Abstract
This paper presents a new approach to disaster monitoring using an automatic change detection system onboard small satellites that features image tiling and fuzzy inference. Unlike other onboard change detection systems for satellites, the proposed system performs change detection on an image tile level rather than on a pixel-by-pixel basis. This image tiling approach allows for more robust change detection performance in the presence of misregistration errors. An important block in the automatic change detection system is the fuzzy inference engine, which generates control signals that trigger different onboard tasks such as image compression, issuing of warning alerts, transmission and rescheduling. The proposed scheme uses not only spectral information as the input data but also cloud cover information to improve the change detection results. Experimental results on accuracy of change detection and flood detection using satellite images are presented.
Highlights
Man-made and natural disasters can cause devastation resulting in casualties, loss of infrastructure and livestock on an enormous scale
Earth Observation (EO) satellites flying in low Earth orbit (LEO) have been used as a tool to monitor disasters by providing satellite imagery
This paper presents a new approach to change detection, which is based on image tiling and fuzzy inference
Summary
Man-made and natural disasters can cause devastation resulting in casualties, loss of infrastructure and livestock on an enormous scale. Earth Observation (EO) satellites flying in low Earth orbit (LEO) have been used as a tool to monitor disasters by providing satellite imagery These satellites supply valuable data for assessment of the damaged areas (Borrero 2005, Chen et al 2005, Miura et al.2006). The ability to detect temporal changes in images is one of the most important functions in intelligent image processing systems for hazard and disaster monitoring applications This capability could ensure a quick response that would greatly benefit the monitoring of disasters such as floods, earthquakes, oilspills, etc. Image processing on board small satellites is a very challenging task due to limited computing resources
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