Improving vegetation parameter retrieval using surface reflectance anisotropy modelling

Earth Observation (EO) in the reflective solar domain can provide a number of key biophysical and biochemical products of vegetation, such as the fraction of absorbed photosynthetically active radiation (fAPAR), leaf area index (LAI), canopy structure (e.g., leaf angle and orientation), chlorophyll content and water content. Various algorithms are used for deriving these products, but they often are not treating surface anisotropy with sufficient care. For operational EO applications increased use has to be made of a combination of sensors on different satellites, different orbits and different observation geometries to obtain the required temporal resolution, making information on surface anisotropy even more important.

A major research item for the coming years is assessing the anisotropic reflectance behaviour of vegetation and soils, as described by the bidirectional reflectance distribution function (BRDF). Information on the BRDF of targets is relevant for normalizing images taken under different illumination and/or viewing conditions, but on the other hand multi-angular observations also provide additional information that can be used to improve the accuracy of retrieved products.

The main objective of this work is to derive novel methods for retrieving canopy biophysical and biochemical parameters including the BRDF information. In particular the increase in retrieval accuracy of land products derived from EO satellites like the upcoming Sentinel-2 and Sentinel-3 by anisotropy modelling will be studied. A BRDF library with angular measurements of the main agricultural crops, various soil types and small tree canopies will be made available for the scientific community.