Mitigation of saturation in satellite pasture measurement via incorporation of a statistical pasture growth model

Abstract

Measurement of pasture biomass is useful to farmers, as it enables timely and accurate management decisions. Satellite pasture measurement allows this information to be obtained with minimal time and labour on the part of the farmer. However, the accuracy of satellite measurements for high levels of pasture biomass can be impacted by a phenomenon called saturation, in which the response of the satellite estimate to increased biomass is diminished in situations of high biomass. In this investigation, a statistical pasture growth model was combined with satellite pasture measurements, with the aim of mitigating the effect of saturation on estimation accuracy. Data were captured for five farms, across two regions and an 18–21 month measurement period. Where satellite measurements appeared to be saturated, the growth model estimate was substituted. This process resulted in improved accuracy (R² improved from 0.672 to 0.703; RMSE improved from 334 to 309 kg DM/ha; and average bias improved from -62 to -9 kg DM/ha). The statistical improvements were more pronounced where terrestrial estimates were higher so the impact of saturation would be greatest. These results indicate that the problem of saturation in satellite pasture measurement can be addressed by the incorporation of modelled data.

Prior research has predicted that improved accuracy of pasture measurement would be associated with increased profitability, and this work helps achieve that goal for farmers using satellite measurement services.