Change Detection Analysis on Time Series of Satellite Images with Variable Illumination Conditions and Spatial Resolution

Very recently satellite systems for remote sensing are required to provide images with a spatial and temporal resolution suitable to be applied for disaster management. High resolution (HR) satellite imagery can provide a good insight into the magnitude of a disaster and a detailed assessment of the damage. To meet these objectives, HR imagery has to be collected immediately after the disaster and precisely in the areas that have been damaged by the event. Presently, space based remote sensing systems result unsuitable to provide useful information when disastrous events require simultaneously high temporal and spatial resolutions. Furthermore, due to the technological limits of the transmission systems, a very high resolution is usually coupled with a reduced sensor swath. This means that the observation can be carried out when the area to be imaged is known. Low-resolution satellites (e.g. geostationary satellite) could also provide, in principle, some information with the required promptness in presence of event characterized by sudden temperature increases (fires, explosions, volcanic eruption, etc). The University of Rome (Centro di Ricerca Progetto San Marco) is studying the suitability of a satellite based system able to monitor national borders and/or given regions of the Earth in a quasi-continuous way with an adequate spatial resolution. To meet this requirement, the so-called Multi-Stationary (MS) orbits have been introduced. A constellation of few (4) satellites located on this kind of orbits allows a quasi-continuous monitoring of a selected region of the Earth. This paper is devoted to assess the impact of the variability of the images spatial resolution and illumination conditions on change detection methods based on a time-series of images.