Abstract:

Based on combined data of a field survey and Landsat 5 Thematic Mapper (TM) images, we studied effects of six topographic correction models, including Teillet-regression, Cosine, C, SCS, SCS+C, and Minnaert, on aboveground forest biomass estimation of Phyllostachys praecox. Results showed: Except for Cosine and SCS correction methods, the rest four methods provided satisfactory correction results; Six topographic correction methods all improved correlations between TM data (TM4 and TM5) and aboveground biomass, as well as the correlations between aboveground biomass and three vegetation indices (RVI,NDVI and SAVI);Compared to the original image, the calibrated images by using the six correction methods improved to a certain degree biomass estimation performance, in particular, the Teillet correction method provided the highest accuracy, the correlation coefficient increased from 0.441 to 0.687 and the RMSE decreased by around 17%; Although Cosine correction method much improved the correlation coefficients between TM data (TM4 and TM5) and aboveground biomass, the Cosine-based correction result had lower estimation accuracy than the Teillet-based correction method did due to overcorrection with the Cosine-based method;Although the calibration methods improved the correlations between vegetation indices and Phyllostachys praecox aboveground biomass, the five vegetation indices were not selected as variables used in the models, this is probably due to the high density of Phyllostachys praecox.

Key words: topographic correction, Phyllostachys praecox, vegetation index, biomass, satellite-based estimation