Large scale soil erosion modeling for a mountainous watershed
Soil erosion control requires a quantitative evaluation of potential soil erosion on a specific site. The Revised Universal Soil Loss Equation (RUSLE), Remote Sensing (RS), and Geographic Information System (GIS) were used to model soil erosion intensity for soil conservation and vegetation rehabili...
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| Veröffentlicht in: | Geo-Environment and Landscape Evolution II: Evolution, Monitoring, Simulation, Management and Remediation of the Geological Environment and Landscape Monitoring, Simulation, Management and Remediation of the Geological Environment and Landscape, 2006, Vol.1, p.55-67 |
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| container_title | Geo-Environment and Landscape Evolution II: Evolution, Monitoring, Simulation, Management and Remediation of the Geological Environment and Landscape |
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| creator | Zhou, P Nieminen, J Tokola, T Luukkanen, O Oliver, T |
| description | Soil erosion control requires a quantitative evaluation of potential soil erosion on a specific site. The Revised Universal Soil Loss Equation (RUSLE), Remote Sensing (RS), and Geographic Information System (GIS) were used to model soil erosion intensity for soil conservation and vegetation rehabilitation in an Upper Min River (UMR) watershed, which is in the Upper Yangtze River basin. Data used in this study to generate the soil loss were Landsat Enhanced Thematic Mapper (ETM) images, Digitized Elevation Model (DEM), soil erodibility, rainfall erosivity, and inventory data. The non-parametric k-nearest neighbor (k-NN) method was used to produce the cover management map by integrating the ETM images and vegetation coverage data measured in the 625 sample plots. The root mean square errors and significance of biases at pixel level were evaluated in order to find optimal parameters. Four raster maps have been produced for the soil erodibility, rainfall erosivity, slope length and steepness, and cover management factor, and the map with different soil loss risks has been produced for soil erosion potential. The result can be beneficial to the erosion control and ecological restoration in the degraded mountainous watershed. |
| doi_str_mv | 10.2495/GEO060071 |
| format | Article |
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The Revised Universal Soil Loss Equation (RUSLE), Remote Sensing (RS), and Geographic Information System (GIS) were used to model soil erosion intensity for soil conservation and vegetation rehabilitation in an Upper Min River (UMR) watershed, which is in the Upper Yangtze River basin. Data used in this study to generate the soil loss were Landsat Enhanced Thematic Mapper (ETM) images, Digitized Elevation Model (DEM), soil erodibility, rainfall erosivity, and inventory data. The non-parametric k-nearest neighbor (k-NN) method was used to produce the cover management map by integrating the ETM images and vegetation coverage data measured in the 625 sample plots. The root mean square errors and significance of biases at pixel level were evaluated in order to find optimal parameters. Four raster maps have been produced for the soil erodibility, rainfall erosivity, slope length and steepness, and cover management factor, and the map with different soil loss risks has been produced for soil erosion potential. The result can be beneficial to the erosion control and ecological restoration in the degraded mountainous watershed.</description><identifier>ISSN: 1746-448X</identifier><identifier>ISBN: 184564168X</identifier><identifier>ISBN: 9781845641689</identifier><identifier>EISSN: 1743-3541</identifier><identifier>DOI: 10.2495/GEO060071</identifier><language>eng</language><publisher>Southampton: W I T Press</publisher><subject>Digital Elevation Models ; Digitization ; Ecological effects ; Environmental restoration ; Erosion control ; Erosion mechanisms ; Geographic information systems ; Image enhancement ; Landsat ; Landsat satellites ; Mountains ; Order parameters ; Quantitative analysis ; Rainfall ; Rehabilitation ; Remote sensing ; Restoration ; River basins ; Rivers ; Satellite imagery ; Slopes ; Soil conservation ; Soil erosion ; Soil mapping ; Vegetation ; Watersheds</subject><ispartof>Geo-Environment and Landscape Evolution II: Evolution, Monitoring, Simulation, Management and Remediation of the Geological Environment and Landscape, 2006, Vol.1, p.55-67</ispartof><rights>2006. 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Four raster maps have been produced for the soil erodibility, rainfall erosivity, slope length and steepness, and cover management factor, and the map with different soil loss risks has been produced for soil erosion potential. 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The Revised Universal Soil Loss Equation (RUSLE), Remote Sensing (RS), and Geographic Information System (GIS) were used to model soil erosion intensity for soil conservation and vegetation rehabilitation in an Upper Min River (UMR) watershed, which is in the Upper Yangtze River basin. Data used in this study to generate the soil loss were Landsat Enhanced Thematic Mapper (ETM) images, Digitized Elevation Model (DEM), soil erodibility, rainfall erosivity, and inventory data. The non-parametric k-nearest neighbor (k-NN) method was used to produce the cover management map by integrating the ETM images and vegetation coverage data measured in the 625 sample plots. The root mean square errors and significance of biases at pixel level were evaluated in order to find optimal parameters. Four raster maps have been produced for the soil erodibility, rainfall erosivity, slope length and steepness, and cover management factor, and the map with different soil loss risks has been produced for soil erosion potential. The result can be beneficial to the erosion control and ecological restoration in the degraded mountainous watershed.</abstract><cop>Southampton</cop><pub>W I T Press</pub><doi>10.2495/GEO060071</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Geo-Environment and Landscape Evolution II: Evolution, Monitoring, Simulation, Management and Remediation of the Geological Environment and Landscape, 2006, Vol.1, p.55-67 |
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| source | Alma/SFX Local Collection |
| subjects | Digital Elevation Models Digitization Ecological effects Environmental restoration Erosion control Erosion mechanisms Geographic information systems Image enhancement Landsat Landsat satellites Mountains Order parameters Quantitative analysis Rainfall Rehabilitation Remote sensing Restoration River basins Rivers Satellite imagery Slopes Soil conservation Soil erosion Soil mapping Vegetation Watersheds |
| title | Large scale soil erosion modeling for a mountainous watershed |
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