassava, potatoes, sugar cane, sugar beets, tobacco, coffee, and cotton. These datasets represent the state of agriculture circa the year 2000 and will be made available for applications in ecological analysis, modeling, visualization, and education.

Gap Shape Classification using Landscape Indices and Multivariate Statistics

PubMed Central

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-01-01

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap. PMID:27901127

Gap Shape Classification using Landscape Indices and Multivariate Statistics.

PubMed

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-11-30

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks' lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.

Delineation of marsh types of the Texas coast from Corpus Christi Bay to the Sabine River in 2010

USGS Publications Warehouse

Enwright, Nicholas M.; Hartley, Stephen B.; Brasher, Michael G.; Visser, Jenneke M.; Mitchell, Michael K.; Ballard, Bart M.; Parr, Mark W.; Couvillion, Brady R.; Wilson, Barry C.

2014-01-01

Coastal zone managers and researchers often require detailed information regarding emergent marsh vegetation types for modeling habitat capacities and needs of marsh-reliant wildlife (such as waterfowl and alligator). Detailed information on the extent and distribution of marsh vegetation zones throughout the Texas coast has been historically unavailable. In response, the U.S. Geological Survey, in cooperation and collaboration with the U.S. Fish and Wildlife Service via the Gulf Coast Joint Venture, Texas A&M University-Kingsville, the University of Louisiana-Lafayette, and Ducks Unlimited, Inc., has produced a classification of marsh vegetation types along the middle and upper Texas coast from Corpus Christi Bay to the Sabine River. This study incorporates approximately 1,000 ground reference locations collected via helicopter surveys in coastal marsh areas and about 2,000 supplemental locations from fresh marsh, water, and “other” (that is, nonmarsh) areas. About two-thirds of these data were used for training, and about one-third were used for assessing accuracy. Decision-tree analyses using Rulequest See5 were used to classify emergent marsh vegetation types by using these data, multitemporal satellite-based multispectral imagery from 2009 to 2011, a bare-earth digital elevation model (DEM) based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables believed to be important for delineating the extent and distribution of marsh vegetation communities. Image objects were generated from segmentation of high-resolution airborne imagery acquired in 2010 and were used to refine the classification. The classification is dated 2010 because the year is both the midpoint of the multitemporal satellite-based imagery (2009–11) classified and the date of the high-resolution airborne imagery that was used to develop image objects. Overall accuracy corrected for bias (accuracy estimate incorporates true marginal proportions) was 91 percent (95 percent confidence interval [CI]: 89.2–92.8), with a kappa statistic of 0.79 (95 percent CI: 0.77–0.81). The classification performed best for saline marsh (user’s accuracy 81.5 percent; producer’s accuracy corrected for bias 62.9 percent) but showed a lesser ability to discriminate intermediate marsh (user’s accuracy 47.7 percent; producer’s accuracy corrected for bias 49.5 percent). Because of confusion in intermediate and brackish marsh classes, an alternative classification containing only three marsh types was created in which intermediate and brackish marshes were combined into a single class. Image objects were reattributed by using this alternative three-marsh-type classification. Overall accuracy, corrected for bias, of this more general classification was 92.4 percent (95 percent CI: 90.7–94.2), and the kappa statistic was 0.83 (95 percent CI: 0.81–0.85). Mean user’s accuracy for marshes within the four-marsh-type and three-marsh-type classifications was 65.4 percent and 75.6 percent, respectively, whereas mean producer’s accuracy was 56.7 percent and 65.1 percent, respectively. This study provides a more objective and repeatable method for classifying marsh types of the middle and upper Texas coast at an extent and greater level of detail than previously available for the study area. The seamless classification produced through this work is now available to help State agencies (such as the Texas Parks and Wildlife Department) and landscape-scale conservation partnerships (such as the Gulf Coast Prairie Landscape Conservation Cooperative and the Gulf Coast Joint Venture) to develop and (or) refine conservation plans targeting priority natural resources. Moreover, these data may improve projections of landscape change and serve as a baseline for monitoring future changes resulting from chronic and episodic stressors.

A new map of standardized terrestrial ecosystems of Africa

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Hak, Jon; Josse, Carmen; Bow, Jacquie; Warner, Harumi; Larwanou, Mahamane; Kelbessa, Ensermu; Bekele, Tamrat; Kehl, Harald; Amena, Ruba; Andriamasimanana, Rado; Ba, Taibou; Benson, Laurence; Boucher, Timothy; Brown, Matthew; Cress, Jill J.; Dassering, Oueddo; Friesen, Beverly A.; Gachathi, Francis; Houcine, Sebei; Keita, Mahamadou; Khamala, Erick; Marangu, Dan; Mokua, Fredrick; Morou, Boube; Mucina, Ladislav; Mugisha, Samuel; Mwavu, Edward; Rutherford, Michael; Sanou, Patrice; Syampungani, Stephen; Tomor, Bojoi; Vall, Abdallahi Ould Mohamed; Vande Weghe, Jean Pierre; Wangui, Eunice; Waruingi, Lucy

2013-01-01

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

Forest Loss and the Biodiversity Threshold: An Evaluation Considering Species Habitat Requirements and the Use of Matrix Habitats

PubMed Central

Estavillo, Candelaria; Pardini, Renata; da Rocha, Pedro Luís Bernardo

2013-01-01

Habitat loss is the main driver of the current biodiversity crisis, a landscape-scale process that affects the survival of spatially-structured populations. Although it is well-established that species responses to habitat loss can be abrupt, the existence of a biodiversity threshold is still the cause of much controversy in the literature and would require that most species respond similarly to the loss of native vegetation. Here we test the existence of a biodiversity threshold, i.e. an abrupt decline in species richness, with habitat loss. We draw on a spatially-replicated dataset on Atlantic forest small mammals, consisting of 16 sampling sites divided between forests and matrix habitats in each of five 3600-ha landscapes (varying from 5% to 45% forest cover), and on an a priori classification of species into habitat requirement categories (forest specialists, habitat generalists and open-area specialists). Forest specialists declined abruptly below 30% of forest cover, and spillover to the matrix occurred only in more forested landscapes. Generalists responded positively to landscape heterogeneity, peaking at intermediary levels of forest cover. Open area specialists dominated the matrix and did not spillover to forests. As a result of these distinct responses, we observed a biodiversity threshold for the small mammal community below 30% forest cover, and a peak in species richness just above this threshold. Our results highlight that cross habitat spillover may be asymmetrical and contingent on landscape context, occurring mainly from forests to the matrix and only in more forested landscapes. Moreover, they indicate the potential for biodiversity thresholds in human-modified landscapes, and the importance of landscape heterogeneity to biodiversity. Since forest loss affected not only the conservation value of forest patches, but also the potential for biodiversity-mediated services in anthropogenic habitats, our work indicates the importance of proactive measures to avoid human-modified landscapes to cross this threshold. PMID:24324776

Geospatial Analysis of Atmospheric Haze Effect by Source and Sink Landscape

NASA Astrophysics Data System (ADS)

Yu, T.; Xu, K.; Yuan, Z.

2017-09-01

Based on geospatial analysis model, this paper analyzes the relationship between the landscape patterns of source and sink in urban areas and atmospheric haze pollution. Firstly, the classification result and aerosol optical thickness (AOD) of Wuhan are divided into a number of square grids with the side length of 6 km, and the category level landscape indices (PLAND, PD, COHESION, LPI, FRAC_MN) and AOD of each grid are calculated. Then the source and sink landscapes of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. Next, to make the following analysis more efficient, the indices selected before should be determined through the correlation coefficient between them. Finally, due to the spatial dependency and spatial heterogeneity of the data used in this paper, spatial autoregressive model and geo-weighted regression model are used to analyze atmospheric haze effect by source and sink landscape from the global and local level. The results show that the source landscape of atmospheric haze pollution is the building, and the sink landscapes are shrub and woodland. PLAND, PD and COHESION are suitable for describing the atmospheric haze effect by source and sink landscape. Comparing these models, the fitting effect of SLM, SEM and GWR is significantly better than that of OLS model. The SLM model is superior to the SEM model in this paper. Although the fitting effect of GWR model is more unsuited than that of SLM, the influence degree of influencing factors on atmospheric haze of different geography can be expressed clearer. Through the analysis results of these models, following conclusions can be summarized: Reducing the proportion of source landscape area and increasing the degree of fragmentation could cut down aerosol optical thickness; And distributing the source and sink landscape evenly and interspersedly could effectively reduce aerosol optical thickness which represents atmospheric haze pollution; For Wuhan City, the method of adjusting the built-up area slightly and planning the non-built-up areas reasonably can be taken to reduce atmospheric haze pollution.

Large-scale high-resolution non-invasive geophysical archaeological prospection for the investigation of entire archaeological landscapes

NASA Astrophysics Data System (ADS)

Trinks, Immo; Neubauer, Wolfgang; Hinterleitner, Alois; Kucera, Matthias; Löcker, Klaus; Nau, Erich; Wallner, Mario; Gabler, Manuel; Zitz, Thomas

2014-05-01

Over the past three years the 2010 in Vienna founded Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology (http://archpro.lbg.ac.at), in collaboration with its ten European partner organizations, has made considerable progress in the development and application of near-surface geophysical survey technology and methodology mapping square kilometres rather than hectares in unprecedented spatial resolution. The use of multiple novel motorized multichannel GPR and magnetometer systems (both Förster/Fluxgate and Cesium type) in combination with advanced and centimetre precise positioning systems (robotic totalstations and Realtime Kinematic GPS) permitting efficient navigation in open fields have resulted in comprehensive blanket coverage archaeological prospection surveys of important cultural heritage sites, such as the landscape surrounding Stonehenge in the framework of the Stonehenge Hidden Landscape Project, the mapping of the World Cultural Heritage site Birka-Hovgården in Sweden, or the detailed investigation of the Roman urban landscape of Carnuntum near Vienna. Efficient state-of-the-art archaeological prospection survey solutions require adequate fieldwork methodologies and appropriate data processing tools for timely quality control of the data in the field and large-scale data visualisations after arrival back in the office. The processed and optimized visualisations of the geophysical measurement data provide the basis for subsequent archaeological interpretation. Integration of the high-resolution geophysical prospection data with remote sensing data acquired through aerial photography, airborne laser- and hyperspectral-scanning, terrestrial laser-scanning or detailed digital terrain models derived through photogrammetric methods permits improved understanding and spatial analysis as well as the preparation of comprehensible presentations for the stakeholders (scientific community, cultural heritage managers, public). Of paramount importance in regard to large-scale high-resolution data acquisition when using motorized survey systems is the exact data positioning as well as the removal of any measurement effects caused by the survey vehicle. The large amount of generated data requires efficient semi-automatic and automatized tools for the extraction and rendering of important information. Semi-automatic data segmentation and classification precede the detailed 3D archaeological interpretation, which still requires considerable manual input. We present the latest technological and methodological developments in regard to motorized near-surface GPR and magnetometer prospection as well as application examples from different iconic European archaeological sites.

Mapping ecological states in a complex environment

NASA Astrophysics Data System (ADS)

Steele, C. M.; Bestelmeyer, B.; Burkett, L. M.; Ayers, E.; Romig, K.; Slaughter, A.

2013-12-01

The vegetation of northern Chihuahuan Desert rangelands is sparse, heterogeneous and for most of the year, consists of a large proportion of non-photosynthetic material. The soils in this area are spectrally bright and variable in their reflectance properties. Both factors provide challenges to the application of remote sensing for estimating canopy variables (e.g., leaf area index, biomass, percentage canopy cover, primary production). Additionally, with reference to current paradigms of rangeland health assessment, remotely-sensed estimates of canopy variables have limited practical use to the rangeland manager if they are not placed in the context of ecological site and ecological state. To address these challenges, we created a multifactor classification system based on the USDA-NRCS ecological site schema and associated state-and-transition models to map ecological states on desert rangelands in southern New Mexico. Applying this system using per-pixel image processing techniques and multispectral, remotely sensed imagery raised other challenges. Per-pixel image classification relies upon the spectral information in each pixel alone, there is no reference to the spatial context of the pixel and its relationship with its neighbors. Ecological state classes may have direct relevance to managers but the non-unique spectral properties of different ecological state classes in our study area means that per-pixel classification of multispectral data performs poorly in discriminating between different ecological states. We found that image interpreters who are familiar with the landscape and its associated ecological site descriptions perform better than per-pixel classification techniques in assigning ecological states. However, two important issues affect manual classification methods: subjectivity of interpretation and reproducibility of results. An alternative to per-pixel classification and manual interpretation is object-based image analysis. Object-based image analysis provides a platform for classification that more closely resembles human recognition of objects within a remotely sensed image. The analysis presented here compares multiple thematic maps created for test locations on the USDA-ARS Jornada Experimental Range ranch. Three study sites in different pastures, each 300 ha in size, were selected for comparison on the basis of their ecological site type (';Clayey', ';Sandy' and a combination of both) and the degree of complexity of vegetation cover. Thematic maps were produced for each study site using (i) manual interpretation of digital aerial photography (by five independent interpreters); (ii) object-oriented, decision-tree classification of fine and moderate spatial resolution imagery (Quickbird; Landsat Thematic Mapper) and (iii) ground survey. To identify areas of uncertainty, we compared agreement in location, areal extent and class assignation between 5 independently produced, manually-digitized ecological state maps and with the map created from ground survey. Location, areal extent and class assignation of the map produced by object-oriented classification was also assessed with reference to the ground survey map.

Local disturbance cycles and the maintenance of heterogeneity across scales in marine metapopulations.

PubMed

Gouhier, Tarik C; Guichard, Frédéric

2007-03-01

In marine systems, the occurrence and implications of disturbance-recovery cycles have been revealed at the landscape level, but only in demographically open or closed systems where landscape-level dynamics are assumed to have no feedback effect on regional dynamics. We present a mussel metapopulation model to elucidate the role of landscape-level disturbance cycles for regional response of mussel populations to onshore productivity and larval transport. Landscape dynamics are generated through spatially explicit rules, and each landscape is connected to its neighbor through unidirectional larval dispersal. The role of landscape disturbance cycles in the regional system behavior is elucidated (1) in demographically open vs. demographically coupled systems, in relation to (2) onshore reproductive output and (3) the temporal scale of landscape disturbance dynamics. By controlling for spatial structure at the landscape and metapopulation levels, we first demonstrate the interaction between landscape and oceanographic connectivity. The temporal scale of disturbance cycles, as controlled by mussel colonization rate, plays a critical role in the regional behavior of the system. Indeed, fast disturbance cycles are responsible for regional synchrony in relation to onshore reproductive output. Slow disturbance cycles, however, lead to increased robustness to changes in productivity and to demographic coupling. These testable predictions indicate that the occurrence and temporal scale of local disturbance-recovery dynamics can drive large-scale variability in demographically open systems, and the response of metapopulations to changes in nearshore productivity.

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-12-09

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed

Luna-José, Azucena de Lourdes; Aguilar, Beatriz Rendón

2012-07-12

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants-soil-vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources.

Tidal wetlands of the Yaquina and Alsea River estuaries, Oregon: Geographic Information Systems layer development and recommendations for National Wetlands Inventory revisions

USGS Publications Warehouse

Brophy, Laura S.; Reusser, Deborah A.; Janousek, Christopher N.

2013-01-01

Geographic Information Systems (GIS) layers of current, and likely former, tidal wetlands in two Oregon estuaries were generated by enhancing the 2010 National Wetlands Inventory (NWI) data with expert local field knowledge, Light Detection and Ranging-derived elevations, and 2009 aerial orthophotographs. Data were generated for two purposes: First, to enhance the NWI by recommending revised Cowardin classifications for certain NWI wetlands within the study area; and second, to generate GIS data for the 1999 Yaquina and Alsea River Basins Estuarine Wetland Site Prioritization study. Two sets of GIS products were generated: (1) enhanced NWI shapefiles; and (2) shapefiles of prioritization sites. The enhanced NWI shapefiles contain recommended changes to the Cowardin classification (system, subsystem, class, and/or modifiers) for 286 NWI polygons in the Yaquina estuary (1,133 acres) and 83 NWI polygons in the Alsea estuary (322 acres). These enhanced NWI shapefiles also identify likely former tidal wetlands that are classified as upland in the current NWI (64 NWI polygons totaling 441 acres in the Yaquina estuary; 16 NWI polygons totaling 51 acres in the Alsea estuary). The former tidal wetlands were identified to assist strategic planning for tidal wetland restoration. Cowardin classifications for the former tidal wetlands were not provided, because their current hydrology is complex owing to dikes, tide gates, and drainage ditches. The scope of this project did not include the field evaluation that would be needed to determine whether the former tidal wetlands are currently wetlands, and if so, determine their correct Cowardin classification. The prioritization site shapefiles contain 49 prioritization sites totaling 2,177 acres in the Yaquina estuary, and 39 prioritization sites totaling 1,045 acres in the Alsea estuary. The prioritization sites include current and former (for example, diked) tidal wetlands, and provide landscape units appropriate for basin-scale wetland restoration and conservation action planning. Several new prioritization sites (not included in the 1999 prioritization) were identified in each estuary, consisting of NWI polygons formerly classified as nontidal wetland or upland. The GIS products of this project improve the accuracy and utility of the NWI data, and provide useful tools for estuarine resource management.

Spatial disaggregation of complex soil map units at regional scale based on soil-landscape relationships

NASA Astrophysics Data System (ADS)

Vincent, Sébastien; Lemercier, Blandine; Berthier, Lionel; Walter, Christian

2015-04-01

Accurate soil information over large extent is essential to manage agronomical and environmental issues. Where it exists, information on soil is often sparse or available at coarser resolution than required. Typically, the spatial distribution of soil at regional scale is represented as a set of polygons defining soil map units (SMU), each one describing several soil types not spatially delineated, and a semantic database describing these objects. Delineation of soil types within SMU, ie spatial disaggregation of SMU allows improved soil information's accuracy using legacy data. The aim of this study was to predict soil types by spatial disaggregation of SMU through a decision tree approach, considering expert knowledge on soil-landscape relationships embedded in soil databases. The DSMART (Disaggregation and Harmonization of Soil Map Units Through resampled Classification Trees) algorithm developed by Odgers et al. (2014) was used. It requires soil information, environmental covariates, and calibration samples, to build then extrapolate decision trees. To assign a soil type to a particular spatial position, a weighed random allocation approach is applied: each soil type in the SMU is weighted according to its assumed proportion of occurrence in the SMU. Thus soil-landscape relationships are not considered in the current version of DSMART. Expert rules on soil distribution considering the relief, parent material and wetlands location were proposed to drive the procedure of allocation of soil type to sampled positions, in order to integrate the soil-landscape relationships. Semantic information about spatial organization of soil types within SMU and exhaustive landscape descriptors were used. In the eastern part of Brittany (NW France), 171 soil types were described; their relative area in the SMU were estimated, geomorphological and geological contexts were recorded. The model predicted 144 soil types. An external validation was performed by comparing predicted with effectively observed soil types derived from available soil maps at scale of 1:25.000 or 1:50.000. Overall accuracies were 63.1% and 36.2%, respectively considering or not the adjacent pixels. The introduction of expert rules based on soil-landscape relationships to allocate soil types to calibration samples enhanced dramatically the results in comparison with a simple weighted random allocation procedure. It also enabled the production of a comprehensive soil map, retrieving expected spatial organization of soils. Estimation of soil properties for various depths is planned using disaggregated soil types, according to the GlobalSoilmap.net specifications. Odgers, N.P., Sun, W., McBratney, A.B., Minasny, B., Clifford, D., 2014. Disaggregating and harmonising soil map units through resampled classification trees. Geoderma 214, 91-100.

Mapping wetland and forest landscapes in Siberia with Landsat data

NASA Astrophysics Data System (ADS)

Maksyutov, Shamil; Kleptsova, Irina; Glagolev, Mikhail; Sedykh, Vladimir; Kuzmenko, Ekaterina; Silaev, Anton; Frolov, Alexander; Nikolaeva, Svetlana; Fedorov, Alexander

2014-05-01

Landsat data availability provides opportunity for improving the knowledge of the Siberian ecosystems necessary for quantifying the response of the regional carbon cycle to the climate change. We developed a new wetland map based on Landsat data for whole West Siberia aiming at scaling up the methane emission observations. Mid-summer Landsat scenes were used in supervised classification method, based on ground truth data obtained during multiple field surveys. The method allows distinguishing following wetland types: pine-dwarf shrubs-sphagnum bogs or ryams, ridge-hollows complexes, shallow-water complexes, sedge-sphagnum poor fens, herbaceous-sphagnum poor fens, sedge-(moss) poor fens and fens, wooded swamps or sogra, palsa complexes. In our estimates wetlands cover 36% of the taiga area. Total methane emission from WS taiga mires is estimated as 3.6 TgC/yr,which is 77% larger as compared to the earlier estimate based on partial Landsat mapping combined with low resolution map due to higher fraction of fen area. We make an attempt to develop a forest typology system useful for a dynamic vegetation modeling and apply it to the analysis of the forest type distribution for several test areas in West and East Siberia, aiming at capability of mapping whole Siberian forests based on Landsat data. Test region locations are: two in West Siberian middle taiga (Laryegan and Nyagan), and one in East Siberia near Yakutsk. The ground truth data are based on analysis of the field survey, forest inventory data from the point of view of the successional forest type classification. Supervised classification was applied to the areas where ample ground truth and inventory data are available, using several limited area maps and vegetation survey. In Laryegan basin the upland forest areas are dominated (as climax forest species) by Scots pine on sandy soils and Siberian pine with presence of fir and spruce on the others. Those types are separable using Landsat spectral data alone. In the permafrost area around Yakutsk the most widespread succession type is birch to larch succession. Three stages of the birch to larch succession are detectable from Landsat image. When Landsat data is used in both West and East Siberia, distinction between deciduous broad-leaved species (birch, aspen, and willow) is difficult due to similarity in spectral signatures. Same problem exists for distinguishing between dark coniferous species (Siberian pine, fir and spruce). Forest classification can be improved by applying landscape type analysis, such as separation into floodplain, terrace, sloping hills.

Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object based classification approaches

Treesearch

Dacia M. Meneguzzo; Greg C. Liknes; Mark D. Nelson

2013-01-01

Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics....

Using a terrestrial ecosystem survey to estimate the historical density of ponderosa pine trees

Treesearch

Scott R. Abella; Charles W. Denton; David G. Brewer; Wayne A. Robbie; Rory W. Steinke; W. Wallace Covington

2011-01-01

Maps of historical tree densities for project areas and landscapes may be useful for a variety of management purposes such as determining site capabilities and planning forest thinning treatments. We used the U.S. Forest Service Region 3 terrestrial ecosystem survey in a novel way to determine if the ecosystem classification is a useful a guide for estimating...

Analysis of landscape fragmentation in the Peloncillo Mountains in relation to wildfire, prescribed burning, and cattle grazing

Treesearch

John Rogan; Kelley O' Neal; Stephen Yool

2005-01-01

This paper examined the application of state-of-the-art remote sensing image enhancement and classification techniques for mapping land cover change in the Peloncillo Mountains of Arizona and New Mexico. Spectrally enhanced images acquired August 1985, 1991, 1996, and 2000 were combined with environmental variables such as slope and aspect to map land cover...

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

NASA Astrophysics Data System (ADS)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods. Results show that both STARFM and FSDAF predicted in low accuracy in second type pixels and small patches. Classification results used spatial-temporal image fusion method proposed in this study showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87.

Neighbourhood-scale urban forest ecosystem classification.

PubMed

Steenberg, James W N; Millward, Andrew A; Duinker, Peter N; Nowak, David J; Robinson, Pamela J

2015-11-01

Urban forests are now recognized as essential components of sustainable cities, but there remains uncertainty concerning how to stratify and classify urban landscapes into units of ecological significance at spatial scales appropriate for management. Ecosystem classification is an approach that entails quantifying the social and ecological processes that shape ecosystem conditions into logical and relatively homogeneous management units, making the potential for ecosystem-based decision support available to urban planners. The purpose of this study is to develop and propose a framework for urban forest ecosystem classification (UFEC). The multifactor framework integrates 12 ecosystem components that characterize the biophysical landscape, built environment, and human population. This framework is then applied at the neighbourhood scale in Toronto, Canada, using hierarchical cluster analysis. The analysis used 27 spatially-explicit variables to quantify the ecosystem components in Toronto. Twelve ecosystem classes were identified in this UFEC application. Across the ecosystem classes, tree canopy cover was positively related to economic wealth, especially income. However, education levels and homeownership were occasionally inconsistent with the expected positive relationship with canopy cover. Open green space and stocking had variable relationships with economic wealth and were more closely related to population density, building intensity, and land use. The UFEC can provide ecosystem-based information for greening initiatives, tree planting, and the maintenance of the existing canopy. Moreover, its use has the potential to inform the prioritization of limited municipal resources according to ecological conditions and to concerns of social equity in the access to nature and distribution of ecosystem service supply. Copyright © 2015 Elsevier Ltd. All rights reserved.

Methods for integrated modeling of landscape change: Interior Northwest Landscape Analysis System.

Treesearch

Jane L. Hayes; Alan. A. Ager; R. James Barbour

2004-01-01

The Interior Northwest Landscape Analysis System (INLAS) links a number of resource, disturbance, and landscape simulations models to examine the interactions of vegetative succession, management, and disturbance with policy goals. The effects of natural disturbance like wildfire, herbivory, forest insects and diseases, as well as specific management actions are...

Monitoring landscape metrics by point sampling: accuracy in estimating Shannon's diversity and edge density.

PubMed

Ramezani, Habib; Holm, Sören; Allard, Anna; Ståhl, Göran

2010-05-01

Environmental monitoring of landscapes is of increasing interest. To quantify landscape patterns, a number of metrics are used, of which Shannon's diversity, edge length, and density are studied here. As an alternative to complete mapping, point sampling was applied to estimate the metrics for already mapped landscapes selected from the National Inventory of Landscapes in Sweden (NILS). Monte-Carlo simulation was applied to study the performance of different designs. Random and systematic samplings were applied for four sample sizes and five buffer widths. The latter feature was relevant for edge length, since length was estimated through the number of points falling in buffer areas around edges. In addition, two landscape complexities were tested by applying two classification schemes with seven or 20 land cover classes to the NILS data. As expected, the root mean square error (RMSE) of the estimators decreased with increasing sample size. The estimators of both metrics were slightly biased, but the bias of Shannon's diversity estimator was shown to decrease when sample size increased. In the edge length case, an increasing buffer width resulted in larger bias due to the increased impact of boundary conditions; this effect was shown to be independent of sample size. However, we also developed adjusted estimators that eliminate the bias of the edge length estimator. The rates of decrease of RMSE with increasing sample size and buffer width were quantified by a regression model. Finally, indicative cost-accuracy relationships were derived showing that point sampling could be a competitive alternative to complete wall-to-wall mapping.

Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

NASA Astrophysics Data System (ADS)

Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Mohd. Saleh, N.; Wong, C. J.; Surbakti, M. S.

2008-03-01

Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

Aerial Images from AN Uav System: 3d Modeling and Tree Species Classification in a Park Area

NASA Astrophysics Data System (ADS)

Gini, R.; Passoni, D.; Pinto, L.; Sona, G.

2012-07-01

The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs) is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment): it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes). Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs) were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS) and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.

Multiple coupled landscapes and non-adiabatic dynamics with applications to self-activating genes.

PubMed

Chen, Cong; Zhang, Kun; Feng, Haidong; Sasai, Masaki; Wang, Jin

2015-11-21

Many physical, chemical and biochemical systems (e.g. electronic dynamics and gene regulatory networks) are governed by continuous stochastic processes (e.g. electron dynamics on a particular electronic energy surface and protein (gene product) synthesis) coupled with discrete processes (e.g. hopping among different electronic energy surfaces and on and off switching of genes). One can also think of the underlying dynamics as the continuous motion on a particular landscape and discrete hoppings among different landscapes. The main difference of such systems from the intra-landscape dynamics alone is the emergence of the timescale involved in transitions among different landscapes in addition to the timescale involved in a particular landscape. The adiabatic limit when inter-landscape hoppings are fast compared to continuous intra-landscape dynamics has been studied both analytically and numerically, but the analytical treatment of the non-adiabatic regime where the inter-landscape hoppings are slow or comparable to continuous intra-landscape dynamics remains challenging. In this study, we show that there exists mathematical mapping of the dynamics on 2(N) discretely coupled N continuous dimensional landscapes onto one single landscape in 2N dimensional extended continuous space. On this 2N dimensional landscape, eddy current emerges as a sign of non-equilibrium non-adiabatic dynamics and plays an important role in system evolution. Many interesting physical effects such as the enhancement of fluctuations, irreversibility, dissipation and optimal kinetics emerge due to non-adiabaticity manifested by the eddy current illustrated for an N = 1 self-activator. We further generalize our theory to the N-gene network with multiple binding sites and multiple synthesis rates for discretely coupled non-equilibrium stochastic physical and biological systems.

Characterization of the Nencki Affective Picture System by discrete emotional categories (NAPS BE).

PubMed

Riegel, Monika; Żurawski, Łukasz; Wierzba, Małgorzata; Moslehi, Abnoss; Klocek, Łukasz; Horvat, Marko; Grabowska, Anna; Michałowski, Jarosław; Jednoróg, Katarzyna; Marchewka, Artur

2016-06-01

The Nencki Affective Picture System (NAPS; Marchewka, Żurawski, Jednoróg, & Grabowska, Behavior Research Methods, 2014) is a standardized set of 1,356 realistic, high-quality photographs divided into five categories (people, faces, animals, objects, and landscapes). NAPS has been primarily standardized along the affective dimensions of valence, arousal, and approach-avoidance, yet the characteristics of discrete emotions expressed by the images have not been investigated thus far. The aim of the present study was to collect normative ratings according to categorical models of emotions. A subset of 510 images from the original NAPS set was selected in order to proportionally cover the whole dimensional affective space. Among these, using three available classification methods, we identified images eliciting distinguishable discrete emotions. We introduce the basic-emotion normative ratings for the Nencki Affective Picture System (NAPS BE), which will allow researchers to control and manipulate stimulus properties specifically for their experimental questions of interest. The NAPS BE system is freely accessible to the scientific community for noncommercial use as supplementary materials to this article.

Who Died, Where? Quantification of Drought-Induced Tree Mortality in Texas

NASA Astrophysics Data System (ADS)

Schwantes, A.; Swenson, J. J.; Johnson, D. M.; Domec, J. C.; Jackson, R. B.

2014-12-01

During 2011, Texas experienced a severe drought that killed millions of trees across the state. Drought-induced tree mortality can have significant ecological impacts and is expected to increase with climate change. We identify methods to quantify tree mortality in central Texas by using remotely sensed images before and after the drought at multiple spatial resolutions. Fine-scale tree mortality maps were created by classifying 1-m orthophotos from the National Agriculture Imagery Program. These classifications showed a high correlation with field estimates of percent canopy loss (RMSE = 2%; R2=0.9), and were thus used to calibrate coarser scale 30-m Landsat imagery. Random Forest, a machine learning method, was applied to obtain sub-pixel estimates of tree mortality. Traditional per-pixel classification techniques can map mortality of whole stands of trees (e.g. fire). However, these methods are often inadequate in detecting subtle changes in land cover, such as those associated with drought-induced tree mortality, which is often a widespread but scattered disturbance. Our method is unique, because it is capable of mapping death of individual canopies within a pixel. These 30-m tree mortality maps were then used to identify ecological systems most impacted by the drought and edaphic factors that control spatial distributions of tree mortality across central Texas. Ground observations coupled with our remote sensing analyses revealed that the majority of the mortality was Juniperus ashei. From a physiological standpoint this is surprising, because J. ashei is a drought-resistant tree. However, over the last century, this species has recently encroached into many areas previously dominated by grassland. Also, J. ashei tends to occupy landscape positions with lower available water storage, which could explain its high mortality rate. Predominantly tree mortality occurred in dry landscape positions (e.g. areas dominated by shallow soils, a low compound topographic index, and a high heat index). As increases in extreme drought events are predicted to occur with climate change, it will become more important to establish methods capable of detecting associated drought-induced tree mortality, to recognize vulnerable ecological systems, and to identify edaphic factors that predispose trees to mortality.

Understanding Patchy Landscape Dynamics: Towards a Landscape Language

PubMed Central

Gaucherel, Cédric; Boudon, Frédéric; Houet, Thomas; Castets, Mathieu; Godin, Christophe

2012-01-01

Patchy landscapes driven by human decisions and/or natural forces are still a challenge to be understood and modelled. No attempt has been made up to now to describe them by a coherent framework and to formalize landscape changing rules. Overcoming this lacuna was our first objective here, and this was largely based on the notion of Rewriting Systems, also called Formal Grammars. We used complicated scenarios of agricultural dynamics to model landscapes and to write their corresponding driving rule equations. Our second objective was to illustrate the relevance of this landscape language concept for landscape modelling through various grassland managements, with the final aim to assess their respective impacts on biological conservation. For this purpose, we made the assumptions that a higher grassland appearance frequency and higher land cover connectivity are favourable to species conservation. Ecological results revealed that dairy and beef livestock production systems are more favourable to wild species than is hog farming, although in different ways. Methodological results allowed us to efficiently model and formalize these landscape dynamics. This study demonstrates the applicability of the Rewriting System framework to the modelling of agricultural landscapes and, hopefully, to other patchy landscapes. The newly defined grammar is able to explain changes that are neither necessarily local nor Markovian, and opens a way to analytical modelling of landscape dynamics. PMID:23049935

Climate and landscape explain richness patterns depending on the type of species' distribution data

NASA Astrophysics Data System (ADS)

Tsianou, Mariana A.; Koutsias, Nikolaos; Mazaris, Antonios D.; Kallimanis, Athanasios S.

2016-07-01

Understanding the patterns of species richness and their environmental drivers, remains a central theme in ecological research and especially in the continental scales where many conservation decisions are made. Here, we analyzed the patterns of species richness from amphibians, reptiles and mammals at the EU level. We used two different data sources for each taxon: expert-drawn species range maps, and presence/absence atlases. As environmental drivers, we considered climate and land cover. Land cover is increasingly the focus of research, but there still is no consensus on how to classify land cover to distinct habitat classes, so we analyzed the CORINE land cover data with three different levels of thematic resolution (resolution of classification scheme ˗ less to more detailed). We found that the two types of species richness data explored in this study yielded different richness maps. Although, we expected expert-drawn range based estimates of species richness to exceed those from atlas data (due to the assumption that species are present in all locations throughout their region), we found that in many cases the opposite is true (the extreme case is the reptiles where more than half of the atlas based estimates were greater than the expert-drawn range based estimates). Also, we detected contrasting information on the richness drivers of biodiversity patterns depending on the dataset used. For atlas based richness estimates, landscape attributes played more important role than climate while for expert-drawn range based richness estimates climatic variables were more important (for the ectothermic amphibians and reptiles). Finally we found that the thematic resolution of the land cover classification scheme, also played a role in quantifying the effect of land cover diversity, with more detailed thematic resolution increasing the relative contribution of landscape attributes in predicting species richness.

Marine habitat mapping of the Milford Haven Waterway, Wales, UK: Comparison of facies mapping and EUNIS classification for monitoring sediment habitats in an industrialized estuary

NASA Astrophysics Data System (ADS)

Carey, Drew A.; Hayn, Melanie; Germano, Joseph D.; Little, David I.; Bullimore, Blaise

2015-06-01

A detailed map and dataset of sedimentary habitats of the Milford Haven Waterway (MHW) was compiled for the Milford Haven Waterway Environmental Surveillance Group (MHWESG) from seafloor images collected in May, 2012 using sediment-profile and plan-view imaging (SPI/PV) survey techniques. This is the most comprehensive synoptic assessment of sediment distribution and benthic habitat composition available for the MHW, with 559 stations covering over 40 km2 of subtidal habitats. In the context of the MHW, an interpretative framework was developed that classified each station within a 'facies' that included information on the location within the waterway and inferred sedimentary and biological processes. The facies approach provides critical information on landscape-scale habitats including relative location and inferred sediment transport processes and can be used to direct future monitoring activities within the MHW and to predict areas of greatest potential risk from contaminant transport. Intertidal sediment 'facies' maps have been compiled in the past for MHW; this approach was expanded to map the subtidal portions of the waterway. Because sediment facies can be projected over larger areas than individual samples (due to assumptions based on physiography, or landforms) they represent an observational model of the distribution of sediments in an estuary. This model can be tested over time and space through comparison with additional past or future sample results. This approach provides a means to evaluate stability or change in the physical and biological conditions of the estuarine system. Initial comparison with past results for intertidal facies mapping and grain size analysis from grab samples showed remarkable stability over time for the MHW. The results of the SPI/PV mapping effort were cross-walked to the European Nature Information System (EUNIS) classification to provide a comparison of locally derived habitat mapping with European-standard habitat mapping. Cross-walk was conducted by assigning each facies (or group of facies) to a EUNIS habitat (Levels 3 or 5) and compiling maps comparing facies distribution with EUNIS habitat distribution. The facies approach provides critical information on landscape-scale habitats including relative location and inferred sediment transport processes. The SPI/PV approach cannot consistently identify key species contained within the EUNIS Level 5 Habitats. For regional planning and monitoring efforts, a combination of EUNIS classification and facies description provides the greatest flexibility for management of dynamic soft-bottom habitats in coastal estuaries. The combined approach can be used to generate and test hypotheses of linkages between biological characteristics (EUNIS) and physical characteristics (facies). This approach is practical if a robust cross-walk methodology is developed to utilize both classification approaches. SPI/PV technology can be an effective rapid ground truth method for refining marine habitat maps based on predictive models.

A proposed new framework for valorization of geoheritage in Norway

NASA Astrophysics Data System (ADS)

Dahl, Rolv; Bergengren, Anna; Heldal, Tom

2015-04-01

The geological history of Norway is a complex one, . The exploitation of geological resources of different kinds has always provided the backbone of the Norwegian community. Nevertheless, the perception of geology and the geological processes that created the landscape is little appreciated, compared to bio-diversity and cultural heritage. Some geological localities play an important role in our perception and scientific understanding of the landscape. Other localities are, or could be, important tourist destinations. Other localities can in turn be important for geoscience education on all levels, whereas other plays a major role in the understanding of geodiversity and geoheritage and should be protected as natural monuments. A database based on old registrations has been compiled and a web mapping server is recently launched based on old and new registrations. However, no systematical classification and identification of important sites has been done for the last thirty years. We are now calling for a crowdsourcing process in the geological community in order to validate and valorize the registrations, as well as defining new points and areas of interest. Furthermore, we are developing a valorization system for these localities. The framework for this system is based on studies from inventories in other countries, as well as suggestions from ProGeo. The aim is to raise awareness of important sites, and how they are treated and utilized for scientific, or educational purposes, as tourist destinations or heritage sites. Our presentation will focus on the development of the framework and its implications.

Using laser altimetry-based segmentation to refine automated tree identification in managed forests of the Black Hills, South Dakota

Treesearch

Eric Rowell; Carl Selelstad; Lee Vierling; Lloyd Queen; Wayne Sheppard

2006-01-01

The success of a local maximum (LM) tree detection algorithm for detecting individual trees from lidar data depends on stand conditions that are often highly variable. A laser height variance and percent canopy cover (PCC) classification is used to segment the landscape by stand condition prior to stem detection. We test the performance of the LM algorithm using canopy...

Detection of land-use and land cover changes in Franklin, Gulf, and Liberty Counties, Florida, with multitemporal landsat thematic mapper images

Treesearch

Shufen Pan; Guiying Li

2007-01-01

Florida Panhandle region has been experiencing rapid land transformation in the recent decades. To quantify land use and land-cover (LULC) changes and other landscape changes in this area, three counties including Franklin, Liberty and Gulf were taken as a case study and an unsupervised classification approach implemented to Landsat TM images acquired from 1985 to 2005...

Placing man in regional landscape classification: Use of Forest Survey data to assess human influences for southern U.S. forest ecosystems

Treesearch

Victor A. Rudis; John B. Tansey

1991-01-01

Information from plots surveyed by U.S.D.A., Forest Service, Forest Inventory and Analysis (FIA) units provides a basis for classifying human-dominated ecosystems at the regional scale of resolution.Attributes include forest stand measures, evidence of human influence, and other disturbances.Data from recent FIA surveys suggest that human influences are common to...

Stratifying FIA Ground Plots Using A 3-Year Old MRLC Forest Cover Map and Current TM Derived Variables Selected By "Decision Tree" Classification

Treesearch

Michael Hoppus; Stan Arner; Andrew Lister

2001-01-01

A reduction in variance for estimates of forest area and volume in the state of Connecticut was accomplished by stratifying FIA ground plots using raw, transformed and classified Landsat Thematic Mapper (TM) imagery. A US Geological Survey (USGS) Multi-Resolution Landscape Characterization (MRLC) vegetation cover map for Connecticut was used to produce a forest/non-...

Landscape assessment of tree communities in the northern karst region of Puerto Rico.

Treesearch

Juliann E. Aukema; Tomas A. Carlo; Jaime A. Collazo

2007-01-01

The northern karst of Puerto Rico is a unique formation that contains one of the island’s largest remaining forested tracts. The region is under ever-increasing human pressure, but large portions of it are being considered for conservation. Forest classification of the region is at a coarse scale, such that it is considered one vegetation type. We asked whether there...

Integrating Flow, Form, and Function for Improved Environmental Water Management

NASA Astrophysics Data System (ADS)

Albin Lane, Belize Arela

Rivers are complex, dynamic natural systems. The performance of river ecosystem functions, such as habitat availability and sediment transport, depends on the interplay of hydrologic dynamics (flow) and geomorphic settings (form). However, most river restoration studies evaluate the role of either flow or form without regard for their dynamic interactions. Despite substantial recent interest in quantifying environmental water requirements to support integrated water management efforts, the absence of quantitative, transferable relationships between river flow, form, and ecosystem functions remains a major limitation. This research proposes a novel, process-driven methodology for evaluating river flow-form-function linkages in support of basin-scale environmental water management. This methodology utilizes publically available geospatial and time-series data and targeted field data collection to improve basic understanding of river systems with limited data and resource requirements. First, a hydrologic classification system is developed to characterize natural hydrologic variability across a highly altered, physio-climatically diverse landscape. Next, a statistical analysis is used to characterize reach-scale geomorphic variability and to investigate the utility of topographic variability attributes (TVAs, subreach-scale undulations in channel width and depth), alongside traditional reach-averaged attributes, for distinguishing dominant geomorphic forms and processes across a hydroscape. Finally, the interacting roles of flow (hydrologic regime, water year type, and hydrologic impairment) and form (channel morphology) are quantitatively evaluated with respect to ecosystem functions related to hydrogeomorphic processes, aquatic habitat, and riparian habitat. Synthetic river corridor generation is used to evaluate and isolate the role of distinct geomorphic attributes without the need for intensive topographic surveying. This three-part methodology was successfully applied in the Sacramento Basin of California, USA, a large, heavily altered Mediterranean-montane basin. A spatially-explicit hydrologic classification of California distinguished eight natural hydrologic regimes representing distinct flow sources, hydrologic characteristics, and rainfall-runoff controls. A hydro-geomorphic sub-classification of the Sacramento Basin based on stratified random field surveys of 161 stream reaches distinguished nine channel types consisting of both previously identified and new channel types. Results indicate that TVAs provide a quantitative basis for interpreting non-uniform as well as uniform geomorphic processes to better distinguish linked channel forms and functions of ecological significance. Finally, evaluation of six ecosystem functions across alternative flow-form scenarios in the Yuba River watershed highlights critical tradeoffs in ecosystem performance and emphasizes the significance of spatiotemporal diversity of flow and form for maintaining ecosystem integrity. The methodology developed in this dissertation is broadly applicable and extensible to other river systems and ecosystem functions, where findings can be used to characterize complex controls on river ecosystems, assess impacts of proposed flow and form alterations, and inform river restoration strategies. Overall, this research improves scientific understanding of the linkages between hydrology, geomorphology, and river ecosystems to more efficiently allocate scare water resources for human and environmental objectives across natural and built landscapes.

Spatiotemporal variation characteristics of green space ecosystem service value at urban fringes: A case study on Ganjingzi District in Dalian, China.

PubMed

Yang, Jun; Guan, Yingying; Xia, Jianhong Cecilia; Jin, Cui; Li, Xueming

2018-10-15

In this study, a green space classification system for urban fringes was established based on multisource land use data from Ganjingzi District, China (2000-2015). The purpose of this study was to explore the spatiotemporal variation of green space landscapes and ecosystem service values (ESV). During 2006-2015, as urbanization advanced rapidly, the green space area decreased significantly (359.57 to 213.46 km 2 ), the ESV decreased from 397.42 to 124.93 million yuan, and the dynamic degrees of ESV variation were always <0. The green space large plaque index and class area both declined and the number of plaques and plaque density increased, indicating green space landscape fragmentation. The dynamic degrees of ESV variation in western and northern regions (with relatively intensive green space distributions) were higher than in the east. The ESV for closed forestland and sparse woodland had the highest functional values of ecological regulation and support, whereas dry land and irrigated cropland provided the highest functional values of production supply. The findings of this study are expected to provide support for better construction practices in Dalian and for the improvement of the ecological environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

[Spatiotemporal dynamics of land cover in northern Tibetan Plateau with responses to climate change].

PubMed

Song, Chun-qiao; You, Song-cai; Ke, Ling-hong; Liu, Gao-huan; Zhong, Xin-ke

2011-08-01

By using the 2001-2008 MOMS land cover products (MCDl2Ql) and based on the modified classification scheme embodied the characteristics of land cover in northern Tibetan Plateau, the annual land cover type maps of the Plateau were drawn, with the dynamic changes of each land cover type analyzed by classification statistics, dynamic transfer matrix, and landscape pattern indices. In 2001-2008, due to the acceleration of global climate warming, the areas of glacier and snow-covered land in the Plateau decreased rapidly, and the melted snow water gathered into low-lying valley or basin, making the lake level raised and the lake area enlarged. Some permanent wetlands were formed because of partially submersed grassland. The vegetation cover did not show any evident meliorated or degraded trend. From 2001 to 2004, as the climate became warmer and wetter, the spatial distribution of desert began to shrink, and the proportions of sparse grassland and grassland increased. From 2006 to 2007, due to the warmer and drier climate, the desert bare land increased, and the sparse grassland decreased. From 2001 to 2008, both the landscape fragmentation degree and the land cover heterogeneity decreased, and the differences in the proportions of all land cover types somewhat enlarged.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Thresholds for soil cover and weathering in mountainous landscapes

NASA Astrophysics Data System (ADS)

Dixon, Jean; Benjaram, Sarah

2017-04-01

The patterns of soil formation, weathering, and erosion shape terrestrial landscapes, forming the foundation on which ecosystems and human civilizations are built. Several fundamental questions remain regarding how soils evolve, especially in mountainous landscapes where tectonics and climate exert complex forcings on erosion and weathering. In these systems, quantifying weathering is made difficult by the fact that soil cover is discontinuous and heterogeneous. Therefore, studies that attempt to measure soil weathering in such systems face a difficult bias in measurements towards more weathered portions of the landscape. Here, we explore current understanding of erosion-weathering feedbacks, and present new data from mountain systems in Western Montana. Using field mapping, analysis of LiDAR and remotely sensed land-cover data, and soil chemical analyses, we measure soil cover and surface weathering intensity across multiple spatial scales, from the individual soil profile to a landscape perspective. Our data suggest that local emergence of bedrock cover at the surface marks a landscape transition from supply to kinetic weathering regimes in these systems, and highlights the importance of characterizing complex critical zone architecture in mountain landscapes. This work provides new insight into how landscape morphology and erosion may drive important thresholds for soil cover and weathering.

Long-term landscape change and bird abundance in Amazonian rainforest fragments.

PubMed

Stouffer, Philip C; Bierregaard, Richard O; Strong, Cheryl; Lovejoy, Thomas E

2006-08-01

The rainforests of the Amazon basin are being cut by humans at a rate >20,000 km2/year leading to smaller and more isolated patches of forest, with remaining fragments often in the range of 1-100 ha. We analyzed samples of understory birds collected over 20 years from a standardized mist-netting program in 1- to 100-ha rainforest fragments in a dynamic Amazonian landscape near Manaus, Brazil. Across bird guilds, the condition of second growth immediately surrounding fragments was often as important as fragment size or local forest cover in explaining variation in abundance. Some fragments surrounded by 100 m of open pasture showed reductions in insectivorous bird abundance of over 95%, even in landscapes dominated by continuous forest and old second growth. These extreme reductions may be typical throughout Amazonia in small (< or =10 ha), isolated fragments of rainforest. Abundance for some guilds returned to preisolation levels in 10- and 100-ha fragments connected to continuous forest by 20-year-old second growth. Our results show that the consequences of Amazonian forest loss cannot be accurately described without explicit consideration of vegetation dynamics in matrix habitat. Any dichotomous classification of the landscape into 'forest" and "nonforest" misses essential information about the matrix.

Utility of Mobile phones to support In-situ data collection for Land Cover Mapping

NASA Astrophysics Data System (ADS)

Oduor, P.; Omondi, S.; Wahome, A.; Mugo, R. M.; Flores, A.

2017-12-01

With the compelling need to create better monitoring tools for our landscapes to enhance better decision making processes, it becomes imperative to do so in much more sophisticated yet simple ways. Making it possible to leverage untapped potential of our "lay men" at the same time enabling us to respond to the complexity of the information we have to get out. SERVIR Eastern and Southern Africa has developed a mobile app that can be utilized with very little prior knowledge or no knowledge at all to collect spatial information on land cover. This set of in-situ data can be collected by masses because the tools is very simple to use, and have this information fed in classification algorithms than can then be used to map out our ever changing landscape. The LULC Mapper is a subset of JiMap system and is able to pull the google earth imagery and open street maps to enable user familiarize with their location. It uses phone GPS, phone network information to map location coordinates and at the same time gives the user sample picture of what to categorize their landscape. The system is able to work offline and when user gets access to internet they can push the information into an amazon database as bulk data. The location details including geotagged photos allows the data to be used in development of a lot of spatial information including land cover data. The app is currently available in Google Play Store and will soon be uploaded on Appstore for utilization by a wider community. We foresee a lot of potential in this tool in terms of making data collection cheaper and affordable. Taking advantage of the advances made in phone technology. We envisage to do a data collection campaign where we can have the tool used for crowdsourcing.

Classification of crops across heterogeneous agricultural landscape in Kenya using AisaEAGLE imaging spectroscopy data

NASA Astrophysics Data System (ADS)

Piiroinen, Rami; Heiskanen, Janne; Mõttus, Matti; Pellikka, Petri

2015-07-01

Land use practices are changing at a fast pace in the tropics. In sub-Saharan Africa forests, woodlands and bushlands are being transformed for agricultural use to produce food for the rapidly growing population. The objective of this study was to assess the prospects of mapping the common agricultural crops in highly heterogeneous study area in south-eastern Kenya using high spatial and spectral resolution AisaEAGLE imaging spectroscopy data. Minimum noise fraction transformation was used to pack the coherent information in smaller set of bands and the data was classified with support vector machine (SVM) algorithm. A total of 35 plant species were mapped in the field and seven most dominant ones were used as classification targets. Five of the targets were agricultural crops. The overall accuracy (OA) for the classification was 90.8%. To assess the possibility of excluding the remaining 28 plant species from the classification results, 10 different probability thresholds (PT) were tried with SVM. The impact of PT was assessed with validation polygons of all 35 mapped plant species. The results showed that while PT was increased more pixels were excluded from non-target polygons than from the polygons of the seven classification targets. This increased the OA and reduced salt-and-pepper effects in the classification results. Very high spatial resolution imagery and pixel-based classification approach worked well with small targets such as maize while there was mixing of classes on the sides of the tree crowns.

"In my opinion, work would be in first place and family in second": young women's imagined gender-work relations in post-Soviet Lithuania.

PubMed

Reiter, Herwig

2010-01-01

This article explores young women's orientation to work and motherhood in the post-communist context of radical socio-economic transformation in Europe. Based on a qualitative-explorative study into meanings of work and unemployment among young people in post-Soviet Lithuania, the paper introduces an empirically grounded classification of imagined gender-work arrangements. The single patterns of the classification are based on the three configurations of work and motherhood, work and partnership, and work and provision. The findings inform the reconstruction of the 'landscape' of imagined gendered adulthoods in Europe as well as the analysis of emerging gender relations under conditions of rapid social change.

Assessment of Classification Accuracies of SENTINEL-2 and LANDSAT-8 Data for Land Cover / Use Mapping

NASA Astrophysics Data System (ADS)

Hale Topaloğlu, Raziye; Sertel, Elif; Musaoğlu, Nebiye

2016-06-01

This study aims to compare classification accuracies of land cover/use maps created from Sentinel-2 and Landsat-8 data. Istanbul metropolitan city of Turkey, with a population of around 14 million, having different landscape characteristics was selected as study area. Water, forest, agricultural areas, grasslands, transport network, urban, airport- industrial units and barren land- mine land cover/use classes adapted from CORINE nomenclature were used as main land cover/use classes to identify. To fulfil the aims of this research, recently acquired dated 08/02/2016 Sentinel-2 and dated 22/02/2016 Landsat-8 images of Istanbul were obtained and image pre-processing steps like atmospheric and geometric correction were employed. Both Sentinel-2 and Landsat-8 images were resampled to 30m pixel size after geometric correction and similar spectral bands for both satellites were selected to create a similar base for these multi-sensor data. Maximum Likelihood (MLC) and Support Vector Machine (SVM) supervised classification methods were applied to both data sets to accurately identify eight different land cover/ use classes. Error matrix was created using same reference points for Sentinel-2 and Landsat-8 classifications. After the classification accuracy, results were compared to find out the best approach to create current land cover/use map of the region. The results of MLC and SVM classification methods were compared for both images.

Combining aesthetic with ecological values for landscape sustainability.

PubMed

Yang, Dewei; Luo, Tao; Lin, Tao; Qiu, Quanyi; Luo, Yunjian

2014-01-01

Humans receive multiple benefits from various landscapes that foster ecological services and aesthetic attractiveness. In this study, a hybrid framework was proposed to evaluate ecological and aesthetic values of five landscape types in Houguanhu Region of central China. Data from the public aesthetic survey and professional ecological assessment were converted into a two-dimensional coordinate system and distribution maps of landscape values. Results showed that natural landscapes (i.e. water body and forest) contributed positively more to both aesthetic and ecological values than semi-natural and human-dominated landscapes (i.e. farmland and non-ecological land). The distribution maps of landscape values indicated that the aesthetic, ecological and integrated landscape values were significantly associated with landscape attributes and human activity intensity. To combine aesthetic preferences with ecological services, the methods (i.e. field survey, landscape value coefficients, normalized method, a two-dimensional coordinate system, and landscape value distribution maps) were employed in landscape assessment. Our results could facilitate to identify the underlying structure-function-value chain, and also improve the understanding of multiple functions in landscape planning. The situation context could also be emphasized to bring ecological and aesthetic goals into better alignment.

Combining Aesthetic with Ecological Values for Landscape Sustainability

PubMed Central

Yang, Dewei; Luo, Tao; Lin, Tao; Qiu, Quanyi; Luo, Yunjian

2014-01-01

Humans receive multiple benefits from various landscapes that foster ecological services and aesthetic attractiveness. In this study, a hybrid framework was proposed to evaluate ecological and aesthetic values of five landscape types in Houguanhu Region of central China. Data from the public aesthetic survey and professional ecological assessment were converted into a two-dimensional coordinate system and distribution maps of landscape values. Results showed that natural landscapes (i.e. water body and forest) contributed positively more to both aesthetic and ecological values than semi-natural and human-dominated landscapes (i.e. farmland and non-ecological land). The distribution maps of landscape values indicated that the aesthetic, ecological and integrated landscape values were significantly associated with landscape attributes and human activity intensity. To combine aesthetic preferences with ecological services, the methods (i.e. field survey, landscape value coefficients, normalized method, a two-dimensional coordinate system, and landscape value distribution maps) were employed in landscape assessment. Our results could facilitate to identify the underlying structure-function-value chain, and also improve the understanding of multiple functions in landscape planning. The situation context could also be emphasized to bring ecological and aesthetic goals into better alignment. PMID:25050886

Recognition and characterization of networks of water bodies in the Arctic ice-wedge polygonal tundra using high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Skurikhin, A. N.; Gangodagamage, C.; Rowland, J. C.; Wilson, C. J.

2013-12-01

Arctic lowland landscapes underlain by permafrost are often characterized by polygon-like patterns such as ice-wedge polygons outlined by networks of ice wedges and complemented with polygon rims, troughs, shallow ponds and thermokarst lakes. Polygonal patterns and corresponding features are relatively easy to recognize in high spatial resolution satellite imagery by a human, but their automated recognition is challenging due to the variability in their spectral appearance, the irregularity of individual trough spacing and orientation within the patterns, and a lack of unique spectral response attributable to troughs with widths commonly between 1 m and 2 m. Accurate identification of fine scale elements of ice-wedge polygonal tundra is important as their imprecise recognition may bias estimates of water, heat and carbon fluxes in large-scale climate models. Our focus is on the problem of identification of Arctic polygonal tundra fine-scale landscape elements (as small as 1 m - 2 m width). The challenge of the considered problem is that while large water bodies (e.g. lakes and rivers) can be recognized based on spectral response, reliable recognition of troughs is more difficult. Troughs do not have unique spectral signature, their appearance is noisy (edges are not strong), their width is small, and they often form connected networks with ponds and lakes, and thus they have overlapping spectral response with other water bodies and surrounding non-water bodies. We present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components across the range of spatial scales, such as troughs, ponds, river- and lake-like objects, using high spatial resolution satellite imagery. The novelty of the approach lies in: (1) the combined use of segmentation and shape-based classification to identify a broad range of water bodies, including troughs, and (2) the use of high-resolution WorldView-2 satellite imagery (with resolution of 0.6 m) for this identification. The approach starts by segmenting water bodies from an image, which are then categorized using shape-based classification. Segmentation uses combination of pan sharpened multispectral bands and is based on the active contours without edges technique. The segmentation is robust to noise and can detect objects with weak boundaries that is important for extraction of troughs. We then categorize the segmented regions via shape based classification. Because segmentation accuracy is the main factor impacting the quality of the shape-based classification, for segmentation accuracy assessment we created reference image using WorldView-2 satellite image of ice-wedge polygonal tundra. Reference image contained manually labelled image regions which cover components of drainage networks, such as troughs, ponds, rivers and lakes. The evaluation has shown that the approach provides a good accuracy of segmentation and reasonable classification results. The overall accuracy of the segmentation is approximately 95%, the segmentation user's and producer's accuracies are approximately 92% and 97% respectively.

Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China.

PubMed

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2015-11-09

Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems.

The concept of hydrologic landscapes

USGS Publications Warehouse

Winter, T.C.

2001-01-01

Hydrologic landscapes are multiples or variations of fundamental hydrologic landscape units. A fundamental hydrologic landscape unit is defined on the basis of land-surface form, geology, and climate. The basic land-surface form of a fundamental hydrologic landscape unit is an upland separated from a lowland by an intervening steeper slope. Fundamental hydrologic landscape units have a complete hydrologic system consisting of surface runoff, ground-water flow, and interaction with atmospheric water. By describing actual landscapes in terms of land-surface slope, hydraulic properties of soils and geologic framework, and the difference between precipitation and evapotranspiration, the hydrologic system of actual landscapes can be conceptualized in a uniform way. This conceptual framework can then be the foundation for design of studies and data networks, syntheses of information on local to national scales, and comparison of process research across small study units in a variety of settings. The Crow Wing River watershed in central Minnesota is used as an example of evaluating stream discharge in the context of hydrologic landscapes. Lake-research watersheds in Wisconsin, Minnesota, North Dakota, and Nebraska are used as an example of using the hydrologic-landscapes concept to evaluate the effect of ground water on the degree of mineralization and major-ion chemistry of lakes that lie within ground-water flow systems.

Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China

PubMed Central

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2015-01-01

Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution—severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems. PMID:26569270

Kernel Method Based Human Model for Enhancing Interactive Evolutionary Optimization

PubMed Central

Zhao, Qiangfu; Liu, Yong

2015-01-01

A fitness landscape presents the relationship between individual and its reproductive success in evolutionary computation (EC). However, discrete and approximate landscape in an original search space may not support enough and accurate information for EC search, especially in interactive EC (IEC). The fitness landscape of human subjective evaluation in IEC is very difficult and impossible to model, even with a hypothesis of what its definition might be. In this paper, we propose a method to establish a human model in projected high dimensional search space by kernel classification for enhancing IEC search. Because bivalent logic is a simplest perceptual paradigm, the human model is established by considering this paradigm principle. In feature space, we design a linear classifier as a human model to obtain user preference knowledge, which cannot be supported linearly in original discrete search space. The human model is established by this method for predicting potential perceptual knowledge of human. With the human model, we design an evolution control method to enhance IEC search. From experimental evaluation results with a pseudo-IEC user, our proposed model and method can enhance IEC search significantly. PMID:25879050

The Role of Landscape in the Distribution of Deer-Vehicle Collisions in South Mississippi

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

McKee, Jacob J; Cochran, David

2012-01-01

Deer-vehicle collisions (DVCs) have a negative impact on the economy, traffic safety, and the general well-being of otherwise healthy deer. To mitigate DVCs, it is imperative to gain a better understanding of factors that play a role in their spatial distribution. Much of the existing research on DVCs in the United States has been inconclusive, pointing to a variety of causal factors that seem more specific to study site and region than indicative of broad patterns. Little DVC research has been conducted in the southern United States, making the region particularly important with regard to this issue. In this study,more » we evaluate landscape factors that contributed to the distribution of 347 DVCs that occurred in Forrest and Lamar Counties of south Mississippi, from 2006 to 2009. Using nearest-neighbor and discriminant analysis, we demonstrate that DVCs in south Mississippi are not random spatial phenomena. We also develop a classification model that identified seven landscape metrics, explained 100% of the variance, and could distinguish DVCs from control sites with an accuracy of 81.3 percent.« less

Feedbacks in human-landscape systems

NASA Astrophysics Data System (ADS)

Chin, Anne

2015-04-01

As human interactions with Earth systems intensify in the "Anthropocene", understanding the complex relationships among human activity, landscape change, and societal responses to those changes is increasingly important. Interdisciplinary research centered on the theme of "feedbacks" in human-landscape systems serves as a promising focus for unraveling these interactions. Deciphering interacting human-landscape feedbacks extends our traditional approach of considering humans as unidirectional drivers of change. Enormous challenges exist, however, in quantifying impact-feedback loops in landscapes with significant human alterations. This paper illustrates an example of human-landscape interactions following a wildfire in Colorado (USA) that elicited feedback responses. After the 2012 Waldo Canyon Fire, concerns for heightened flood potential and debris flows associated with post-fire hydrologic changes prompted local landowners to construct tall fences at the base of a burned watershed. These actions changed the sediment transport regime and promoted further landscape change and human responses in a positive feedback cycle. The interactions ultimately increase flood and sediment hazards, rather than dampening the effects of fire. A simple agent-based model, capable of integrating social and hydro-geomorphological data, demonstrates how such interacting impacts and feedbacks could be simulated. Challenges for fully capturing human-landscape feedback interactions include the identification of diffuse and subtle feedbacks at a range of scales, the availability of data linking impact with response, the identification of multiple thresholds that trigger feedback mechanisms, and the varied metrics and data needed to represent both the physical and human systems. By collaborating with social scientists with expertise in the human causes of landscape change, as well as the human responses to those changes, geoscientists could more fully recognize and anticipate the coupled human-landscape interactions that will drive the evolution of Earth systems into the future.

Mapping Post-Fire Vegetation Recovery at Different Lithologies of Taygetos mt (greece) with Multi-Temporal Remote Sensing Data

NASA Astrophysics Data System (ADS)

Vassilakis, Emmanuel; Mallinis, George; Christopoulou, Anastasia; Farangitakis, Georgios-Pavlos; Papanikolaou, Ioannis; Arianoutsou, Margarita

2017-04-01

Mt Taygetos (2407m), located at southern Peloponnese (Greece) suffered a large fire during the summer of 2007. The fire burned approximately 45% of the area covered by the endemic Greek fir (Abies cephalonica) and Black Pine (Pinus nigra) forest ecosystems. The aim of the current study is to examine the potential differences on post-fire vegetation recovery imposed by the lithology as well as the geomorphology of the given area over sites of the same climatic and landscape conditions (elevation, aspect, slope etc.). The main lithologies consist of carbonate, permeable, not easily erodible formations (limestones and marbles) and clastic, impermeable (schists, slate and flysch) erodible ones. A time-series of high spatial resolution satellite images were interpreted, analyzed and compared in order to detect changes in vegetation coverage which could prioritize areas of interest for fieldwork campaigns. The remote sensing datasets were acquired before (Ikonos-2), a few months after (Quickbird-2) and some years after (Worldview-3) the 2007 fire. High resolution Digital Elevation Model was used for the ortho-rectification and co-registration of the remote sensing data, but also for the extraction of the mountainous landscape characteristics. The multi-temporal image dataset was analyzed through GEographic-Object Based Image Analysis (GEOBIA). Objects corresponding to different vegetation types through time were identified through spectral and textural features. The classification results were combined with basic layers such as lithological outcrops, pre-fire vegetation, landscape morphology etc., supplementing a spatial geodatabase used for classifying burnt areas with varying post-fire plant community recovery. We validated the results of the classification during fieldwork and found that at a local scale, where the landscape features are quite similar, the bedrock type proves to be an important factor for vegetation recovery, as it clearly defines the soil generation along with its properties. Plant species recovery seems to be controlled by the local lithology as it was found weaker in plots overlying limestones and marbles, comparing to that observed over schists, even for the same species. In conclusion, post-fire vegetation recovery seems to be a complex process controlled not only from species biology, but also from the geological features.

Impact of the Spatial Arrangement of Agricultural Land Use on Ecosystems Services and Peri-Urban Livelihoods at the Landscape Scale.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Fürst, C.

2014-12-01

The relationship between agricultural land uses (ALU) and their impact on ecosystems services (ES) including biodiversity conservation is complex. This complexity has been augmented by isolated research on the impact of ALU on the landscape's capacity to provide ES in most climatically vulnerable areas of Sub-Saharan Africa. Though a considerable number of studies emphasise the nexus between specific land use types and their impact on ES, a sufficient modelling basis for an empirical consideration of spatial interactions between different agricultural land uses at the landscape scale within peri-urban areas in Sub-Saharan Africa is consistently missing. The need to assess and address significant issues regarding size, shape, spatial location, and interactivity of different land use patches in assessing land use interactions and their impact on ecosystem service provision necessitated this investigation. To formulate a methodology to correspond to this complexity, ES obtained from a characteristically agricultural and urbanizing landscapes were mapped using analytical hierarchical processes and management expert approaches. Further, landscape metrics and mean enrichment factor approaches are explored as neighbourhood assessment tools aimed at assessing the mutual impact gradient of agricultural and adjacent urban land uses on ES provision. Implementation is undertaken in GISCAME using a 2012 rapideye image classification and primary data collected on selected ES from local farmers within the VEA catchment of Upper East, Ghana. The outcome aims to provide the understanding of expected trade-offs and synergies varying ALU could pose to current and potential ES provision within urbanizing landscapes. Policy implications for observed trade-offs and synergies of ALU interaction on ES, rural livelihoods, and food security are communicated to farmers and decision makers. Keywords: Agricultural land use, neighbourhood interaction, ecosystems services, livelihoods, GISCAME.

Integrating ecosystem sampling, gradient modeling, remote sensing, and ecosystem simulation to create spatially explicit landscape inventories

Treesearch

Robert E. Keane; Matthew G. Rollins; Cecilia H. McNicoll; Russell A. Parsons

2002-01-01

Presented is a prototype of the Landscape Ecosystem Inventory System (LEIS), a system for creating maps of important landscape characteristics for natural resource planning. This system uses gradient-based field inventories coupled with gradient modeling remote sensing, ecosystem simulation, and statistical analyses to derive spatial data layers required for ecosystem...

Enhancing the performance of regional land cover mapping

NASA Astrophysics Data System (ADS)

Wu, Weicheng; Zucca, Claudio; Karam, Fadi; Liu, Guangping

2016-10-01

Different pixel-based, object-based and subpixel-based methods such as time-series analysis, decision-tree, and different supervised approaches have been proposed to conduct land use/cover classification. However, despite their proven advantages in small dataset tests, their performance is variable and less satisfactory while dealing with large datasets, particularly, for regional-scale mapping with high resolution data due to the complexity and diversity in landscapes and land cover patterns, and the unacceptably long processing time. The objective of this paper is to demonstrate the comparatively highest performance of an operational approach based on integration of multisource information ensuring high mapping accuracy in large areas with acceptable processing time. The information used includes phenologically contrasted multiseasonal and multispectral bands, vegetation index, land surface temperature, and topographic features. The performance of different conventional and machine learning classifiers namely Malahanobis Distance (MD), Maximum Likelihood (ML), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs) and Random Forests (RFs) was compared using the same datasets in the same IDL (Interactive Data Language) environment. An Eastern Mediterranean area with complex landscape and steep climate gradients was selected to test and develop the operational approach. The results showed that SVMs and RFs classifiers produced most accurate mapping at local-scale (up to 96.85% in Overall Accuracy), but were very time-consuming in whole-scene classification (more than five days per scene) whereas ML fulfilled the task rapidly (about 10 min per scene) with satisfying accuracy (94.2-96.4%). Thus, the approach composed of integration of seasonally contrasted multisource data and sampling at subclass level followed by a ML classification is a suitable candidate to become an operational and effective regional land cover mapping method.

Scientometric and patentometric analyses to determine the knowledge landscape in innovative technologies: The case of 3D bioprinting

PubMed Central

2017-01-01

This research proposes an innovative data model to determine the landscape of emerging technologies. It is based on a competitive technology intelligence methodology that incorporates the assessment of scientific publications and patent analysis production, and is further supported by experts’ feedback. It enables the definition of the growth rate of scientific and technological output in terms of the top countries, institutions and journals producing knowledge within the field as well as the identification of main areas of research and development by analyzing the International Patent Classification codes including keyword clusterization and co-occurrence of patent assignees and patent codes. This model was applied to the evolving domain of 3D bioprinting. Scientific documents from the Scopus and Web of Science databases, along with patents from 27 authorities and 140 countries, were retrieved. In total, 4782 scientific publications and 706 patents were identified from 2000 to mid-2016. The number of scientific documents published and patents in the last five years showed an annual average growth of 20% and 40%, respectively. Results indicate that the most prolific nations and institutions publishing on 3D bioprinting are the USA and China, including the Massachusetts Institute of Technology (USA), Nanyang Technological University (Singapore) and Tsinghua University (China), respectively. Biomaterials and Biofabrication are the predominant journals. The most prolific patenting countries are China and the USA; while Organovo Holdings Inc. (USA) and Tsinghua University (China) are the institutions leading. International Patent Classification codes reveal that most 3D bioprinting inventions intended for medical purposes apply porous or cellular materials or biologically active materials. Knowledge clusters and expert drivers indicate that there is a research focus on tissue engineering including the fabrication of organs, bioinks and new 3D bioprinting systems. Our model offers a guide to researchers to understand the knowledge production of pioneering technologies, in this case 3D bioprinting. PMID:28662187

Scientometric and patentometric analyses to determine the knowledge landscape in innovative technologies: The case of 3D bioprinting.

PubMed

Rodríguez-Salvador, Marisela; Rio-Belver, Rosa María; Garechana-Anacabe, Gaizka

2017-01-01

This research proposes an innovative data model to determine the landscape of emerging technologies. It is based on a competitive technology intelligence methodology that incorporates the assessment of scientific publications and patent analysis production, and is further supported by experts' feedback. It enables the definition of the growth rate of scientific and technological output in terms of the top countries, institutions and journals producing knowledge within the field as well as the identification of main areas of research and development by analyzing the International Patent Classification codes including keyword clusterization and co-occurrence of patent assignees and patent codes. This model was applied to the evolving domain of 3D bioprinting. Scientific documents from the Scopus and Web of Science databases, along with patents from 27 authorities and 140 countries, were retrieved. In total, 4782 scientific publications and 706 patents were identified from 2000 to mid-2016. The number of scientific documents published and patents in the last five years showed an annual average growth of 20% and 40%, respectively. Results indicate that the most prolific nations and institutions publishing on 3D bioprinting are the USA and China, including the Massachusetts Institute of Technology (USA), Nanyang Technological University (Singapore) and Tsinghua University (China), respectively. Biomaterials and Biofabrication are the predominant journals. The most prolific patenting countries are China and the USA; while Organovo Holdings Inc. (USA) and Tsinghua University (China) are the institutions leading. International Patent Classification codes reveal that most 3D bioprinting inventions intended for medical purposes apply porous or cellular materials or biologically active materials. Knowledge clusters and expert drivers indicate that there is a research focus on tissue engineering including the fabrication of organs, bioinks and new 3D bioprinting systems. Our model offers a guide to researchers to understand the knowledge production of pioneering technologies, in this case 3D bioprinting.

Composition-based classification of short metagenomic sequences elucidates the landscapes of taxonomic and functional enrichment of microorganisms

PubMed Central

Liu, Jiemeng; Wang, Haifeng; Yang, Hongxing; Zhang, Yizhe; Wang, Jinfeng; Zhao, Fangqing; Qi, Ji

2013-01-01

Compared with traditional algorithms for long metagenomic sequence classification, characterizing microorganisms’ taxonomic and functional abundance based on tens of millions of very short reads are much more challenging. We describe an efficient composition and phylogeny-based algorithm [Metagenome Composition Vector (MetaCV)] to classify very short metagenomic reads (75–100 bp) into specific taxonomic and functional groups. We applied MetaCV to the Meta-HIT data (371-Gb 75-bp reads of 109 human gut metagenomes), and this single-read-based, instead of assembly-based, classification has a high resolution to characterize the composition and structure of human gut microbiota, especially for low abundance species. Most strikingly, it only took MetaCV 10 days to do all the computation work on a server with five 24-core nodes. To our knowledge, MetaCV, benefited from the strategy of composition comparison, is the first algorithm that can classify millions of very short reads within affordable time. PMID:22941634

Spatial organization of agricultural landscape, farming activities and hydrological risk assessment

NASA Astrophysics Data System (ADS)

Viaud, V.; Merot, P.

2003-04-01

Agriculture intensification is considered as a major cause of water pollution since it has gone both with an increasing use of fertilisers and significant changes in land-use patterns. Among the prescriptions for pollution control, the management of buffer zones at the landscape scale is supported by the environmental policies, but often without consideration of the systems of human activities they are aimed at. Agricultural landscapes, with fields potentially source of pollution and buffer zones, are spatially organized and managed by farming activities. In a perspective of sustainable management, an integrating approach of environmental issues and farming activities is thus required. This approach was applied to bocage landscapes (landscapes with cultivated fields surrounded by hedgerow systems) in Brittany (Western France). Bocage landscapes are frequently encountered, especially in Europe, and many studies put forward their hydrological and hydrochemical buffer functions. Those results provide informations on the link between spatial organization of hedgerow systems and their environmental effectiveness. They enable to design models of functional bocage landscapes. The objective of this work was to pick out, among those theoretical models, the models compatible with the farming activities. The results will be presented and the additional constraints for the farming systems created by a functional landscape, from a hydrological and hydrochemical perspective, will be discussed.

Research Summary: Projecting Vegetation and Wildfire Response to Changing Climate and Fire Management in Interior Alaska

DTIC Science & Technology

2016-08-21

USER GUIDE Research Summary: Projecting Vegetation and Wildfire Response to Changing Climate and Fire Management in Interior Alaska SERDP Project...Summary: Projecting Vegetation and Wildfire Response to Changing Climate and Fire Management in Interior Alaska 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...forecast landscape change in response to projected changes in climate , fire regime, and fire management. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF

Advancing Our Understanding of the Etiologies and Mutational Landscapes of Basal-Like, Luminal A, and Luminal B Breast Cancers

DTIC Science & Technology

2017-10-01

study to identify how various breast cancer risk factors differ in their relationships to different molecular subtypes of breast cancer and to further...characterize molecular differences between these subtypes. To address the existing research gaps regarding the etiologies of different molecular ... molecular subtypes of breast cancer, basal-like, luminal A, and luminal B tumors, breast cancer risk factors 16. SECURITY CLASSIFICATION OF: 17

Advancing Our Understanding of the Etiologies and Mutational Landscapes of Basal-Like, Luminal A, and Luminal B Breast Cancers

DTIC Science & Technology

2017-10-01

various breast cancer risk factors differ in their relationships to different molecular subtypes of breast cancer and to further characterize... molecular differences between these subtypes. To address the existing research gaps regarding the etiologies of different molecular subtypes of breast... molecular subtypes of breast cancer, basal-like, luminal A, and luminal B tumors, breast cancer risk factors 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

Globalization and WMD Proliferation Networks: The Policy Landscape

DTIC Science & Technology

2006-07-01

scientific advances, it moved to shut down this network by classifying all information relating to the Manhattan Project . This security action had only...As with the U.S. efforts during World War II to deny access to Manhattan Project Report Documentation Page Form ApprovedOMB No. 0704-0188 Public...the scientific discoveries paving the way for the atomic bomb, as well as of the U.S. government’s subsequent classification of Manhattan Project information

Transboundary conservation: An ecoregional approach to protect neotropical migratory birds in South America

NASA Astrophysics Data System (ADS)

Roca, Roberto; Adkins, Leslie; Wurschy, Maria Christina; Skerl, Kevin

1996-11-01

Future conservation efforts will need to transcend geopolitical boundaries in efforts to protect entire landscapes and ecosystems. Neotropical migratory birds are as a group a useful conservation tool for linking diverse landscapes and people due to their dependence on multiple habitats, sensitivity to habitat changes, and universal public appeal. The conservation of neotropical migrants can therefore function as a powerful hemispheric umbrella for ecosystem protection. Efforts to protect neotropical migratory birds on their nonbreeding grounds have traditionally been focused on Mexico, Central America, and the Caribbean. To assess the importance of South America to neotropical migrants, an ecoregional classification system was used to determine species distributions in the Andean/Southern Cone Region (Bolivia, Colombia, Ecuador, Paraguay, Peru, and Venezuela). The occurrence of migrants in protected areas that are part of The Nature Conservancy's Parks in Peril program was also assessed. Of the 406 neotropical migrant species, nearly one third (132) occur as regular nonbreeding residents in the region and for almost half of these species (53), South America is their main nonbreeding ground. All Parks in Peril sites were found to harbor neotropical migrants. Forty-eight species (36%) have declining longterm North American Breeding Bird Survey population trends and/or high Partners in Flight concern scores and thus are of significant conservation concern. Most importantly, 29 species (22%) of conservation concern use South America as their primary nonbreeding ground, indicating a need for focused conservation action. The nature of the ecoregional approach used in this endeavor makes future prioritization of ecoregions and conservation strategies for neotropical migrants across national boundaries possible. The ability to link diverse landscapes using a common element such as migratory birds allows for unique transboundary partnerships and opportunities for habitat conservation, which support the goal of the Conservancy's new Migratory Bird Initiative.

