Machine learning increases the accuracy of pasture cover estimation using satellite data
Above: PhD Student Blessing Nneena Azubuike
Lead Author: Blessing Nneena Azubuike
Project P1a Remote pasture monitoring
On Australian grazing-based dairy farms, effective feed budgeting and pasture management requires accurate estimation of pasture cover. To date, the accuracy of satellite-derived estimates has been limited by the satellite’s ability to detect differences in dense pastures, especially during peak growth periods (saturation effects).
This research aimed to improve the accuracy of predicting pasture cover using machine learning. It developed a framework that integrates raw satellite data with paddock-specific and weather information. The study demonstrated that robust remote cover forecasting is achievable with advanced data manipulation without heavy reliance on standard vegetation indices. The findings offer insights for optimal model configuration and improved pasture cover estimates.
About Dairy UP
Dairy UP is a collaborative research, development and extension program for the NSW dairy industry. It aims to unlock the potential of pastures, cows, water and milk to increase productivity and profitability, and de-risk the industry and develop new markets.