Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.