A canopy radiative transfer model suitable for heterogeneous Agro-Forestry scenes

Landscape heterogeneity is a common natural phenomenon but is seldom considered in current radiative transfer models for predicting the surface reflectance. This paper developed an analytical Radiative Transfer model for heterogeneous Agro-Forestry scenes (RTAF). The scattering contribution of the non-boundary regions can be estimated from the SAILH model as homogeneous canopies, whereas that of the boundary regions is calculated based on the bidirectional gap probability by considering the interactions and mutual shadowing effects among different patches. The multi-angular airborne observations and Discrete Anisotropic Radiative Transfer (DART) model simulations were used to validate and evaluate the RTAF model over an agro-forestry scene in Heihe River Basin, China. The results suggest the RTAF model can accurately simulate the hemispherica-directional reflectance factors (HDRFs) of the heterogeneous scenes 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 scenes.

[1]  A. Strahler,et al.  Geometric-Optical Modeling of a Conifer Forest Canopy , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Sylvain G. Leblanc,et al.  A four-scale bidirectional reflectance model based on canopy architecture , 1997, IEEE Trans. Geosci. Remote. Sens..

[3]  Qinhuo Liu,et al.  An Optimal Sampling Design for Observing and Validating Long-Term Leaf Area Index with Temporal Variations in Spatial Heterogeneities , 2015, Remote. Sens..

[4]  Y. Knyazikhin,et al.  Radiative transfer based scaling of LAI retrievals from reflectance data of different resolutions , 2003 .

[5]  Jing Li,et al.  A Sampling Strategy for Remotely Sensed LAI Product Validation Over Heterogeneous Land Surfaces , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[6]  Marie Weiss,et al.  Mapping Biophysical Variables From Solar and Thermal Infrared Remote Sensing: Focus on Agricultural Landscapes With Spatial Heterogeneity , 2014, IEEE Geoscience and Remote Sensing Letters.

[7]  B. Hapke.  Bidirectional reflectance spectroscopy: 1. Theory , 1981 .

[8]  Yaping Shao,et al.  Quantification of land‐surface heterogeneity via entropy spectrum method , 2014 .

[9]  Qinhuo Liu,et al.  Improving Leaf Area Index Retrieval Over Heterogeneous Surface by Integrating Textural and Contextual Information: A Case Study in the Heihe River Basin , 2015, IEEE Geoscience and Remote Sensing Letters.

[10]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modeling: The Scattering by Arbitrarily Inclined Leaves (SAIL) model , 1984 .