Characterization of Soil Salinity in Arid Region (Kashan) by Digital Processing of IRS_1D Data
2006
Matinfar, Hamid Reza | Sarmadian, Fereydun | Alavipanah, Kazem
Soil salinity is one of the main increasing problems of the world. In the recent years application of remote sensing and GIS techniques in order to assess saline soils is used because these methods bring about vast uniform coverage of ground phenomena at the sometime along with performing this deal in a short time . The images of LISS III sensor of the Indian satellite (IRS) were used. The Brightness index (BI) could discriminate highly saline soils from non âsaline soils and the salinity index (SI) show high potential to separate very high, high and non- saline soils. Results of supervised classification without combination DEM and remote sensing data have overall accuracy of 76%, producer accuracy of 78% and user's accuracy of 82%. While in supervised classification with combination of remotely sensed data and DEM have overall accuracy of 98.1% , producer accuracy of 98.28% and user's accuracy of 98.4% .The reason for low accuracy of the classification , before combination of remote sensing and topographic data , can be explained by highly moist saline soils spectral interference with non-saline soils (soil with 25 to 65% gravels) , but these two soils had different topographic condition with 200 meters elevation , thus , with combination of the DEM , this kind of area and other area with similar condition have been separated from each other .
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