Next Article in Journal
Monitoring the Vulnerability of the Dam and Dikes in Germano Iron Mining Area after the Collapse of the Tailings Dam of Fundão (Mariana-MG, Brazil) Using DInSAR Techniques with TerraSAR-X Data
Next Article in Special Issue
Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth’s Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations
Previous Article in Journal
Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter
Previous Article in Special Issue
Simulation of Bidirectional Reflectance in Broken Clouds: From Individual Realization to Averaging over an Ensemble of Cloud Fields
Open AccessArticle

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

1
Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
2
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
3
Macro Agriculture Research Institute, College of Resource and Environment, Huazhong Agricultural University, 1 Shizishan Street, Wuhan 430070, China
4
Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
5
School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN 47907, USA
6
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1508; https://doi.org/10.3390/rs10101508
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
Show Figures

Figure 1

MDPI and ACS Style

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop