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• Land use change detection along the Pravara River basin in Maharashtra, using remote sensing and GIS techniques

  71-86

  Veena Joshi

  Vikas Nagare

  Views:

  235

  In the past few decades there has been an increasing pressure of population all over the world, especially in India, resulting in the utilization of every available patch of available land from woodlands to badlands. The study area represents a basin which is economically growing fast by converting the fallow lands, badlands and woodlands to agricultural land for the past few decades. IRS (Indian Remote sensing Satellites) 1 C – LISS III and IRS 1 C PAN and IRS P6 – LISS III and IRS 1 D PAN Images were merged to generate imageries with resolution matching to the landscape processes operating in the area. The images of the year 1997, 2000, 2004 and 2007 were analyzed to detect the changes in the landuse and landcover in the past ten years. The analysis reveals that there has been 20% increase in the agricultural area over the past ten years. Built up area also has increased from 1.35% to 6.36% of the area and dense vegetation also has marginally increased. The remarkable increase in the agricultural area occurs owing to the reclaim of the natural ravines and fallow lands. Presently the area looks promising, but it is necessary to understand the sedimentological and geomorphological characteristics of the area before massive invasion on any such landscapes because the benefit may be short lived.

• Correction of Atmospheric Haze of IRS-1C LISS-III Multispectral Satellite Imagery: An Empirical and Semi-Empirical Based Approach

  63-74

  Sheikh Mustak

  Naresh Baghmar

  Sudhir Singh

  Views:

  428

  The atmospheric effect greatly affects the quality of satellite data and mostly found in the polluted urban area in the great extent. In this paper, the atmospheric correction has been carried out on IRS-1C LISS-III multispectral satellite image for efficient results for the Raipur city, India. The atmospheric conditions during satellite data acquisition was very clear hence very clear relative scattering model of improved dark object subtraction method for the correction of atmospheric effects in the data has been carried out to produce the realistic results. The haze values (HV) for green band (band 2), red band (band 3), NIR band (band 4) and SWIR (band 5) are 79, 53, 54 and 124, respectively; were used for the corrections of haze effects using simple dark object subtraction method (SDOS). But the final predicted haze value (FPHV) for these bands are 79, 49.85, 21.31 and 0.13 that were used for the corrections of haze effects applying improved dark object subtraction method (IDOS). We found that IDOS method produces very realistic results when compared with SDOS method for urban land use mapping and change detection analysis. Consequently, ATCOR2 model provides better results when compared with SDOS and IDOS in the study.