Ahmad, Mobin (2018) Forest Cover Change Analysis Based on Remote Sensing & GIS of West Singbhum District, Jharkhand. International Journal of Research in Applied Science and Engineering Technology , 6 (V). pp. 1039-1050. ISSN 2321-9653
Full text not available from this repository.Abstract
Forest is a part of the land surface of the earth, with lots of plants and animals, they are need forests to live and survive. The major objective of this study is to detect the magnitude of forest cover change in the duration of the last 20 years (1997 to 2017) in West Singhbhum district of Jharkhand, India. The spectral information of the satellite image is more important to generate forest cover change model using LULC, NDVI and SAVI. The data included a series of topographical sheets, open series maps and satellite imageries from Landsat-5 TM (1997) and Landsat-8 OLI (2017) to recognize forest cover changes during the chosen period. A very useful method used to complete the study, which are generation of Land Use/Land Cover (LULC), Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) model of the study area. The LULC employing the maximum likelihood supervised classification (MLC) algorithm mainly focused on forest cover and other parameters. On the classified map, accuracy assessment is performed, which produced error matrices and overall accuracy, the calculated overall accuracy found 87.18% in 1997 and 86.11% by 2017. The change detection analysis revealed that the area has remarkable changes specifically, the forest covers land reduced 2017.037 km2 (26.17%) of the total study area of 5,364.789 km2 in between 20 years, 5079.723 km2 (65.58%) in 1997 to 3062.686 km2 (40.41%) in the year 2017. Key words: LU/LC, NDVI, Remote Sensing (RS), Geographic Information System (GIS), Change Detection, Image Differencing, Accuracy Assessment, Error Matrix.
Item Type: | Article |
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Subjects: | Iron Ore Mining |
Divisions: | UNSPECIFIED |
Depositing User: | Mr. B. R. Panduranga |
Date Deposited: | 25 Nov 2019 05:21 |
Last Modified: | 25 Nov 2019 05:21 |
URI: | http://cimfr.csircentral.net/id/eprint/2084 |
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