Mapping Cultural Ecosystem Services in Vilnius using Hot-Spot Analysis.

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Depellegrin, Daniel; Egarter-Vigl, Lukas; Oliva, Marc; Misiune, Ieva; Keesstra, Saskia; Estebaranz, Ferran; Cerda, Artemi

2017-04-01

Cultural services in urban areas are very important to promote tourism activities and develop the economy. These activities are fundamental for the sustainability of the urban areas since can represent an important monetary source. However, one of the major threats to the sustainability of cultural services is the high amount of visitants that can lead to a degradation of the services provided (Depellegrin et al., 2016). Mapping the potential of cultural ecosystems services is fundamental to assess the capacity that the territory have to provide it. Previous works used land use classification to identify the ecosystem services potential, and revealed to be a good methodology to attribute to each type of land use a specific capacity (Burkhard et al., 2008). The objective of this work is to map the cultural services in Vilnius area using a hot-spot analysis. Ecosystem services potential was assessed using the matrix developed by Burkhard et al. (2009), which ranks ES capacity from 0= no capacity to 5=very high relevant capacity to a different land use type. The results showed that with the exception of Cultural Heritage ecosystem services that had a random pattern (Z-score=0.62, p<0.530), all the others had clustered pattern: Recreation and Tourism (Z-score=4.02, p<0.001), Landscape Aesthetics (Z-score=4.44, p<0.001), Knowledge Systems (Z-score=4.15, p<0.001), Religious and Spiritual (Z-score=3.80, p<0.001) and Natural Heritage (Z-score=5.64, p<0.001). The incremental Moran's I result showed that Recreation and Tourism ecosystem services had the maximum spatial correlation at the distance of 5125.12 m, Landscape Aesthetics at 3495.70 m, Knowledge Systems at 5218.66 m, Religious and Spiritual at 3495.70 m, Cultural Heritage at 6746.17 m and Natural Heritage at 6205.82 m. This showed that the cultural services studied have a different spatial correlation. References Burkhard B, Kroll F, Müller F, Windhorst W. 2009. Landscapes' capacities to provide ecosystem services- a concept for land-cover based assessments. Landscape Online. 15, 1-22. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. Mapping Ecosystem Services potential in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

USGS Publications Warehouse

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a Bayesian hierarchical discrete-choice model for resource selection can provide managers with 2 components of population-level inference: average population selection and variability of selection. Both components are necessary to make sound management decisions based on animal selection.

Enhanced systems for measuring and monitoring REDD+: Opportunities to improve the accuracy of emission factor and activity data in Indonesia

NASA Astrophysics Data System (ADS)

Solichin

The importance of accurate measurement of forest biomass in Indonesia has been growing ever since climate change mitigation schemes, particularly the reduction of emissions from deforestation and forest degradation scheme (known as REDD+), were constitutionally accepted by the government of Indonesia. The need for an accurate system of historical and actual forest monitoring has also become more pronounced, as such a system would afford a better understanding of the role of forests in climate change and allow for the quantification of the impact of activities implemented to reduce greenhouse gas emissions. The aim of this study was to enhance the accuracy of estimations of carbon stocks and to monitor emissions in tropical forests. The research encompassed various scales (from trees and stands to landscape-sized scales) and a wide range of aspects, from evaluation and development of allometric equations to exploration of the potential of existing forest inventory databases and evaluation of cutting-edge technology for non-destructive sampling and accurate forest biomass mapping over large areas. In this study, I explored whether accuracy--especially regarding the identification and reduction of bias--of forest aboveground biomass (AGB) estimates in Indonesia could be improved through (1) development and refinement of allometric equations for major forest types, (2) integration of existing large forest inventory datasets, (3) assessing nondestructive sampling techniques for tree AGB measurement, and (4) landscape-scale mapping of AGB and forest cover using lidar. This thesis provides essential foundations to improve the estimation of forest AGB at tree scale through development of new AGB equations for several major forest types in Indonesia. I successfully developed new allometric equations using large datasets from various forest types that enable us to estimate tree aboveground biomass for both forest type specific and generic equations. My models outperformed the existing local equations, with lower bias and higher precision of the AGB estimates. This study also highlights the potential advantages and challenges of using terrestrial lidar and the acoustic velocity tool for non-destructive sampling of tree biomass to enable more sample collection without the felling of trees. Further, I explored whether existing forest inventories and permanent sample plot datasets can be integrated into Indonesia's existing carbon accounting system. My investigation of these existing datasets found that through quality assurance tests these datasets are essential to be integrated into national and provincial forest monitoring and carbon accounting systems. Integration of this information would eventually improve the accuracy of the estimates of forest carbon stocks, biomass growth, mortality and emission factors from deforestation and forest degradation. At landscape scale, this study demonstrates the capability of airborne lidar for forest monitoring and forest cover classification in tropical peat swamp ecosystems. The mapping application using airborne lidar showed a more accurate and precise classification of land and forest cover when compared with mapping using optical and active sensors. To reduce the cost of lidar acquisition, this study assessed the optimum lidar return density for forest monitoring. I found that the density of lidar return could be reduced to at least 1 return per 4 m2. Overall, this study provides essential scientific background to improve the accuracy of forest AGB estimates. Therefore, the described results and techniques should be integrated into the existing monitoring systems to assess emission reduction targets and the impact of REDD+ implementation.

Sampling the energy landscape of Pt13 with metadynamics

NASA Astrophysics Data System (ADS)

Pavan, Luca; Di Paola, Cono; Baletto, Francesca

2013-02-01

The potential energy surface of a metallic nanoparticle formed by 13 atoms of platinum is efficiently explored using metadynamics in combination with empirical potential molecular dynamics. The scenario obtained is wider and more complex of what was previously reported: more than thirty independent energy basins are found, corresponding to different local minima of Pt. It is demonstrated that in almost all the cases these motifs are local minima even at ab-initio level, hence proving the effectiveness of the method to sample the energy landscape. A classification of the minima in structural families is proposed, and a discussion regarding the shape and the connections between energy basins is reported. ISSPIC 16 - 16th International Symposium on Small Particles and Inorganic Clusters, edited by Kristiaan Temst, Margriet J. Van Bael, Ewald Janssens, H.-G. Boyen and Françoise Remacle.

Creating a three level building classification using topographic and address-based data for Manchester

NASA Astrophysics Data System (ADS)

Hussain, M.; Chen, D.

2014-11-01

Buildings, the basic unit of an urban landscape, host most of its socio-economic activities and play an important role in the creation of urban land-use patterns. The spatial arrangement of different building types creates varied urban land-use clusters which can provide an insight to understand the relationships between social, economic, and living spaces. The classification of such urban clusters can help in policy-making and resource management. In many countries including the UK no national-level cadastral database containing information on individual building types exists in public domain. In this paper, we present a framework for inferring functional types of buildings based on the analysis of their form (e.g. geometrical properties, such as area and perimeter, layout) and spatial relationship from large topographic and address-based GIS database. Machine learning algorithms along with exploratory spatial analysis techniques are used to create the classification rules. The classification is extended to two further levels based on the functions (use) of buildings derived from address-based data. The developed methodology was applied to the Manchester metropolitan area using the Ordnance Survey's MasterMap®, a large-scale topographic and address-based data available for the UK.

Monte Carlo Sampling in Fractal Landscapes

NASA Astrophysics Data System (ADS)

Leitão, Jorge C.; Lopes, J. M. Viana Parente; Altmann, Eduardo G.

2013-05-01

We design a random walk to explore fractal landscapes such as those describing chaotic transients in dynamical systems. We show that the random walk moves efficiently only when its step length depends on the height of the landscape via the largest Lyapunov exponent of the chaotic system. We propose a generalization of the Wang-Landau algorithm which constructs not only the density of states (transient time distribution) but also the correct step length. As a result, we obtain a flat-histogram Monte Carlo method which samples fractal landscapes in polynomial time, a dramatic improvement over the exponential scaling of traditional uniform-sampling methods. Our results are not limited by the dimensionality of the landscape and are confirmed numerically in chaotic systems with up to 30 dimensions.

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed Central

2012-01-01

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants–soil–vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources. PMID:22789155

Landscape permeability for large carnivores in Washington: a geographic information system weighted-distance and least-cost corridor assessment.

Treesearch

Peter H. Singleton; William L. Gaines; John F. Lehmkuhl

2002-01-01

We conducted a regional-scale evaluation of landscape permeability for large carnivores in Washington and adjacent portions of British Columbia and Idaho. We developed geographic information system based landscape permeability models for wolves (Canis lupus), wolverine (Gulo gulo), lynx (Lynx canadensis),...

Balanced VS Imbalanced Training Data: Classifying Rapideye Data with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ustuner, M.; Sanli, F. B.; Abdikan, S.

2016-06-01

The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imagery and landscape heterogeneity. The design of training set is still a challenging issue since the sensitivity of classifier algorithm at learning stage is different for the same dataset. In this paper, the classification of RapidEye imagery with balanced and imbalanced training data for mapping the crop types was addressed. Classification with imbalanced training data may result in low accuracy in some scenarios. Support Vector Machines (SVM), Maximum Likelihood (ML) and Artificial Neural Network (ANN) classifications were implemented here to classify the data. For evaluating the influence of the balanced and imbalanced training data on image classification algorithms, three different training datasets were created. Two different balanced datasets which have 70 and 100 pixels for each class of interest and one imbalanced dataset in which each class has different number of pixels were used in classification stage. Results demonstrate that ML and NN classifications are affected by imbalanced training data in resulting a reduction in accuracy (from 90.94% to 85.94% for ML and from 91.56% to 88.44% for NN) while SVM is not affected significantly (from 94.38% to 94.69%) and slightly improved. Our results highlighted that SVM is proven to be a very robust, consistent and effective classifier as it can perform very well under balanced and imbalanced training data situations. Furthermore, the training stage should be precisely and carefully designed for the need of adopted classifier.

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.

The problem with coal-waste dumps inventory in Upper Silesian Coal Basin

NASA Astrophysics Data System (ADS)

Abramowicz, Anna; Chybiorz, Ryszard

2017-04-01

Coal-waste dumps are the side effect of coal mining, which has lasted in Poland for 250 years. They have negative influence on the landscape and the environment, and pollute soil, vegetation and groundwater. Their number, size and shape is changing over time, as new wastes have been produced and deposited changing their shape and enlarging their size. Moreover deposited wastes, especially overburned, are exploited for example road construction, also causing the shape and size change up to disappearing. Many databases and inventory systems were created in order to control these hazards, but some disadvantages prevent reliable statistics. Three representative databases were analyzed according to their structure and type of waste dumps description, classification and visualization. The main problem is correct classification of dumps in terms of their name and type. An additional difficulty is the accurate quantitative description (area and capacity). A complex database was created as a result of comparison, verification of the information contained in existing databases and its supplementation based on separate documentation. A variability analysis of coal-waste dumps over time is also included. The project has been financed from the funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies for the period 2014-2018.

Urban Thermal Environment Dynamics: A Case Study in Hangzhou During 2005-2015

NASA Astrophysics Data System (ADS)

Sun, W.; Li, F.; Yang, G.

2017-12-01

Hangzhou, as the Capital of Zhejiang Province in East China, has experienced the rapid urbanization process and associated urban heat island effect in the past twenty decades. In this study, we implemented Landsat satellite remote sensing images to investigate the relationship between landscape changes and thermal environment dynamics during 2005-2015 in Hangzhou City. A total of 48 Landsat TM/ETM+/OLR/TIRS images spanning four different seasons were downloaded from the USGS website and utilized in the study. Preprocessing works, i.e., radiometric correction and removing cloud- and fog -contaminated pixels, were conducted, and the land surface temperature (LST) was derived using the radiative transfer equation. Meanwhile, the land use and land cover (LULC) classification was accomplished by using the Support Vector Machine (SVM) classifier, and four main landscape indexes (i.e., Shannon Diversity Index, Landscape Division Index, Shannon Evenness Index, and Aggregation Index) were estimated from the LULC map. Our preliminary results show that: 1) the magnitude of urban thermal environment has obviously increased from 2005 to 2015, and the summer season shows more significant heat island effect than other three seasons; 2) the general landscape pattern of Hangzhou becomes more diversified and fragmentized from 2005 to 2015, and different landscape patterns bring that four different function zones (i.e., urban core zone, tourism function zone, industrial development zone and ecological reservation zone) of Hangzhou have different characteristics in urban thermal environment; 3) significant hot spots of LST point to the construction land while cold spots of LST coincides with the vegetation land.

Multi-scale curvature for automated identification of glaciated mountain landscapes☆

PubMed Central

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2014-01-01

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes. PMID:24748703

Comparing carbon storage of Siberian tundra and taiga permafrost ecosystems at very high spatial resolution

NASA Astrophysics Data System (ADS)

Siewert, Matthias B.; Hanisch, Jessica; Weiss, Niels; Kuhry, Peter; Maximov, Trofim C.; Hugelius, Gustaf

2015-10-01

Permafrost-affected ecosystems are important components in the global carbon (C) cycle that, despite being vulnerable to disturbances under climate change, remain poorly understood. This study investigates ecosystem carbon storage in two contrasting continuous permafrost areas of NE and East Siberia. Detailed partitioning of soil organic carbon (SOC) and phytomass carbon (PC) is analyzed for one tundra (Kytalyk) and one taiga (Spasskaya Pad/Neleger) study area. In total, 57 individual field sites (24 and 33 in the respective areas) have been sampled for PC and SOC, including the upper permafrost. Landscape partitioning of ecosystem C storage was derived from thematic upscaling of field observations using a land cover classification from very high resolution (2 × 2 m) satellite imagery. Nonmetric multidimensional scaling was used to explore patterns in C distribution. In both environments the ecosystem C is mostly stored in the soil (≥86%). At the landscape scale C stocks are primarily controlled by the presence of thermokarst depressions (alases). In the tundra landscape, site-scale variability of C is controlled by periglacial geomorphological features, while in the taiga, local differences in catenary position, soil texture, and forest successions are more important. Very high resolution remote sensing is highly beneficial to the quantification of C storage. Detailed knowledge of ecosystem C storage and ground ice distribution is needed to predict permafrost landscape vulnerability to projected climatic changes. We argue that vegetation dynamics are unlikely to offset mineralization of thawed permafrost C and that landscape-scale reworking of SOC represents the largest potential changes to C cycling.

Analysis of land cover change and its driving forces in a desert oasis landscape of southern Xinjiang, China

NASA Astrophysics Data System (ADS)

Amuti, T.; Luo, G.

2014-07-01

The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of Southern Xinjiang, Northwest China. This study examined land cover changes during 1990-2008 to characterize and quantify the transformations in the typical oasis of Hotan. Land cover classifications of these images were performed based on the supervised classification scheme integrated with conventional vegetation and soil indexes. Change-detection techniques in remote sensing (RS) and a geographic information system (GIS) were applied to quantify temporal and spatial dynamics of land cover changes. The overall accuracies, Kappa coefficients, and average annual increase rate or decrease rate of land cover classes were calculated to assess classification results and changing rate of land cover. The analysis revealed that major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert-oasis ecotone, which led to accelerated soil salinization and plant deterioration within the oasis. These changes were mainly attributed to the intensified human activities. The results indicated that the newly created agricultural land along the margins of the Hotan oasis could result in more potential areas of land degradation. If no effective measures are taken against the deterioration of the oasis environment, soil erosion caused by land cover change may proceed. The trend of desert moving further inward and the shrinking of the ecotone may lead to potential risks to the eco-environment of the Hotan oasis over the next decades.

The invasive species Ulex europaeus (Fabaceae) shows high dynamism in a fragmented landscape of south-central Chile.

PubMed

Altamirano, Adison; Cely, Jenny Paola; Etter, Andrés; Miranda, Alejandro; Fuentes-Ramirez, Andres; Acevedo, Patricio; Salas, Christian; Vargas, Rodrigo

2016-08-01

Ulex europaeus (gorse) is an invasive shrub deemed as one of the most invasive species in the world. U. europaeus is widely distributed in the south-central area of Chile, which is considered a world hotspot for biodiversity conservation. In addition to its negative effects on the biodiversity of natural ecosystems, U. europaeus is one of the most severe pests for agriculture and forestry. Despite its importance as an invasive species, U. europaeus has been little studied. Although information exists on the potential distribution of the species, the interaction of the invasion process with the spatial dynamic of the landscape and the landscape-scale factors that control the presence or absence of the species is still lacking. We studied the spatial and temporal dynamics of the landscape and how these relate to U. europaeus invasion in south-central Chile. We used supervised classification of satellite images to determine the spatial distribution of the species and other land covers for the years 1986 and 2003, analysing the transitions between the different land covers. We used logistic regression for modelling the increase, decrease and permanence of U. europaeus invasion considering landscape variables. Results showed that the species covers only around 1 % of the study area and showed a 42 % reduction in area for the studied period. However, U. europaeus was the cover type which presented the greatest dynamism in the landscape. We found a strong relationship between changes in land cover and the invasion process, especially connected with forest plantations of exotic species, which promotes the displacement of U. europaeus. The model of gorse cover increase presented the best performance, and the most important predictors were distance to seed source and landscape complexity index. Our model predicted high spread potential of U. europaeus in areas of high conservation value. We conclude that proper management for this invasive species must take into account the spatial dynamics of the landscape within the invaded area in order to address containment, control or mitigation of the invasion.

Landscape pattern metrics and regional assessment

Treesearch

Robert V. O' Neill; Kurt H. Riitters; J.D. Wickham; Bruce K. Jones

1999-01-01

The combination of remote imagery data, geographic information systems software, and landscape ecology theory provides a unique basis for monitoring and assessing large-scale ecological systems. The unique feature of the work has been the need to develop interpret quantitative measures of spatial patter-the landscape indices. This article reviews what is known about...

Managing for naturalness in wildland and agricultural landscapes

Treesearch

Joan Nassauer

1979-01-01

Visual management systems operate from the premise that people have expectations for landscape views, and that people's positive expectations should be fulfilled. Both the Forest Service and Bureau of Land Management visual management systems assume that people expect wildlands to look natural. People also like to see natural landscapes in rural Iowa. Research I...

The Emerging Genomic Landscape of Endometrial Cancer

PubMed Central

Le Gallo, Matthieu; Bell, Daphne W.

2014-01-01

BACKGROUND Endometrial cancer is responsible for ~74,000 deaths amongst women worldwide each year. It is a heterogeneous disease that consists of multiple different histological subtypes. In the United States, the majority of deaths from endometrial carcinoma are attributed to the serous and endometrioid subtypes. An understanding of the fundamental genomic alterations that drive serous and endometrioid endometrial carcinomas lays the foundation for the identification of molecular markers that could improve the clinical management of patients presenting with these tumors. CONTENT Herein we review the current state of knowledge of the somatic genomic alterations that are present in serous and endometrioid endometrial tumors. We present this knowledge in a historical context – reviewing the genomic alterations that have been identified over the past two decades or more, from studies of individual genes and proteins, followed by a review of very recent studies that have conducted comprehensive, systematic surveys of genomic, exomic, transcriptomic, epigenomic, and proteomic alterations in serous and endometrioid endometrial carcinomas. SUMMARY The recent mapping of the genomic landscape of serous and endometrioid endometrial carcinomas has resulted in the first comprehensive molecular classification of these tumors and has distinguished four molecular subgroups: a POLE ultramutated subgroup, a hypermutated/microsatellite unstable subgroup, a copy number low/microsatellite stable subgroup, and a copy number high subgroup. This molecular classification may ultimately serve to refine the diagnosis and treatment of women with endometrioid and serous endometrial tumors. PMID:24170611

Recent advances in understanding the interaction of groundwater and surface water

USGS Publications Warehouse

Winter, Thomas C.

1995-01-01

The most common image of the interaction of groundwater and surface water is that of the interaction of streams with a contiguous alluvial aquifer. This type of system has been the focus of study for more than 100 years, from the work of Boussinesq (1877) to the present, and stream-aquifer interaction continues to be the most common topic of papers discussing the interaction of groundwater and surface water. However, groundwater and surface water interact in a wide variety of landscapes from alpine to coastal. Within these landscapes, ground-water systems range in scale from local to regional, and the types of surface water include streams, lakes, wetlands, and oceans. Given the broad spectrum of the topic of groundwater and surface water interaction, an overview of studies of this topic could be organized according to surface water type, landscape type, scale of hydrologic systems, or field and analytical methods. All these factors are discussed, but this paper is organized according to landscape type because of the great increase in studies of the interaction of groundwater and surface water in landscapes other than riverine systems in the last 15 years. Furthermore, discussing studies by landscape type facilitates comparison of methods and results from different geologic and climatic settings. The general landscapes discussed are mountain terrane, riverine systems, coastal terrane, hummocky terrane, and karst terrane.

Patents and nanomedicine.

PubMed

Bawa, Raj

2007-06-01

Big pharma's business model, which relies on a few blockbusters to generate profits, is clearly broken. Patent expiration on numerous blockbusters in recent years is already altering the drug landscape. Drug companies are also facing other challenges that necessitate development and implementation of novel R&D strategies, including those that focus on nanotechnology and miniaturization. Clearly, there is enormous excitement and expectation regarding nanomedicine's potential impact. However, securing valid and defensible patent protection will be critical. Although early forecasts for nanomedicine commercialization are encouraging, there are numerous bottlenecks as well. One of the major hurdles is an emerging thicket of patent claims, resulting primarily from patent proliferation as well as continued issuance of surprisingly broad patents by the US Patent and Trademark Office (PTO). Adding to this confusion is the fact that the US National Nanotechnology Initiative's widely cited definition of nanotechnology is inaccurate and irrelevant from a nanomedicine perspective. It is also the cause of the inadequate patent classification system that was recently unveiled by the PTO. All of this is creating a chaotic, tangled patent landscape in various sectors of nanomedicine where the competing players are unsure of the validity and enforceability of numerous issued patents. If this trend continues, it could stifle competition and limit access to some inventions. Therefore, reforms are urgently needed at the PTO to address problems ranging from poor patent quality and questionable examination practices to inadequate search capabilities, rising attrition, poor employee morale and a skyrocketing patent application backlog. Only a robust patent system will stimulate the development of commercially viable nanomedicine products that can drastically improve a patient's quality of life and reduce healthcare costs.

Landscape ecological security response to land use change in the tidal flat reclamation zone, China.

PubMed

Zhang, Runsen; Pu, Lijie; Li, Jianguo; Zhang, Jing; Xu, Yan

2016-01-01

As coastal development becomes a national strategy in Eastern China, land use and landscape patterns have been affected by reclamation projects. In this study, taking Rudong County, China as a typical area, we analyzed land use change and its landscape ecological security responses in the tidal flat reclamation zone. The results show that land use change in the tidal flat reclamation zone is characterized by the replacement of natural tidal flat with agricultural and construction land, which has also led to a big change in landscape patterns. We built a landscape ecological security evaluation system, which consists of landscape interference degree and landscape fragile degree, and then calculated the landscape ecological security change in the tidal flat reclamation zone from 1990 to 2008 to depict the life cycle in tidal flat reclamation. Landscape ecological security exhibited a W-shaped periodicity, including the juvenile stage, growth stage, and maturation stage. Life-cycle analysis demonstrates that 37 years is required for the land use system to transform from a natural ecosystem to an artificial ecosystem in the tidal flat reclamation zone.

