Linking Kubelka-Munk and recollision probability theories for radiative transfer simulations in turbid canopy
文献类型：期刊论文
| 作者 | Yang, Peiqi5,6; Verhoef, Wout4; Fang, Hongliang2,3,5; Fan, Wenjie1; van der Tol, Christiaan4 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2025-05-01 |
| 卷号 | 321页码:114680 |
| 关键词 | Radiative transfer models KM theory P -theory Spectral invariant Analytical solution |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2025.114680 |
| 产权排序 | 4 |
| 文献子类 | Article |
| 英文摘要 | Radiative transfer (RT) theories formulate vegetation radiative transfer models (RTMs) that link the biophysical properties of vegetation with remote sensing signals. Compared to classical RT theories, the recollision probability theory (also known as p-theory) is distinctive as it predicts some optical properties of vegetation canopies using fewer spectral invariants and simpler mathematical functions. This theory commonly employs an effective recollision probability (pE) that is assumed to spectrally independent for vegetation-photon interactions, to describe the absorptive and reflective properties of a vegetation canopy at any wavelength. Most p-theory studies approximate pE using the canopy-average recollision probability at different locations within the canopy, enabling its estimation based on canopy structural properties. However, the canopy-average recollision probability and pE different meanings. As an effective parameter, pE should be obtained by fitting the p-theory formulations, as done in previous studies using simulated and measured canopy optical properties for specific canopies. These studies have empirically shown that pE generally increases with canopy leaf area and exhibits some spectral variability. Building on this empirical evidence, we explore an analytical expression for pE and its dependence on leaf optical and canopy structural properties. In this study, we link the recollision probability theory with the classical Kubelka-Munk (KM) theory, a twostream RT theory which predicts canopy optical properties by solving the corresponding differential equations. By using the KM theory as applied in the SAIL model, we derive the analytical expression for the absorptance of vegetation canopies illuminated by diffuse radiation. This absorptance is then used to derive pE based on its relationship with absorptance in the p-theory. In this way, we express pE as a function of leaf albedo (omega l) and canopy leaf area index (LAI, L). Our findings demonstrate that, for a given canopy, pE could be approximated as a function of LAI (pL) by using Taylor series expansion. This approximation aligns with Stenberg's, 2007 canopyaverage recollision probability, although the two have different meanings and are derived using different approaches. More importantly, we demonstrate that pE increases with leaf albedo and that the difference between the LAI-based and true spectrally-dependent pE scales with root & sdot;L, reaching up to 0.15. Consequently, the use of LAI-based pE in the p-theory could lead to some errors in simulating canopy absorptive and reflective properties. This study bridges two widely used RT theories and presents an estimation of pE. We provide an analytical expression for spectrally-dependent pE for turbid canopies, and mathematically demonstrate how it can be approximated by spectrally-independent pL. These findings clarify the rationale and limitations of assuming spectral invariance in the p-theory. |
| URL标识 | 查看原文 |
| WOS关键词 | SPECTRAL INVARIANTS ; MULTIPLE-SCATTERING ; VEGETATION ; LIGHT ; LEAF |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001438363900001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/213298]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Yang, Peiqi |
| 作者单位 | 1.Peking Univ, Inst RS & GIS, Sch Earth & Space Sci, Beijing 100871, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China; 3.Chinese Acad Sci, LREIS, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 4.Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, POB 217, NL-7500 AE Enschede, Netherlands; 5.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Peoples R China; 6.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Yang, Peiqi,Verhoef, Wout,Fang, Hongliang,et al. Linking Kubelka-Munk and recollision probability theories for radiative transfer simulations in turbid canopy[J]. REMOTE SENSING OF ENVIRONMENT,2025,321:114680. |
| APA | Yang, Peiqi,Verhoef, Wout,Fang, Hongliang,Fan, Wenjie,&van der Tol, Christiaan.(2025).Linking Kubelka-Munk and recollision probability theories for radiative transfer simulations in turbid canopy.REMOTE SENSING OF ENVIRONMENT,321,114680. |
| MLA | Yang, Peiqi,et al."Linking Kubelka-Munk and recollision probability theories for radiative transfer simulations in turbid canopy".REMOTE SENSING OF ENVIRONMENT 321(2025):114680. |
入库方式： OAI收割
来源：地理科学与资源研究所
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