Time-geographic density estimation for home range analysis

  title={Time-geographic density estimation for home range analysis},
  author={Joni A. Downs and Mark W. Horner and Anton D. Tucker},
  journal={Annals of GIS},
  pages={163 - 171}
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… 

Testing time-geographic density estimation for home range analysis using an agent-based model of animal movement

This paper tests TGDE’s effectiveness as a home range estimator using simulated movement data and demonstrates that TGDE is the most effective at estimating core areas, home ranges and total areas at high sampling frequencies, while CHP performs better at low sampling frequencies.

Adaptive-Velocity Time-Geographic Density Estimation for Mapping the Potential and Probable Locations of Mobile Objects

A more robust formulation of time-geographic density estimation, termed adaptive-velocity TGDE, which allows the maximum-vel velocity parameter to vary for each segment of the space-time path is developed.

Elliptical Time‐Density model to estimate wildlife utilization distributions

We present a new animal space‐use model (elliptical time density – ETD) that uses discrete‐time tracking data collected in wildlife movement studies. The ETD model provides a trajectory‐based,

Is there a single best estimator? Selection of home range estimators using area-under-the-curve

Estimators of home range collected with GPS technology performed better than those estimated with VHF technology regardless of estimator used, and estimators that incorporate a temporal component appeared to be the most reliable regardless of whether kernel-based or Brownian bridge-based algorithms were used.

Incorporating Uncertainty into Time-geographic Density Estimates

This research develops an approach for explicitly incorporating GPS error into timegeographic density estimates, and quantified the magnitude of positional error for GPS waterfowl-tracking devices under five different land cover types.

Voxel-based probabilistic space-time prisms for analysing animal movements and habitat use

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

Modeling movement probabilities within heterogeneous spatial fields

  • J. Long
  • Sociology
    J. Spatial Inf. Sci.
  • 2018
The field-based time geographic model is compared with two alternative approaches that are commonly employed to estimate probabilistic space-time prisms— (truncated) Brownian bridges and time geographic kernel density estimation and it is demonstrated that only field- based time geography captures underlying heterogeneity in output movement probabilities.



Time-Geographic Density Estimation for Moving Point Objects

The main advantages of this time-geographic method of density estimation for moving point objects are that positive intensities are only assigned to locations within a moving object's potential path area and that it avoids arbitrary parameter selection as the amount of smoothing is controlled by the object's maximum potential velocity.

Effects of Point Pattern Shape on Home-Range Estimates

Abstract Home-range estimators are commonly tested with simulated animal locational data in the laboratory before the estimators are used in practice. Although kernel density estimation (KDE) has

Network-based Home Range Analysis Using Delaunay Triangulation

  • J. DownsM. Horner
  • Computer Science
    4th International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2007)
  • 2007
It is suggested that KDE is inappropriate for home range estimation, because it assumes Euclidean-based space usage, and a network-based home range estimator is developed using Delaunay triangulation.

A Characteristic‐Hull Based Method for Home Range Estimation

This study explores the use of characteristic hull polygons (CHPs) as a new method of home range estimation using simulated animal locational data conforming to five point pattern shapes at three sample sizes to demonstrate the method has potential as a home range estimator.

Kernels Are Not Accurate Estimators of Home-range Size for Herpetofauna

Abstract Kernel home-range estimators are becoming more widely used to determine the home-range size for herpetofauna, despite the problems associated with selecting the appropriate smoothing factor.


Simulations are necessary to assess the performance of home-range estimators because the true distribution of empirical data is unknown, but we must question whether that performance applies to

Are kernels the mustard? Data from global positioning system (GPS) collars suggests problems for kernel home- range analyses with least-squares cross-validation

1. Kernel-density estimation (KDE) is one of the most widely used home-range estimators in ecology. The recommended implementation uses least squares cross-validation (LSCV) to calculate the

Estimated home ranges can misrepresent habitat relationships on patchy landscapes

A local nearest-neighbor convex-hull construction of home ranges and utilization distributions

A new method for estimating the area of home ranges and constructing utilization distributions (UDs) from spatial data is described and a minimum spurious hole covering (MSHC) rule is proposed for selecting k and interpreted in terms of type I and type II statistical errors.