Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 18, Pages: 1-7
Nikita Roy Mukherjee1 and Christopher Samuel2*
1Remote Sensing and Geographic Information System, SRM University, Kattankulathur – 603 203, Kanchipuram District, Tamil Nadu, India 2Department of Civil Engineering, SRM University, Kattankulathur – 603 203, Kanchipuram District, Tamil Nadu, India; [email protected]
*Author for correspondence
Department of Civil Engineering, SRM University, Kattankulathur – 603 203, Kanchipuram District, Tamil Nadu, India; [email protected]
Urban India is witnessing a rapid growth that has an impact on the fate of water bodies. Chennai, one of the fastest growing metropolitan cities in India, is not an exception to this urbanization process. Chennai’s precious water resources are under severe stress. Further, the recent, 100-year flood disaster that occurred in November–December 2015 over Chennai has had tragic consequences on its population and has brought back the focus on its water bodies. Remote sensing combined with GIS techniques enable accurate spatiotemporal change detection of natural resources. Landsat and multispectral imageries provide reliable and accurate data for the detection of changes in the areal extents of surface water bodies. Spatiotemporal change analyses on the surface water bodies in Chennai and its surrounding areas were conducted through water extraction techniques by using indexes, such as WRI, NDWI and MNDWI using GIS software. The changes in the surface water bodies were estimated by analyzing and using Landsat images for the pre- and post-monsoon periods of the years1977–78, 1988–89, 1997–98, 2006–07 and 2015–16. The changes and their variations in the indexes and the interpretation of these changes are discussed. NDWI is most suitable for extracting surface water bodies. WRI and MNDWI can be used for the extraction of surface water bodies only from those satellite imageries that have the MIR band. However, MNDWI is suitable for inundated areas within a largely urban-covered region. Hence, urban planners can utilize these results for better urban planning and flood-disaster management.
Keywords: Change Detection, Chennai, Disaster Management, Landsat Imagery, MNDWI, NDWI, Remote Sensing and GIS, Surface Water Bodies, Urban Planning, Water Extraction Techniques, WRI
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