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Adaptive volume coherence optimization for forest height inversion in mountainous areas using innovative spaceborne L-band bistatic InSAR

文献类型：期刊论文

作者Wan, Jie1; Wang, Changcheng1; Lei, Yang2; Chen, Erxue3; Fu, Anmin5; Liu, Yu4; Zhao, Lei3; Liu, Xiaotong5; Xu, Jie5; Fan, Yaxiong3
刊名GISCIENCE & REMOTE SENSING
出版日期2026-12-31
卷号63期号:1页码:2637240
关键词Spaceborne bistatic interferometric SAR forest height volume coherence optimization frequency-domain information enhancement random volume over ground (RVoG) model
ISSN号1548-1603
DOI10.1080/15481603.2026.2637240
产权排序5
文献子类Article
英文摘要Spaceborne L-band bistatic interferometric synthetic aperture radar (InSAR) is an advanced remote sensing technology used for forest height inversion. It enables the detection of forest vertical structures and avoids the effects of temporal decorrelation. However, forest height inversion using single-polarization L-band bistatic InSAR in mountainous areas still faces several challenges. First, multi-parameter scattering models cannot be directly resolved using single-polarization InSAR observations. Second, ground scattering in L-band InSAR significantly affects the accuracy of forest height inversion. Moreover, mountainous terrain alters the interaction between InSAR signals and forest scatterers, further increasing the inversion uncertainty. To address such challenges, this paper proposes a frequency-domain information enhancement adaptive volume coherence optimization (Ada-VolOpt) method using single-polarization LuTan-1 bistatic InSAR data. The proposed method expands the observation space of InSAR through time-frequency analysis. Subsequently, based on frequency-domain information enhancement and the random volume over ground (RVoG) model, an adaptive volume coherence optimization method is proposed to overcome the adverse effects of significant ground scattering on forest height inversion in mountainous areas. Finally, forest height inversion is performed using a slope-adaptive scattering model. The effectiveness of the proposed method was validated across three test sites in China. A total area of 63.11 thousand km2 (6.31 million hectares) was used to test the proposed method, resulting in reliable forest height products. The forest height is estimated with an accuracy of 5.04 m for tropical forests, 3.41 m for mixed forests, and 2.44 m for boreal forests, respectively. Compared to the method that ignores ground contributions, the proposed method improves the accuracy by 8%, 10%, and 33%, respectively. This study provides a comprehensive benchmark evaluation of the performance of large-scale forest height inversion using LuTan-1 bistatic InSAR data.
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WOS关键词TANDEM-X ; SAR ; MODEL ; PARAMETERS ; VEGETATION ; MISSION
WOS研究方向Physical Geography ; Remote Sensing
语种英语
WOS记录号WOS:001705905500001
出版者TAYLOR & FRANCIS LTD
源URL[http://ir.igsnrr.ac.cn/handle/311030/221167]  
专题生态系统网络观测与模拟院重点实验室_外文论文
通讯作者Wang, Changcheng
作者单位1.Cent South Univ, Sch Geosci & Info Phys, Changsha, Peoples R China;
2.Chinese Acad Sci, Natl Space Sci Ctr, Beijing, Peoples R China;
3.Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing, Peoples R China;
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
5.Natl Forestry & Grassland Adm China, Acad Forest & Grass Inventory & Planning, Beijing, Peoples R China;
推荐引用方式
GB/T 7714		 Wan, Jie,Wang, Changcheng,Lei, Yang,et al. Adaptive volume coherence optimization for forest height inversion in mountainous areas using innovative spaceborne L-band bistatic InSAR[J]. GISCIENCE & REMOTE SENSING,2026,63(1):2637240.
APA Wan, Jie.,Wang, Changcheng.,Lei, Yang.,Chen, Erxue.,Fu, Anmin.,...&Song, Qing.(2026).Adaptive volume coherence optimization for forest height inversion in mountainous areas using innovative spaceborne L-band bistatic InSAR.GISCIENCE & REMOTE SENSING,63(1),2637240.
MLA Wan, Jie,et al."Adaptive volume coherence optimization for forest height inversion in mountainous areas using innovative spaceborne L-band bistatic InSAR".GISCIENCE & REMOTE SENSING 63.1(2026):2637240.

入库方式： OAI收割

来源：地理科学与资源研究所

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