Experiment of Multispectral Images using Spectral Angle Mapper Algorithm for Land Cover Classification
KeertiKulkarni1, P. A. Vijaya2
1Keerti Kulkarni, Associate Professor, Department of Electronics and Communication Engineering, B.N.M. Institute of Technology, Bangalore.
2Dr. P. A. Vijaya, Professor & Head, Department of Electronics and Communication Engineering, B.N.M. Institute of Technology, Bangalore.
Manuscript received on 05 April 2019 | Revised Manuscript received on 12 April 2019 | Manuscript Published on 26 July 2019 | PP: 96-99 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F10180486S419/19©BEIESP | DOI: 10.35940/ijitee.F1018.0486S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Urbanization plays a key role in the health of the water bodies in any region. In a rapidly growing country like India, especially Bangalore district, rapid urbanization has seen a steep decline in the number of water bodies the region is famous for. In this paper, Land Use and Land Cover change is analysed for the remotely sensed images of Bangalore District using Spectral Angle Mapper Algorithm. Data for the purpose of analysis was obtained from BHUVAN (NRSC, ISRO). The study area is Bangalore District and data was collected from the time period 2008-2016. The major classes used in the classification are Land(Built-up), water bodies (Lakes), Vegetation (Gardens), Soil (Barren and fertile). The satellite images and the accompanying classification algorithms indicate that the percentage of water bodies have drastically shrunk (from 2.9% in 2008to1.8% in 2016) in the area of study. The results of this study can be used by the civic authorities to implement decisions to conserve the water bodies in the area.
Keywords: Land Use and Land Cover (LULC), Bangalore District, Multispectral Images, Spectral Angle Mapper Algorithm.
Scope of the Article: Classification