Urban Sprawl Prediction for Coastal City, Chennai.

Manveen Ahluwalia

GE4001

The project focuses on study and prediction of urban sprawl for the city of Chennai. The study area was selected on certain parameters and giving the adequate weights. It was then followed by landuse classsification of mullti-temporal satellite images for the years 2006, 2009, 2011 and 2017. By using two urban sprawl model MOLUSCE and Land Change Modeller, urban sprawl was predicted for the year 2021.

Report Content

Adopted methodology

Phase 1 - Selection of study area

Landuse classification using Maximum Liklihood of Landsat (5 & 8) images 2006, 2009, 2011, 2017.

Area change statistics, increments or decrements in area of each class and change detection matrix from 2006 to 2017. Accuracy of 74.4% was achieved for the base year 2006.

Urban Sprawl Model - MOLUSCE

Giving adequate weights to input factors : distance from coastline, distance from roads, slope, Restricted ares

The model was first simulated for 2017 and validated with the existing landuse classification of the same. MOLUSCE result - Urban sprawl prediction for 2021 by giving inputs of landuse of 2011 and 2017.

Land Change Modeller

Probability Matrix

LCM results