Landscape approach to the formation of the ecological frame of Moscow

NASA Astrophysics Data System (ADS)

Nizovtsev, Vyacheslav; Natalia, Erman

2015-04-01

The territory of Moscow, in particular in its former borders, is distinct for its strong transformation of the natural properties of virtually all types of landscape complexes. The modern landscape structure is characterized by fragmentation of natural land cover. Natural and quasinatural (natural and anthropogenic) landscape complexes with preserved natural structure are represented by isolated areas and occupy small areas. During recent years landscape diversity in general and biodiversity in particular have been rapidly declining, and many of the natural landscape complexes are under ever-increasing degradation. Ecological balance is broken, and preserved natural landscapes are not able to maintain it. Effective territorial organization of Moscow and the rational use of its territory are impossible without taking into account the natural component of the city as well as the properties and potential of the landscape complexes that integrate all natural features in specific areas. The formation of the ecological framework of the city is particularly important. It should be a single system of interrelated and complementary components that make up a single environmental space: habitat-forming cores (junctions), ecological corridors and elements of environmental infrastructure. Systemic unity of the environmental framework can support the territorial ecological compensation where a break of the ecological functions of one part of the system is compensated by maintaining or restoring them in another part and contribute to the polarization of incompatible types of land use. Habitat-forming cores should include as mandatory parts all the specifically protected natural areas (SPNAs), particularly valuable landscape complexes, as well as preserved adjacent forest areas. Their most important function should be to maintain resources and area reproducing abilities of landscapes, landscape diversity and biodiversity. Ecological corridors which perform environmental and operating transit functions should include unified landscape systems of river valleys, their hollow-beam upstreams and drained lows. The most important elements of environmental infrastructure include the most valuable forest and wetland complexes, springs and other landscape and aquatic complexes, cultural and historical landscape complexes, landscape complexes with high concentration of cultural heritage sites, sites of natural and green areas with great potential of natural and recreational resources, natural and recreational parks, natural monuments. They can serve as centers of landscape and biological diversity and perform partial transit (migration) and buffer functions. The territory of the ecological framework can be used for strictly regulated or limited recreation (tourism, short leisure). The adjacent natural and green spaces and natural parks may play a buffer role for the SPNAs and valuable landscape complexes. The spatial pattern of the landscape complexes of Moscow allows to create a single ecological framework based on the landscape, distinct for its interrelated and complementary components. Its basis may be consisted of uniform landscape complexes of valley outwash plains and river valleys, their hollow-beam upstreams and drained lows which perform system forming, environmental and transit functions. In the plan river valleys and small erosional forms are as if enclosed in the gullies and constitute single paradynamic systems unified by lateral flows. Therefore not only the edges of river valleys, but also the rear seams of the valley outwash plains should become important natural boundaries, limiting urban development of the area. Their most important functional feature is that they serve as local collectors and surface water runoff channels. These landscape complexes are distinct for most dynamic natural processes and thus negative exogenous processes. The authors have drawn indigenous (conditionally restored) and modern landscapes of Moscow on a scale of 1: 50,000 and on their basis an ecological framework map of Moscow. These maps are an important natural basis for the analysis of conditions and identification of limiting factors of the urban development of the big city.

Roads in landscape modeling: a case study of a road data layer and use in the interior northwest landscape analysis system.

Treesearch

Marti Aitken; Jane L. Hayes

2006-01-01

Roads are important ecological features of forest landscapes, but their cause-and effect relationships with other ecosystem components are only recently becoming included in integrated landscape analyses. Simulation models can help us to understand how forested landscapes respond over time to disturbance and socioeconomic factors, and potentially to address the...

Genetic landscapes GIS Toolbox: tools to map patterns of genetic divergence and diversity.

USGS Publications Warehouse

Vandergast, Amy G.; Perry, William M.; Lugo, Roberto V.; Hathaway, Stacie A.

2011-01-01

The Landscape Genetics GIS Toolbox contains tools that run in the Geographic Information System software, ArcGIS, to map genetic landscapes and to summarize multiple genetic landscapes as average and variance surfaces. These tools can be used to visualize the distribution of genetic diversity across geographic space and to study associations between patterns of genetic diversity and geographic features or other geo-referenced environmental data sets. Together, these tools create genetic landscape surfaces directly from tables containing genetic distance or diversity data and sample location coordinates, greatly reducing the complexity of building and analyzing these raster surfaces in a Geographic Information System.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysis.

PubMed

Sahm, Felix; Schrimpf, Daniel; Stichel, Damian; Jones, David T W; Hielscher, Thomas; Schefzyk, Sebastian; Okonechnikov, Konstantin; Koelsche, Christian; Reuss, David E; Capper, David; Sturm, Dominik; Wirsching, Hans-Georg; Berghoff, Anna Sophie; Baumgarten, Peter; Kratz, Annekathrin; Huang, Kristin; Wefers, Annika K; Hovestadt, Volker; Sill, Martin; Ellis, Hayley P; Kurian, Kathreena M; Okuducu, Ali Fuat; Jungk, Christine; Drueschler, Katharina; Schick, Matthias; Bewerunge-Hudler, Melanie; Mawrin, Christian; Seiz-Rosenhagen, Marcel; Ketter, Ralf; Simon, Matthias; Westphal, Manfred; Lamszus, Katrin; Becker, Albert; Koch, Arend; Schittenhelm, Jens; Rushing, Elisabeth J; Collins, V Peter; Brehmer, Stefanie; Chavez, Lukas; Platten, Michael; Hänggi, Daniel; Unterberg, Andreas; Paulus, Werner; Wick, Wolfgang; Pfister, Stefan M; Mittelbronn, Michel; Preusser, Matthias; Herold-Mende, Christel; Weller, Michael; von Deimling, Andreas

2017-05-01

The WHO classification of brain tumours describes 15 subtypes of meningioma. Nine of these subtypes are allotted to WHO grade I, and three each to grade II and grade III. Grading is based solely on histology, with an absence of molecular markers. Although the existing classification and grading approach is of prognostic value, it harbours shortcomings such as ill-defined parameters for subtypes and grading criteria prone to arbitrary judgment. In this study, we aimed for a comprehensive characterisation of the entire molecular genetic landscape of meningioma to identify biologically and clinically relevant subgroups. In this multicentre, retrospective analysis, we investigated genome-wide DNA methylation patterns of meningiomas from ten European academic neuro-oncology centres to identify distinct methylation classes of meningiomas. The methylation classes were further characterised by DNA copy number analysis, mutational profiling, and RNA sequencing. Methylation classes were analysed for progression-free survival outcomes by the Kaplan-Meier method. The DNA methylation-based and WHO classification schema were compared using the Brier prediction score, analysed in an independent cohort with WHO grading, progression-free survival, and disease-specific survival data available, collected at the Medical University Vienna (Vienna, Austria), assessing methylation patterns with an alternative methylation chip. We retrospectively collected 497 meningiomas along with 309 samples of other extra-axial skull tumours that might histologically mimic meningioma variants. Unsupervised clustering of DNA methylation data clearly segregated all meningiomas from other skull tumours. We generated genome-wide DNA methylation profiles from all 497 meningioma samples. DNA methylation profiling distinguished six distinct clinically relevant methylation classes associated with typical mutational, cytogenetic, and gene expression patterns. Compared with WHO grading, classification by individual and combined methylation classes more accurately identifies patients at high risk of disease progression in tumours with WHO grade I histology, and patients at lower risk of recurrence among WHO grade II tumours (p=0·0096) from the Brier prediction test). We validated this finding in our independent cohort of 140 patients with meningioma. DNA methylation-based meningioma classification captures clinically more homogenous groups and has a higher power for predicting tumour recurrence and prognosis than the WHO classification. The approach presented here is potentially very useful for stratifying meningioma patients to observation-only or adjuvant treatment groups. We consider methylation-based tumour classification highly relevant for the future diagnosis and treatment of meningioma. German Cancer Aid, Else Kröner-Fresenius Foundation, and DKFZ/Heidelberg Institute of Personalized Oncology/Precision Oncology Program. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient retrieval of landscape Hessian: Forced optimal covariance adaptive learning

NASA Astrophysics Data System (ADS)

Shir, Ofer M.; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

2014-06-01

Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳104). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling

USGS Publications Warehouse

Keane, Robert E.; Burgan, Robert E.; Van Wagtendonk, Jan W.

2001-01-01

Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

Object-based forest classification to facilitate landscape-scale conservation in the Mississippi Alluvial Valley

USGS Publications Warehouse

Mitchell, Michael; Wilson, R. Randy; Twedt, Daniel J.; Mini, Anne E.; James, J. Dale

2016-01-01

The Mississippi Alluvial Valley is a floodplain along the southern extent of the Mississippi River extending from southern Missouri to the Gulf of Mexico. This area once encompassed nearly 10 million ha of floodplain forests, most of which has been converted to agriculture over the past two centuries. Conservation programs in this region revolve around protection of existing forest and reforestation of converted lands. Therefore, an accurate and up to date classification of forest cover is essential for conservation planning, including efforts that prioritize areas for conservation activities. We used object-based image analysis with Random Forest classification to quickly and accurately classify forest cover. We used Landsat band, band ratio, and band index statistics to identify and define similar objects as our training sets instead of selecting individual training points. This provided a single rule-set that was used to classify each of the 11 Landsat 5 Thematic Mapper scenes that encompassed the Mississippi Alluvial Valley. We classified 3,307,910±85,344 ha (32% of this region) as forest. Our overall classification accuracy was 96.9% with Kappa statistic of 0.96. Because this method of forest classification is rapid and accurate, assessment of forest cover can be regularly updated and progress toward forest habitat goals identified in conservation plans can be periodically evaluated.

Hydropodelogy From the Pedon to the Landscape: Challenges and Accomplishments in the National Cooperative Soil Survey

NASA Astrophysics Data System (ADS)

Hammer, D.; Richardson, J.; Hempel, J.; Market, P.

2005-12-01

American pedology has focused on the National Cooperative Soil Survey. Primary responsibility rests with the U.S. Department of Agriculture. The primary goals, are legislatively mandated, are to map the country's soils, make interpretations, provide information to clients, maintain and market the soil survey. The first goal is near completion and focus is shifting to the other three. Concomitantly, American pedological science is being impacted by several conditions: technological advances; land use changes at unprecedented scales and magnitudes; a burgeoning population increasingly "separated" from the land; and a major emphasis in universities upon biological ("life") sciences at the DNA scale - as if soil, nutrients and water are not life essentials. Effects of the Flood of 1993 and Hurricane Katrina suggest that humans do not understand earth/climate interactions, particularly climatic extremes. Pedologists know the focus on soil classification and mapping was at the expense of understanding processes. Hydropedology is a holistic approach to understanding soil and geomorphic process in order to predict the impacts of perturbations. Water movement on and in the soil is the primary mechanism of distributing and altering sediments and chemicals (pedogenesis), and depends for its success upon understanding that the soil profile is the record of developmental history at that landscape site. Hydropedologists believe soil scientists can use pedons (point data) from appropriate locations from flownets in complex landscapes to extrapolate processes. This is the "pedotransfer function" concept. Technological advances are coupled with the existing soil survey information to create important soil-landscape interpretations at a variety of scales. Early results have been very successful. Quantification of soil systems can be classified broadly into three categories; hard data, soft data and tacit knowledge. "Hard data" are measured numbers, and include such attributes as pH, texture, cation exchange capacity and event-specific rainfall. "Soft data" include soil maps, SSURGO data and climate maps. Soft data are combinations of observations, measurements and inferences that produce maps and models at various scales. "Tacit knowledge" is human understanding that results from focused experience within a system. A skilled soil scientist with tacit knowledge specific to a particular region can combination hard and soft data to develop important and useful interpretations and predictions. Illustrations from natural and urban settings will be provided. Soils and climate are temporally and spatially variable at all scales. Soil systems respond differently to different climates and perturbations. For example, the recent pluvial period in the Prairie Pothole region is changing surface soil sodium concentrations and locations and sizes of discharge wetlands. This is a relatively short-term response to a regional climate shift. Climatic shift in Oxisol landscapes will have little effect on soil cations. To optimize soil interpretations, focus must be on quantifying region-specific "dynamic" soil, geomorphic and climatic attributes. Recognizing these needs, the National Cooperative Soil Survey will develop regional watershed projects that focus on quantifying soil-water relationships that can be used at a variety of scales.

Organic Farming and Landscape Structure: Effects on Insect-Pollinated Plant Diversity in Intensively Managed Grasslands

PubMed Central

Power, Eileen F.; Kelly, Daniel L.; Stout, Jane C.

2012-01-01

Parallel declines in insect-pollinated plants and their pollinators have been reported as a result of agricultural intensification. Intensive arable plant communities have previously been shown to contain higher proportions of self-pollinated plants compared to natural or semi-natural plant communities. Though intensive grasslands are widespread, it is not known whether they show similar patterns to arable systems nor whether local and/or landscape factors are influential. We investigated plant community composition in 10 pairs of organic and conventional dairy farms across Ireland in relation to the local and landscape context. Relationships between plant groups and local factors (farming system, position in field and soil parameters) and landscape factors (e.g. landscape complexity) were investigated. The percentage cover of unimproved grassland was used as an inverse predictor of landscape complexity, as it was negatively correlated with habitat-type diversity. Intensive grasslands (organic and conventional) contained more insect-pollinated forbs than non-insect pollinated forbs. Organic field centres contained more insect-pollinated forbs than conventional field centres. Insect-pollinated forb richness in field edges (but not field centres) increased with increasing landscape complexity (% unimproved grassland) within 1, 3, 4 and 5km radii around sites, whereas non-insect pollinated forb richness was unrelated to landscape complexity. Pollination systems within intensive grassland communities may be different from those in arable systems. Our results indicate that organic management increases plant richness in field centres, but that landscape complexity exerts strong influences in both organic and conventional field edges. Insect-pollinated forb richness, unlike that for non-insect pollinated forbs, showed positive relationships to landscape complexity reflecting what has been documented for bees and other pollinators. The insect-pollinated forbs, their pollinators and landscape context are clearly linked. This needs to be taken into account when managing and conserving insect-pollinated plant and pollinator communities. PMID:22666450

Spatial relations between floodplain environments and land use - land cover of a large lowland tropical river valley: Pánuco basin, México.

PubMed

Hudson, Paul F; Colditz, René R; Aguilar-Robledo, Miguel

2006-09-01

Large lowland river valleys include a variety of floodplain environments that represent opportunities and constraints for human activities. This study integrates extensive field observations and geomorphic data with analysis of satellite remote sensing data to examine spatial relations between land use/land cover (LULC) and floodplain environments in the lower Pánuco basin of eastern Mexico. The floodplain of the lower Pánuco basin was delineated by combining a digital elevation model with a satellite image of a large flood event. The LULC was classified by combining a hybrid classification strategy with image stratification, applied to 15-m-resolution ASTER data. A geomorphic classification of floodplain environments was performed using a dry-stage image (ASTER data) and a 1993 Landsat image acquired during a large flood event. Accuracy assessment was based on aerial photographs (1:38,000), global positioning satellite ground-truthing, and a Landsat 7ETM(+) image from 2000, which resulted in an overall accuracy of 82.9% and a KHAT of 79.8% for the LULC classification. The geomorphic classification yielded 83.5% overall accuracy, whereas the KHAT was 81.5%. LULC analysis was performed for the entire floodplain and individually within four valley segments. The analysis indicates that the study area is primarily utilized for grazing and farming. Agriculture is primarily associated with coarse-grained (sandy/silty) natural levee and point bar units close to the river channel, whereas cattle grazing occurs in distal and lower-lying reaches dominated by cohesive fine-grained (clayey) deposits, such as backswamps. In the Pánuco valley, wetlands and lakes occur within backswamp environments, whereas in the Moctezuma segments, wetlands and lakes are associated with relict channels. This study reveals considerable variation in LULC related to spatial differences in floodplain environments and illustrates the importance of considering older anthropogenic influences on the landscape. The research design should be applicable for other large lowland coastal plain river valleys where agriculture is a major component of the floodplain landscape.

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

The threshold algorithm: Description of the methodology and new developments

NASA Astrophysics Data System (ADS)

Neelamraju, Sridhar; Oligschleger, Christina; Schön, J. Christian

2017-10-01

Understanding the dynamics of complex systems requires the investigation of their energy landscape. In particular, the flow of probability on such landscapes is a central feature in visualizing the time evolution of complex systems. To obtain such flows, and the concomitant stable states of the systems and the generalized barriers among them, the threshold algorithm has been developed. Here, we describe the methodology of this approach starting from the fundamental concepts in complex energy landscapes and present recent new developments, the threshold-minimization algorithm and the molecular dynamics threshold algorithm. For applications of these new algorithms, we draw on landscape studies of three disaccharide molecules: lactose, maltose, and sucrose.

Landscape functionality of plant communities in the Impala Platinum mining area, Rustenburg.

PubMed

van der Walt, L; Cilliers, S S; Kellner, K; Tongway, D; van Rensburg, L

2012-12-30

The tremendous growth of the platinum mining industry in South Africa has affected the natural environment adversely. The waste produced by platinum mineral processing is alkaline, biologically sterile and has a low water-holding capacity. These properties in the environment may constitute dysfunctional areas that will create 'leaky' and dysfunctional landscapes, limiting biological development. Landscape Function Analysis (LFA) is a monitoring procedure that assesses the degradation of landscapes, as brought about by human, animal and natural activities, through rapidly assessing certain soil surface indicators which indicate the biophysical functionality of the system. The "Trigger-Transfer-Reserve-Pulse" (TTRP) conceptual framework forms the foundation for assessing landscape function when using LFA. The two main aspects of this framework are the loss of resources from the system and the utilisation of resources by the system. After a survey of landscape heterogeneity to reflect the spatial organisation of the landscape, soil surface indicators are assessed within different patch types (identifiable units that retains resources that pass through the system) and interpatches (units between patches where vital resources are not retained, but lost) to assess the capacity of patches with various physical properties in regulating the effectiveness of resource control in the landscape. Indices describing landscape organisation are computed by a spreadsheet analysis, as well as soil surface quality indices. When assembled in different combinations, three indices emerge that reflect soil productive potential, namely: the (1) surface stability, (2) infiltration capacity, and (3) the nutrient cycling potential of the landscape. In this study we compared the landscape functionality of natural thornveld areas, rehabilitated opencast mines and rehabilitated slopes of tailings dams in the area leased for mining in the Rustenburg area. Our results show that the rehabilitated areas had a higher total SSA functionality due to higher infiltration and nutrient cycling indices than the natural thornveld landscapes. The length of interpatches and the width of patches greatly influenced the landscape function of the studied areas. The natural thornveld areas had a marginally higher total patch area than the rehabilitated areas. Vegetated patches (grass-, sparse grass-, grassy forb-, and grassy shrub-patches) generally scored the highest functionality indices, whilst bare soil interpatches contributed to the landscape functionality of the various plant communities the least. Copyright © 2012 Elsevier Ltd. All rights reserved.

Landscape preference assessment of Louisiana river landscapes: a methodological study

Treesearch

Michael S. Lee

1979-01-01

The study pertains to the development of an assessment system for the analysis of visual preference attributed to Louisiana river landscapes. The assessment system was utilized in the evaluation of 20 Louisiana river scenes. Individuals were tested for their free choice preference for the same scenes. A statistical analysis was conducted to examine the relationship...

Overview and example application of the Landscape Treatment Designer

Treesearch

Alan A. Ager; Nicole M. Vaillant; David E. Owens; Stuart Brittain; Jeff Hamann

2012-01-01

The Landscape Treatment Designer (LTD) is a multicriteria spatial prioritization and optimization system to help design and explore landscape fuel treatment scenarios. The program fills a gap between fire model programs such as FlamMap, and planning systems such as ArcFuels, in the fuel treatment planning process. The LTD uses inputs on spatial treatment objectives,...

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

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

Parresol, Bernard, R.; Scott, Joe, H.; Andreu, Anne

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting thosemore » into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior parameters represent reasonably identifiable stand conditions, being: (1) pine dominated stands with more litter and down woody debriscomponents than other stands, (2) hardwood and pine stands with no shrubs, (3) hardwood dominated stands with low shrub and high non-woody biomass and high down woody debris, (4) stands with high grass and forb (i.e., non-woody) biomass as well as substantial shrub biomass, (5) stands with both high shrub and litter biomass, (6) pine-mixed hardwood stands with moderate litter biomass and low shrub biomass, and (7) baldcypress-tupelo stands. Models representing these stand clusters generated flame lengths from 0.6 to 2.3 musing a 30 km h{sub 1} wind speed and fireline intensities of 100-1500 kW m{sub 1} that are typical within the range of experience on this landscape. The fuel models ranked 1 < 2 < 7 < 5 < 4 < 3 < 6 in terms of both flame length and fireline intensity. The method allows for ecologically complex data to be utilized in order to create a landscape representative of measured fuel conditions and to create models that interface with geospatial fire models.« less

Does reintroducing large wood influence the hydraulic landscape of a lowland river system?

NASA Astrophysics Data System (ADS)

Matheson, Adrian; Thoms, Martin; Reid, Michael

2017-09-01

Our understanding of the effectiveness of reintroduced large wood for restoration is largely based on studies from high energy river systems. By contrast, few studies of the effectiveness of reintroducing large wood have been undertaken on large, low energy, lowland river systems: river systems where large wood is a significant physical feature on the in-channel environment. This study investigated the effect of reintroduced large wood on the hydraulic landscape of the Barwon-Darling River, Australia, at low flows. To achieve this, the study compared three hydraulic landscapes of replicated reference (naturally wooded), control (unwooded,) and managed (wood reintroduced) treatments on three low flow periods. These time periods were prior to the reintroduction of large wood to managed reaches; several months after the reintroduction of large wood into the managed reaches; and then more than four years after wood reintroduction following several large flood events. Hydraulic landscapes of reaches were characterised using a range of spatial measures calculated from velocity measurements taken with a boat-mounted Acoustic Doppler Profiler. We hypothesised that reintroduced large wood would increase the diversity of the hydraulic landscape at low flows and that managed reaches would be more similar to the reference reaches. Our results suggest that the reintroduction of large wood did not significantly change the character of the hydraulic landscape at the reach scale after several months (p = 0.16) or several years (p = 0.29). Overall, the character of the hydraulic landscape in the managed reaches was more similar to the hydraulic landscape of the control reaches than the hydraulic landscape of the reference reaches, at low flows. Some variability in the hydraulic landscapes was detected over time, and this may reflect reworking of riverbed sediments and sensitivity to variation in discharge. The lack of a response in the low flow hydraulic landscape to the reintroduction of large wood is inferred because the character (the size and complexity of individual pieces) and positioning of large wood in managed reaches did not mimic that of reference reaches effectively despite the abundance of wood pieces being similar in the reference and managed reaches. The results of this study highlight the importance of understanding the natural character and distribution of large wood on hydraulic landscapes in large low energy lowland river systems, especially when reintroducing large wood for river management purposes.

Defining the human deubiquitinating enzyme interaction landscape.

PubMed

Sowa, Mathew E; Bennett, Eric J; Gygi, Steven P; Harper, J Wade

2009-07-23

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

Defining the Human Deubiquitinating Enzyme Interaction Landscape

PubMed Central

Sowa, Mathew E.; Bennett, Eric J.; Gygi, Steven P.; Harper, J. Wade

2009-01-01

Summary Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform, called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel non-reciprocal proteomic datasets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, sub-cellular localization and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway. PMID:19615732

A lake-centric geospatial database to guide research and inform management decisions in an Arctic watershed in northern Alaska experiencing climate and land-use changes

USGS Publications Warehouse

Jones, Benjamin M.; Arp, Christopher D.; Whitman, Matthew S.; Nigro, Debora A.; Nitze, Ingmar; Beaver, John; Gadeke, Anne; Zuck, Callie; Liljedahl, Anna K.; Daanen, Ronald; Torvinen, Eric; Fritz, Stacey; Grosse, Guido

2017-01-01

Lakes are dominant and diverse landscape features in the Arctic, but conventional land cover classification schemes typically map them as a single uniform class. Here, we present a detailed lake-centric geospatial database for an Arctic watershed in northern Alaska. We developed a GIS dataset consisting of 4362 lakes that provides information on lake morphometry, hydrologic connectivity, surface area dynamics, surrounding terrestrial ecotypes, and other important conditions describing Arctic lakes. Analyzing the geospatial database relative to fish and bird survey data shows relations to lake depth and hydrologic connectivity, which are being used to guide research and aid in the management of aquatic resources in the National Petroleum Reserve in Alaska. Further development of similar geospatial databases is needed to better understand and plan for the impacts of ongoing climate and land-use changes occurring across lake-rich landscapes in the Arctic.

A Bird's-Eye View of Eco-Geomorphology From a Small Unmanned Aircraft System (UAS)

NASA Astrophysics Data System (ADS)

LeClair, A. J.; Hugenholtz, C.

2012-12-01

Physical disturbance regimes play important roles in shaping ecosystems and landscapes; however, our ability to detect disturbance often depends on the method and scale of observation. Here we use a relatively new method in order to detect and map the eco-geomorphic impacts of fossorial mammals in a grassland setting. It is well-known that digging and mound building activity by these animals is a form of biological disturbance that has a number of eco-geomorphic consequences, including: soil formation, hydrology, nutrient cycling, and succession. All these processes contribute to landscape heterogeneity and often increase local micro-topographic variations through mound formation. Most studies that have examined the eco-geomorphic role of fossorial mammals have been limited to observations using traditional field-based methods. While this has yielded important data about the localized effects, the cumulative, landscape-level impacts of such small-scale disturbance events are still largely unknown. While fossorial mammals such as pocket gophers (family Geomyidae) are assumed to be ubiquitous in the environments in which they occur, the small size of individual mounds has meant that mapping their biological footprint using traditional methods has been extremely difficult. Individual mounds disappear in the pixels of conventional remote sensing imagery, while their spatial distribution makes it impractical to study them beyond the plot scale. However, recent advances in both low cost, high-resolution digital cameras, and unmanned aerial systems (UAS), have made it possible to acquire landscape-level data that matches the scale of their disturbance, thus potentially bridging the gap between ground-based field methods and traditional remote sensing imagery. In this study we used UAS-acquired, sub-decimeter resolution imagery to map and quantify the extent of fossorial mammal disturbance in a 4 km2 area of the Great Sand Hills - a stabilized dune field in southwestern Saskatchewan, Canada. This area is densely populated by both the northern pocket gopher (Thomomys talpoides) and the thirteen-lined ground squirrel (Ictidomys tridecemlineatus), both of which are active throughout the growing season. Mounds of bare sand occur both singly, and in larger, clustered networks. Older mounds are darker due to higher vegetation cover and litter accumulation, while more recent mounds are brighter due to absence of vegetation and litter. Based on objective image classification we estimate that nearly 20% of the landscape is affected by mound disturbance, while in some localized regions up to 50% of the surface is affected by recent disturbance. Overall, our case study demonstrates the potential value of UAS platforms for acquiring high-resolution remote sensing data for detecting and mapping small-scale biological disturbance.

