The Research On The Remote Sensing Model For Forest Biomass In Daxingan Mountains

Forest biomass reflects the forest management level and the potential for forest exploitation. In addition, forest biomass indicates the complex relation between material cycle and energy flow in forest and environment. So the research on forest biomass has great value in theory and practice.Using the Landsat 5 TM images in 2002 as source data, we constructed seven individual tree biomass model based on the data from field work and fixed plots in Tahe and Amur forest region in Daxiangan Mountains. The remote sensing biomass model between TM images and data from forest fixed plots was built by multiple linear regression and BP neutral net. 20 variables of remote sensing factors and topographical factors were analyzed by stepwise regression and the two variables -t452 and pca1 were determined. The model was tested by independent sample data.The result showed that R in multiple linear regression model was 0.764 and the model passed the F test, D-W test and multiple collinearity test. In the independent sample estimation, the neutral net model with the precision of 91.25% was significantly higher than multiple linear regression model with the precision of 81.02%. Although the "black-box" neutral net model could not give the analytical equation, this kind of model with high precision might be applied to estimate the forest biomass in large forest biomass.