不同波长极化SAR数据水云模型森林生物量反演对比分析  

Comparative analysis of forest biomass retrieval from water cloud model(WCM)of polarized SAR data with different wavelengths

作　　者：姬永杰[1] 徐昆鹏 张王菲 史建敏 张甫香 Ji Yongjie;Xu Kunpeng;Zhang Wangfei;Shi Jianmin;Zhang Fuxiang(School of Geography and Ecotourism,Southwest Forestry University,Kunming 650224,Yunnan,China;Institute of Forest Resources Information Technique,Chinese Academy of Forestry,Beijing 100091,China;College of Forestry,Southwest Forestry University,Kunming 650224,Yunnan,China)

机构地区：[1]西南林业大学地理与生态旅游学院,云南昆明650224 [2]中国林业科学研究院资源信息研究所,北京100091 [3]西南林业大学林学院,云南昆明650224

出　　处：《北京林业大学学报》2023年第2期24-33,共10页Journal of Beijing Forestry University

基　　金：国家自然科学基金项目(41871279、32160365、42161059、31860240)。

摘　　要：【目的】水云模型(WCM)是一种采用SAR数据反演森林地上生物量(AGB)应用较为广泛的半经验模型,探索将不同波长、极化方式、极化信息等引入WCM,以期为提高森林AGB反演精度提供科学依据。【方法】本文以X、C、L、P波段多频极化SAR数据为数据源,首先将各波长各极化后向散射系数用于WCM进行森林AGB反演,对比其反演精度;接着采用极化分解分量构建地体散射比参数,并将其引入WCM发展为极化水云模型(PolWCM),同时对比分析其在X、C、L、P波段森林AGB的反演结果。【结果】(1)在X、C、L、P 4个波段中,除X波段外,将HV极化后向散射系数代入WCM进行森林AGB反演,精度均高于基于其他极化通道后向散射系数的反演结果;且长波长(L和P)的反演精度高于短波长(X和C)的反演精度。在L波段,将HV极化后向散射系数代入WCM进行森林AGB反演,R2和RMSE分别为0.46和18.00 t/hm2;P波段HV极化反演结果的R2和RMSE分别为0.43和21.18 t/hm2。(2)将极化信息以地体散射比的形式引入WCM,PolWCM模型在X、C、L、P各个波段均可提高反演精度,反演结果的RMSE值分别为24.90、24.71、17.70和18.08 t/hm2。【结论】采用WCM进行森林AGB反演具有极化、波长依赖性,其中将L波段HV极化后向散射系数代入WCM进行森林AGB反演时精度最优;将极化信息以地体散射比的方式引入WCM,发展PolWCM,可以明显提高森林AGB的反演精度。[Objective]Water cloud model(WCM)is a semi empirical model using SAR data to retrieve forest aboveground biomass(AGB).The objective of this study is to explore the capability of introducing different wavelengths at different polarization channels into WCM for forest AGB inversion.And through the exploration,it is expected to provide scientific reference for improving the accuracy of forest AGB retrieval.[Method]In this paper,firstly,we applied WCM in forest AGB estimation at X-,C-,L-and Pband with HH,HV,and VV polarizations,respectively,and their results were compared and analyzed.Then a parameter named the ratio of surface scattering power and volume scattering power was constructed based on polarization decomposition components and embedded in WCM,here we named it PolWCM.The potential of PolWCM on forest AGB estimation was explored by X-,C-,L-and P-band polarimetric decomposition components.[Result](1)HV backscattering coefficients showed best performance in forest AGB estimation using WCM at C-,L-and P-band,among them,L-and P-band performed better than Xand C-band(R~2=0.46,RMSE=18.0 t/ha for L-band and R~2=0.43,RMSE=21.18 t/ha for P-band).(2)PolWCM performed better than WCM for forest AGB estimation at X-,C-,L-and P-band,respectively.Their RMSE values for X-,C-,L-and P-band were 24.90,24.71,17.70 and 18.08 t/ha,respectively.[Conclusion]The forest AGB estimation of WCM shows obvious dependence on wavelength and polarization,HV backscatter coefficients at L-band perform best in forest AGB estimation.Polarimetric information embedded in WCM through the ratio of surface scattering power and volume scattering power can improve the forest AGB estimation accuracy.

关 键 词：X、C、L、P波段SAR数据 森林地上生物量 极化 地体散射比 

分 类 号：S771.8[农业科学—森林工程]