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Navy

Automatic asset detection for disaster relief

Identifies strategic water sources for firefighters

Software & Information Technology

Satellite ImageSpectrum refers to all or a select range of frequencies, and can refer to a specific type of wave such as electromagnetic, light, or sound. A Spectral Angle Mapper (SAM) is a classification system derived from an algorithm involving the relationship between angle and spectra wavelength. A SAM is important to remote sensing because features captured on images like rocks, plants, or water will have a spectral signature, and this signature can be used to determine the composition of the image.

Navy researchers have invented detection algorithms that can analyze satellite images to locate assets required for disaster relief. Regions of interest (ROI) can be selected on large area satellite images, then algorithms perform a spectral analysis by comparing it to a database of spectral angle mapper (SAM) definitions. The algorithms use this comparison to determine asset availability and location, marking them on the ROI. This invention could be set to detect the spectrum that is most likely to indicate a body of water. Situations where this would be useful is when a fire breaks out in a less developed region not far from a suburban community; or when the fire is in an area that is difficult to reach and the best option for controlling the fire is to use choppers equipped with water buckets. The invention could examine the ROI, and detect and mark ponds, creeks, and swimming pools as refill points, none of which would have been on a standard map. The algorithms allow the image to be sharpened and enhanced to show where the desired assets are located. This innovation is not limited to examining satellite images – any high altitude, wide area image from planes, balloons, and drones will work. Potential applications include emergency fire services, water resource inventory, image processing, city planning, and disaster relief.

This technology is related to US patent 8,369,567.

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