A Radiative Transfer Model for Heterogeneous Agro-Forestry Scenarios

• Published in: IEEE transactions on geoscience and remote sensing Vol. 54; no. 8; pp. 4613 - 4628
• Main Authors: Yelu Zeng, Jing Li, Qinhuo Liu, Huete, Alfredo R., Gaofei Yin, Baodong Xu, Weiliang Fan, Jing Zhao, Kai Yan, Xihan Mu
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agro-forestry scenario; Atmospheric modeling; Band spectra; Biological system modeling; Boundaries; canopy structure; Computational modeling; Computer simulation; Discrete cosine transforms; Freshwater; hemispherical–directional reflectance factor (HDRF); heterogeneity; Mathematical models; Radiative transfer; radiative transfer (RT); Reflectance; Reflectivity; Remote sensing; Scattering; Solid modeling; China, People's Rep., Heihe R. basin; China, People's Rep; hemispherical–directional reflectance factor (HDRF); radiative transfer (RT); heterogeneity; Agro-forestry scenario; canopy structure
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2016.2547326

Landscape heterogeneity is a common natural phenomenon but is seldom considered in current radiative transfer (RT) models for predicting the surface reflectance. This paper developed an analytical RT model for heterogeneous Agro-Forestry scenarios (RTAF) by dividing the scenario into nonboundary regions (NRs) and boundary regions (BRs). The scattering contribution of the NRs can be estimated from the scattering-by-arbitrarily-inclined-leaves-with-the-hot-spot-effect model as homogeneous canopies, whereas that of the BRs is calculated based on the bidirectional gap probability by considering the interactions and mutual shadowing effects among different patches. The multiangular airborne observations and discrete-anisotropic-RT model simulations were used to validate and evaluate the RTAF model over an agro-forestry scenario in the Heihe River Basin, China. The results suggest that the RTAF model can accurately simulate the hemispherical-directional reflectance factors (HDRFs) of the heterogeneous scenarios in the red and near-infrared (NIR) bands. The boundary effect can significantly influence the angular distribution of the HDRFs and consequently enlarge the HDRF variations between the backward and forward directions. Compared with the widely used dominant cover type (DCT) and spectral linear mixture (SLM) models, the RTAF model reduced the maximum relative error from 25.7% (SLM) and 23.0% (DCT) to 9.8% in the red band and from 19.6% (DCT) and 13.7% (SLM) to 8.7% in the NIR band. The RTAF model provides a promising way to improve the retrieval of biophysical parameters (e.g., leaf area index) from remote sensing data over heterogeneous agro-forestry scenarios.