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Prediction of industrial land use using linear regression and mola techniques: A Case Study of Siltara Industrial belt
59-70Views:258The Siltara Industrial belt is an important industrial pocket of Chattisgarh state located in the northern part of the Raipur city, which is rapidly growing. In this process spatial, cultural, political and administrative factors are controlling its rate, direction and pattern. The Simple Linear Regression (SLR) and Multi-Objective Land Allocation (MOLA) techniques, which are embedded in SPSS and Idrisi Kilimanjaro software respectively, and have been used for the estimation of future scenario of the industrial growth. In this model, a suitable platform has been prepared in which future industrialization has been estimated by integrating physical, social, cultural factors and land acquisition policy. In this article, results have revealed that industrialization has occurred very fast during last one decade. The industrial land was 6.15 km2 in 2001 and 18.725 km2 in 2011 and estimated as 31.30 km2 in 2021 and 43.87 km2 in 2031 using SLR. The rapid industrial growth is very critical issues for agrarian society and fresh environment. This model very accurately estimating (overall accuracy=95.39%, Kno=97.24%, agreement=98.63 %) the future growth of industrial land. This work will be useful to the planners and policy makers of private and government sectors to regulate the sustainable planning practices and smart decision-making.
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Remote Sensing and GIS based site suitability analysis for tourism development in Vaishali block, Bihar, India
12-22Views:514Geographic Information Systems (GIS) and Remote Sensing are presently recognized generally as an improve instrument for overseeing, breaking down, and showing gigantic volumes of fluctuated information suitable to numerous neighborhood and provincial arranging exercises. Because of the composite idea of the travel industry arranging issues, the planned of GIS in settling these issues is progressively perceived. This paper will think a portion of the conceivable outcomes of GIS applications in the travel industry arranging. For the most part, GIS applications in the travel industry have been tight to recreational office stock, the travel industry situated land the board, and diversion untamed life strife; and have been thin by absence of financing, and awkward techniques. Utilizing the case of site wellness investigation for the travel industry improvement and mapping, this paper features a few uses of GIS in the travel industry arranging in vaishali square, Bihar. According to our present investigation; the most reasonable the travel industry site recognized by the examination is inside significant towns. The urban focus with plausibility to develop into the travel industry focuses. The rest of the land shows a low appropriateness scale because of absence of significant appreciation for make a solid force factor. Availability is an essential for the travel industry advancement. Great street organize availability with closeness to railroads station or air terminal demonstrated solid vacationer potential site, this combined with proximity to grand magnificence delineates high appropriateness. Significant vacation destinations, for example, legacy locales, gardens and water bodies or lake demonstrated high appropriateness. This can be corresponded to the way that legacy destinations and other high appropriate highlights are converted into reasonable the travel industry site.
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Correction of Atmospheric Haze of IRS-1C LISS-III Multispectral Satellite Imagery: An Empirical and Semi-Empirical Based Approach
63-74Views:247The 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.