Integrating SAR Backscatter, ICESAT GLAS Metrics and Allometric Functions towards an Improved Estimation of Forest Biomass

Abstract

In this study we present results of above-ground biomass (AGB) estimation for Sweden based on ALOS PALSAR backscatter data. The retrieval was performed within the framework of the BIOMASAR algorithm, and the validation was based on the Swedish National Forest Inventory (NFI) plots. The main focus, however, is about the modelling framework on the retrieval of AGB by integrating PALSAR backscatter, ICESAT GLAS metrics and allometric functions to improve the estimation of AGB. To evaluate the AGB retrieval, the average stem volume for each Swedish county from the NFI plots and the corresponding pixels covered by the inventory plots was computed. The result show an high agreement in terms of an RMSE of 8.2%, a bias of -1.9 m3/ha and a R2 value of 0.82. The results indicate that stem volume derived from ALOS PALSAR data can be used to support statistics for Sweden and spatially explicit give information on stem volume distribution across the country, albeit local fluctuations due to the still simplified modelling framework here implemented.