CS(AR)-12/99-2000 : Applicability of remote sensing technique to monitor changes in land use and water spread area

Abstract

Information on the rate and kind of changes in land and water resources is essential for planning, management and regularising the use of such resources. Detection of changes in land use/cover over a period of time has become possible in less time, at lower cost and with better accuracy through remote sensing technology. Remote sensing technique is the most advantageous among the new technologies because of its repetitive coverage and the availability of data in different parts of the electromagnetic spectrum. Its application have been operationalised in the natural resources management themes and at present the trend is on integrated surveys to arrive at sustainable development packages. Similarly, the information on estimating hydrological land use/cover types and how they change over time is a prerequisite for sustainable resource development planning. Effective resource management is impossible without a reasonable estimation of the resources in question.

In the present study, land use/land cover and water spread area maps for Yelberga and Kustagi talukas of Koppal district in Karnataka state have been prepared by using the digital interpretation of the IRS satellite data and ILWIS software for the years 1989, 1995 and 1998. Five major land use/land cover categories have been identified as per the spectral, radiometric and spatial variation as well as the tone/colour, shape, size, texture, pattern, location and association of the particular feature. These land use/covers are built-up land, agricultural land, degraded forest, waste land and water bodies. The dominant land use in the study area is agricultural cropland. There is a substantial increase in the water spread area may be due to construction of new water bodies as well as the spectral resolution capacity of IRS LISS III data This information of the temporal changes in water spread area will be helpful for the surface water potential estimation and its effective utilisation to mitigate the drought problem in the area.