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Modeling Earth Systems and Environment

, Volume 5, Issue 1, pp 217–226 | Cite as

Mapping and monitoring of mangrove along the Odisha coast based on remote sensing and GIS techniques

  • Santanu RoyEmail author
  • Manik Mahapatra
  • Abhishekh Chakraborty
Original Article
  • 38 Downloads

Abstract

Digital image processing techniques using multi-temporal satellite imagery are widely used to understand landscape dynamics. In this study, we analysed the spatio-temporal changes of mangrove along the Odisha coast, India using Landsat satellite images of four different time periods, i.e., Landsat-5 Thematic Mapper satellite images of 1990 and 2009, Landsat-7 Enhanced Thematic Mapper Plus satellite images of 2000 and Landsat-8 Operational Land Imager satellite images of 2015. Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI) and Normalized Difference Wetland Index (NDWI) are used to extract and classify the mangroves into three classes such as dense mangrove, sparse mangrove and open mangrove. The study reveals that total mangrove of the study area increased from 18573.49 ha (1990) to 23871.49 ha (2015) during the last three decades. This may be attributed to mangrove plantation, restoration and proper coastal zone management plan. The paper highlights the importance of digital change detection techniques using NDVI, SAVI and NDWI for mangrove mapping and monitoring along the Odisha coast. This study aids Odisha coastal zone management authority to take timely decisions for conservation of mangrove and future mangrove plantation plans with help of satellite image processing in GIS environment.

Keywords

Mangrove Remote sensing NDVI SAVI NDWI Odisha 

Notes

Acknowledgements

The authors express their sincere gratitude to Dr. Ashis Kumar Paul Professor, Vidyasagar University for providing valuable guidance, support and constant encouragement. The authors are also thankful to Dr. Ramkrrishna Maiti, Professor, Vidyasagar University and Dr. Jatisankar Bandyopadhyay, Assistant Professor, Vidyasagar University for providing valuable guidance.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Remote Sensing and GISVidyasagar UniversityMidnaporeIndia
  2. 2.National Centre for Sustainable Coastal ManagementChennaiIndia

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