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9 October 2018 Remote sensing and GIS for assessment and prediction of environmental hazards due to mine waste: case study from Daitari iron ore mines, Odisha, India
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Abstract
The main objective of this study is to investigate the environmental impacts of Daitari iron-ore mines zone using Landsat TM (2000), Landsat ETM7+ (2010), Landsat8 (2015) and Landsat8 (2017) satellite data. This paper also delineates to propose a land use- land cover (LULC) classification scheme, evaluate their accuracy in different years and to detect the land cover changes from 2000 to 2017 in this mining area using digital image-processing. Supervised classification methodology using maximum likelihood technique was employed in ENVI 4.5 software. It was observed that the built up area and mining area were increased from 8.32% to 29.13% and 14.85% to 30.7% respectively between 2000 and 2017. Also the area with vegetation land was decreased by 47.16% and waste dump increased from 18.2% to 28.7% in Daitari test site area. Finally the mine waste hazard map has been prepared from the spectral characteristics of digital image analysis, laboratory assessment of different elements present at Daitari iron ore mines and getting the idea of generating various maps like contour map, aspect map, flow direction map etc. of this iron ore mines. From the Markov chain analysis, the projected LULC statistics for the year of 2020 has been calculated and the result suggested that iron ore mines area as well as the settlement area will be increased rapidly whereas, vegetation, forest land, barren land and water bodies will be decreased drastically by the year 2020 leading to severe environmental impact.
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Atasi De and Dheeraj Kumar "Remote sensing and GIS for assessment and prediction of environmental hazards due to mine waste: case study from Daitari iron ore mines, Odisha, India", Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 107900W (9 October 2018); https://doi.org/10.1117/12.2326709
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