New approaches in multi-angular proximal sensing of vegetation: Accounting for spatial heterogeneity and diffuse radiation in directional reflectance distribution models

The development of tower-mounted automated multi-angular hyperspectral systems has brought new opportunities and challenges for the characterization of the Bidirectional Reflectance Distribution Function (BRDF) on a continuous basis. This study describes the deployment of one of these systems in a Mediterranean savanna ecosystem (AMSPEC-MED), and proposes new approaches for modeling of directional effects. In this study, a Hemispherical-Directional Reflectance Distribution Function (HDRDF) was introduced in order to quantify the effect of diffuse radiation on the estimation of BRDF. The HDRDFs of the two covers of the ecosystem- trees and grasses were un-mixed using a 3-Dimensional (3-D) model of the observed scene. Up-scaling HDRDF estimates to MODIS BRDF product (r(2) is an element of [0.74, 0.86]) and down-scaling to hand held spectral measurements (r(2) = 0.88) achieved a reasonable accuracy (RMSE is an element of [1.81, 3.14]). Despite the uncertainties in the estimation of diffuse irradiance and the 3-D representation of the scene, HDRDF un-mixing demonstrates the potential of automated multi-angular proximal sensing to study vegetation properties in heterogeneous ecosystems and the correction of directional effects of different sources. (C) 2016 Elsevier Inc. All rights reserved.