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The data collection was done from both primary and secondary sources. The main sources of primary data (for image analyses, training data) were from the field (using GPS), the Survey of India (SOI) toposheets of 1:50,000 scale and the multispectral sensors (MSS) data of the Indian Remote sensing satellite (IRS 1C). The secondary data were collected from the government agencies (Directorate of census operations, agriculture department, forest department, and horticulture department). LISS- III MSS data devoid of radiometric errors corresponding to the district as given in the figure 4, for the paths-rows (100, 63), (100, 64) and (101, 64) was procured from the National Remote Sensing Agency (http://www.nrsa.gov.in).

The IRS-1C rectified (geo corrected) scenes for Kolar corresponding to paths-rows (100,63), (100,64) and (101,64) for band 4 (near infrared) with district boundary is given in figure 5.

Figure 5: IRS 1C rectified scenes for scenes corresponding to (100,63), (100,64) and (101,64)

This includes the development of GRDSS and testing considering the Kolar district data for land use analyses.

Development of GRDSS entailed:

• Development of GUI in TCL/TK incorporating functionality of display, raster analysis (import/export, enhancement, rectification, transformation, mosaic, classification, interpretation, rasterisation, etc.), vector analyses, DEM/DTM.
• Development of GIS analysis and visualisation module.
• Development of database module.
• Database integration to drive modules.
• Dialogue management.
• Design of a decision support system.

• Creation of base layers like district boundary, district with taluk and village boundaries, road network, drainage network, mapping of waterbodies, etc. from the SOI toposheets.
• Extraction of bands from the data procured from NRSA.
• Identification of ground control points and geo-correction of bands through resampling.
• Generation of FCC (False Colour Composite) and identification of training sites on FCC.
• Collection of attribute information from field corresponding to the chosen training sites using GPS.
• Classification of remote sensing data.
• Generation of confusion matrix and accuracy assessment.