Skip to main navigation Skip to search Skip to main content

Correlating GPS Movement Metrics with Animal Behaviour

  • Robin C Dobos
  • , Mark Trotter
  • , David Lamb
  • , Geoffrey Hinch

Research output: Contribution to conferenceAbstract

Abstract

The continuous recording of animal activity will enhance our understanding of animal behaviour and landscape utilisation by grazing livestock. Traditionally, collection of animal behaviour data relied on manual observations which are time consuming, expensive and may be unrepresentative of the full range of behaviours. Recent advances in animal tracking technology have meant that position loggers have become more readily available. GPS or local, radio frequency-based position loggers offer great potential for improving the management of grazing livestock, however position loggers generate a large amount of data. The question then is how do livestock managers use this information to make better decisions? With support from the Cooperative Research Centre for Spatial Information (CRCSI), the Precision Agriculture Research Group at University of New England (UNE-PARG) are investigating the use of GPS-based position loggers on grazing sheep and cattle to answer this question. The main aim is to correlate movement metrics eg velocity, distance travelled with the animals' physical environment and observed behaviour. We will then use the best metric of behaviours in models and decision support tools (DST) to help livestock managers improve feeding management decisions in variable climates.
Original languageEnglish
Pages117-117
Publication statusPublished - 2011
EventAgri-Sensing 2011: International Symposium on Sensing in Agriculture In Memory of Dahlia Greidinger - Haifa, Israel
Duration: 21 Feb 201124 Feb 2011

Conference

ConferenceAgri-Sensing 2011: International Symposium on Sensing in Agriculture In Memory of Dahlia Greidinger
CityHaifa, Israel
Period21/02/1124/02/11

Keywords

  • Agricultural Spatial Analysis and Modelling

Fingerprint

Dive into the research topics of 'Correlating GPS Movement Metrics with Animal Behaviour'. Together they form a unique fingerprint.

Cite this