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Geomatics Based Analysis of Predicted Sea Level Rise and its Impacts in Parts of Tamil Nadu Coast,India
Authors:SM. Ramasamy  C. J. Kumanan  J. Saravanavel  A. S. Rajawat  V. Tamilarasan  Ajay
Affiliation:(1) Gandhigram Rural University, Gandhigram, Dindigul, 624302, Tamil Nadu, India;(2) Centre for Remote Sensing, Bharathidasan University, Tiruchirappalli, 620 023, Tamil Nadu, India;(3) Marine and Earth Sciences Group (MESG), Remote Sensing Applications Area (RESA), Space Applications Centre (SAC), Ahmedabad, 38 0015, India
Abstract:The coastal zones around the world are very densely populated and hence heavily packed with related infrastructures. So, the territorial nations have obvious apprehensions against the IPCC SRES (Intergovernmental Panel on Climate Change, Special Report on Emission Scenario) predicted sea level rise, as it would cause flooding of the low lying coasts and also other related chains of environmental endangers. This has driven these nations to initiate research studies in multiple directions for scientifically evaluating the phenomenon and impacts of sea level rise using all possible technologies including the Geomatics which possesses unique credentials in geosystem mapping. But certain advanced virtues available with Geomatics technology are yet to be capitalized deservingly in this. In addition, almost all the earlier studies have focused only on the impacts of sea level rise (SLR) and not on the predicted shift of high tide line (HTL) and the related inter tidal activities, which would cause a series of environmental disaster. Hence, the present research study was undertaken in a test site of 750 km2 in central Tamil Nadu coast to visualize the areas prone to submergence due to predicted SLR and areas prone to environmental disasters/degradation viz. erosion, deposition, salination of agricultural lands, pollution of aquifers, etc. due to predicted shift of HTL, using digital elevation models derived from SRTM data (Shuttle Radar Topographic Mission), geomorphology and land use/cover maps interpreted using IRS P6 LISS IV satellite data. The paper narrates the certain newer concepts and methodologies adopted in the study and the results.
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