Automatic generation of frequently updated land cover products at national level using COSMO-SkyMed SAR imagery

Abstract

SAR images from Italian COSMO-SkyMed mission can have a significant impact on the production and updates of land cover maps. However, for the full exploitation of the data and their application to nationwide extensions, robust automatic procedures need to be designed. In this paper we present the preliminary results obtained by the implementation of a processing scheme using COSMO-SkyMed images to provide, and regularly update every six months, land cover maps for the whole Italian territory. Most of the automatic processing is based on Neural Networks (NN) algorithms. In particular PCNN (Pulse Coupled NN) have been considered for change detection purposes while Multi-Layer Perceptrons (MLP) have been used for classifying the pixels belonging to a detected changed area.