Multi-sensor data fusion for deriving bio-physical variables in the Cyclopes project

The objective of the Cyclopes project is to provide coherent estimates of bio-physical variables such as land surface albedo and leaf area index at regional and global scales and to demonstrate their application in the fields of land cover change detection and carbon cycle modeling. An essential element of the project strategy is to provide sensor-independent estimates by exploiting the synergy of an ensemble of medium resolution imaging instruments. The differences in the orbital configurations (angular sampling, frequency of observations) and sensor characteristics (spectral sensitivity, pixel size) potentially offer complementary information allowing us to increase the precision of the variable estimates. However, from a technical point of view these differences pose a number of problems and for the implementation in operational processing chains a compromise between the optimal use of the available information and the practical feasibility needs to be found. In this contribution we outline possible scenarios for achieving the multi-sensor data fusion.