Estimating above ground biomass (agb) and tree density using sentinel-1 data

Abstract

Assessment of the forest above ground biomass (AGB) and tree density is essential for various studies related to forest structure, productivity, carbon cycle, atmospheric processes, climate change etc. including forest cover management activities and framing the conservation policies. The freely available C-band Sentinel-1 microwave data allows to estimate forest cover biomass at high spatial resolution; moreover, the Sentinel-2 optical data enables to integrate the biophysical attributes. In the current study, the AGB has been estimated in a Shorea robusta (sal) dominated forest cover in sub-tropical region employing the Sentinel-1 microwave data. The inventory of forest cover attributes has been collected in 40 sample plots, where the in-situ AGB was geo-statistically linked with the satellite observations. Employing the univariate linear regression, it has been observed that the microwave backscatter obtained in the VH band well explained (R2 = 0.63) the variability of the in-situ AGB in comparison to the backscatter received in VV band (R2 = 0.44) and optical data derived EVI image (R2 = 0.45). The predicted biomass map verified with the test data points indicated an accuracy of R2 = 0.45, with low RMSE (±17 tonnes/ha) and slight underestimation (bias = −0.024). However, the accuracy in tree density estimation obtained from the AGB map was observed much higher (R2 = 0.87). The field observed AGB varied between 88.56 tonnes/ha and 170.29 tonnes/ha, where the satellite data derived AGB estimated the range of 44.1 tonnes/ha and 249 tonnes/ha for the entire study area. Majority of the biomass was estimated in the range of 100–200 tonnes/ha, which was contributed by majority of the tree density region varying between 69/ha and 75/ha. However, few patches are observed to have much higher and lower AGB, which could be indicating the highly dense and less dense forest cover regions in the study area, respectively. The uniform AGB map indicates the selected region to be more homogenous forest cover area.