Modeling and Simulation of Deciduous Forest Canopy and Its Anisotropic Reflectance Properties Using the Digital Image and Remote Sensing Image Generation (DIRSIG) Tool

Extraction of biophysical information from forest canopies using temporal analysis of multispectral and hyperspectral data can be significantly improved by understanding its anisotropic reflectance properties. However, limitations on the accessibility and data collection techniques in the field reduce the availability of high-resolution bidirectional reflectance measurements (BRDF) to a few datasets. These limitations can be mitigated in a virtual environment and this paper presents an approach to model the spectral BRDF of a forest canopy using the Digital Image and Remote Sensing Image Generation (DIRSIG) tool. The three-dimensional geometries of the trees were modeled using forest inventory data and OnyxTree, while the spectral properties of the geometric elements were assigned based on the field collected spectra and PROSPECT inversion model. The DIRSIG tool was used as a virtual goniometer to measure the BRDF observations for varying sun-view geometries and a full hemispherical BRDF model was constructed by fitting the measurements to a semiempirical BRDF model. This paper discusses the methods involved in modeling the forest canopy scene, sensitivity of the radiative transfer, BRDF sampling and modeling strategies, model accuracy and its effect on real-world simulations. The model fit results indicate a root mean square error of less than 5% relative to the forests reflectance in the VIS-NIR-SWIR region. The simulated BRDF matched to within 2% of the Landsat-8 surface reflectance product in the red and NIR bands. The results can be used directly to evaluate BRDF modeling algorithms and the proposed method can be easily extended for other biomes.