项目名称: 干涉SAR与LIDAR森林参数协同反演模型与方法
项目编号: No.40871173
项目类型: 面上项目
立项/批准年度: 2009
项目学科: 金属学与金属工艺
项目作者: 曹春香
作者单位: 中国科学院遥感与数字地球研究所
项目金额: 37万元
中文摘要: 为进一步加强主动微波和主动光学辐射机理和森林结构参数反演算法研究,实现两种主动遥感森林结构参数协同反演,提高单一传感器森林结构参数反演精度。在干涉SAR散射模型、小光斑LIDAR参数提取、大光斑LIDAR波形模拟的基础上,分析干涉SAR和LIDAR对森林结构及地形参数的敏感性,在DEM和林冠两个层次的几何光学模型的基础上,考虑多尺度效应,实现干涉SAR和LIDAR综合反演森林参数,比单一数据反演有5-10%的精度提高。选择干涉SAR和LIDAR两种数据的综合应用,可望从平面到垂直分布全面提高森林结构参数的探测能力。
中文关键词: 森林结构参数;干涉SAR和LIDAR;尺度效应;协同反演
英文摘要: In order to accelerate the study of radiation mechanism and forest structure parameters inversion based on active microwave and active optical, implement the synergistic inversion of forest structure parameters based on these two kind of sensors,improve the accuracy of each sensor. On the basis of InSAR scattering model, parameter extraction of small spot LiDAR and the waveform simulation of large spot LiDAR, their sensitivity of to forest structure and topography parameters was analyzed. On the basis of the geometrical optics model on DEM and canopy level, considering the effect of multi-scale, a InSAR and LiDAR synergistically inversion algorithm was proposed. This new algorithm improved the accuracy 5-10% compared with the single data inversion. The synergistic applications of InSAR and LiDAR were expected to improve the detection capacity of forest structural parameters horizontally and vertically.
英文关键词: Forest structure parameters; interferometric SAR and LIDAR; the scale effect; synergistic inversion