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Using the Geographical Information System and Remote Sensing Techniques for Soil Erosion Assessment
Landscape Architecture Ankara, Turkey
Pol. J. Environ. Stud. 2010;19(5):881–886
universal soil loss equation
The objective of this study is to establish a geographical information system method for spatial assessment of soil erosion based on the universal soil loss equation (USLE), and to evaluate the utility of GIS with regard to soil erosion mapping. The study area, Goynuk, covers 1,437 square kilometers and is located in the southeastern part of Bolu, Turkey. In this study, USLE factors including rainfall erosivity (R-factor), soil erodibility (K-factor), slope and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (Pfactor) were studied and reviewed. Each factor, which consists of a set of logically related geographic features and attributes, was used as an input for analysis. A land use map of the study area was generated from (Landsat TM 2000) satellite imagery. A digital elevation model (DEM) interpolated from elevation contours was used to generate the slope and LS-factor. Spatial vegetative cover, extracted from Landsat TM imagery, was used to determine the spatial C-factor and P-factor, values of which are based on experimental results from the literature. USLE model calculation applied to the resultant polygonal layer gave values of soil loss in tons/ha/year. These are then ranked into three classes as low, moderate, and high. The study indicated that highly eroded areas are bare lands and steep conditions, whereas less eroded areas are low slope classes. As a conclusion the study confirms that the use of GIS and remotely sensed data can greatly enhance spatial modeling for soil erosion.
Rural Fire Risk Assessment in GIS Environment Using Fuzzy Logic and the AHP Approaches
Analysis of Rainfall Factors and Soil Erosion in Different Soil and Water Conservation Measures in the Karst Plateau-Mountain
Assessment of Soil Erosion Rates Using Revised Universal Soil Loss Equation (RUSLE) and GIS in Bačka (Serbia)
Monitoring Soil Salinity Changes, Comparison of Different Maps and Indices Extracted from Landsat Satellite Images (Case Study: Atabieh, Khuzestan)
Estimation of Carrying Capacity of Livestock and Poultry Based on RS and GIS: a Case in Minhou County, Fuzhou City
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