Bicheron, P, Leroy, M (1999). A method of biophysical parameter retrieval at global scale by inversion of a vegetation reflectance model. REMOTE SENSING OF ENVIRONMENT, 67(3), 251-266.
The objective of the paper is to study a physically based method of retrieval of leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (fAPAR) parameters from global data sets of new generation wide field of view optical satellite sensors, such as POLDER/ADEOS, VGT/SPOT4, MODIS/EOS, MISR/EOS, MERIS/ENVISAT, and so forth. The method uses the bidirectional reflectance distribution function (BRDF) model of Kuusk (1995), which simultaneously predicts the spectral and directional behavior of reflectances, as a function of LAI, chlorophyll concentration, ratio of leaf size to canopy height, and other optical or structural parameters of the soil and vegetation. The same model is used irrespective of surface type, and no ancillary data is needed. This approach is evaluated with field and airborne data acquired over three different types of surfaces: Sahelian vegetation in the HAPEX-Sahel (1992) experiment, boreal forest in the BOREAS (1994) experiment, and cultivated nr-eas in the Alpilles (1996) experiment. The results shore that the LAI is restituted with a fair accuracy [root-mean-square (rms) difference between model results and observations of 0.70], better than that obtained with a semiempirical relation LAI-vegetation index. The daily fAPAR is restituted accurately, with a rms difference between measured and modeled fAPAR of 0.097. In the example of HAPEX, the model reproduces to some extent the temporal evolution of measured LAI and fAPAR. Reflectances reconstructed with the model are in acceptable agreement with observed reflectances, with a rms difference between observed and measured values of 0.017 on average. It is concluded that the retrieval of biophysical parameters from inversion of a BRDF model is promising from the perspective of a quantitative characterization of the terrestrial biosphere from space. (C) Elsevier Science Inc., 1999.