Improvement of pasture biomass modelling using high-resolution satellite imagery and machine learning.

Robust quantification of vegetative biomass using satellite imagery using one or more forms of machine learning (ML) has hitherto been hindered by the extent and quality of training data. Here, we showcase how ML predictive demonstrably improves when additional training data is used. We collated field datasets of pasture biomass obtained via destructive sampling, 'C-Dax' reflective measurements and rising plate meters (RPM) from ten livestock farms across four States in Australia.

2019-2020 Bushfire impacts on sediment and contaminant transport following rainfall in the Upper Murray River catchment.

During the 2019-2020 Australian bushfire season, large expanses (~47%) of agricultural and forested land in the Upper Murray River catchment of southeastern (SE) Australia were burned. Storm activity and rainfall following the fires increased sediment loads in rivers, resulting in localized fish kills and widespread water-quality deterioration. We collected water samples from the headwaters of the Murray River for sediment and contaminant analysis and assessed changes in water quality using long-term monitoring data.