Presentation_with_acharya_dst_sept_14_2010 - GISE


Reducing Vulnerability of Coastal Zones due to

Accelerated Sea Level Rise using Remote

Sensing and GIS: An Indian Case Study


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.


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)

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.


• Assess sea level rise for the 2030, 2050 and 2100 for


• 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 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


ERDAS Imagine

Arc Map

Research Methodology


• 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

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

Thank you and questions