A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface
文献类型：期刊论文
| 作者 | He, Min1,2,3; Wen, Jianguang1,3; Wu, Shengbiao1; Meng, Lei4; Lin, Xingwen5; Han, Yuan1,3; You, Dongqin1; Tang, Yong1; Liu, Qinhuo1,3 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2024 |
| 卷号 | 62页码:18 |
| ISSN号 | 0196-2892 |
| 关键词 | Forestry Reflectivity Indexes Surface topography Biological system modeling Atmospheric modeling Vegetation mapping Bidirectional reflectance effective leaf area index (LAI) geometrical optical model (GOM) remote sensing radiative transfer (RT) scattering by arbitrarily inclined leaves (SAIL) topography |
| DOI | 10.1109/TGRS.2023.3343876 |
| 通讯作者 | Wen, Jianguang(wenjg@radi.ac.cn) |
| 英文摘要 | In this study, a novel algorithm for high spatial resolution leaf area index (LAI) retrieval, specifically tailored for mountain forests, has been developed. As an essential climate variable, LAI has been incorporated into many ecohydrological process simulation models; however, the majority of the algorithms are developed on the assumption of flat terrain. Previous studies have proved that neglecting the influence of topography may introduce significant biases and uncertainties into LAI estimates particularly in rugged areas. As an important species in the mountain area, forests occupy a large land area worldwide; nevertheless, it is still challenging to obtain high-quality LAIs from satellite images due to their complex canopy structures. In spite of numerous attempts having been made to address such issues with topographic correction (TC) or mountain canopy reflectance models, few algorithms were actually available for LAI estimation of mountain forests. Here, we try to employ the geometric optical and mutual shadowing and scattering from the arbitrarily inclined-leaves model coupled with the topography (GOSAILT) model to retrieve forest LAI over complex terrain. GOSAILT is a combined model that incorporates the radiative transfer model (RTM) into the geometrical optical model (GOM) on the slope surface. It is capable of characterizing the bidirectional reflectance of both discrete and continuous canopies. The validations against computer-simulated LAIs reveal root-mean square errors (RMSEs) being 1.7160 and 0.6260, corresponding to terrain-ignored scenario and terrain-considered scenario, respectively. Besides, the validation against in situ LAIs demonstrated that the RMSE is 0.9262 over flat terrain and 0.6402 over sloped terrain. This evidence underscores the robust performance of the newly developed algorithm. |
| WOS关键词 | PHOTOSYNTHETICALLY ACTIVE RADIATION ; TOPOGRAPHIC CORRECTION ; GLOBAL PRODUCTS ; PART 1 ; VEGETATION ; MODEL ; CANOPY ; REFLECTANCE ; MODIS ; FRACTION |
| 资助项目 | National Key Research and Development Program of China |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:001136708200005 |
| 资助机构 | National Key Research and Development Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202208]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wen, Jianguang |
| 作者单位 | 1.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100101, Peoples R China 5.Zhejiang Normal Univ, Coll Geog & Environm Sci, Jinhua 321004, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Min,Wen, Jianguang,Wu, Shengbiao,et al. A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2024,62:18. |
| APA | He, Min.,Wen, Jianguang.,Wu, Shengbiao.,Meng, Lei.,Lin, Xingwen.,...&Liu, Qinhuo.(2024).A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,62,18. |
| MLA | He, Min,et al."A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 62(2024):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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