Remote Sensing Retrieval Of China’s Forest Biomass Based On The Climatic Elements

Carbon cycling in terrestrial ecosystems is an important component of the global carbon cycle and plays a pivotal role in the global warming process. As the main terrestrial ecosystems, terrestrial vegetation biomass accounted for the total biomass of the forest85%to90%, which is an important indicator of forest carbon sequestration, and also an important parameter to assess forest carbon budget. Thus, the inversion of forest biomass becomes one of the hottest issues in today’s global change research. With the development of remote sensing technology as well as the study of forest biomass research, the inversion of large scale forest biomass has become possible, domestic and foreign scholars have conducted a lot of research. However, most of these studies using the statistical model method, its applicability limitations of time and space. This study is based allometric and resource limitations theory, structure of forest area density of trees and wood density factor establish allometric and resource limitations biomass model, the study on the regional scale model parameterization methods to analyze the impact of factors, in support of surface types,elevation and other prior knowledge, the establishment of multisource utilization of satellite remote sensing data and climate data inversion of aboveground biomass of forest coverage plan. This paper completed the following tasks:1. GLAS data extraction methods. GLAS extraction of forest because of the terrain height has an important impact, and therefore the use of topographic correction method for optimal Chinese forest actual maximum tree height on the basis of previous studies.2. Tree height optimization model. The maximum height is an important parameter of allometric and resource limitations biomass model, tree height model is to study the basis of estimates of forest biomass, Existing tree height models can calculate the maximum potential Chinese forest tree height, but cannot accurately reflect the Chinese forest actual tree height, so the inversion of forest biomass does not make much sense. Therefore, the use of discrete data GLAS tree height model parameters were optimized to the inversion of the actual maximum continuous Chinese forest tree height, and verified and contrasted. The results show that the inversion of China’s largest forest tree height and tree height GLAS has a good consistency.(R2=0.71, RMSE=4.48m)3. Allometric and resource limitations forest biomass model. Based on previous studies, we built on an allometric and resource limitations forest biomass model to determine the inversion biomass equations. Finally, Chinese forest biomass is inversed by using remote sensing data, climate data, geography data, and other related data.4. Biomass optimization model. Biomass data measured using ground biomass model parameter optimization, so the inversion of the actual area covered by forest biomass Chinese continuous distribution. The results showed that the measured biomass and forest biomass in China retrieved with relatively better consistency, better able to reflect the spatial distribution of forest biomass in China.(R2=0.52, RMSE=25.28t*hm2)...