@article {Downs:2014:1365-8816:875,
title = "Voxel-based probabilistic space-time prisms for analysing animal movements and habitat use",
journal = "International Journal of Geographical Information Science",
parent_itemid = "infobike://tandf/tgis",
publishercode ="tandf",
year = "2014",
volume = "28",
number = "5",
publication date ="2014-05-04T00:00:00",
pages = "875-890",
itemtype = "ARTICLE",
issn = "1365-8816",
eissn = "1365-8824",
url = "https://www.ingentaconnect.com/content/tandf/tgis/2014/00000028/00000005/art00004",
doi = "doi:10.1080/13658816.2013.850170",
keyword = "spatial analysis, landscape ecology, mobile objects",
author = "Downs and Horner and Hyzer and Lamb and Loraamm",
abstract = "Time-geographic analysis has been limited in the past by its capacity to model only potential locations for moving objects, without sufficiently evaluating which locations are more probable. This paper expands upon existing research in probabilistic time geography by accomplishing two
main tasks. First, a new geocomputational approach is presented for generating probabilistic space-time prisms. Here, probabilistic space-time prisms are represented as three-dimensional rasters of volume elements, or voxels, that record the probability that an object was located at any location
at any time. After describing the geocomputational approach, its utility is illustrated through a detailed analysis of tracking data collected for a Muscovy duck (Cairina mochata). Specifically, probabilistic space-time prisms are used to map the ducks fine-scale movement patterns
over five complete days of global positioning system (GPS)-tracking. Then, the space-time prisms are used in conjunction with a detailed habitat map of the study area in order to quantify the ducks habitat usage over the course of each day. This application highlights the utility of
probabilistic space-time prisms for understanding the movements and activities of animals at fine temporal and spatial scales.",
}