Mapping pasture dieback impact and recovery using an aerial imagery time series: a central Queensland case study

Abstract

Context.
Pasture dieback has emerged as a significant threat to the health and productivity of sown pastures in eastern Queensland and northern New South Wales, Australia.
Aims.
We aimed to address knowledge gaps on spatial spread patterns, recovery trajectories and floristic changes using remote sensing and ground surveys.
Methods.
We used a time series of high-resolution (12–25 cm) aerial imagery to quantify and compare pasture dieback spread over 7 years in three land-use areas:
ungrazed pasture, grazed pasture and rehabilitation following mining.
The green leaf index was applied using supervised random forest algorithms to classify areas affected between 2015 and 2021. Flora surveys were conducted to compare impacted and unimpacted areas for the three land uses and validate classifications.
Key results.
The first emergence of pasture dieback was in ungrazed pasture, and these areas recorded the highest rate of dieback spread at 1.88 ha month−1, compared with 0.54 and 0.19 ha month−1 in rehabilitated and grazed pastures respectively. Field validation showed that dieback-impacted pastures shifted from buffel grass (Cenchrus ciliaris L.), to forb-dominated communities with significantly different species mix, biomass and cover conditions. An analysis of local climate data showed that winter night-time temperatures and rainfall were notably higher than long-term means in the year preceding the first detection of pasture dieback.
Conclusions.
High resolution aerial imagery and ground surveys can be used to monitor pasture health by employing vegetation indices and random forest classifiers.
Implications. Ungrazed pastures and roadside areas should be managed to protect the region from further outbreaks.