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

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)

•
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.

• 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

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

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

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