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Title: Modeling Discrete Forest Anisotropic Reflectance Over a Sloped Surface With an Extended GOMS and SAIL Model

Abstract

Topographic effects on canopy reflectance play a pivotal role in the retrieval of surface biophysical variables over rugged terrain. In this paper, we proposed a new canopy anisotropic reflectance model for discrete forests, Geometric Optical and Mutual Shadowing and Scattering-from-Arbitrarily-Inclined-Leaves model coupled with Topography (GOSAILT), which considers the effects of slope, aspect, geotropic nature of tree growth, multiple scattering, and diffuse skylight. GOSAILT-simulated areal proportions of four scene components (i.e., sunlit crown, shaded crown, sunlit background, and shaded background) were evaluated using the Geometric Optical model for Sloping Terrains (GOST) model. The canopy reflectances simulated by GOSAILT were validated against two reflectance data sets: Discrete anisotropic radiative transfer (DART) simulations and wide-angle infrared dual-model line/area array scanner (WIDAS) observations. Compared with a horizontal surface, the forest canopy reflectance over a steep slope (60°) is significantly distorted with absolute (relative) bias values of 0.048 (79.60%) and 0.056 (12.02%) for the red and near-infrared (NIR) bands, respectively. The GOSAILT-simulated component areal proportions show close agreements with GOST. Moreover, GOSAILT simulations have high overall accuracy (red band: coefficient of determination (R²) = 0.96; root-mean-square error (RMSE) = 0.003; and mean absolute percentage error (MAPE) = 3.91%; and NIR band: R² = 0.78, RMSEmore » = 0.019; MAPE = 3.94%) when compared with the DART simulations. In conclusion, these extensive validations indicate good performances of GOSAILT in canopy reflectance simulations over sloped surfaces.« less

Authors:
 [1];  [2];  [1];  [1];  [3];  [1];  [2];  [4]
+ Show Author Affiliations
  1. Chinese Academy of Sciences, Beijing (China); Univ. of Chinese Academy of Sciences, Beijing (China)
  2. Chinese Academy of Sciences, Beijing (China); Univ. of Chinese Academy of Sciences, Beijing (China); Joint Center for Global Change Studies, Beijing (China)
  3. Chinese Academy of Sciences, Beijing (China)
  4. Singapore-MIT Alliance for Research and Technology (Singapore)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1471234
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Geoscience and Remote Sensing
Additional Journal Information:
Journal Volume: 57; Journal Issue: 2; Journal ID: ISSN 0196-2892
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; canopy reflectance; diffuse skylight (SKYL); geometric optical (GO); radiative transfer (RT); sloped surface

Citation Formats

Wu, Shengbiao, Wen, Jianguang, Lin, Xingwen, Hao, Dalei, You, Dongqin, Xiao, Qing, Liu, Qinhuo, and Yin, Tiangang. Modeling Discrete Forest Anisotropic Reflectance Over a Sloped Surface With an Extended GOMS and SAIL Model. United States: N. p., 2018. Web. doi:10.1109/TGRS.2018.2863605.
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Wu, Shengbiao, Wen, Jianguang, Lin, Xingwen, Hao, Dalei, You, Dongqin, Xiao, Qing, Liu, Qinhuo, & Yin, Tiangang. Modeling Discrete Forest Anisotropic Reflectance Over a Sloped Surface With an Extended GOMS and SAIL Model. United States. https://doi.org/10.1109/TGRS.2018.2863605
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Wu, Shengbiao, Wen, Jianguang, Lin, Xingwen, Hao, Dalei, You, Dongqin, Xiao, Qing, Liu, Qinhuo, and Yin, Tiangang. Mon . "Modeling Discrete Forest Anisotropic Reflectance Over a Sloped Surface With an Extended GOMS and SAIL Model". United States. https://doi.org/10.1109/TGRS.2018.2863605. https://www.osti.gov/servlets/purl/1471234.
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@article{osti_1471234,
title = {Modeling Discrete Forest Anisotropic Reflectance Over a Sloped Surface With an Extended GOMS and SAIL Model},
author = {Wu, Shengbiao and Wen, Jianguang and Lin, Xingwen and Hao, Dalei and You, Dongqin and Xiao, Qing and Liu, Qinhuo and Yin, Tiangang},
abstractNote = {Topographic effects on canopy reflectance play a pivotal role in the retrieval of surface biophysical variables over rugged terrain. In this paper, we proposed a new canopy anisotropic reflectance model for discrete forests, Geometric Optical and Mutual Shadowing and Scattering-from-Arbitrarily-Inclined-Leaves model coupled with Topography (GOSAILT), which considers the effects of slope, aspect, geotropic nature of tree growth, multiple scattering, and diffuse skylight. GOSAILT-simulated areal proportions of four scene components (i.e., sunlit crown, shaded crown, sunlit background, and shaded background) were evaluated using the Geometric Optical model for Sloping Terrains (GOST) model. The canopy reflectances simulated by GOSAILT were validated against two reflectance data sets: Discrete anisotropic radiative transfer (DART) simulations and wide-angle infrared dual-model line/area array scanner (WIDAS) observations. Compared with a horizontal surface, the forest canopy reflectance over a steep slope (60°) is significantly distorted with absolute (relative) bias values of 0.048 (79.60%) and 0.056 (12.02%) for the red and near-infrared (NIR) bands, respectively. The GOSAILT-simulated component areal proportions show close agreements with GOST. Moreover, GOSAILT simulations have high overall accuracy (red band: coefficient of determination (R²) = 0.96; root-mean-square error (RMSE) = 0.003; and mean absolute percentage error (MAPE) = 3.91%; and NIR band: R² = 0.78, RMSE = 0.019; MAPE = 3.94%) when compared with the DART simulations. In conclusion, these extensive validations indicate good performances of GOSAILT in canopy reflectance simulations over sloped surfaces.},
doi = {10.1109/TGRS.2018.2863605},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
number = 2,
volume = 57,
place = {United States},
year = {Mon Sep 10 00:00:00 EDT 2018},
month = {Mon Sep 10 00:00:00 EDT 2018}
}
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Publisher's Version of Record
https://doi.org/10.1109/TGRS.2018.2863605
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Works referencing / citing this record:

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