Mapping the environmental risk potential on surface water of pesticide contamination in the Prosecco's vineyard terraced landscape

NASA Astrophysics Data System (ADS)

Pizarro, Patricia; Ferrarese, Francesco; Loddo, Donato; Eugenio Pappalardo, Salvatore; Varotto, Mauro

2016-04-01

Intensive cropping systems today represent a paramount issue in terms of environmental impacts, since agricultural pollutants can constitute a potential threat to surface water, non-target organisms and aquatic ecosystems. Levels of pesticide concentrations in surface waters are indeed unquestionably correlated to crop and soil management practices at field-scale. Due to the numerous applications of pesticides required, orchards and vineyards can represent relevant non-point sources for pesticide contamination of water bodies, mainly prompted by soil erosion, surface runoff and spray drift. To reduce risks of pesticide contamination of surface water, the Directive 2009/128/CET imposed the local implementation of agricultural good practices and mitigation actions such as the use of vegetative buffer filter strips and hedgerows along river and pond banks. However, implementation of mitigation actions is often difficult, especially in extremely fragmented agricultural landscapes characterized by a complex territorial matrix set up on urban sprawling, frequent surface water bodies, important geomorphological processes and protected natural areas. Typically, such landscape matrix is well represented by the, Prosecco-DOCG vineyards area (NE of Italy, Province of Treviso) which lays on hogback hills of conglomerate, marls and sandstone that ranges between 50 and 500 m asl. Moreover such vineyards landscape is characterized by traditional and non-traditional agricultural terraces The general aim of this paper is to identify areas of surface water bodies with high potential risk of pesticide contamination from surrounding vineyards in the 735 ha of Lierza river basin (Refrontolo, TV), one of the most representative terraced landscape of the Prosecco-DOCG area. Specific aims are i) mapping terraced Prosecco-DOCG vineyards, ii) classifying potential risk from pesticide of the different areas. Remote sensing technologies such as four bands aerial photos (RGB+NIR) and Light Detection and Ranging (LiDAR) have been used to map vineyards and to evaluate slope and drainage systems. All the data and statistics analyses have been performed in GIS environment. The areas of surface water located within a buffer zone of 20 linear meters from vineyard perimeter were considered at risk of pesticide contamination, according to European guidelines and on-site experimental results about the pesticide drift effect. Preliminary results show that 26 ha of the total vineyards within the river basin can potentially affect surface water bodies, highlighting that 19,410 m of perimeter is within 20 m from water courses. Moreover, vineyard classification based on proximity analysis indicates that 6.8 ha are at very high potential risk (<1m from water courses), 8.6 ha are at high risk level (from 1 to 5 m); 4.3 ha are at medium level (from 5 to 10 m), while 8.6 ha are at low level (>10 m).

Planning of Green Space Ecological Network in Urban Areas: An Example of Nanchang, China

PubMed Central

Li, Haifeng; Chen, Wenbo; He, Wei

2015-01-01

Green space plays an important role in sustainable urban development and ecology by virtue of multiple environmental, recreational, and economic benefits. Constructing an effective and harmonious urban ecological network and maintaining a sustainable living environment in response to rapid urbanization are the key issues required to be resolved by landscape planners. In this paper, Nanchang City, China was selected as a study area. Based on a series of landscape metrics, the landscape pattern analysis of the current (in 2005) and planned (in 2020) green space system were, respectively, conducted by using FRAGSTATS 3.3 software. Considering the actual situation of the Nanchang urban area, a “one river and two banks, north and south twin cities” ecological network was constructed by using network analysis. Moreover, the ecological network was assessed by using corridor structure analysis, and the improvement of an ecological network on the urban landscape was quantitatively assessed through a comparison between the ecological network and green space system planning. The results indicated that: (1) compared to the green space system in 2005, the planned green space system in 2020 of the Nanchang urban area will decline in both districts (Changnan and Changbei districts). Meanwhile, an increase in patch density and a decrease in mean patch size of green space patches at the landscape level implies the fragmentation of the urban green space landscape. In other words, the planned green space system does not necessarily improve the present green space system; (2) the ecological network of two districts has high corridor density, while Changnan’s ecological network has higher connectivity, but Changbei’s ecological network is more viable from an economic point of view, since it has relatively higher cost efficiency; (3) decrease in patch density, Euclidean nearest neighbor distance, and an increase in mean patch size and connectivity implied that the ecological network could improve landscape connectivity greatly, as compared with the planned green space system. That is to say, the planned ecological network would reduce landscape fragmentation, and increase the shape complexity of green space patches and landscape connectivity. As a result, the quality of the urban ecological environment would be improved. PMID:26501298

Planning of Green Space Ecological Network in Urban Areas: An Example of Nanchang, China.

PubMed

Li, Haifeng; Chen, Wenbo; He, Wei

2015-10-15

Green space plays an important role in sustainable urban development and ecology by virtue of multiple environmental, recreational, and economic benefits. Constructing an effective and harmonious urban ecological network and maintaining a sustainable living environment in response to rapid urbanization are the key issues required to be resolved by landscape planners. In this paper, Nanchang City, China was selected as a study area. Based on a series of landscape metrics, the landscape pattern analysis of the current (in 2005) and planned (in 2020) green space system were, respectively, conducted by using FRAGSTATS 3.3 software. Considering the actual situation of the Nanchang urban area, a "one river and two banks, north and south twin cities" ecological network was constructed by using network analysis. Moreover, the ecological network was assessed by using corridor structure analysis, and the improvement of an ecological network on the urban landscape was quantitatively assessed through a comparison between the ecological network and green space system planning. The results indicated that: (1) compared to the green space system in 2005, the planned green space system in 2020 of the Nanchang urban area will decline in both districts (Changnan and Changbei districts). Meanwhile, an increase in patch density and a decrease in mean patch size of green space patches at the landscape level implies the fragmentation of the urban green space landscape. In other words, the planned green space system does not necessarily improve the present green space system; (2) the ecological network of two districts has high corridor density, while Changnan's ecological network has higher connectivity, but Changbei's ecological network is more viable from an economic point of view, since it has relatively higher cost efficiency; (3) decrease in patch density, Euclidean nearest neighbor distance, and an increase in mean patch size and connectivity implied that the ecological network could improve landscape connectivity greatly, as compared with the planned green space system. That is to say, the planned ecological network would reduce landscape fragmentation, and increase the shape complexity of green space patches and landscape connectivity. As a result, the quality of the urban ecological environment would be improved.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher’s Geometric Model?

PubMed Central

Blanquart, François; Bataillon, Thomas

2016-01-01

The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher’s model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher’s model was able to explain several statistical properties of the landscapes—including the mean and SD of selection and epistasis coefficients—it was often unable to explain the full structure of fitness landscapes. PMID:27052568

Site Plan & Site Section of Citrus Landscape (Showing Relationship ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Site Plan & Site Section of Citrus Landscape (Showing Relationship of Groves & Irrigation System to Grove Canal) - Arlington Heights Citrus Landscape, Southwestern portion of city of Riverside, Riverside, Riverside County, CA

Implementing landscape fragmentation as an indicator in the Swiss Monitoring System Of Sustainable Development (Monet).

PubMed

Jaeger, Jochen A G; Bertiller, René; Schwick, Christian; Müller, Kalin; Steinmeier, Charlotte; Ewald, Klaus C; Ghazoul, Jaboury

2008-09-01

There is an increasing need and interest in including indicators of landscape fragmentation in monitoring systems of sustainable landscape management. Landscape fragmentation due to transportation infrastructure and urban development threatens human and environmental well-being by noise and pollution from traffic, reducing the size and viability of wildlife populations, facilitating the spread of invasive species, and impairing the scenic and recreational qualities of the landscape. This paper provides the rationale, method, and data for including landscape fragmentation in monitoring systems, using as an example the Swiss Monitoring System of Sustainable Development (Monet). We defined and compared four levels of fragmentation analysis, or fragmentation geometries (FGs), each based on different fragmenting elements, e.g., only anthropogenic, or combinations of anthropogenic and natural elements. As each FG has specific strengths and weaknesses, the most appropriate choice of FG depends on the context and objectives of a study. We present data on the current degree of landscape fragmentation for the five ecoregions and 26 cantons in Switzerland for all four FGs. Our results show that the degree of landscape fragmentation as quantified by the effective mesh size method is strongly supported by the postulates and indicator selection criteria of Monet, and we identify the most suitable FG focusing on the land area below 2,100 m (e.g., excluding lakes) and allowing for an equitable comparison of fragmentation degrees among regions that differ in area covered by lakes and high mountains. For a more detailed analysis of landscape fragmentation in the context of environmental impact assessments and strategic environmental assessments, a combination of all four FGs may provide a more informative tool than any single FG.

Hypersomnia in Mood Disorders: a Rapidly Changing Landscape

PubMed Central

2015-01-01

Hypersomnia is commonly comorbid with depressive illness and is associated with treatment resistance, symptomatic relapse, and functional impairment. This review highlights recent changes in nosological classifications of hypersomnia. In addition, emergent findings regarding the neurobiologic underpinnings, assessment, and treatment of hypersomnia in mood disorders are reviewed, as well as the effects of hypersomnolence on illness course. Future strategies for research are proposed that may elucidate the causes of hypersomnia in mood disorders and lead to the development of improved diagnostic and therapeutic strategies. PMID:26258003

Mapping dominant runoff processes: an evaluation of different approaches using similarity measures and synthetic runoff simulations

NASA Astrophysics Data System (ADS)

Antonetti, Manuel; Buss, Rahel; Scherrer, Simon; Margreth, Michael; Zappa, Massimiliano

2016-07-01

The identification of landscapes with similar hydrological behaviour is useful for runoff and flood predictions in small ungauged catchments. An established method for landscape classification is based on the concept of dominant runoff process (DRP). The various DRP-mapping approaches differ with respect to the time and data required for mapping. Manual approaches based on expert knowledge are reliable but time-consuming, whereas automatic GIS-based approaches are easier to implement but rely on simplifications which restrict their application range. To what extent these simplifications are applicable in other catchments is unclear. More information is also needed on how the different complexities of automatic DRP-mapping approaches affect hydrological simulations. In this paper, three automatic approaches were used to map two catchments on the Swiss Plateau. The resulting maps were compared to reference maps obtained with manual mapping. Measures of agreement and association, a class comparison, and a deviation map were derived. The automatically derived DRP maps were used in synthetic runoff simulations with an adapted version of the PREVAH hydrological model, and simulation results compared with those from simulations using the reference maps. The DRP maps derived with the automatic approach with highest complexity and data requirement were the most similar to the reference maps, while those derived with simplified approaches without original soil information differed significantly in terms of both extent and distribution of the DRPs. The runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and their coarse resolution, but problems were also linked with the use of topography as a proxy for the storage capacity of soils. The perception of the intensity of the DRP classes also seems to vary among the different authors, and a standardised definition of DRPs is still lacking. Furthermore, we argue not to use expert knowledge for only model building and constraining, but also in the phase of landscape classification.

What happens when catchments get excited? Exploring the link between hydrologic states and responses across spatial scales

NASA Astrophysics Data System (ADS)

Wrede, S.; Lyon, S. W.; Martinez-Carreras, N.; Pfister, L.; Uhlenbrook, S.

2010-12-01

Investigating relationships between dynamic hydrologic states and associated hydrologic responses of catchments is essential for a better understanding and conceptualization of hydrologic functioning and classification across spatial scales. Nevertheless, the question of “What happens when catchments get excited?” still remains unanswered for most catchments to date. This is especially true with regard to underlying landscape controls and how their relative importance can shift given the state of the various storages in a catchment. To help answering this question, we combined hydrometric and tracer approaches with landscape analysis in 24 nested catchments in Luxembourg, Europe with contrasting bedrock geology ranging from 0.5 to 1091 km2. In our study we discerned two major hydrological states (dry and wet) for each basin according to slope changes in double mass curves of cumulated discharge and precipitation. For each of these states the long-term (i.e. interannual) response of catchment behavior was characterized using conventional runoff signatures, such as master recession curves and average lag time between rainfall and runoff response. We found significantly different hydrologic responses for different hydrologic states of the catchments. These are typified by faster flow recessions, but longer average lag times during wet states and slower flow recessions, but shorter lag times during dry states. Dominating landscape controls on hydrological responses differed during these distinct hydrologic states and were identified as variables related to geology (percentage of impervious bedrock area) and soils (average soil depth), indicating different controls on hydrologic processes under different hydrologic states. Clustering of biweekly conductivity and silica stream water concentration data of the catchments further illustrated the dominant control of the geology on stream chemistry and revealed similar patterns during different hydrologic states. Our findings demonstrate that hydrologic response and their associated controls are closely linked to the dynamic hydrologic states of the catchments and hence should not be neglected in catchment modeling and classification approaches.

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

Classification of leafy spurge with earth observing-1 advanced land imager

USGS Publications Warehouse

Stitt, S.; Root, R.; Brown, K.; Hager, S.; Mladinich, C.; Anderson, G.L.; Dudek, K.; Bustos, M.R.; Kokaly, R.

2006-01-01

Leafy spurge (Euphorbia esula L.) is an invasive exotic plant that can completely displace native plant communities. Automated techniques for monitoring the location and extent of leafy spurge, especially if available on a seasonal basis, could add greatly to the effectiveness of control measures. As part of a larger study including multiple sensors, this study examines the utility of mapping the location and extent of leafy spurge in Theodore Roosevelt National Park using Earth Observing-1 satellite Advanced Land Imager (ALI) scanner data. An unsupervised classification methodology was used producing accuracies in the range of 59% to 66%. Existing field studies, with their associated limitations, were used for identifying class membership and accuracy assessment. This sensor could be useful for broad landscape scale mapping of leafy spurge, from which control measures could be based.

Nitrous oxide emissions from agricultural landscapes: quantification tools, policy development, and opportunities for improved management

NASA Astrophysics Data System (ADS)

Tonitto, C.; Gurwick, N. P.

2012-12-01

Policy initiatives to reduce greenhouse gas emissions (GHG) have promoted the development of agricultural management protocols to increase SOC storage and reduce GHG emissions. We review approaches for quantifying N2O flux from agricultural landscapes. We summarize the temporal and spatial extent of observations across representative soil classes, climate zones, cropping systems, and management scenarios. We review applications of simulation and empirical modeling approaches and compare validation outcomes across modeling tools. Subsequently, we review current model application in agricultural management protocols. In particular, we compare approaches adapted for compliance with the California Global Warming Solutions Act, the Alberta Climate Change and Emissions Management Act, and by the American Carbon Registry. In the absence of regional data to drive model development, policies that require GHG quantification often use simple empirical models based on highly aggregated data of N2O flux as a function of applied N - Tier 1 models according to IPCC categorization. As participants in development of protocols that could be used in carbon offset markets, we observed that stakeholders outside of the biogeochemistry community favored outcomes from simulation modeling (Tier 3) rather than empirical modeling (Tier 2). In contrast, scientific advisors were more accepting of outcomes based on statistical approaches that rely on local observations, and their views sometimes swayed policy practitioners over the course of policy development. Both Tier 2 and Tier 3 approaches have been implemented in current policy development, and it is important that the strengths and limitations of both approaches, in the face of available data, be well-understood by those drafting and adopting policies and protocols. The reliability of all models is contingent on sufficient observations for model development and validation. Simulation models applied without site-calibration generally result in poor validation results, and this point particularly needs to be emphasized during policy development. For cases where sufficient calibration data are available, simulation models have demonstrated the ability to capture seasonal patterns of N2O flux. The reliability of statistical models likewise depends on data availability. Because soil moisture is a significant driver of N2O flux, the best outcomes occur when empirical models are applied to systems with relevant soil classification and climate. The structure of current carbon offset protocols is not well-aligned with a budgetary approach to GHG accounting. Current protocols credit field-scale reduction in N2O flux as a result of reduced fertilizer use. Protocols do not award farmers credit for reductions in CO2 emissions resulting from reduced production of synthetic N fertilizer. To achieve the greatest GHG emission reductions through reduced synthetic N production and reduced landscape N saturation requires a re-envisioning of the agricultural landscape to include cropping systems with legume and manure N sources. The current focus on on-farm GHG sources focuses credits on simple reductions of N applied in conventional systems rather than on developing cropping systems which promote higher recycling and retention of N.

Incorporating bioenergy into sustainable landscape designs

DOE PAGES

Dale, Virginia H.; Kline, Keith L.; Buford, Marilyn A.; ...

2015-12-30

In this paper, we describe an approach to landscape design that focuses on integrating bioenergy production with other components of environmental, social and economic systems. Landscape design as used here refers to a spatially explicit, collaborative plan for management of landscapes and supply chains. Landscape design can involve multiple scales and build on existing practices to reduce costs or enhance services. Appropriately applied to a specific context, landscape design can help people assess trade-offs when making choices about locations, types of feedstock, transport, refining and distribution of bioenergy products and services. The approach includes performance monitoring and reporting along themore » bioenergy supply chain. Examples of landscape design applied to bioenergy production systems are presented. Barriers to implementation of landscape design include high costs, the need to consider diverse land-management objectives from a wide array of stakeholders, up-front planning requirements, and the complexity and level of effort needed for successful stakeholder involvement. A landscape design process may be stymied by insufficient data or participation. An impetus for coordination is critical, and incentives may be required to engage landowners and the private sector. In conclusion, devising and implementing landscape designs for more sustainable outcomes require clear communication of environmental, social, and economic opportunities and concerns.« less

Incorporating bioenergy into sustainable landscape designs

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

Dale, Virginia H.; Kline, Keith L.; Buford, Marilyn A.

In this paper, we describe an approach to landscape design that focuses on integrating bioenergy production with other components of environmental, social and economic systems. Landscape design as used here refers to a spatially explicit, collaborative plan for management of landscapes and supply chains. Landscape design can involve multiple scales and build on existing practices to reduce costs or enhance services. Appropriately applied to a specific context, landscape design can help people assess trade-offs when making choices about locations, types of feedstock, transport, refining and distribution of bioenergy products and services. The approach includes performance monitoring and reporting along themore » bioenergy supply chain. Examples of landscape design applied to bioenergy production systems are presented. Barriers to implementation of landscape design include high costs, the need to consider diverse land-management objectives from a wide array of stakeholders, up-front planning requirements, and the complexity and level of effort needed for successful stakeholder involvement. A landscape design process may be stymied by insufficient data or participation. An impetus for coordination is critical, and incentives may be required to engage landowners and the private sector. In conclusion, devising and implementing landscape designs for more sustainable outcomes require clear communication of environmental, social, and economic opportunities and concerns.« less

[Landscape pattern and productivity characteristics of the oasis landscape ecosystem in Linze, Gansu, China].

PubMed

Liu, Xuelu; Ren, Jizhou; Zhang, Zihe

2002-08-01

Oasis landscape ecosystem is composed of 10 landscape elements, i.e., residence land, cultivated land, grassland, forestland, water area, water system, road, rocky desert, sandy desert, and gravel desert. Among the elements, cultivated land formed by human being production covers the most of the area, is most connected, and hence, is the matrix of the oasis landscape ecosystem. Residence land, grassland, forestland, water area, rocky desert, sandy desert, and gravel desert are patches. Residence land and forestland generate from human being production, while rocky desert, gravel desert and sandy desert are the remnant with the human being disturbance. Water region and grassland are the environmental resources remnant after natural disturbance. Water system and road are corridors. Cultivated land dominated in plant production should be utilized with more productive layers through developing animal production other than expanding used-area to maintain the landscape heterogeneity and diversity of the oasis landscape ecosystem. For remnant and environmental resource patches, it should be profitable in preserving and stabilizing landscape heterogeneity and diversity, exploiting the functions of water and soil conservation, tourism, windbreak and sand fixation. For landscape elements remnant only, it should be fruitful in avoiding degeneration of the landscape pattern to explore their preceding plant production with moderate plant production.

Organic Farming: Biodiversity Impacts Can Depend on Dispersal Characteristics and Landscape Context

PubMed Central

Feber, Ruth E.; Johnson, Paul J.; Bell, James R.; Chamberlain, Dan E.; Firbank, Leslie G.; Fuller, Robert J.; Manley, Will; Mathews, Fiona; Norton, Lisa R.; Townsend, Martin; Macdonald, David W.

2015-01-01

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower dispersal abilities generally. The evidence for interactions among landscape and farming system in their effects on spiders highlights the importance of developing strategies for managing farmland at the landscape-scale for most effective conservation of biodiversity. PMID:26309040

Organic Farming: Biodiversity Impacts Can Depend on Dispersal Characteristics and Landscape Context.

PubMed

Feber, Ruth E; Johnson, Paul J; Bell, James R; Chamberlain, Dan E; Firbank, Leslie G; Fuller, Robert J; Manley, Will; Mathews, Fiona; Norton, Lisa R; Townsend, Martin; Macdonald, David W

2015-01-01

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower dispersal abilities generally. The evidence for interactions among landscape and farming system in their effects on spiders highlights the importance of developing strategies for managing farmland at the landscape-scale for most effective conservation of biodiversity.

Wetland Hydrologic Connectivity to Downstream Waters: A Classification Approach and National Assessment

NASA Astrophysics Data System (ADS)

Leibowitz, S. G.; Hill, R. A.; Weber, M.; Jones, C., Jr.; Rains, M. C.; Creed, I. F.; Christensen, J.

2017-12-01

Connectivity has become a major focus of hydrological and ecological studies. Connectivity enhances fluxes among landscape features, whereas isolation eliminates or reduces such flows. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrologic connectivity is particularly significant, since chemical and biological flows are often associated with water movement. Wetlands have many important functions, and the degree to which they are hydrologically connected influences the effect they have on downstream waters. Wetlands with high connectivity can serve as sources (e.g., net exporters of dissolved organic carbon), while those with low connectivity can function as sinks (e.g., net importers of suspended sediments). We developed a system to classify wetlands based on type, magnitude, and frequency of hydrologic connectivity with downstream waters. We determined type (riparian, non-riparian surface, and non-riparian subsurface) by considering soil and bedrock permeability. For magnitude, we developed indices to represent travel time based on Manning's kinematic and Darcy's equations. We used soil drainage class as an indicator of frequency. We also included an index that assesses relative level of anthropogenic impacts to connectivity (e.g., presence of canals and ditches and impervious surfaces). The classification system was designed to be applied at various spatial scales using available data. The system was applied to 4.7 million wetlands in the conterminous United States, using the National Land Cover Dataset and other nationally available geospatial data, and the resulting maps were assessed for patterns in wetland connectivity. While wetland connectivity was dominated by fast, frequent riparian connections nationally, distributions of connectivity were characteristic for each region. Consideration of these distributions of connectivity should promote better management of watershed functions such as flood control and water quality improvement.

Landscape and zonal features of the formation of producing economy in Russia

NASA Astrophysics Data System (ADS)

Nizovtsev, Vyacheslav; Natalia, Erman

2016-04-01

Based on analysis of the extensive source base, including complex landscape, component, paleogeographic and archeological published and scientific materials as well as the connected analysis of published paleogeographical, paleolandscape and historical and geographic maps of the territory of Russia landscape and zonal features of the transition from appropriating economy to producing economy were determined. All the specifics of historical changes in the landscape use of the vast areas of Russia is caused by the variety of its landscape zones and the specifics of their constituent landscapes. Human economic activities as a factor of differentiation and development of landscapes became apparent almost in all landscape zones together with the emergence of the producing type of economy from the Aeneolithic-Bronze Age (Atlantic period) in the southern steppe regions (in the northern areas of the main centers of the producing economy) and from the Bronze Age in the forest areas. The emergence of the producing economy in the forest-steppe and steppe landscape zones on the territory of Russia is dated IV (Aeneolithic) - III (Early Bronze Age) millennium BC. It is from this period that on the European part of Russia and in Siberia the so-called Neolithic revolution begins. The use of copper and bronze axes helped to develop new areas for planting crops in the forest-steppe zone. In the forest-steppe zone swidden and lea tillage cultivation develops. In the steppe and forest-steppe Eurasia depending on the local landscape conditions two ways of producing economy with a predominance of cattle-breeding developed: nomadic cattle breeding and house cattle breeding with a significant influence of agriculture in the economy and long-term settlements. The steppe areas were completely dominated by the mobile nomadic herding, breeding cattle and small cattle. Along with the valley landscapes the interfluvial landscapes were also actively explored. Almost in all the steppe areas there was a cattle breeding economic and cultural type of producing economy with a simplified system of natural and anthropogenic and anthropogenic landscapes involving a maximum of 4-5 natural and economic systems. In the forest-steppe zone a significant part of the population was settled in the valley landscapes. The basis of the economy was pastoral and house cattle breeding with a predominance of beef cattle and pigs and hoe-mattock agriculture, which was only possible in the floodplain landscape complexes. In the areas of permanent settlements long grazing in one place led to the complete destruction of vegetation. The forced reduction of the agricultural land areas led to significant ecologic crisis. In the forest zone, along with hunters, fishermen and gatherers there appear the first tribes, who already engaged in the forest cattle breeding. First, they raised pigs and then small and beef cattle, while hunting and fishing were of subordinate nature. Pastures were situated mainly in floodplains and lakeside lowlands which had more open spaces. It is the extensive economy of that time that can be associated with the deforestation of flood plains of rivers and lakes and the emergence of meadows. There arises a natural-economic system with floodplain cattle-breeding (agricultural geo-systems of pasture type with floodplain meadows and woodlands), which existed for a long time. In all landscape zones the character of the relationship between men and the landscape was determined by the nature of producing activity, as well as natural features of "accommodating" landscape. The formation of nature use systems and settlement patterns strictly depend on the local landscape structure. In all earlier historical periods in similar landscape (zonal) conditions the settlers had the same type of economy, thus forming the same types of natural and economic systems and similar anthropogenically transformed landscapes. The dramatic change in the nature use occurs with the settlement in the forest and steppe zones of the Iron Age tribes, which had a complex cattle-breeding and agricultural economy. Irreversible changes captured many of the components, including soils and lithogenic basis, of the landscapes. In the morphological structure of the landscapes there appear new permanent stable elements of anthropogenic origin: residential and arable, many of which have survived to this day. The work is performed under the project of Russian Foundation for Basic Research № 14-05-00618

Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

PubMed

Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

2018-04-18

There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

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

Dale, Virginia H; Kline, Keith L; Kaffka, Stephen R

Landscape sustainability of agricultural systems considers effects of farm activities on social, economic, and ecosystem services at local and regional scales. Sustainable agriculture entails: defining sustainability, developing easily measured indicators of sustainability, moving toward integrated agricultural systems, and offering incentives or imposing regulations to affect farmer behavior. A landscape perspective is useful because landscape ecology provides theory and methods for dealing with spatial heterogeneity, scaling, integration, and complexity. To implement agricultural sustainability, we propose adopting a systems perspective, recognizing spatial heterogeneity, addressing the influences of context, and integrating landscape-design principles. Topics that need further attention at local and regional scalesmore » include (1) protocols for quantifying material and energy flows; (2) effects of management practices; (3) incentives for enhancing social, economic, and ecosystem services; (4) integrated landscape planning and management; (5) monitoring and assessment; (6) effects of societal demand; and (7) consistent and holistic policies for promoting agricultural sustainability.« less

The depth of the honeybee's backup sun-compass systems.

