文献类型：会议论文

英文题名：DYNAMIC ANALYSIS AND MODELING OF FOREST ABOVE-GROUND BIOMASS

作者：Tian, Xin[1] Li, Zengyuan[1] Guo, Yun[1] Yan, Min[1] Chen, Erxue[1] Su, Zhongbo[] van der Tol, Christiaan[] Ling, Feilong[]

第一作者：田昕

通信作者：Li, ZY[1]

机构：[1]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

会议论文集：IEEE Joint International Geoscience and Remote Sensing Symposium (IGARSS) / 35th Canadian Symposium on Remote Sensing

会议日期：JUL 13-18, 2014

会议地点：Quebec City, CANADA

语种：英文

外文关键词：Dynamic analysis and modeling; remote sensing; forest carbon; Biome-BGC model

年份：2014

摘要：Estimating forest above-ground biomass (AGB) and monitoring its variation are relevant for sustainable forest management, monitoring global change, carbon accounting, particularly for the Qilian Mountains (QMs), a water resource protection zone. In this work, the results of aboveground biomass (AGB) estimates from Landsat Thematic Mapper 5 (TM) images and field data from the fragmented landscape of the upper reaches of the Heihe River Basin (HRB), located in the Qilian Mountains of Gansu province in northwest China, are presented. An optimized k-Nearest Neighbor (k-NN) method was determined by varying both the mathematical formulation of the algorithm and remote sensing data input which resulted in 3,000 different model configurations. Following the suncanopy-sensor plus C (SCS+ C) topographic correction, performance of the optimized k-NN method was satisfied (R-2 = 0.59, RMSE=24.92 ton/ha) which indicated that the optimized k-NN is capable of operational applications of forest AGB estimates in regions where only a few inventory data are available. Afterwards, the calibrated BIOME-BGC was applied to simulate the carbon fluxes over QMs forests with satisfactory accuracy. Finally, the dynamic analysis and modeling of forest AGB was conducted based on the remotely sensed estimation of forest AGB and the annual forest AGB increment from the ecological process model.