文献类型：期刊文献

英文题名：Error Analysis and Compensation for SINC Simplified Model in Forest Height Inversion

作者：Li, Wenmei[1] Zhang, Yu[1,2,3] Zhao, Lei[2,3] Chen, Huaihuai[1]

第一作者：Li, Wenmei

机构：[1] School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, China; [2] Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China; [3] Nfga, The Key Laboratory of Forestry Remote Sensing and Information System, Beijing, 100091, China

年份：2022

卷号：2022-July

起止页码：2542-2545

外文期刊名：International Geoscience and Remote Sensing Symposium (IGARSS)

收录：EI(收录号：20224313008517)

语种：英文

摘要：The errors of the theoretical model and the simplified SINC model in forest height inversion are analyzed. Simulation results show that the higher the tree height, the lower the kz value, the error between the theoretical and simplified SINC model is greater in inverting the forest height. When kz is 0.03 and forest height is 40 meters, the difference of the inversion height between theoretical and simplified SINC model can reach 1.5 meters. To address this problem, bisection iterative algorithm is utilized to eliminate or minimize the error between theoretical and simplified SINC forest height inversion model based on X-band airborne interferometric synthetic aperture radar (InSAR) coherence data. Lidar H-{100} CHM data are used to verify the effectiveness of bisection iterative algorithm. Compared with simplified SINC model, the performance of bisection iterative algorithm is better in retrieving the real value in the theoretical SINC model. The results show that the average height error of the bisection iterative algorithm is 0.5 m lower than that of the simplified SINC model in the inversion of forest parameters in the height range of 15-20 m. ? 2022 IEEE.