Current Science

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This study analyses the status and temporal dynamics of the tropical forest aboveground carbon (AGC) stocks. We used an integrated geospatial approach incorporating satellite synthetic aperture radar (SAR) data with a continuous forest inventory over a tenyear period utilizing statistical up-scaling procedure over a tropical deciduous forest of India as a case study. Logarithmic regression relationship was observed as the best fit model to derive the aboveground biomass from SAR backscatter coefficients with an absolute model accuracy of 80.61%. This was further employed to model the change in forest AGC stock from 2007 to 2016. Results show a significant decrease in carbon stock and the release of 918.5 Gg of carbon in the atmosphere from deforestation and forest degradation in the study area within the ten-year period.

Keywords

Carbon, Forest Aboveground Biomass, Regression, Synthetic Aperture Radar.
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