PubMed

Dovey, Katelyn M; Kemfort, Jordan R; Towne, William F

2013-06-01

Honeybees have at least three compass mechanisms: a magnetic compass; a celestial or sun compass, based on the daily rotation of the sun and sun-linked skylight patterns; and a backup celestial compass based on a memory of the sun's movements over time in relation to the landscape. The interactions of these compass systems have yet to be fully elucidated, but the celestial compass is primary in most contexts, the magnetic compass is a backup in certain contexts, and the bees' memory of the sun's course in relation to the landscape is a backup system for cloudy days. Here we ask whether bees have any further compass systems, for example a memory of the sun's movements over time in relation to the magnetic field. To test this, we challenged bees to locate the sun when their known celestial compass systems were unavailable, that is, under overcast skies in unfamiliar landscapes. We measured the bees' knowledge of the sun's location by observing their waggle dances, by which foragers indicate the directions toward food sources in relation to the sun's compass bearing. We found that bees have no celestial compass systems beyond those already known: under overcast skies in unfamiliar landscapes, bees attempt to use their landscape-based backup system to locate the sun, matching the landscapes or skylines at the test sites with those at their natal sites as best they can, even if the matches are poor and yield weak or inconsistent orientation.

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

Monitoring Freeze-Thaw States in the Pan-Arctic: Application of Microwave Remote Sensing to Monitoring Hydrologic and Ecological Processes

NASA Astrophysics Data System (ADS)

McDonald, K. C.; Kimball, J. S.

2004-12-01

The transition of the landscape between predominantly frozen and non-frozen conditions in seasonally frozen environments impacts climate, hydrological, ecological and biogeochemical processes profoundly. Satellite microwave remote sensing is uniquely capable of detecting and monitoring a range of related biophysical processes associated with the measurement of landscape freeze/thaw status. We present the development, physical basis, current techniques and selected hydrological applications of satellite-borne microwave remote sensing of landscape freeze/thaw states for the terrestrial cryosphere. Major landscape hydrological processes embracing the remotely-sensed freeze/thaw signal include timing and spatial dynamics of seasonal snowmelt and associated soil thaw, runoff generation and flooding, ice breakup in large rivers and lakes, and timing and length of vegetation growing seasons and associated productivity and trace gas exchange. Employing both active and passive microwave sensors, we apply a selection of temporal change classification algorithms to examine a variety of hydrologic processes. We investigate contemporaneous and retrospective applications of the QuikSCAT scatterometer, and the SSM/I and SMMR radiometers to this end. Results illustrate the strong correspondence between regional thawing, seasonal ice break up for rivers, and the springtime pulse in river flow. We present the physical principles of microwave sensitivity to landscape freeze/thaw state, recent progress in applying these principles toward satellite remote sensing of freeze/thaw processes over broad regions, and potential for future global monitoring of this significant phenomenon of the global cryosphere. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, and at the University of Montana, Missoula, under contract to the National Aeronautics and Space Administration.

Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA.

PubMed

Veselka, Walter; Anderson, James T; Kordek, Walter S

2010-05-01

Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that "biological integrity" is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland's position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Where can pixel counting area estimates meet user-defined accuracy requirements?

NASA Astrophysics Data System (ADS)

Waldner, François; Defourny, Pierre

2017-08-01

Pixel counting is probably the most popular way to estimate class areas from satellite-derived maps. It involves determining the number of pixels allocated to a specific thematic class and multiplying it by the pixel area. In the presence of asymmetric classification errors, the pixel counting estimator is biased. The overarching objective of this article is to define the applicability conditions of pixel counting so that the estimates are below a user-defined accuracy target. By reasoning in terms of landscape fragmentation and spatial resolution, the proposed framework decouples the resolution bias and the classifier bias from the overall classification bias. The consequence is that prior to any classification, part of the tolerated bias is already committed due to the choice of the spatial resolution of the imagery. How much classification bias is affordable depends on the joint interaction of spatial resolution and fragmentation. The method was implemented over South Africa for cropland mapping, demonstrating its operational applicability. Particular attention was paid to modeling a realistic sensor's spatial response by explicitly accounting for the effect of its point spread function. The diagnostic capabilities offered by this framework have multiple potential domains of application such as guiding users in their choice of imagery and providing guidelines for space agencies to elaborate the design specifications of future instruments.

Land cover mapping at sub-pixel scales

NASA Astrophysics Data System (ADS)

Makido, Yasuyo Kato

One of the biggest drawbacks of land cover mapping from remotely sensed images relates to spatial resolution, which determines the level of spatial details depicted in an image. Fine spatial resolution images from satellite sensors such as IKONOS and QuickBird are now available. However, these images are not suitable for large-area studies, since a single image is very small and therefore it is costly for large area studies. Much research has focused on attempting to extract land cover types at sub-pixel scale, and little research has been conducted concerning the spatial allocation of land cover types within a pixel. This study is devoted to the development of new algorithms for predicting land cover distribution using remote sensory imagery at sub-pixel level. The "pixel-swapping" optimization algorithm, which was proposed by Atkinson for predicting sub-pixel land cover distribution, is investigated in this study. Two limitations of this method, the arbitrary spatial range value and the arbitrary exponential model of spatial autocorrelation, are assessed. Various weighting functions, as alternatives to the exponential model, are evaluated in order to derive the optimum weighting function. Two different simulation models were employed to develop spatially autocorrelated binary class maps. In all tested models, Gaussian, Exponential, and IDW, the pixel swapping method improved classification accuracy compared with the initial random allocation of sub-pixels. However the results suggested that equal weight could be used to increase accuracy and sub-pixel spatial autocorrelation instead of using these more complex models of spatial structure. New algorithms for modeling the spatial distribution of multiple land cover classes at sub-pixel scales are developed and evaluated. Three methods are examined: sequential categorical swapping, simultaneous categorical swapping, and simulated annealing. These three methods are applied to classified Landsat ETM+ data that has been resampled to 210 meters. The result suggested that the simultaneous method can be considered as the optimum method in terms of accuracy performance and computation time. The case study employs remote sensing imagery at the following sites: tropical forests in Brazil and temperate multiple land mosaic in East China. Sub-areas for both sites are used to examine how the characteristics of the landscape affect the ability of the optimum technique. Three types of measurement: Moran's I, mean patch size (MPS), and patch size standard deviation (STDEV), are used to characterize the landscape. All results suggested that this technique could increase the classification accuracy more than traditional hard classification. The methods developed in this study can benefit researchers who employ coarse remote sensing imagery but are interested in detailed landscape information. In many cases, the satellite sensor that provides large spatial coverage has insufficient spatial detail to identify landscape patterns. Application of the super-resolution technique described in this dissertation could potentially solve this problem by providing detailed land cover predictions from the coarse resolution satellite sensor imagery.

Effective Management of Trans boundary Landscapes - Geospatial Applications

NASA Astrophysics Data System (ADS)

Kotru, R.; Rawal, R. S.; Mathur, P. K.; Chettri, N.; Chaudhari, S. A.; Uddin, K.; Murthy, M. S. R.; Singh, S.

2014-11-01

The Convention on Biological Diversity advocates the use of landscape and ecosystem approaches for managing biodiversity, in recognition of the need for increased regional cooperation. In this context, ICIMOD and regional partners have evolved Transboundary Landscape concept to address the issues of conservation and sustainable use of natural resources and systems (e.g., biodiversity, rangelands, farming systems, forests, wetlands, and watersheds, etc.). This concept defines the landscapes by ecosystems rather than political/administrative boundaries. The Hindu Kush Himalayan (HKH) region is extremely heterogeneous, with complex inter linkages of biomes and habitats as well as strong upstream-downstream linkages related to the provisioning of ecosystem services. Seven such transboundary landscapes, identified across west to east extent of HKH, have been considered for programmatic cooperation, include: Wakhan, Karakoram-Pamir, Kailash, Everest, Kangchenjunga, Brahmaputra-Salween, and Cherrapunjee- Chittagong. The approach is people centered and considers the cultural conservation as an essential first step towards resource conservation efforts in the region. Considering the multi-scale requirements of study, the geospatial technology has been effectively adopted towards: (i) understanding temporal changes in landscapes, (ii) long term ecological and social monitoring, (ii) identifying potential bio corridors, (iii) assessing landscape level vulnerability due to climatic and non-climatic drivers, and (iv) developing local plans on extractions of high value economic species supporting livelihoods, agroforestry system and ecotourism, etc. We present here our recent experiences across different landscapes on assessment of three decadal changes, vegetation type mapping, assessment of socio-ecological drivers, corridor assessment, ecosystem services assessment, models for optimal natural resource use systems and long term socio-ecological monitoring.

Synergies for Improving Oil Palm Production and Forest Conservation in Floodplain Landscapes

PubMed Central

Abram, Nicola K.; Xofis, Panteleimon; Tzanopoulos, Joseph; MacMillan, Douglas C.; Ancrenaz, Marc; Chung, Robin; Peter, Lucy; Ong, Robert; Lackman, Isabelle; Goossens, Benoit; Ambu, Laurentius; Knight, Andrew T.

2014-01-01

Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world’s tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates ($413/ha− yr–$637/ha− yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of $-299/ha− yr-$-65/ha− yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes. PMID:24887555

Synergies for improving oil palm production and forest conservation in floodplain landscapes.

PubMed

Abram, Nicola K; Xofis, Panteleimon; Tzanopoulos, Joseph; MacMillan, Douglas C; Ancrenaz, Marc; Chung, Robin; Peter, Lucy; Ong, Robert; Lackman, Isabelle; Goossens, Benoit; Ambu, Laurentius; Knight, Andrew T

2014-01-01

Lowland tropical forests are increasingly threatened with conversion to oil palm as global demand and high profit drives crop expansion throughout the world's tropical regions. Yet, landscapes are not homogeneous and regional constraints dictate land suitability for this crop. We conducted a regional study to investigate spatial and economic components of forest conversion to oil palm within a tropical floodplain in the Lower Kinabatangan, Sabah, Malaysian Borneo. The Kinabatangan ecosystem harbours significant biodiversity with globally threatened species but has suffered forest loss and fragmentation. We mapped the oil palm and forested landscapes (using object-based-image analysis, classification and regression tree analysis and on-screen digitising of high-resolution imagery) and undertook economic modelling. Within the study region (520,269 ha), 250,617 ha is cultivated with oil palm with 77% having high Net-Present-Value (NPV) estimates ($413/ha-yr-$637/ha-yr); but 20.5% is under-producing. In fact 6.3% (15,810 ha) of oil palm is commercially redundant (with negative NPV of $-299/ha-yr-$-65/ha-yr) due to palm mortality from flood inundation. These areas would have been important riparian or flooded forest types. Moreover, 30,173 ha of unprotected forest remain and despite its value for connectivity and biodiversity 64% is allocated for future oil palm. However, we estimate that at minimum 54% of these forests are unsuitable for this crop due to inundation events. If conversion to oil palm occurs, we predict a further 16,207 ha will become commercially redundant. This means that over 32,000 ha of forest within the floodplain would have been converted for little or no financial gain yet with significant cost to the ecosystem. Our findings have globally relevant implications for similar floodplain landscapes undergoing forest transformation to agriculture such as oil palm. Understanding landscape level constraints to this crop, and transferring these into policy and practice, may provide conservation and economic opportunities within these seemingly high opportunity cost landscapes.

The hills are alive: Earth surface dynamics in the University of Arizona Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

DeLong, S.; Troch, P. A.; Barron-Gafford, G. A.; Huxman, T. E.; Pelletier, J. D.; Dontsova, K.; Niu, G.; Chorover, J.; Zeng, X.

2012-12-01

To meet the challenge of predicting landscape-scale changes in Earth system behavior, the University of Arizona has designed and constructed a new large-scale and community-oriented scientific facility - the Landscape Evolution Observatory (LEO). The primary scientific objectives are to quantify interactions among hydrologic partitioning, geochemical weathering, ecology, microbiology, atmospheric processes, and geomorphic change associated with incipient hillslope development. LEO consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1 meter of basaltic tephra ground to homogenous loamy sand and contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. Each ~1000 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation), to facilitate better quantification of evapotraspiration. Each landscape has an engineered rain system that allows application of precipitation at rates between3 and 45 mm/hr. These landscapes are being studied in replicate as "bare soil" for an initial period of several years. After this initial phase, heat- and drought-tolerant vascular plant communities will be introduced. Introduction of vascular plants is expected to change how water, carbon, and energy cycle through the landscapes, with potentially dramatic effects on co-evolution of the physical and biological systems. LEO also provides a physical comparison to computer models that are designed to predict interactions among hydrological, geochemical, atmospheric, ecological and geomorphic processes in changing climates. These computer models will be improved by comparing their predictions to physical measurements made in LEO. The main focus of our iterative modeling and measurement discovery cycle is to use rapid data assimilation to facilitate validation of newly coupled open-source Earth systems models. LEO will be a community resource for Earth system science research, education, and outreach. The LEO project operational philosophy includes 1) open and real-time availability of sensor network data, 2) a framework for community collaboration and facility access that includes integration of new or comparative measurement capabilities into existing facility cyberinfrastructure, 3) community-guided science planning and 4) development of novel education and outreach programs.Artistic rendering of the University of Arizona Landscape Evolution Observatory

Influence of landscape structure, topography, and forest type on spatial variation in historical fire regimes, central Oregon, USA

USGS Publications Warehouse

Merschel, Andrew; Heyerdahl, Emily K.; Spies, Thomas A; Loehman, Rachel A.

2018-01-01

Context In the interior Northwest, debate over restoring mixed-conifer forests after a century of fire exclusion is hampered by poor understanding of the pattern and causes of spatial variation in historical fire regimes. Objectives To identify the roles of topography, landscape structure, and forest type in driving spatial variation in historical fire regimes in mixed-conifer forests of central Oregon. Methods We used tree rings to reconstruct multicentury fire and forest histories at 105 plots over 10,393 ha. We classified fire regimes into four types and assessed whether they varied with topography, the location of fuel-limited pumice basins that inhibit fire spread, and an updated classification of forest type. Results We identified four fire-regime types and six forest types. Although surface fires were frequent and often extensive, severe fires were rare in all four types. Fire regimes varied with some aspects of topography (elevation), but not others (slope or aspect) and with the distribution of pumice basins. Fire regimes did not strictly co-vary with mixed-conifer forest types. Conclusions Our work reveals the persistent influence of landscape structure on spatial variation in historical fire regimes and can help inform discussions about appropriate restoration of fire-excluded forests in the interior Northwest. Where the goal is to restore historical fire regimes at landscape scales, managers may want to consider the influence of topoedaphic and vegetation patch types that could affect fire spread and ignition frequency.

Remote sensing of physiographic soil units of Bennett County, South Dakota

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Gropper, J. L.; Westin, F. C.

1973-01-01

A study was conducted in Bennett County, South Dakota, to establish a rangeland test site for evaluating the usefulness of ERTS data for mapping soil resources in rangeland areas. Photographic imagery obtained in October, 1970, was analyzed to determine which type of imagery is best for mapping drainage and land use patterns. Imagery of scales ranging from 1:1,000,000 to 1.20,000 was used to delineate soil-vegetative physiographic units. The photo characteristics used to define physiographic units were texture, drainage pattern, tone pattern, land use pattern and tone. These units will be used as test data for evaluating ERTS data. The physiographic units were categorized into a land classification system. The various categories which were delineated at the different scales of imagery were designed to be useful for different levels of land use planning. The land systems are adequate only for planning of large areas for general uses. The lowest category separated was the facet. The facets have a definite soil composition and represent different soil landscapes. These units are thought to be useful for providing natural resource information needed for local planning.

Ichthyoplankton abundance and variance in a large river system concerns for long-term monitoring

USGS Publications Warehouse

Holland-Bartels, Leslie E.; Dewey, Michael R.; Zigler, Steven J.

1995-01-01

System-wide spatial patterns of ichthyoplankton abundance and variability were assessed in the upper Mississippi and lower Illinois rivers to address the experimental design and statistical confidence in density estimates. Ichthyoplankton was sampled from June to August 1989 in primary milieus (vegetated and non-vegated backwaters and impounded areas, main channels and main channel borders) in three navigation pools (8, 13 and 26) of the upper Mississippi River and in a downstream reach of the Illinois River. Ichthyoplankton densities varied among stations of similar aquatic landscapes (milieus) more than among subsamples within a station. An analysis of sampling effort indicated that the collection of single samples at many stations in a given milieu type is statistically and economically preferable to the collection of multiple subsamples at fewer stations. Cluster analyses also revealed that stations only generally grouped by their preassigned milieu types. Pilot studies such as this can define station groupings and sources of variation beyond an a priori habitat classification. Thus the minimum intensity of sampling required to achieve a desired statistical confidence can be identified before implementing monitoring efforts.

Characterizing fish community diversity across Virginia landscapes: Prerequisite for conservation

USGS Publications Warehouse

Angermeier, P.L.; Winston, M.R.

1999-01-01

The number of community types occurring within landscapes is an important, but often unprotected, component of biological diversity. Generally applicable protocols for characterizing community diversity need to be developed to facilitate conservation. We used several multivariate techniques to analyze geographic variation in the composition of fish communities in Virginia streams. We examined relationships between community composition and six landscape variables: drainage basin, physiography, stream order, elevation, channel slope, and map coordinates. We compared patterns at two scales (statewide and subdrainage-specific) to assess sensitivity of community classification to spatial scale. We also compared patterns based on characterizing communities by species composition vs. ecological composition. All landscape variables explained significant proportions of the variance in community composition. Statewide, they explained 32% of the variance in species composition and 48% of the variance in ecological composition. Typical communities in each drainage or physiography were statistically distinctive. Communities in different combinations of drainage, physiography, and stream size were even more distinctive, but composition was strongly spatially autocorrelated. Ecological similarity and species similarity of community pairs were strongly related, but replacement by ecologically similar species was common among drainage-physiography combinations. Landscape variables explained significant proportions of variance in community composition within selected subdrainages, but proportions were less than at the statewide scale, and the explanatory power of individual variables varied considerably among subdrainages. Community variation within subdrainages appeared to be much more closely related to environmental variation than to replacement among ecologically similar species. Our results suggest that taxonomic and ecological characterizations of community composition are complementary; both are useful in a conservation context. Landscape features such as drainage, physiography, and water body size generally may provide a basis for assessing aquatic community diversity, especially in regions where the biota is poorly known. Systematic conservation of community types would be a major advance relative to most current conservation programs, which typically focus narrowly on populations of imperiled species. More effective conservation of aquatic biodiversity will require new approaches that recognize the value of both species and assemblages, and that emphasize protection of key landscape-scale processes.

The influence of anthropogenic landscape changes on weather in south Florida

USGS Publications Warehouse

Pielke, R.A.; Walko, R.L.; Steyaert, L.T.; Vidale, P.L.; Liston, G.E.; Lyons, W.A.; Chase, T.N.

1999-01-01

Using identical observed meteorology for lateral boundary conditions, the Regional Atmospheric Modeling System was integrated for July-August 1973 for south Florida. Three experiments were performed-one using the observed 1973 landscape, another the 1993 landscape, and the third the 1900 landscape, when the region was close to its natural state. Over the 2-month period, there was a 9% decrease in rainfall averaged over south Florida with the 1973 landscape and an 11% decrease with the 1993 landscape, as compared with the model results when the 1900 landscape is used. The limited available observations of trends in summer rainfall over this region are consistent with these trends.

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Split-step eigenvector-following technique for exploring enthalpy landscapes at absolute zero.

PubMed

Mauro, John C; Loucks, Roger J; Balakrishnan, Jitendra

2006-03-16

The mapping of enthalpy landscapes is complicated by the coupling of particle position and volume coordinates. To address this issue, we have developed a new split-step eigenvector-following technique for locating minima and transition points in an enthalpy landscape at absolute zero. Each iteration is split into two steps in order to independently vary system volume and relative atomic coordinates. A separate Lagrange multiplier is used for each eigendirection in order to provide maximum flexibility in determining step sizes. This technique will be useful for mapping the enthalpy landscapes of bulk systems such as supercooled liquids and glasses.

Ecologically-Relevant Maps of Landforms and Physiographic Diversity for Climate Adaptation Planning

PubMed Central

Theobald, David M.; Harrison-Atlas, Dylan; Monahan, William B.; Albano, Christine M.

2015-01-01

Key to understanding the implications of climate and land use change on biodiversity and natural resources is to incorporate the physiographic platform on which changes in ecological systems unfold. Here, we advance a detailed classification and high-resolution map of physiography, built by combining landforms and lithology (soil parent material) at multiple spatial scales. We used only relatively static abiotic variables (i.e., excluded climatic and biotic factors) to prevent confounding current ecological patterns and processes with enduring landscape features, and to make the physiographic classification more interpretable for climate adaptation planning. We generated novel spatial databases for 15 landform and 269 physiographic types across the conterminous United States of America. We examined their potential use by natural resource managers by placing them within a contemporary climate change adaptation framework, and found our physiographic databases could play key roles in four of seven general adaptation strategies. We also calculated correlations with common empirical measures of biodiversity to examine the degree to which the physiographic setting explains various aspects of current biodiversity patterns. Additionally, we evaluated the relationship between landform diversity and measures of climate change to explore how changes may unfold across a geophysical template. We found landform types are particularly sensitive to spatial scale, and so we recommend using high-resolution datasets when possible, as well as generating metrics using multiple neighborhood sizes to both minimize and characterize potential unknown biases. We illustrate how our work can inform current strategies for climate change adaptation. The analytical framework and classification of landforms and parent material are easily extendable to other geographies and may be used to promote climate change adaptation in other settings. PMID:26641818

Planetary Landscape Geography

NASA Astrophysics Data System (ADS)

Hargitai, H.

INTRODUCTION Landscape is one of the most often used category in physical ge- ography. The term "landshap" was introduced by Dutch painters in the 15-16th cen- tury. [1] The elements that build up a landscape (or environment) on Earth consists of natural (biogenic and abiogenic - lithologic, atmospheric, hydrologic) and artificial (antropogenic) factors. Landscape is a complex system of these different elements. The same lithology makes different landscapes under different climatic conditions. If the same conditions are present, the same landscape type will appear. Landscapes build up a hierarchic system and cover the whole surface. On Earth, landscapes can be classified and qualified according to their characteristics: relief forms (morphology), and its potential economic value. Aesthetic and subjective parameters can also be considered. Using the data from landers and data from orbiters we can now classify planetary landscapes (these can be used as geologic mapping units as well). By looking at a unknown landscape, we can determine the processes that created it and its development history. This was the case in the Pathfinder/Sojourner panoramas. [2]. DISCUSSION Planetary landscape evolution. We can draw a raw landscape develop- ment history by adding the different landscape building elements to each other. This has a strong connection with the planet's thermal evolution (age of the planet or the present surface materials) and with orbital parameters (distance from the central star, orbit excentricity etc). This way we can build a complex system in which we use differ- ent evolutional stages of lithologic, atmospheric, hydrologic and biogenic conditions which determine the given - Solar System or exoplanetary - landscape. Landscape elements. "Simple" landscapes can be found on asteroids: no linear horizon is present (not differentiated body, only impact structures), no atmosphere (therefore no atmospheric scattering - black sky as part of the landscape) and no hydrosphere (no erosion). Adding new elements (differentiated body: horizon, atmosphere: blue/purple etc sky as visually important elements; complex lithology (mountains of tectonic ori- gin); atmosphere (which can alter temperature) and hydrosphere (erosion, rivers, de- position) a more complex landscape will appear. As a first step, by making a "landscape model", we can input general parameters of atmosphere, lithosphere, hydrosphere, biosphere, the distance from the Sun, orbital parameters, last resurfacing date, age of the planet and the model will output the pos- 1 sible landscape elements in the planet. This can be refined by inputing the actual pa- rameters (place on planet, climate region etc.) from which the actual landscape can be the result. The landscape altering processes are: exogenic (impact), mass movement, endogenic (volcanism, thermal conditions), weathering, aeolic, fluvial, glacial, biogenic, antro- pogenic processes. Comparing planets and moons, all of these processes work on Earth, only half of them works on Mars and Venus, and even fewer on Mercury and Moon [3], where most of the surface is an "post-impact" landscape. A Planetary view. Science-fiction writers often describe planets with one characteris- tic: "desert planet", "ocean planet", "forest planet". Generally, planetary flyby missions verify these images (Europa - ice plain planet or Io - volcano world), but a orbiter mis- sion makes clear than in any planet, several significantly different landcape units are present, but from planet to planet, the average climatic and lithologic conditions do change and characterize the given planet. LANDSCAPE RESOURCES, LANDSCAPE "HOT SPOTS" Landscape hot spots has "high values" in the factors listed below. Physical landscape values. Small object not detectable from orbiters: individual rocks or the local physical characteristics of the upper layer of the regolith, the sediment or bedrock characteristics along with relief forms will be the important factors of the landscape. Unique or common landscape forms: Depending on the given planet, one feature can have special value (or can be of different scientific importance): on Io, a impact crater would be more important, than on the Moon, etc. Current processes: Naturally, "living" landscapes (with active volcanoes, geysers, dust devils or active weather processes) are more valuable than "dead" ones. Cultural landscape values. Human presence on a extraterrestrial body is of high impor- tance. Human landing sites with footprints or landing sites with spacecraft "debris" or scientific devices makes any - otherwise unimportant - landscape valuable for us. Even the proper names of surface features will change their physical value: for a Hungarian, for example, a crater named after a Hungarian scientist will have a special value and will attract more interest than other craters. These factors are comparable with our tourist value categories. Economical landscape values. As on Earth, it makes an area more valuable if it has economically usable and profitable raw materials: minerals, rocks (impactites and other materials formed in special conditions or a long time ago). Aesthetic landscape values. We, humans, consider this as an other important factor since the German painter A. Altdorfer in the 16th century has first chosen certain land- 2 scapes that he considered to be of artistic value even without human figures present in the landscape. Parts of aesthetic landscape values are not part of the surface or local environment but of the planet or planetary system: the color of lack of the atmosphere, clouds, the characteristics of the visible moons. The abiogenic surface elements of this category are for example sand dunes, relief forms with order in their shape or distri- bution, or extreme landforms: extensive smooth plains or deep canyons. "Human presence (or life) - friendliness" values. Conditions for longer human pres- ence will be one of the most important factors when we start building Lunar or Martian bases. Factors of this category are the presence of water, 24 h communication oppor- tunity with Earth, radio noise free sky, radiation, temperature etc conditions. Since the emergence of the discipline of astrobiology, potentially habitable niches - and espe- cially the so far undiscovered de facto inhabited niches - make very high value of a given landscape. CONCLUSION As we have closer touch with planetary surfaces other than our, and as human (and manned) exploration of the Solar System will again be in the agenda, in addition to physical geographic or geologic factors, new ones: economical, cultural, aesthetic and geofactors together will determine the value of a certain landscape in a given area. Its study will be more geographic than geologic. The above listed ele- ments can be important when chosing a base or landing site on any planetary body. The landscape values can be merged in a GIS system and this way we can more ea- sity determine not only landcape types but also the optimal landing sites for future missions. References [1] Mezõsi , G.: A földrajzi táj (geographic landscape), in: Általános ter- mészerföldrajz, Budapest, 1993. pp 807-818. [2] Baker, V. R.: Extraterrestrial Geo- morphology: An Introduction. Geomorphology 37 (2001) pp 175-178. [3] Jakucs, L.: A földrajzi burok kozmogén és endogén dinamikája (Endogenic and Cosmogenic Dy- namics of the Geospheres). JATEPress, 1997. 3

Cavitation transition in the energy landscape: Distinct tensile yielding behavior in strongly and weakly attractive systems.

