International Symposium on
Drylands Ecology and Human Security
Using Geographical Information Systems and Remote Sensing Techniques
Ahani H.1, Baghernezhad M.2, Fallah Shamsi S.R.3, Masoudi M.4, Sameni M.5
1, 3, 4 Department of Desert Region Management, College of Agriculture, Shiraz University, Shiraz, Iran
2, 5 Department of Soil Science, College of Agriculture, Shiraz University, Shiraz, Iran
Soil erosion is recognized as a serious threat to man’s-being worldly wide. Accelerating soil erosion also has adverse economic and environmental impacts on sustainable development.
Geographical Information Systems (GIS) is a modern tool, which provides information on all geographical variables and has been frequently used in soil erosion studies. Remotely sensed satellite images are also helpful for generating up-to-date land use/cover maps of earth Surface facilitate the identification of erosion-prone areas.
In this study, it has been planned to develop a GIS and Remote Sensing based spatial model using USLE model for assessing soil erosion prone areas in Rahim-abad Catchments, located in the central Fars province of Iran. The various steps for the implementation of USLE model under GIS environment have been automated by developing computer programs of ArcGIS 9.1 software. The land use/ land cover map has been generated from the Landsat-7 ETM+ images, using ERDAS IMAGINE software. The thematic maps used as the factors of USLE model have been analyzed simultaneously to assess total soil erosion which finally has been divided into four soil erosion classes from very slight (0-5 t/he/year), slight (5-10 t/he/year), moderate (10-30 t/he/year) classes to high (30-61t/he/year) one using GIS. Digital Elevation Model (DEM) has been used to improve digital image classification processes in land use and cover mapping. The DEM has been created using Tin Plate Smoothing Splin (TPSS) in ArcGIS9.
The appropriate soil conservation measures have been proposed for the high soil erosion prone areas depending upon prevailing terrain conditions.
Keywords: Soil Erosion, USLE, Modeling, GIS, RS