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Time-geographic Density Estimation for Home Range Analysis

September 26, 2011

Annals of GISAnnals of GIS, Volume 17, Issue 3, 2011

Joni A. Downs, Mark W. Horner, and Anton D. Tucker

“This research presents time-geographic density estimation (TGDE) as a new technique of animal home range analysis in geographic information science (GIS). TGDE combines methodologies of time geography and statistical density estimation to produce a continuous probability distribution of an object’s spatial position over time. Once TGDE is applied to animal tracking data to create a density surface, home ranges and core areas can be delineated using specified contours of relative intensity (e.g., 95% or 50%). This article explores the use of TGDE for home range analysis using three data sets: a fixed-interval simulated data set and two variable-interval satellite tracks for a loggerhead sea turtle (Caretta caretta) corresponding to internesting and post-migration foraging periods. These applications are used to illustrate the influence of several parameters, including sample size, temporal sampling scheme, selected distance-weighted geoellipse function, and specified maximum velocity, on home range estimates. The results demonstrate how TGDE produces reasonable home range estimates even given irregular tracking data with wide temporal gaps. The advantages of TGDE as compared with traditional methods of home range estimation such as kernel density estimation are as follows: (1) intensities are not assigned to locations where the animal could not have been located given space and time constraints; (2) the density surface represents the actual uncertainty about an animal’s spatial position during unsampled time periods; (3) the amount of smoothing applied is objectively specified based on the animal’s movement velocity rather than arbitrarily chosen; and (4) uneven sampling intervals are easily accommodated since the density estimates are calculated based on the elapsed time between observed locations. In summary, TGDE is a useful method of home range estimation and shows promise for numerous applications to moving objects in GIS.”

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