Non-linear time sampling driven by surface temperature for the monitoring of vegetated areas using multi- and hyper-temporal satellite image time series

This work presents a methodology for the fast exploitation of the large volumes of high temporal and spectral resolution data that will be available with the future Earth Observation missions. A new approach integrating temperature and phenological information for the characterisation of land cover classes is given, as part of a fully automatic system for the generation of large area land cover maps. No selection of cloud-free dates, masking of unsuitable regions, or user interaction is needed. Analysis of its performance is undertaken, and future directions are identified.