Modelling the movement and behaviour of cattle
The journal Ecological Modelling has published results from experiments using high sample rate GPS data to develop a model of cattle movement and behavioural state (relocating, grazing, and bedding). This novel animal modelling methodology can successfully recognise and model each individual animal, as well as their herding behaviour. It not only shows that cattle graze pastures in a non-homogeneous way but also begins to identify some of the underlying processes that lead to uneven grazing pressure. Understanding herbivore landscape grazing interactions can lead to improved management intervention strategies such as identifying the optimal location of watering points to prevent localised overgrazing effects.
Contour plot of the density of six cows during a 4-day period.
The dataset used for the modelling came from six cows whose GPS position was recorded every 10 seconds for 4 days. Each animal had a monitoring collar fitted which consisted of a Fleck™ unit for wireless networking, and a number of sensors including GPS, 3-axis accelerometer, and 3-axis magnetometer. The animals were able to move freely around a 7-ha paddock during data collection.
Ying Guo1, Geoff Poulton1, Peter Corke1, Greg Bishop-Hurley2, Tim Wark1, and David Swain2. "Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model". Ecological Modelling, Volume 220, Issue 17, 10 September 2009, Pages 2068-2075.
1Autonomous Systems Laboratory, CSIRO ICT Centre
2Autonomous Livestock Systems, CSIRO Division of Livestock Industries
The full article is available here.
Read more about the use of sensor networks in agriculture.
