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GPU-Accelerated Multiple Observer Siting

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We present two fast parallel implementations of the Franklin-Vogt multiple observer siting algorithm, using either OpenMP or CUDA. In this problem, the objective is to site observers on a raster terrain such that the joint area visible by them is maximized. On a portion of terrain with 16,385×16,385 cells, assuming that observers can see out to a radius-of-interest of 100 cells, finding the approximate 15,000 observers that have the greatest coverage takes only 17s in CUDA. That is a factor of 70 speedup from the sequential version. The OpenMP version exhibits a factor of 17 speedup on a 16 core system. Applications for the multiple observer siting problem include radio transmission towers, environmental monitoring sites, and path planning for surveillance drones. The algorithm has four steps: finding the visibility indices of all points, selecting a candidate subset of potential top observers, finding each one's viewshed, and greedily constructing the final solution.
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Document Type: Research Article

Publication date: 01 June 2017

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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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