Comparative Analysis of HJ-1B CCD2 and SPOT4 HRVIR Data for Aboveground Biomass Estimation in Forest Stands

The paper presents a method for estimating the aboveground biomass of forest stands using vegetation index and principle component analysis methods; and in a case study in the Mt. Gongga region, combines remote sensing data (HJ-1B CCD2 and SPOT4 HRVIR) with field measurements to evaluate the method. The accuracies of aboveground biomass estimation were assessed through the cross validation method, and comparative analysis was done for HJ-1B CCD2 and SPOT4 HRVIR sensors in order to evaluate their abilities and differences on the estimation of aboveground biomass in forest stands. The results showed that the retrieval model of aboveground biomass based on the simple ratio vegetation index performed better than other vegetation indices, and the performance of HJ-1B CCD2 was superior to SPOT4 HRVIR in a single linear regression model. As for the model of biomass estimation using multiple vegetation indices, their differences on the estimation of aboveground biomass were not apparent, according to the results of cross validation for HJ-1B CCD2 (r: 0.5458; RMSE: 27.8114 t·ha) and SPOT4 HRVIR sensors (r: 0.5634; RMSE: 27.1696 t·ha). Moreover, the performance of HJ-1B CCD2 was better than SPOT4 HRVIR for the principle component analysis method. In general, both of HJ-1B CCD2 and SPOT4 HRVIR sensors could satisfy the need for aboveground biomass estimation in Mt. Gongga region. Additionally, the results of HJ-1B CCD2 data were found to outperform SPOT4 HRVIR.