All Categories : Technical Papers : 2014 ASPRS Louisville Proceedings Bookmark and Share

Title : Mobile Device Visualization of Cloud Generated Terrain Viewsheds
Company : Penn State University
File Name : Mangold.pdf
Size : 593919
Type : application/pdf
Date : 16-Jul-2014
Downloads : 9

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Author: Chris Mangold

Cloud GIS based services, large scale DEM GIS datasets, and onboard mobile device graphic and sensor resources allow creation of a functional terrain viewshed least observed path (LOP) geovisualization mobile application. The LOP application enables a mobile device user to visualize the best path to travel, from their current location to a point visible through their device’s camera, minimizing the possibility of being seen from one or more application identified observer points. The application consumes cloud generated terrain viewsheds, for the identified observer points, combines the viewsheds locally and constructs an augmented reality color scaled geolayer. The application’s dashboard viewer overlays the generated geolayer on the devices live camera feed to provide the LOP view. The LOP view updates as the mobile user’s location changes and traverses observer point viewsheds. The LOP Android application implemented several critical technical decisions. Sensor orchestration algorithms manage GPS, accelerometer, gyroscope and device orientation input to synchronize the LOP geolayer with the live camera feed. Key system elements supporting the application include services and data hosted by a cloud GIS. Utilizing cloud based services significantly reduces computational times to perform viewshed terrain analysis for identified observer points. The cloud also provides large scale storage of DEM datasets providing a geospatially wide operational domain. Field tests of the LOP application utilized SRTM 3 arc-second, ASTER GDEM 1 arc-second, NED 1/3 and 1/9 arc-second, and 1 meter lidar first return. Initial performance results indicate DEM data source resolution has negligible impact on computational processing times on the cloud and mobile platforms but LOP results vary based on DEM data sources in urban landscape The LOP results and user experience can be improved by considering nearest neighbor results when calculating the LOP geolayer.
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