1. Reducing Vulnerability of Coastal Zones due to Accelerated Sea Level Rise using Remote Sensing and GIS: An Indian Case Study By Abhijat Arun Abhyankar Post Doctoral Fellow Department of Computer Science and Engineering, IIT Bombay

2. Introduction Global scenario United Nations (UN’s) Inter Governmental Panel on Climate Change (IPCC) predicts globally temperature rise of 1.8 to 4 degree -result in sea level rise from 6 cm to 100 cms Climate change will results in change in patterns of water cycle, ecosystem, coasts and oceans, agriculture and food supply, human life, energy, industry, insurance. National India has large coastal region-Around 6500 kms. 60% of economic activity happens in these areas India coastal zones has low adaptive capacity due to huge population density Poor and illiterate India has one of the lowest Low HDI Mumbai Metropolitan Region Projections -Mumbai could overtake Tokyo as the world’s largest city by 2050 (population) OECD (2007)-Mumbai as a port has highest exposure and vulnerability (in terms of exposed population)

3. Literature review Yang (1997)-Coastal flooding in the yellow river delta Determined the flooded areas due to sea level rise Used: IDRISI software By 2100 : 6.7% area would be submerged Unnikrishan (2007)- Sea level rise increasing for Mumbai 1.20 mm per year Data used-PSMPL (data till 2004) The results are in line with global estimate Chen (2008)-flood vulnerability index Index is made up of Biophysical, social and economic category and further subdivided into 16 parameters.

4. Objectives Assess sea level rise for the 2030, 2050 and 2100 for MMR Identify vulnerable areas to seas level rise at sub district level using GIS and remote sensing tools (Municipal ward wise) Assess economic loss due to sea level rise Reduce vulnerability to these area due to sea level rise-using policy statement

5. Data requirement and software's Data requirements 1)SOI toposheets-1:500 2)High resolution remote sensing images 3)Sea level rise data of Mumbai-100 years 4)DEM/LIDAR data Softwares ERDAS Imagine Arc Map

6. Research Methodology Steps Regression analysis-time series analysis to estimate sea level rise temporally Landcover classification of high resolution remote sensing Segmentation and Classification Development of Composite Vulnerability Index at sub district level using GIS Reduce Vulnerability to sea level rise using policy statement

7. Work done till date 1) Literature review 2) Data availability and sources a) SOI, Dehradun-sea level rise for all 18 ports of India-hourly/daily/month etc. Major Shri Srivastava-G &R department b) SOI, Dehradun SOI toposheets-high resolution toposheets

8. Thank you and questions