Advantages of BRDF Information for the Interpretation of Reflectance Measurements over Vegetation

The interpretation of the reflected radiation measured by wide angle instruments or in off-nadir directions requires the knowledge of the bi-directional reflectance distribution function (BRDF). By using atmospheric radiative transfer calculations we demonstrate how several vegetation indices are influenced by the BRDF and by the atmosphere. We present two methods to retrieve the leaf area index (LAI) using bi-directional reflectance factors in the near infrared spectral domain. Firstly we use a newly defined Off-Nadir Vegetation Index (ONVI) and a multiple regression analysis. The method was tested on a synthetic data set with a LAI varying between 0 and 10. We achieved a root mean square error of 1.54. Secondly we trained a neural network with synthetic data computed with the BRDF model of Roujean et al. Using observations in backward scattering direction the root mean square error for LAI retrieval was 1.2. To obtain more comprehensive information on the characteristic and stochastic properties of the BRDF a new measuring method was developed. It employs a rotating CCD-line camera mounted on an extendible boom. The data of our field campaigns together with the measurements performed by other groups are arranged in a BRDF catalog