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Abstract

Dairy farms require efficient monitoring of pasture biomass. However, physical proxy or destructive measurements are time-consuming, subject to sampling and collection error, and cannot characterise spatial biomass within entire paddocks. Until recently, spatial resolution and temporal frequency of satellite data have been insufficient to achieve effective management. We developed a model for biomass prediction based on data from new Planet Labs satellites to evaluate its utility in the context of commercial dairy farming. While the model had minimal residual error on the farm with the highest quality data (RMSE 260 kg/ha), validation of the model on new farms was poor. Accurately estimating biomass for the calibration farm is promising, but further work is necessary to develop a model which extrapolates robustly.

Item Type:	Conference or Workshop Item (Paper)
Authors/Creators:	Asher, M and Raedts, P and Harrison, MT and Hills, J and Rawnsley, RP
Keywords:	spatial analysis, PlanetLabs, satellite imagery, Rapid Eye, constellation, pasture biomass, dairy, growth rates, ryegrass, grazing
Journal or Publication Title:	Proceedings of the 2018 Australasian Dairy Science Symposium
Copyright Information:	Copyright 2018 CSIRO Publishing
Related URLs:	Google Scholar: Raedts, P UTAS Profile: Raedts, P Google Scholar: Harrison, MT UTAS Profile: Harrison, MT Google Scholar: Hills, J UTAS Profile: Hills, J Google Scholar: Rawnsley, RP UTAS Profile: Rawnsley, RP
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