Evolutionary Approach for Detection of Buried Remains Using Hyperspectral Images
Hyperspectral imaging has been successfully utilized to locate clandestine graves. This study applied a Genetic Programming technique called Brain Programming (BP) for automating the design of Hyperspectral Visual Attention Models (H-VAM.), which is proposed as a new method for the detection of buried remains. Four graves were simulated and monitored during six months by taking in situ spectral measurements of the ground. Two experiments were implemented using Kappa and weighted Kappa coefficients as classification accuracy measures for guiding the BP search of the best H-VAM. Experimental results demonstrate that the proposed BP method improves classification accuracy compared to a previous approach. A better detection performance was observed for the image acquired after three months from burial. Moreover, results suggest that the use of spectral bands that respond to vegetation and water content of the plants and provide evidence that the number of buried bodies plays a crucial role on a successful detection.
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Document Type: Review Article
Publication date: 01 July 2018
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- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies.
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