Estimating Forest Biomass Based On Microwave Remote Sensing

Forest, as the major component of the terrestrial ecological system, and the change of forest biomass reflects the influences of forest succession, climate change and human interference,and it has significant meaningful to the study of carbon cycle and climate change in global terrestrial ecological system. At the same time, biomass is one of the important biophysical parameters in forest researches; as a result, it is a popular research on forest biomass. With the flourish development of multiple platforms, data resource, high-resolution remote sensing sensors, it is possible to do researches on forest biomass by the way of high precision and quantity.This paper uses Daxing'anling Tahe Forest and Amuer Forest as the trial area,and the study is based on the technological methods of extracting forest information and ALOS PALSAR L-band HH polarization, using Linear Regression which is based on the Plot data of national forest inventory, geographic factors. Based on the field survey data, correlations between the ALOS PALSAR L-band HH polarization data and Daxing'anling region's forest parameters of each component were systematically analyzed, and the optimal inversion was conducted with simulated forest biomass models, i.e., simple linear model, exponential model, and model with terrain factors included. The result showed that the backscattering coefficient related with the total forest biomass most intimately, followed by the trunk's biomass, suggesting L-HH data could estimate the total aboveground biomass of trees. Among the three models passed the F test,D-W test and multiple co linearity test, the model included the terrain factors greatly reduced the biomass estimation error, with the accuracy reached 0.851and fitting precision reaches 0.781194, and the inversion result coincided with the actual situation best. It was forecasted that under the 41.5°incidence angle L-band HH polarization, the biomass saturation point was at about 15.4 kg-m-2 in Tahe and Amuer forest bureaus of Daxing'anling.