Inference of the activity timeline of cattle foraging on a Mediterranean woodland using GPS and pedometry.

Sensors
E D UngarA Brosh

Abstract

The advent of the Global Positioning System (GPS) has transformed our ability to track livestock on rangelands. However, GPS data use would be greatly enhanced if we could also infer the activity timeline of an animal. We tested how well animal activity could be inferred from data provided by Lotek GPS collars, alone or in conjunction with IceRobotics IceTag pedometers. The collars provide motion and head position data, as well as location. The pedometers count steps, measure activity levels, and differentiate between standing and lying positions. We gathered synchronized data at 5-min resolution, from GPS collars, pedometers, and human observers, for free-grazing cattle (n = 9) at the Hatal Research Station in northern Israel. Equations for inferring activity during 5-min intervals (n = 1,475), classified as Graze, Rest (or Lie and Stand separately), and Travel were derived by discriminant and partition (classification tree) analysis of data from each device separately and from both together. When activity was classified as Graze, Rest and Travel, the lowest overall misclassification rate (10%) was obtained when data from both devices together were subjected to partition analysis; separate misclassification rates were 8, 12, a...Continue Reading

Citations

Mar 19, 2013·Sensors·David J Augustine, Justin D Derner
Jul 23, 2014·Asian-Australasian Journal of Animal Sciences·E E L ValenteI F S Maciel
Oct 4, 2012·Animal : an International Journal of Animal Bioscience·D L Swain, M A Friend
Mar 14, 2013·Journal of Animal Science·C GoldhawkK A Beauchemin
Mar 1, 2021·Journal of Animal Science·William B SmithEric J Scholljegerdes

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Software Mentioned

ArcGIS
JMP
IceTag
IceRobotics
GLST

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