IMHE OpenIR  > 数字山地与遥感应用中心
Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction; Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction
Yin, Gaofei1; Li, Ainong1; Zhao, Wei1; Jin, Huaan1; Bian, Jinhu1; Wu, Shengbiao2
Corresponding AuthorLi, Ainong ; Li, Ainong
2017 ; 2017
Source PublicationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING ; IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892 ; 0196-2892
EISSN1558-0644 ; 1558-0644
Volume55Issue:8Pages:4597-4609
SubtypeArticle ; Article
Abstract

Sloping terrain induces distortion of canopy reflectance (CR), and the retrieval of biophysical variables from remote sensing data needs to account for topographic effects. We developed a 1-D model (the path length correction (PLC)-based model) for simulating CR over sloping terrain. The effects of sloping terrain on single-order and diffuse scatterings are accounted for by PLC and modification of the fraction of incoming diffuse irradiance, respectively. The PLC model was validated via both Monte Carlo and remote sensing image simulations. The comparison with the Monte Carlo simulation revealed that the PLC model can capture the pattern of slope-induced reflectance distortion with high accuracy (red band: R-2 = 0.88; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: R-2 = 0.79; RMSE = 0.041; RRMSE = 16%). The comparison of the PLC-simulated results with remote sensing observations acquired by the Landsat8-OLI sensor revealed an accuracy similar to that with the Monte Carlo simulation (red band: R-2 = 0.83; RMSE = 0.0053; RRMSE = 13%; NIR band: R-2 = 0.77; RMSE = 0.023; RRMSE = 8%). To further validate the PLC model, we used it to implement topographic normalization; the results showed a large reduction in topographic effects after normalization, which implied that the PLC model captures reflectance variations caused by terrain. The PLC model provides a promising tool to improve the simulation of CR and the retrieval of biophysical variables over mountainous regions.

;

Sloping terrain induces distortion of canopy reflectance (CR), and the retrieval of biophysical variables from remote sensing data needs to account for topographic effects. We developed a 1-D model (the path length correction (PLC)-based model) for simulating CR over sloping terrain. The effects of sloping terrain on single-order and diffuse scatterings are accounted for by PLC and modification of the fraction of incoming diffuse irradiance, respectively. The PLC model was validated via both Monte Carlo and remote sensing image simulations. The comparison with the Monte Carlo simulation revealed that the PLC model can capture the pattern of slope-induced reflectance distortion with high accuracy (red band: R-2 = 0.88; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: R-2 = 0.79; RMSE = 0.041; RRMSE = 16%). The comparison of the PLC-simulated results with remote sensing observations acquired by the Landsat8-OLI sensor revealed an accuracy similar to that with the Monte Carlo simulation (red band: R-2 = 0.83; RMSE = 0.0053; RRMSE = 13%; NIR band: R-2 = 0.77; RMSE = 0.023; RRMSE = 8%). To further validate the PLC model, we used it to implement topographic normalization; the results showed a large reduction in topographic effects after normalization, which implied that the PLC model captures reflectance variations caused by terrain. The PLC model provides a promising tool to improve the simulation of CR and the retrieval of biophysical variables over mountainous regions.

KeywordCanopy Reflectance (Cr) Modeling Canopy Reflectance (Cr) Modeling Path Length Correction (Plc) Path Length Correction (Plc) Radiative Transfer Radiative Transfer Remote Sensing Remote Sensing Topographic Effects Topographic Effects
WOS HeadingsScience & Technology ; Science & Technology ; Physical Sciences ; Physical Sciences ; Technology ; Technology
DOI10.1109/TGRS.2017.2694483 ; 10.1109/TGRS.2017.2694483
WOS Subject ExtendedGeochemistry & Geophysics ; Geochemistry & Geophysics ; Engineering ; Engineering ; Remote Sensing ; Remote Sensing ; Imaging Science & Photographic Technology ; Imaging Science & Photographic Technology
Indexed BySCI ; SCI
WOS KeywordLEAF-AREA INDEX ; LEAF-AREA INDEX ; RADIATIVE-TRANSFER MODEL ; RADIATIVE-TRANSFER MODEL ; LANDSAT TM IMAGES ; LANDSAT TM IMAGES ; CLEAR-SKY DAYS ; CLEAR-SKY DAYS ; TOPOGRAPHIC CORRECTION ; TOPOGRAPHIC CORRECTION ; COMPLEX TERRAIN ; COMPLEX TERRAIN ; SOLAR-RADIATION ; SOLAR-RADIATION ; SURFACE REFLECTANCE ; SURFACE REFLECTANCE ; RUGGED TERRAIN ; RUGGED TERRAIN ; MODIS DATA ; MODIS DATA
Language英语 ; 英语
Quartile2区 ; 2区
TOP是 ; 是
WOS SubjectGeochemistry & Geophysics ; Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Engineering, Electrical & Electronic ; Remote Sensing ; Remote Sensing ; Imaging Science & Photographic Technology ; Imaging Science & Photographic Technology
WOS IDWOS:000406178800028 ; WOS:000406178800028
Funding OrganizationNational Natural Science Foundation of China(41601403 ; National Natural Science Foundation of China(41601403 ; China Postdoctoral Science Foundation(2016M592712) ; China Postdoctoral Science Foundation(2016M592712) ; State Key Laboratory of Remote Sensing Science(OFSLRSS201613) ; State Key Laboratory of Remote Sensing Science(OFSLRSS201613) ; Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (CAS)(SDSQB-2015-02) ; Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (CAS)(SDSQB-2015-02) ; CAS ; CAS ; Youth Foundation of the Institute of Mountain Hazards and Environment, CAS ; Youth Foundation of the Institute of Mountain Hazards and Environment, CAS ; 41631180 ; 41631180 ; 41571373) ; 41571373)
Citation statistics
Cited Times:19[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/18903
Collection数字山地与遥感应用中心
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Res Ctr Digital Mt & Remote Sensing Applicat, Chengdu 610041, Sichuan, Peoples R China
2.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Yin, Gaofei,Li, Ainong,Zhao, Wei,et al. Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction, Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2017, 2017,55, 55(8):4597-4609, 4597-4609.
APA Yin, Gaofei,Li, Ainong,Zhao, Wei,Jin, Huaan,Bian, Jinhu,&Wu, Shengbiao.(2017).Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,55(8),4597-4609.
MLA Yin, Gaofei,et al."Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 55.8(2017):4597-4609.
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