Using Remote Sensing and GIS Techniques to Study Soil Degradation Processes in North Shaanxi Province, China

Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1 : 250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and Arc-View softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility (SE) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation,physical degradation and salinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33.75 % of the total land area (120. 330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29. 41% of the total land area has slight or moderate desertification and 37. 465 % is facing severe desertification.

Using Remote Sensing and GIS Techniques to Study Soil Degradation Processes in North Shaanxi Province,China

Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1: 250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and ArcView softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility (SE) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation,physical degradation and sulinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33. 75 % of the total land area (120. 330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29. 41% of the total land area has slight or moderate desertification and 37. 465 % is facing severe desertification.