Assessment of Surface Water Dynamicsin Bangalore Using WRI, NDWI, MNDWI, Supervised Classification and K-T Transformation

Abstract

Bangalore, the IT capital of India, is one of the fastest growing city of Asia. Rapid urbanization of Bangalore during the last two decades has posed a serious threat to the existence of ecological systems, specifically water bodies which play a crucial part in supporting life. Remote Sensing Satellite images can play a significant role in investigation, dynamic monitoring and planning of natural surface water resources. Landsat-7 Enhanced Thematic Mapper(ETM+) imagery havehigh spatial, temporal and multispectral resolution and thereforeprovides reliable and accurate data to detect changesin extent of water bodies. In this paper, a study has been conducted to detect the changesin water body extent during the period of 2002 to 2014 using various methods namely Water Ratio Index (WRI), Normalised Difference Water Index (NDWI), Modified Normalised Difference Water Index (MNDWI),supervised classification and wetness component of K-T transformationand the results are presented.Several iterations were performed to determine a suitable threshold for effective water detection in urban areas for each of the methods. The performance of each of the algorithms was compared and verified via ground survey. This study indicates a considerable variation in water surface area of the city over a span of 12 years.