简缩极化SAR数据支持的森林地上生物量反演  

Retrieval of forest aboveground biomass via compact polarimetric SAR data

作　　者：赵含 张王菲 姬永杰 韩宗涛 ZHAO Han;ZHANG Wangfei;JI Yongjie;HAN Zongtao(College of Forestry,Southwest Forestry University,Kunming 650224,China;Weihai Wuzhou Navi-Tech,Weihai 264400,China)

机构地区：[1]西南林业大学林学院,昆明650224 [2]威海五洲卫星导航科技股份有限公司,威海264400

出　　处：《遥感学报》2024年第9期2416-2426,共11页NATIONAL REMOTE SENSING BULLETIN

基　　金：国家自然科学基金(编号:42161059,32160365,31860240);中国林业科学研究院中央级公益性科研院所基本科研业务费专项资金项目(编号:CAFYBB2021SY006)。

摘　　要：简缩极化CP(Compact Polarimetry) SAR作为一种国内外学者高度关注的新型SAR,目前鲜有将其应用于森林地上生物量AGB(Above Ground Biomass)反演研究。在全球气候变化及“双碳”目标下,森林AGB的精确反演是当下亟待解决的热点问题。为探究CP SAR数据在森林AGB反演中的可行性,以云南省昆明市宜良县小哨林区为研究区,提取水平线性CP Stokes1模式、垂直线性CP Stokes2模式、π/4线性模式及CTLR模式的4种CP SAR数据,并基于波的二分性原理,分别提取了各种模式的若干SAR参数,利用基于快速迭代特征选择的K最近邻(KNN-FIFS)算法开展了研究。结果表明:基于CTLR模式的森林AGB反演结果最优,R^(2)=0.52,RMSE=13.02 t/hm^(2);联合4组CP SAR数据的森林AGB反演结果精度有明显提升,R^(2)=0.58,RMSE=12.16 t/hm^(2);KNN-FIFS适合于采用CP SAR参数进行森林AGB反演,其反演结果与采用全极化SAR数据进行反演的差别并不明显。本研究提取的CP SAR参数中,线极化度m_(l)、倾斜角45°或135°时的线极化分量功率值g_(2)等特征在森林AGB反演中表现出较高的适用性,说明其能更好的表征森林信息。Compact Polarimetric Synthetic Aperture Radar(CP-SAR) is a new type SAR that has attracted most researchers,especially the application of CP-SAR data.However,only a few studies have explored the application of forest aboveground biomass(AGB) retrieval using CP-SAR information.In consideration of the global climate change and the goals of achieving peak carbon emissions and carbon neutrality,the accurate inversion of forest AGB has become urgent in recent years.This study aims to explore the feasibility of CP-SAR data applied in forest AGB inversion.In this study,we took Xiaoshao Forest Farm in Yiliang County as the test site,using simulated CP-SAR data from quad polarimetric GF-3 data with four modes,i.e.,Stokes1 mode(Stokes-related parameters were extracted from horizontal transmission and dual-orthogonal linear receipt),Stokes2 mode(Stokes-related parameters were extracted from vertical transmission and dual-orthogonal linear receipt),π/4 linear mode(π/4 transmission and orthogonal linear receipt),and CTLR mode(circular transmission and dual-orthogonal linear receipt),to explore the potential of CP-SAR data in forest AGB estimation.First,several SAR parameters of various modes were extracted on the basis of wave dichotomy theory,then the k-nearest neighbor algorithms with fast iterative feature selection(KNN-FIFS) method were applied to estimate the forest AGB in the study area.Finally,the accuracy of the KNN-FIFS inversion results were verified using the leave-one-out cross-validation methods.An R^(2) of 0.28 and an RMSE of 16.36 t/hm^(2) were acquired for the forest AGB estimation using Stokes1 mode,and the corresponding optimal feature combination was γ,μ_l,δ;for Stokes2 mode,an R^(2) of 0.35 and an RMSE of 14.96 t/hm^(2) were obtained,and the corresponding optimal feature combination was P_2,γ,m_1,P_1.Compared with Stokes1 and Stokes2 modes,the similar performance was shown inπ/4 mode for forest AGB estimation;the R^(2) value was 0.34,while the RMSE was 15.21 t/hm^(2),and the corresponding optimal fe

关 键 词：遥感 森林AGB GF-3 STOKES 简缩极化SAR KNN-FIFS 

分 类 号：S771.8[农业科学—森林工程] P2[农业科学—林学]