Difference between revisions of "Movement Analysis"

From stgo
Jump to: navigation, search
m
m
Line 15: Line 15:
 
* Calculate core areas
 
* Calculate core areas
 
* Classify home range parts
 
* Classify home range parts
* derive the Skeleton for a home range region.
+
* Derive the Skeleton for a home range region.
* analyze the daily travel
+
* Analyze the daily travel
  
 
The toolbox was originally developed to analyse location data from grizzly bears (ursus arctos) collected with GPS collars within the Grizzly Bear Programm of the [http://foothillsresearchinstitute.ca/ Foothills Research Institute] (FRI, Alberta, Canada). Funding was provided by Canadian Phase IV [http://www.geoide.ulaval.ca/home.aspx GEOIDE] grant (#3).
 
The toolbox was originally developed to analyse location data from grizzly bears (ursus arctos) collected with GPS collars within the Grizzly Bear Programm of the [http://foothillsresearchinstitute.ca/ Foothills Research Institute] (FRI, Alberta, Canada). Funding was provided by Canadian Phase IV [http://www.geoide.ulaval.ca/home.aspx GEOIDE] grant (#3).

Revision as of 22:02, 10 November 2011

We have create a toolbox for the free GIS software OpenJUMP that allows to analyse movement data, called OpenJUMP HoRAE - Home Range Analysis and Estimation (pronounced: hooray). The software is and can be freely distributed under the General Public License verison 2.0 (GPL) - so you can give it to your co-worker or even modify it.

About the Home Range Analysis Toolbox

OpenJUMP HoRAE Screenshot

The toolbox contains functions for visualization of movement tracks and allows the creation and analysis of animal home ranges. Home range estimation methods that have been implemented are (see also the article below):

  • Minimum Convex Polygon (MCP),
  • Kernel Density Estimation (KDE), methods: (a) href, (b) LSCV, and (c) ad-hoc (region split)
  • Line-based KDE, scaled and un-scaled
  • Brownian Bridges
  • Line Buffer
  • Local Convex Hulls (LoCoH), methods: radius r, k-1 nearest neighbors, alpha region.

Additionally one can:

  • perform an Asymptote analysis for MCP, Point-KDE, Line-Buffer
  • Calculate core areas
  • Classify home range parts
  • Derive the Skeleton for a home range region.
  • Analyze the daily travel

The toolbox was originally developed to analyse location data from grizzly bears (ursus arctos) collected with GPS collars within the Grizzly Bear Programm of the Foothills Research Institute (FRI, Alberta, Canada). Funding was provided by Canadian Phase IV GEOIDE grant (#3).

Download

The software should run on Windows and Linux systems. Currently there is a bug that does not allow saving data on MacOSX systems. However, if you write me (Stefan: sstein) I can send you a patched version that allows saving to files, but can't save to a database. Anyway - here to the downloads:

Some preliminary results for a comparison of the estimators with grizzly bear data: GIScience 2010 extended abstract (pdf) and poster (pdf).

A test dataset with 14 GPS points to check out the functions of the toolbox is shipped with the distribution and can be found in the folder "/testdata/".

Documentation

We work on a wiki page with some more online documentation. However, the ABODE manual may be a good start, since most functions implemented were "inspired" by the ABODE toolbox (but software calculations are differently). For now you may check our Home Range Calculation Manual, which contains some info on how using our toolbox.

other supporting documents:

  • Steiniger, S. (2009, unpublished): A vector-based algorithm to detect core, edge, patch and corridor areas and comparison with its raster-based complement. (pdf) --- The document explains the different types of classes such as core, edge, patch and corridor that can be derived with the function MOVEAN>HRE Analysis>Extract Core, Patch, Edge; and: MOVEAN>HRE Analysis>Extract Corridors.
  • Steiniger, S., Hunter, A.J.S. (2010, unpublished): A scaled line-based kernel density estimator for the retrieval of utilization distributions and home ranges from GPS movement tracks. (pdf) --- The document explains how the line-based Kernel Density Estimators (KDE) works and compares it with Point-based KDE and the Brownian Bridge (BB) estimator. The function is to be found under MOVEAN>HRE>Line KD>....

Contact

You can contact me, Stefan Steiniger, writing an email to sstein(=at=)geo.uzh.ch. Alternatively you may contact Andrew Hunter.