Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data

Sudip Manna; Subrata Nandy; Abhra Chanda; Anirban Akhand; Sugata Hazra; Vinay Kumar Dadhwal

doi:10.1117/1.JRS.8.083638

7 May 2014 Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data

Sudip Manna, Subrata Nandy, Abhra Chanda, Anirban Akhand, Sugata Hazra, Vinay Kumar Dadhwal

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 8, Issue 1, 083638 (May 2014). https://doi.org/10.1117/1.JRS.8.083638

Abstract

Mangroves are active carbon sequesters playing a crucial role in coastal ecosystems. In the present study, aboveground biomass (AGB) was estimated in a 5-year-old Avicennia marina plantation (approximate area ≈190 ha ) of Indian Sundarbans using high-resolution satellite data in order to assess its carbon sequestration potential. The reflectance values of each band of LISS IV satellite data and the vegetation indices, viz., normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), and transformed difference vegetation index (TDVI), derived from the satellite data, were correlated with the AGB. OSAVI showed the strongest positive linear relationship with the AGB and hence carbon content of the stand. OSAVI was found to predict the AGB to a great extent ([i]r² =0.72 ) as it is known to nullify the background soil reflectance effect added to vegetation reflectance. The total AGB of the entire plantation was estimated to be 236 metric tons having a carbon stock of 54.9 metric tons, sequestered within a time span of 5 years. Integration of this technique for monitoring and management of young mangrove plantations will give time and cost effective results.

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Sudip Manna, Subrata Nandy, Abhra Chanda, Anirban Akhand, Sugata Hazra, and Vinay Kumar Dadhwal "Estimating aboveground biomass in Avicennia marina plantation in Indian Sundarbans using high-resolution satellite data," Journal of Applied Remote Sensing 8(1), 083638 (7 May 2014). https://doi.org/10.1117/1.JRS.8.083638

Published: 7 May 2014

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