Automatic generation of emissivity maps on a European scale

The remote sensing measurement of the land surface temperature from satellites provides an overview of this magnitude on a continuous and regular basis. The study of its evolution in time and space is a critical factor in many scientific fields such as weather forecasting, detection of forest fires, climate change, and so on. The main problem of making this measurement from satellite data is the need to correct the effects of the atmosphere and the surface emissivity. In this work, these corrections have been made using a split-window algorithm. The aim was to define an enhanced vegetation cover method and develop a system that used it, in order to automatically generate maps of land surface emissivity from images of the AATSR. Its validation was made by comparing the obtained results and the values measured in previous field campaigns carried out Valencia, Spain. The importance of this work is that no maps for this specific sensor were available until now.