Delineating the Mangrove Patches along Coastal Kerala using Geographical Information System, Satellite Data and Field Validation

Pranav, P and Menon, Nandini and Shameem, U and Mini, K G and George, Grinson (2022) Delineating the Mangrove Patches along Coastal Kerala using Geographical Information System, Satellite Data and Field Validation. In: Conservation, Management and Monitoring of Forest Resources in India. Springer, Cham, Denmark, pp. 75-103. ISBN 978-3-030-98233-1

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Abstract

Mangroves, wetlands and coral reefs are dynamic ecosystems that are easily affected by natural calamities as well as human interferences. The 2004 tsunami has served to improve awareness on the need to conserve and sustainably manage the mangroves. Therefore, mangrove areas are categorized as ecologically sensitive under the Indian coastal regulatory zone notification I (CRZ-I) in 2011. An accurate delineation of mangrove areas is important for its in situ conservation. Satellite remote sensing data and geographical information system (GIS) tools can be effectively used to define the boundary of mangrove patches. The advantages are that these are less expensive and less time-consuming than in situ sampling of individual patches. In the present study, we have used Google Earth Pro image search engine, Quantum GIS (Version QGIS 3.10) and SNAP (Sentinel Application Platform Version 8.0)—all open-source GIS softwares to map the distribution and features of mangrove areas. Cloud-free Sentinel-2 multispectral images (MSI) were acquired from the Copernicus data hub hosted by the European Space Agency (ESA). The pre-processing of satellite data and classification using the Random Forest (RF) method were carried out in SNAP and semi-automated classification using the maximum likelihood classification (MLC) method in QGIS. The pixel-based RF classification using Sentinel-2 satellite in SNAP showed the highest accuracy based on Cohen’s kappa coefficient (K) among the three classification algorithms (RF (K = 0.80), MLC (K = 0.68) and K-nearest neighbour (K = 0.61) methods), followed by semi-automated classification in QGIS and Google Earth image-based classification. The pixel-based RF classification enables the fine classification of mangroves from other vegetation. These outputs are field verified with the ground control points (GCPs), collected during an extensive field survey along the coastal districts of Kerala. The successful methodology was employed to delineate the entire mangrove patches throughout the coastal regions of Kerala. This methodology can be adopted for mapping mangroves in the remaining coastal states of India to make an appropriate mangrove distribution library for India. This would help make a successful conservation plan to protect the diminishing mangrove forests in India. This book chapter highlights the utilization of advanced techniques in satellite remote sensing and GIS for better management of mangroves all across the globe.

Item Type: Book Section
Uncontrolled Keywords: Mangrove forests; Mapping; Conservation; Random forest classification; Sentinel-2; QGIS
Subjects: Marine Ecosystems > Mangroves
Oceanography > Remote sensing
Divisions: CMFRI-Kochi > Marine Capture > Fishery Resource Assessment
Subject Area > CMFRI > CMFRI-Kochi > Marine Capture > Fishery Resource Assessment
CMFRI-Kochi > Marine Capture > Fishery Resource Assessment
Subject Area > CMFRI-Kochi > Marine Capture > Fishery Resource Assessment
Depositing User: Arun Surendran
Date Deposited: 08 Aug 2022 06:30
Last Modified: 08 Aug 2022 06:30
URI: http://eprints.cmfri.org.in/id/eprint/16151

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