Mapping forest biomass using ALOS digital surface model and pan-sharpen image

In this study, we examine the applicability of digital surface model (DSM) generated from ALOS PRISM data for mapping forest above ground biomass (AGB). We obtained the digital canopy height model (DCHM) by calculating the differences between the PRISM DSM and surveying-based digital elevation model (DEM), and investigated the relationship between the DCHM values and field measured mean tree height and AGB in Northern Hokkaido, Japan. The results show a strong linear relationship between the field measured AGB and PRISM-DCHM (R = 0.872, n = 25). The RMSE and bias of the regression model, which were evaluated by the leave-one-out cross validation, are 38.1 t/ha (22 %) and -0.2 t/ha, respectively. Saturation at high AGB is not shown. We also demonstrate the wall-to-wall AGB mapping by using the regression model and the PRISM DCHM image. A pan-sharpen image generated from PRISM and AVNIR-2 images is utilized for forest cover mapping. The PRISM-based AGB values are generally reasonable except for high mountain areas. The relationship between the PRISM AGB and backscattering coefficient measured by L-band synthetic aperture radar (PALSAR) is consistent with the regression models discovered by the previous researches.