Volume No. 9 Issue No.: 4 Page No.: 1225-1233 April-June 2015

 

CHANGE DETECTION ANALYSIS OF MANGROVES FOR EFFECTIVE IMPLEMENTATION OF COASTAL ZONE MANAGEMENT PLAN

 

Patil Vikrant, Singh Anju, Naik Neelima, Unnikrishnan Seema* and Khale Prasad

Centre for Environmental Studies, National Institute of Industrial Engineering, Mumbai (INDIA)

 

Received on : January 15, 2015

 

ABSTRACT

 

Mangrove forests are one of the world’s most threatened tropical ecosystems. According to the Coastal Regulation Zone (CRZ) notification, mangrove regions in the country have been categorized under CRZ-I (Ecological Sensitive Zone). However, increasing number of anthropogenic activities like housing and infrastructure development projects have most often resulted in the depletion of mangrove habitat and violation of CRZ notification. This paper aims to discuss the changes in mangrove ecosystems during 1972 - 2010 (as well as to study the recent situation), distribution of mangroves around Ulhas River and the potential of the study area for mangrove regeneration. The present study area is under tremendous anthropogenic pressure because of activities like human settlements, illegal dumping of wastes and dredging of soil. The study was carried out using level 1 product of Landsat TM and ETM+ images acquired from USGS earth explorer website and classified using Maximum Likelihood Classifier in ArcGIS desktop10. Study indicated that, Thane is the worst affected area with loss of 28.19 % i.e. 3.86 km2 of mangroves in the period of 1992 to 2010. This region shows worst impact of anthropogenic activity and least regeneration options. It is observed that total area of mangroves is increasing at times and shrinking at other times, indicating mixed effects of mangrove protection and anthropogenic activities. This paper also highlights the importance of mapping temporarily lost and permanently lost areas, for generating and implementing an effective Coastal Zone Management Plan.

 

Keywords : Mangroves, Change detection analysis, CRZ, Remote sensing, GIS, Landsat

 

 

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