PubMed

Altabet, Y Elia; Fenley, Andreia L; Stillinger, Frank H; Debenedetti, Pablo G

2018-03-21

Particles with cohesive interactions display a tensile instability in the energy landscape at the Sastry density ρ S . The signature of this tensile limit is a minimum in the landscape equation of state, the pressure-density relationship of inherent structures sampled along a liquid isotherm. Our previous work [Y. E. Altabet, F. H. Stillinger, and P. G. Debenedetti, J. Chem. Phys. 145, 211905 (2016)] revisited the phenomenology of Sastry behavior and found that the evolution of the landscape equation of state with system size for particles with interactions typical of molecular liquids indicates the presence of an athermal first-order phase transition between homogeneous and fractured inherent structures, the latter containing several large voids. Here, we study how this tensile limit manifests itself for different interparticle cohesive strengths and identify two distinct regimes. Particles with sufficiently strong cohesion display an athermal first-order phase transition, consistent with our prior characterization. Weak cohesion also displays a tensile instability. However, the landscape equation of state for this regime is independent of system size, suggesting the absence of a first-order phase transition. An analysis of the voids suggests that yielding in the energy landscape of weakly cohesive systems is associated with the emergence of a highly interconnected network of small voids. While strongly cohesive systems transition from exclusively homogeneous to exclusively fractured configurations at ρ S in the thermodynamic limit, this interconnected network develops gradually, starting at ρ S , even at infinite system size.

Systems biology: A tool for charting the antiviral landscape.

PubMed

Bowen, James R; Ferris, Martin T; Suthar, Mehul S

2016-06-15

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as "the antiviral landscape". Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape. Copyright © 2016 Elsevier B.V. All rights reserved.

Cavitation transition in the energy landscape: Distinct tensile yielding behavior in strongly and weakly attractive systems

NASA Astrophysics Data System (ADS)

Altabet, Y. Elia; Fenley, Andreia L.; Stillinger, Frank H.; Debenedetti, Pablo G.

2018-03-01

Particles with cohesive interactions display a tensile instability in the energy landscape at the Sastry density ρS. The signature of this tensile limit is a minimum in the landscape equation of state, the pressure-density relationship of inherent structures sampled along a liquid isotherm. Our previous work [Y. E. Altabet, F. H. Stillinger, and P. G. Debenedetti, J. Chem. Phys. 145, 211905 (2016)] revisited the phenomenology of Sastry behavior and found that the evolution of the landscape equation of state with system size for particles with interactions typical of molecular liquids indicates the presence of an athermal first-order phase transition between homogeneous and fractured inherent structures, the latter containing several large voids. Here, we study how this tensile limit manifests itself for different interparticle cohesive strengths and identify two distinct regimes. Particles with sufficiently strong cohesion display an athermal first-order phase transition, consistent with our prior characterization. Weak cohesion also displays a tensile instability. However, the landscape equation of state for this regime is independent of system size, suggesting the absence of a first-order phase transition. An analysis of the voids suggests that yielding in the energy landscape of weakly cohesive systems is associated with the emergence of a highly interconnected network of small voids. While strongly cohesive systems transition from exclusively homogeneous to exclusively fractured configurations at ρS in the thermodynamic limit, this interconnected network develops gradually, starting at ρS, even at infinite system size.

Ecological Land Classification: Applications to Identify the Productive Potential of Southern Forests

Treesearch

Dennis L. Mengel; D. Thompson Tew; [Editors

1991-01-01

Eighteen papers representing four categories-Regional Overviews; Classification System Development; Classification System Interpretation; Mapping/GIS Applications in Classification Systems-present the state of the art in forest-land classification and evaluation in the South. In addition, nine poster papers are presented.

Machine learning for the structure-energy-property landscapes of molecular crystals.

PubMed

Musil, Félix; De, Sandip; Yang, Jack; Campbell, Joshua E; Day, Graeme M; Ceriotti, Michele

2018-02-07

Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol -1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure-property relations in molecular crystal engineering.

Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

NASA Astrophysics Data System (ADS)

Hong, Liang

2013-10-01

The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

PubMed Central

Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

2013-01-01

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

Landscape-level variation in forest structure and biogeochemistry across a substrate age gradient in Hawaii.

PubMed

Vitousek, Peter; Asner, Gregory P; Chadwick, Oliver A; Hotchkiss, Sara

2009-11-01

We compared forest canopy heights and nitrogen concentrations in long-term research sites and in 2 x 2 km landscapes surrounding these sites along a substrate age gradient in the Hawaiian Islands. Both remote airborne and ground-based measurements were used to characterize processes that control landscape-level variation in canopy properties. We integrated a waveform light detection and ranging (LiDAR) system, a high-resolution imaging spectrometer, and a global positioning system/inertial measurement unit to provide highly resolved images of ground topography, canopy heights, and canopy nitrogen concentrations (1) within a circle 50 m in radius focused on a long-term study site in the center of each landscape; (2) for the entire 2 x 2 km landscape regardless of land cover; and (3) after stratification, for our target cover class, native-dominated vegetation on constructional geomorphic surfaces throughout each landscape. Remote measurements at all scales yielded the same overall patterns as did ground-based measurements in the long-term sites. The two younger landscapes supported taller trees than did older landscapes, while the two intermediate-aged landscapes had higher canopy nitrogen (N) concentrations than did either young or old landscapes. However, aircraft-based analyses detected substantial variability in canopy characteristics on the landscape level, even within the target cover class. Canopy heights were more heterogeneous on the older landscapes, with coefficients of variation increasing from 23-41% to 69-78% with increasing substrate age. This increasing heterogeneity was associated with a larger patch size of canopy turnover and with dominance of most secondary successional stands by the mat-forming fern Dicranopteris linearis in the older landscapes.

Re-wilding Europe's traditional agricultural landscapes: Values and the link between science and practice

Treesearch

Paul H. Gobster

2014-01-01

Landscape and Urban Planning encourages multiple perspectives and approaches to help understand landscapes as social-ecological systems, with the goal that by building a robust science of landscape we can provide sustainable solutions for guiding its change. But the link between science and practice, or more simply put, between knowledge and action, is not always clear...

Change in the forested and developed landscape of the Lake Tahoe basin, California and Nevada, USA, 1940-2002

USGS Publications Warehouse

Raumann, C.G.; Cablk, Mary E.

2008-01-01

The current ecological state of the Lake Tahoe basin has been shaped by significant landscape-altering human activity and management practices since the mid-1850s; first through widespread timber harvesting from the 1850s to 1920s followed by urban development from the 1950s to the present. Consequences of landscape change, both from development and forest management practices including fire suppression, have prompted rising levels of concern for the ecological integrity of the region. The impacts from these activities include decreased water quality, degraded biotic communities, and increased fire hazard. To establish an understanding of the Lake Tahoe basin's landscape change in the context of forest management and development we mapped, quantified, and described the spatial and temporal distribution and variability of historical changes in land use and land cover in the southern Lake Tahoe basin (279 km2) from 1940 to 2002. Our assessment relied on post-classification change detection of multi-temporal land-use/cover and impervious-surface-area data that were derived through manual interpretation, image processing, and GIS data integration for four dates of imagery: 1940, 1969, 1987, and 2002. The most significant land conversion during the 62-year study period was an increase in developed lands with a corresponding decrease in forests, wetlands, and shrublands. Forest stand densities increased throughout the 62-year study period, and modern thinning efforts resulted in localized stand density decreases in the latter part of the study period. Additionally forests were gained from succession, and towards the end of the study period extensive tree mortality occurred. The highest rates of change occurred between 1940 and 1969, corresponding with dramatic development, then rates declined through 2002 for all observed landscape changes except forest density decrease and tree mortality. Causes of landscape change included regional population growth, tourism demands, timber harvest for local use, fire suppression, bark beetle attack, and fuels reduction activities. Results from this study offer land managers within the Lake Tahoe basin and in similar regions a basis for making better informed land-use and management decisions to potentially minimize detrimental ecological impacts of landscape change. The perspective to be gained is based on quantitative retrospection of the effects of human-driven changes and the impacts of management action or inaction to the forested landscape. ?? 2008 Elsevier B.V. All rights reserved.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

Functional connectivity as a possible indicator of desertification in degraded grasslands

NASA Astrophysics Data System (ADS)

Vest, K. R.; Elmore, A. J.; Kaste, J. M.; Okin, G. S.

2011-12-01

Desertification of semi-arid grasslands impacts air quality, climate, biodiversity, and soil fertility. Desertification processes such as wind erosion lead to declining soil resources and sometimes local climate change. Desertification is irreversible; however, identifying when and where ecological changes are irreversible is problematic, requiring observations of a new ecological state, favoring the continued process of wind erosion and continued depletion of soil resources. Scientists hypothesize that an indicator of irreversibility in desertification might be "connected pathways". The connected pathway hypothesis requires that vegetation structure has changed from a grass to a shrub dominated system with increasing number and size of bare soil gaps. These bare soil gaps are functionally connected through the action of wind; therefore, functional connectivity of a landscape is related to the length and size of pathways through vegetation. This study used a combination of field measurements (total horizontal flux (Qtot) and vegetation structure) and landscape modeling to examine the difference in functional connectivity between grassland locations that were either degraded or relatively intact. At our field site, the degradation process was initiated by groundwater pumping, which adversely affects groundwater dependent grasses, providing a useful link to management seeking to limit the effects or extent of desertification. To analyze the functional connectivity of these locations in Owens Valley, we used circuit theory, a novel graph-based approach, which integrates all possible pathways to determine a "resistance distance" between any two points. Circuit theory uses current and resistance to represent movement of wind and the effect of vegetation and soil roughness on wind. Circuit theory was implemented using the open source software package, Circuitscape. To estimate landscape resistance, we performed a supervised classification on 1m aerial photographs. For each landscape class (shrub, grass, and soil), we applied a standardized resistance value which decreased downwind of vegetation. We validated the resistance layer by using Qtot data collected from 13 plots with BSNE catchers (i.e., plots with higher Qtot should be associated with higher connectivity). Next, we developed a focal region grid containing source and ground regions for current at these plots; these regions represent wind directions (N, S, E, W). We ran Circuitscape on data from different locations with similar vegetation structure but differing histories of groundwater withdrawal. From the model output, we found that degraded landscapes have greater connectivity than landscapes that are not degraded. We also found that locations with fewer larger and elongated bare soil gaps had greater connectivity than locations with numerous small bare soil gaps. Our results support the idea that functional connectivity is a possible indicator of desertification and that managing for reduced connectivity might limit the effects and extent of desertification.

Agro-hydrologic landscapes in the Upper Mississippi and Ohio River basins.

PubMed

Schilling, Keith E; Wolter, Calvin F; McLellan, Eileen

2015-03-01

A critical part of increasing conservation effectiveness is targeting the "right practice" to the "right place" where it can intercept pollutant flowpaths. Conceptually, these flowpaths can be inferred from soil and slope characteristics, and in this study, we developed an agro-hydrologic classification to identify N and P loss pathways and priority conservation practices in small watersheds in the U.S. Midwest. We developed a GIS framework to classify 11,010 small watersheds in the Upper Mississippi and Ohio River basins based on soil permeability and slope characteristics of agricultural cropland areas in each watershed. The amount of cropland in any given watershed varied from <10 to >60 %. Cropland areas were classified into five main categories, with slope classes of <2, 2-5, and >5 %, and soil drainage classes of poorly and well drained. Watersheds in the Upper Mississippi River basin (UMRB) were dominated by cropland areas in low slopes and poorly drained soils, whereas less-intensively cropped watersheds in Wisconsin and Minnesota (in the UMRB) and throughout the Ohio River basin were overwhelmingly well drained. Hydrologic differences in cropped systems indicate that a one-size-fits-all approach to conservation selection will not work. Consulting the classification scheme proposed herein may be an appropriate first-step in identifying those conservation practices that might be most appropriate for small watersheds in the basin.

Detection of early landscape evolution through controlled experimentation, data analysis, and numerical modeling at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Troch, Peter A.; Pangle, Luke; Niu, Guo-Yue; Dontsova, Katerina; Barron-Gafford, Greg; van Haren, Joost; Pavao-Zuckerman, Mitch

2014-05-01

The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Embedded solution and gas samplers allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers to study water movement at very high spatial resolutions. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. The rain systems are capable of creating long-term steady state conditions or running complex simulations. The precipitation water supply storage system is flexibly designed to facilitate addition of tracers at constant or time-varying rates for any of the three hillslopes. This presentation will discuss detection of early landscape evolution in terms of hydrological, geochemical and microbial processes through controlled experimentation, data analysis, and numerical modeling during the commissioning phase of the first hillslope at LEO.

Sub-pixel image classification for forest types in East Texas

NASA Astrophysics Data System (ADS)

Westbrook, Joey

Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional supervised classification, which allows a pixel to have only one label. The satellite image used was a Landsat 5 Thematic Mapper (TM) scene of the Stephen F. Austin Experimental Forest in Nacogdoches County, Texas and the four cover type classes are pine, hardwood, mixed forest and non-forest. Once classified, a multi-layer raster datasets was created that comprised four raster layers where each layer showed the percentage of that cover type within the pixel area. Percentage cover type maps were then produced and the accuracy of each was assessed using a fuzzy error matrix for the sub-pixel classifications, and the results were compared to the supervised classification in which a traditional error matrix was used. The overall accuracy of the sub-pixel classification using the aerial photo for both training and reference data had the highest (65% overall) out of the three sub-pixel classifications. This was understandable because the analyst can visually observe the cover types actually on the ground for training data and reference data, whereas using the FIA (Forest Inventory and Analysis) plot data, the analyst must assume that an entire pixel contains the exact percentage of a cover type found in a plot. An increase in accuracy was found after reclassifying each sub-pixel classification from nine classes with 10 percent interval each to five classes with 20 percent interval each. When compared to the supervised classification which has a satisfactory overall accuracy of 90%, none of the sub-pixel classification achieved the same level. However, since traditional per-pixel classifiers assign only one label to pixels throughout the landscape while sub-pixel classifications assign multiple labels to each pixel, the traditional 85% accuracy of acceptance for pixel-based classifications should not apply to sub-pixel classifications. More research is needed in order to define the level of accuracy that is deemed acceptable for sub-pixel classifications.

Introduction to landscape influences on stream habitats and biological assemblages

EPA Science Inventory

Viewing river systems within a landscape context is a relatively new and rapidly developing approach to river ecology. Although the linkages among landscapes and associated physicochemical and biological characteristics of rivers have long been recognized, the development of con...

Chorological classification approach for species and ecosystem conservation practice

NASA Astrophysics Data System (ADS)

Rogova, T. V.; Kozevnikova, M. V.; Prokhorov, V. E.; Timofeeva, N. O.

2018-01-01

The habitat type allocation approach based on the EUNIS Habitat Classification and the JUICE version 7 software is used for the conservation of species and ecosystem biodiversity. Using the vegetation plots of the Vegetation Database of Tatarstan, included in the EVA (European Vegetation Archive) and GIVD (Global Index of Vegetation-plots Databases) types of habitats of dry meadows and steppes are distinguished by differing compositions of the leading families composing their flora - Asteraceae, Fabaceae, Poaceae and Rosaceae. E12a - Semi-dry perennial calcareous grassland, and E12b - Perennial calcareous grassland and basic steppes were identified. The selected group of relevés that do not correspond to any of the EUNIS types can be considered specific for ecotone forest-steppe landscapes of the southeast of the Republic of Tatarstan. In all types of studied habitats, rare and protected plant species are noted, most of which are South-East-European-Asian species.

Processes on the emergent landscapes of biochemical reaction networks and heterogeneous cell population dynamics: differentiation in living matters

PubMed Central

Li, Fangting

2017-01-01

The notion of an attractor has been widely employed in thinking about the nonlinear dynamics of organisms and biological phenomena as systems and as processes. The notion of a landscape with valleys and mountains encoding multiple attractors, however, has a rigorous foundation only for closed, thermodynamically non-driven, chemical systems, such as a protein. Recent advances in the theory of nonlinear stochastic dynamical systems and its applications to mesoscopic reaction networks, one reaction at a time, have provided a new basis for a landscape of open, driven biochemical reaction systems under sustained chemostat. The theory is equally applicable not only to intracellular dynamics of biochemical regulatory networks within an individual cell but also to tissue dynamics of heterogeneous interacting cell populations. The landscape for an individual cell, applicable to a population of isogenic non-interacting cells under the same environmental conditions, is defined on the counting space of intracellular chemical compositions x = (x1,x2, … ,xN) in a cell, where xℓ is the concentration of the ℓth biochemical species. Equivalently, for heterogeneous cell population dynamics xℓ is the number density of cells of the ℓth cell type. One of the insights derived from the landscape perspective is that the life history of an individual organism, which occurs on the hillsides of a landscape, is nearly deterministic and ‘programmed’, while population-wise an asynchronous non-equilibrium steady state resides mostly in the lowlands of the landscape. We argue that a dynamic ‘blue-sky’ bifurcation, as a representation of Waddington's landscape, is a more robust mechanism for a cell fate decision and subsequent differentiation than the widely pictured pitch-fork bifurcation. We revisit, in terms of the chemostatic driving forces upon active, living matter, the notions of near-equilibrium thermodynamic branches versus far-from-equilibrium states. The emergent landscape perspective permits a quantitative discussion of a wide range of biological phenomena as nonlinear, stochastic dynamics. PMID:28490602

Pathohistological classification systems in gastric cancer: Diagnostic relevance and prognostic value

PubMed Central

Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

2014-01-01

Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer. PMID:24914328

Estimated historical distribution of grassland communities of the Southern Great Plains

USGS Publications Warehouse

Reese, Gordon C.; Manier, Daniel J.; Carr, Natasha B.; Callan, Ramana; Leinwand, Ian I.F.; Assal, Timothy J.; Burris, Lucy; Ignizio, Drew A.

2016-12-07

The purpose of this project was to map the estimated distribution of grassland communities of the Southern Great Plains prior to Euro-American settlement. The Southern Great Plains Rapid Ecoregional Assessment (REA), under the direction of the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative, includes four ecoregions: the High Plains, Central Great Plains, Southwestern Tablelands, and the Nebraska Sand Hills. The REA advisors and stakeholders determined that the mapping accuracy of available national land-cover maps was insufficient in many areas to adequately address management questions for the REA. Based on the recommendation of the REA stakeholders, we estimated the potential historical distribution of 10 grassland communities within the Southern Great Plains project area using data on soils, climate, and vegetation from the Natural Resources Conservation Service (NRCS) including the Soil Survey Geographic Database (SSURGO) and Ecological Site Information System (ESIS). The dominant grassland communities of the Southern Great Plains addressed as conservation elements for the REA area are shortgrass, mixed-grass, and sand prairies. We also mapped tall-grass, mid-grass, northwest mixed-grass, and cool season bunchgrass prairies, saline and foothill grasslands, and semi-desert grassland and steppe. Grassland communities were primarily defined using the annual productivity of dominant species in the ESIS data. The historical grassland community classification was linked to the SSURGO data using vegetation types associated with the predominant component of mapped soil units as defined in the ESIS data. We augmented NRCS data with Landscape Fire and Resource Management Planning Tools (LANDFIRE) Biophysical Settings classifications 1) where NRCS data were unavailable and 2) where fifth-level watersheds intersected the boundary of the High Plains ecoregion in Wyoming. Spatial data representing the estimated historical distribution of grassland communities of the Southern Great Plains are provided as a 30 x 30-meter gridded surface (raster dataset). This information will help to address the priority management questions for grassland communities for the Southern Great Plains REA and can be used to inform other regional-level land management decisions.

DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING

EPA Science Inventory

The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...

Potential and flux field landscape theory. I. Global stability and dynamics of spatially dependent non-equilibrium systems.

PubMed

Wu, Wei; Wang, Jin

2013-09-28

We established a potential and flux field landscape theory to quantify the global stability and dynamics of general spatially dependent non-equilibrium deterministic and stochastic systems. We extended our potential and flux landscape theory for spatially independent non-equilibrium stochastic systems described by Fokker-Planck equations to spatially dependent stochastic systems governed by general functional Fokker-Planck equations as well as functional Kramers-Moyal equations derived from master equations. Our general theory is applied to reaction-diffusion systems. For equilibrium spatially dependent systems with detailed balance, the potential field landscape alone, defined in terms of the steady state probability distribution functional, determines the global stability and dynamics of the system. The global stability of the system is closely related to the topography of the potential field landscape in terms of the basins of attraction and barrier heights in the field configuration state space. The effective driving force of the system is generated by the functional gradient of the potential field alone. For non-equilibrium spatially dependent systems, the curl probability flux field is indispensable in breaking detailed balance and creating non-equilibrium condition for the system. A complete characterization of the non-equilibrium dynamics of the spatially dependent system requires both the potential field and the curl probability flux field. While the non-equilibrium potential field landscape attracts the system down along the functional gradient similar to an electron moving in an electric field, the non-equilibrium flux field drives the system in a curly way similar to an electron moving in a magnetic field. In the small fluctuation limit, the intrinsic potential field as the small fluctuation limit of the potential field for spatially dependent non-equilibrium systems, which is closely related to the steady state probability distribution functional, is found to be a Lyapunov functional of the deterministic spatially dependent system. Therefore, the intrinsic potential landscape can characterize the global stability of the deterministic system. The relative entropy functional of the stochastic spatially dependent non-equilibrium system is found to be the Lyapunov functional of the stochastic dynamics of the system. Therefore, the relative entropy functional quantifies the global stability of the stochastic system with finite fluctuations. Our theory offers an alternative general approach to other field-theoretic techniques, to study the global stability and dynamics of spatially dependent non-equilibrium field systems. It can be applied to many physical, chemical, and biological spatially dependent non-equilibrium systems.

Landscape heterogeneity shapes predation in a newly restored predator-prey system.

PubMed

Kauffman, Matthew J; Varley, Nathan; Smith, Douglas W; Stahler, Daniel R; MacNulty, Daniel R; Boyce, Mark S

2007-08-01

Because some native ungulates have lived without top predators for generations, it has been uncertain whether runaway predation would occur when predators are newly restored to these systems. We show that landscape features and vegetation, which influence predator detection and capture of prey, shape large-scale patterns of predation in a newly restored predator-prey system. We analysed the spatial distribution of wolf (Canis lupus) predation on elk (Cervus elaphus) on the Northern Range of Yellowstone National Park over 10 consecutive winters. The influence of wolf distribution on kill sites diminished over the course of this study, a result that was likely caused by territorial constraints on wolf distribution. In contrast, landscape factors strongly influenced kill sites, creating distinct hunting grounds and prey refugia. Elk in this newly restored predator-prey system should be able to mediate their risk of predation by movement and habitat selection across a heterogeneous risk landscape.

Landscape heterogeneity shapes predation in a newly restored predator-prey system

USGS Publications Warehouse

Kauffman, M.J.; Varley, N.; Smith, D.W.; Stahler, D.R.; MacNulty, D.R.; Boyce, M.S.

2007-01-01

Because some native ungulates have lived without top predators for generations, it has been uncertain whether runaway predation would occur when predators are newly restored to these systems. We show that landscape features and vegetation, which influence predator detection and capture of prey, shape large-scale patterns of predation in a newly restored predator-prey system. We analysed the spatial distribution of wolf (Canis lupus) predation on elk (Cervus elaphus) on the Northern Range of Yellowstone National Park over 10 consecutive winters. The influence of wolf distribution on kill sites diminished over the course of this study, a result that was likely caused by territorial constraints on wolf distribution. In contrast, landscape factors strongly influenced kill sites, creating distinct hunting grounds and prey refugia. Elk in this newly restored predator-prey system should be able to mediate their risk of predation by movement and habitat selection across a heterogeneous risk landscape. ?? 2007 Blackwell Publishing Ltd/CNRS.