Exploiting multi-angular observations for vegetation monitoring

Abstract

Remote sensing instruments of the present and future generations include a variety of multi-angular off-nadir measuring facilities. In order to fully exploit their possibilities a thorough understanding of the anisotropic angular reflection properties of terrestrial surfaces is required. These are generally quantified in terms of the bi-directional reflectance distribution function (BRDF). We report on near infrared BRDF measurements of various vegetative surfaces including several crops performed with a CCD camera. While many of the investigated vegetation types show a rather similar reflection behavior, there are also distinct differences observed in some cases. For a quantitative analysis of the results we introduce several statistical measures which describe the characteristic properties of the reflectance distribution. We use these parameters as the input for an unsupervised cluster analysis algorithm. As a result the method provides suggestions for grouping different vegetation types into classes according to their angular reflection properties. This is helpful for evaluating which properties of the plants or the plant canopy structure cause recognizable reflectance features. The results can therefore be used to develop adapted observation strategies for the retrieval of biophysical parameters in agricultural or environmental studies.