More efficient terrain viewshed computation on massive datasets using external memory | W. Randolph Franklin, Rensselaer Polytechnic Institute, Troy NY USA

Chaulio R. Ferreira, Salles V. G. de Magalhães, Marcus V. A. Andrade, W. Randolph Franklin, and André M. Pompermayer. More efficient terrain viewshed computation on massive datasets using external memory. In 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2012). Redondo Beach, CA, 6–9 Nov 2012.
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@inproceedings{ferreira-acmgis-2012,
    author = "Ferreira, Chaulio R. and de Magalhães, Salles V. G. and Andrade, Marcus V. A. and Franklin, W. Randolph and Pompermayer, André M.",
    title = "More efficient terrain viewshed computation on massive datasets using external memory",
    booktitle = "20th {ACM} {SIGSPATIAL} International Conference on Advances in Geographic Information Systems ({ACM SIGSPATIAL GIS} 2012)",
    year = "2012",
    address = "Redondo Beach, CA",
    month = "6--9 Nov",
    href = "\bibhrefpp{159-acmgis2012-viewshed}{159-acmgis2012-viewshed-poster.pdf}",
    customlinkposter = "https://wrfranklin.org/p/159-acmgis2012-viewshed-poster.pdf",
    mykey = "visviewshedsiting marcus salles"
}

Abstract

We present a better algorithm and implementation for external memory viewshed computation. It is about four times faster than the most recent and most efficient published methods. Ours is also much simpler. Since processing large datasets can take hours, this improvement is significant. To reduce the total number of I/O operations, our method is based on subdividing the terrain into blocks which are stored in a special data structure managed as a cache memory. The viewshed is that region of the terrain that is visible by a fixed observer, who may be on or above the terrain. Its applications range from visual nuisance abatement to radio transmitter siting and surveillance.

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