Application of Remote Sensing and GIS Techniques for Decadal Change Detection of Mangroves along Tamil Nadu Coast, India

Abstract

Mangrove forests are among of the most productive and biologically important ecosystems of the world. The mangrove forests aids stabilize shorelines and reduce the devastating impact of natural disasters such as tsunamis and hurricanes. They also provide breeding and nursing grounds for marine and pelagic species, and food, medicine, fuel and building materials for local communities. Despite of its immense importance, it is declining due to increasing coastal population, urbanization and industrial development and frequent natural disasters such as storm surge, tsunami etc. Up-to-date information with regard to the extent and condition of mangrove ecosystems is essential for conservation, restoration measures and proper management of coastal zone. In this article we aims at the decadal changes of mangroves forest during 1991 to 2014 timeframe along the Tamil Nadu coast, India using remote sensing and GIS techniques. Tamil Nadu coast is the longest coastline (1076 km) in the east coast of India. Landsat TM images for the year 1991, Landsat ETM+ for the year 2000 (30 m spatial resolution) and Landsat OLI images dated 2014 (30 m spatial resolution) were used. Normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI) were used to classify the images based on density. The decadal change analysis of mangroves reveals that the extent of mangroves was increased from 5986.20 ha in 1991 to 6421.48 ha in 2000 and it is further increased to 6756.30 ha in 2014 along Tamil Nadu coast. The increase of mangroves happens due to following reasons such as new mangroves plantation, awareness of the benefits of mangroves and coastal zone management plan. The findings of our research are expected to provide up-to-date information of mangroves’ change along the Tamil Nadu coast for conservation and restoration measures.

Keywords: Mangrove forest, FCC, NDVI, SAVI, change analysis, GIS, remote sensing