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Automated Assessment of the Extent of Mangroves Using Multispectral Satellite Remote Sensing Data in Google Earth Engine


Affiliations
1 Central University of Jharkhand, Department of Geoinformatics, Brambe, Ranchi 835 222, India
2 Indian Institute of Space Science and Technology, Thiruvananthapuram 695 547, India
 

This study on the automatic assessment of mangroves uses geometric, textural parameters and vegetation indices derived from Landsat 8 images utilizing the Google Earth Engine. The extent of Indian mangroves is estimated as 5581 sq. km for 2019, with an overall accuracy (OA) of 86% and kappa coefficient (k) of 0.77. Among the five regions studied, maximum OA was obtained for Mumbai (94%; k = 0.89) and minimum for Godavari (81.625%; k = 0.66). Such automated mapping will benefit effective mangrove monitoring and management with a near real-time accurate estimation of mangroves.

Keywords

Automated Mapping, Cloud Platform, Mangrove Ecosystem, Satellite Data.
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  • Automated Assessment of the Extent of Mangroves Using Multispectral Satellite Remote Sensing Data in Google Earth Engine

Abstract Views: 207  |  PDF Views: 72

Authors

Rupsa Sarkar
Central University of Jharkhand, Department of Geoinformatics, Brambe, Ranchi 835 222, India
L. Gnanappazham
Indian Institute of Space Science and Technology, Thiruvananthapuram 695 547, India
A. C. Pandey
Central University of Jharkhand, Department of Geoinformatics, Brambe, Ranchi 835 222, India

Abstract


This study on the automatic assessment of mangroves uses geometric, textural parameters and vegetation indices derived from Landsat 8 images utilizing the Google Earth Engine. The extent of Indian mangroves is estimated as 5581 sq. km for 2019, with an overall accuracy (OA) of 86% and kappa coefficient (k) of 0.77. Among the five regions studied, maximum OA was obtained for Mumbai (94%; k = 0.89) and minimum for Godavari (81.625%; k = 0.66). Such automated mapping will benefit effective mangrove monitoring and management with a near real-time accurate estimation of mangroves.

Keywords


Automated Mapping, Cloud Platform, Mangrove Ecosystem, Satellite Data.

References





DOI: https://doi.org/10.18520/cs%2Fv125%2Fi3%2F299-308