Synergy between a vegetation growth-SVAT model and remotely sensed data. Application to a semi arid area

The role of vegetation canopies in regulating biosphere-atmosphere interactions has long been recognized. An accurate representation of heat and mass transport between the land and the atmosphere requires that the dynamics of the vegetation is taken into account. During the last decades vegetation models have been designed to simulate the seasonal and the inter-annual variability in plant structure and plant function. Some of these vegetation models are now coupled to SVAT and to atmospheric models. As it is the case for most mechanistic SVAT and vegetation models, the model the authors used in this study requires parameters that are difficult to assess except during intensive observation campaigns. In that context, they present a methodology to combine a vegetation growth-SVAT model and remotely-sensed data. Remotely sensed data give access to large domains and also to systematic and repeated observations of the surface. In that respect, they are most valuable where and when systematic ground studies are not possible. The basic idea is to take advantage of both model knowledge and data, by fitting the model to the data, i.e. by assimilating the data in the model.