Predicting accurate paddock-average pasture cover in Waikato dairy farms using satellite images

Abstract

Effective monitoring of pasture cover on a regular basis is essential if dairy farmers are to increase profitability by making better pasture management decisions. We present results of a two-year study on the use of satellite imagery to estimate pasture cover on dairy farms in the Waikato region. Data collection concentrated on the critical time for dairy farm pasture management between June and December. Two distinct relationships between the remotely-sensed normalised difference vegetation index (NDVI) and pasture cover were observed, with an inflexion point in the relationship at NDVI = 0.74. A two-part exponential model was fitted to the data, allowing the prediction error to be minimised both above and below the inflexion point. Model development showed that an algorithm based on NDVI and time-of-year accounted for approximately 80% of the variability in pasture cover measured within paddocks. The validation studies show that pasture cover was estimated with an error of prediction of approximately 10%, which equates to 260 kg DM/ha for a pasture cover range of 1500 to 3400 kg DM/ha. The accuracy demonstrated in this study has given the project's funders the confidence to explore a staged rollout of development, validation and commercial delivery, to make the technology available to all major dairy regions in New Zealand over the next five years. Keywords: Pasture cover, dairy, satellite imagery, rising plate meter, normalised difference vegetation index