ARCHIVES
VOL. 11, ISSUE 3 (2026)
Remote sensing-based assessment of musa spp. cover and carbon sequestration potential in dima hasao district, assam
Authors
Somir Warisa, Arup jyoti Borah, Toshinungla Ao
Abstract
Anthropogenic CO₂ emissions since the
Industrial Revolution have accelerated atmospheric carbon accumulation,
necessitating precise quantification of terrestrial carbon sinks. Plant biomass
remains a critical component of global carbon cycling, and remote sensing
offers a scalable approach to above-ground biomass (AGB) estimation. This study
employed Sentinel-2 Level-2A multispectral imagery and vegetation indices,
processed in QGIS with the Orfeo Toolbox, to quantify banana (Musa sp.) biomass
in Dima Hasao district, India. A random forest classifier achieved 92.1%
overall accuracy in land cover classification, subsequently refined through
manual digitization in Google Earth Pro. Across 1,221.53 ha of banana cover,
carbon storage was estimated at 3.559±1.472ton C ha-1. These
findings demonstrate the robustness of freely available Sentinel-2 data
combined with machine learning classifiers for reliable, cost-efficient biomass
assessment in heterogeneous landscapes.
Download
Pages:210-218
How to cite this article:
Somir Warisa, Arup jyoti Borah, Toshinungla Ao "Remote sensing-based assessment of <i>musa </i>spp. cover and carbon sequestration potential in dima hasao district, assam". International Journal of Botany Studies, Vol 11, Issue 3, 2026, Pages 210-218
Download Author Certificate
Please enter the email address corresponding to this article submission to download your certificate.