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Article: Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction

TitleModeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction
Authors
KeywordsCanopy reflectance (CR) modeling
path length correction (PLC)
radiative transfer
remote sensing
topographic effects
Issue Date2017
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2017, v. 55, n. 8, p. 4597-4609 How to Cite?
AbstractSloping 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: R2 = 0.88 ; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: R2 = 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: R2 = 0.83 ; RMSE = 0.0053; RRMSE = 13%; NIR band: R2 = 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.
Persistent Identifierhttp://hdl.handle.net/10722/327139
ISSN
2023 Impact Factor: 7.5
2023 SCImago Journal Rankings: 2.403
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYin, Gaofei-
dc.contributor.authorLi, Ainong-
dc.contributor.authorZhao, Wei-
dc.contributor.authorJin, Huaan-
dc.contributor.authorBian, Jinhu-
dc.contributor.authorWu, Shengbiao-
dc.date.accessioned2023-03-31T05:29:05Z-
dc.date.available2023-03-31T05:29:05Z-
dc.date.issued2017-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2017, v. 55, n. 8, p. 4597-4609-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/327139-
dc.description.abstractSloping 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: R2 = 0.88 ; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: R2 = 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: R2 = 0.83 ; RMSE = 0.0053; RRMSE = 13%; NIR band: R2 = 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.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectCanopy reflectance (CR) modeling-
dc.subjectpath length correction (PLC)-
dc.subjectradiative transfer-
dc.subjectremote sensing-
dc.subjecttopographic effects-
dc.titleModeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2017.2694483-
dc.identifier.scopuseid_2-s2.0-85018874563-
dc.identifier.volume55-
dc.identifier.issue8-
dc.identifier.spage4597-
dc.identifier.epage4609-
dc.identifier.isiWOS:000406178800028-

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