Estimation of Crop and Forest Areas using Expert System based Knowledge Classifier Approach for Aurangabad District
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چکیده
The present study demonstrates the application of remote sensing for the estimation of areas corresponding to crop and forest lands covered in the district of Aurangabad, (Maharashtra), India. The data acquired by IRS-P6 Advanced Wide Field Sensors (AWiFS) having 56m spatial resolution for the months of October & December 2012 which covered complete study areas with its swath of 740Km has been used for the study. The Maximum Likelihood Classification (MLC) and Knowledge Classification (KC) techniques based on Decision Tree approach were applied. It has basically two elements, knowledge engineering and knowledge classifier. Knowledge engineering provides an interface to build up decision tree which defines the rules and variables represented by three parameters, i. e. Normalized Difference Vegetation Index (NDVI), Soil Adjust Vegetation Index (SAVI), and Normalized Difference Water Index (NDWI)
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تاریخ انتشار 2015