ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING

Altanchimeg, T.; Renchin, T.; De Maeyer, P.; Natsagdorj, E.; Tseveen, B.; Norov, B.

The forest biomass is one of the most important parameters for the global carbon stock. Information on the forest volume, coverage and biomass are important to develop the global perspective on the CO 2 concentration changes. Objective of this research is to estimate forest biomass in the study area. The study area is Hangal sum, Bulgan province, Mongolia. Backscatter coefficients for vertical transmit and vertical receive (VV), for vertical transmit and horizontal receive (VH) from Sentinel data and Leaf Area Index (LAI) from Landsat data were used in the study area. We developed biomass estimation approach using ground truth data which is DBH, height and soil moisture. The coefficient α, β, δ, γ were found from the approach. The output map from the approach was compared with VV and VH, LAI data. The relationship between output map and VH data shows a positive result R 2 = 0.61. This study suggests that the biomass estimation using Remote sensing data can be applied in forest region in the North.

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Altanchimeg, T. / Renchin, T. / De Maeyer, P. / et al: ESTIMATION METHODOLOGY FOR FOREST BIOMASS IN MONGOLIA USING REMOTE SENSING. 2019. Copernicus Publications.

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