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Open AccessArticle

Spectral Invariant Provides a Practical Modeling Approach for Future Biophysical Variable Estimations

Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China
Macro Agriculture Research Institute, College of Resource and Environment, Huazhong Agricultural University, 1 Shizishan Street, Wuhan 430070, China
Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN 47907, USA
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1508;
Received: 1 August 2018 / Revised: 15 September 2018 / Accepted: 16 September 2018 / Published: 20 September 2018
(This article belongs to the Special Issue Radiative Transfer Modelling and Applications in Remote Sensing)
This paper presents a simple radiative transfer model based on spectral invariant properties (SIP). The canopy structure parameters, including the leaf angle distribution and multi-angular clumping index, are explicitly described in the SIP model. The SIP model has been evaluated on its bidirectional reflectance factor (BRF) in the angular space at the radiation transfer model intercomparison platform, and in the spectrum space by the PROSPECT+SAIL (PROSAIL) model. The simulations of BRF by SIP agreed well with the reference values in both the angular space and spectrum space, with a root-mean-square-error (RMSE) of 0.006. When compared with the widely-used Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model on fPAR, the RMSE was 0.006 and the R2 was 0.99, which shows a high accuracy. This study also suggests the newly proposed vegetation index, the near-infrared (NIR) reflectance of vegetation (NIRv), was a good linear approximation of the canopy structure parameter, the directional area scattering factor (DASF), with an R2 of 0.99. NIRv was not influenced much by the soil background contribution, but was sensitive to the leaf inclination angle. The sensitivity of NIRv to canopy structure and the robustness of NIRv to the soil background suggest NIRv is a promising index in future biophysical variable estimations with the support of the SIP model, especially for the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) observations near the hot spot directions. View Full-Text
Keywords: spectral invariant; radiative transfer; canopy structure; leaf inclination angle; hot spot spectral invariant; radiative transfer; canopy structure; leaf inclination angle; hot spot
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Zeng, Y.; Xu, B.; Yin, G.; Wu, S.; Hu, G.; Yan, K.; Yang, B.; Song, W.; Li, J. Spectral Invariant Provides a Practical Modeling Approach for Future Biophysical Variable Estimations. Remote Sens. 2018, 10, 1508.

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