MASARI I.

This paper addresses the challenges of supervised semantic segmentation using Polarimetric Synthetic Aperture Radar (PolSAR) data for land cover mapping. We extend previous approaches relying on spatial-contextual classifier based on Support Vector Machines (SVMs) and Markov Random Field (MRF) models. The kernel used in this work extends a...

Change detection (CD) is among the most important tools in natural disaster monitoring. Special emphasis is on heterogeneous CD methods, which allow for a faster response. In this paper, we propose a novel heterogeneous CD method tailored at working with image domains of very different dimensionality, which allows for a greater applicational...