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1 Bordoloi, R.; Das, B.; Tripathi, O. P.; Sahoo, U. K.; Nath, A. J.; Deb, S.; Das, D. J.; Gupta, A.; Devi, N. B.; Charturvedi, S. S.; Tiwari, B. K.; Paul, A.; Tajo, L. 2022. Satellite based integrated approaches to modelling spatial carbon stock and carbon sequestration potential of different land uses of Northeast India. Environmental and Sustainability Indicators, 13:100166. [doi: https://doi.org/10.1016/j.indic.2021.100166]
Carbon sequestration ; Carbon stock assessments ; Land use ; Land cover ; Satellite imagery ; Landsat ; Vegetation index ; Regression analysis ; Biomass ; Climate change mitigation ; Forest cover ; Remote sensing ; Modelling ; Simulation / India / Arunachal Pradesh / Assam / Manipur / Meghalaya / Mizoram / Nagaland / Sikkim / Tripura
(Location: IWMI HQ Call no: e-copy only Record No: H050887)
https://www.sciencedirect.com/science/article/pii/S2665972721000672/pdfft?md5=2b0c924ff6ef3156dbcfe3c57e940f61&pid=1-s2.0-S2665972721000672-main.pdf
https://vlibrary.iwmi.org/pdf/H050887.pdf
https://vlibrary.iwmi.org/pdf/H050887.pdf
(4.25 MB) (4.25 MB)
The study aims to estimate and predict the aboveground biomass, carbon stock and carbon sequestration potential of different land uses of Northeast India and relate these estimates with the land use changes. Many applications such as carbon stock and sequestration monitoring, forest degradation monitoring, and climate change mitigation, require precise and timely estimation of forest biomass. Although traditional field inventory can reliably estimate forest biomass, remote sensing is emerging as an alternate and fast approach to cover larger area with relative precision for biomass estimation. In this study, a combined approach of field inventory and Landsat OLI derived vegetation indices were used in spatial modelling of aboveground biomass and carbon stock in different land uses. A stepwise multilinear regression algorithm was used to derive the model that used Landsat derived NDVI, SAVI and ARVI as predicators. The predicted AGB ranged from 14.32 to 185.95 Mg ha-1 with an average of 148.78 Mg ha-1. The developed model that used combined vegetation indices showed correlation of R2 = 0.79 with an RMSE of 51.04 Mg ha-1. The present study also applied the empirical model (CO2FIX) to simulate the future scenario of carbon stock and carbon sequestration potential of the different land uses. The carbon stock potential of different land uses were 182.31 Mg ha-1, 158.91 Mg ha-1, 134.98 Mg ha-1, 169.26 Mg ha-1, 133.84, 89.95 Mg ha-1, 128.3 Mg ha-1 and 61.36 Mg ha-1 in Tropical forest, Subtropical forest, Temperate forest, Tropical plantation, Subtropical plantation, Temperate plantation, Shifting fallows and Agricultural land, respectively.
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