###### Abstract  
The live weight (LW) and live weight change (LWC) of cattle in extensive beef production is associated with pasture availability and quality. The remote monitoring of pastures and cattle LWC can be achieved with a combination of satellite imagery and walk-over-weighing (WoW) stations. The objective of the present study is to determine the association, if any, between vegetation indices (VIs) (pasture availability) and the LWC of beef cattle in an extensive breeding operation in Northern Australia. The study also tests a suite of VIs along with variables such as rainfall and Julian day to predict the LWC of breeding cows. The VIs were calculated from Sentinel-2 satellite imagery over a 2-year period from a paddock with 378 cattle. Animal LW was measured remotely using a weighing scale at the water point. The relationship between VIs, the LWC, and LW was assessed using linear mixed-effects regression models and random forest modelling. Findings demonstrate that all VIs calculated had a significant positive relationship with the LWC and LW (\(p<0.001\)). Machine learning predictive modelling showed that the LWC of breeding cows could be predicted from VIs, Julian day, and rainfall information, with a Lin's Concordance Correlation Coefficient of 0.62 when using the leave-one-month-out cross-validation. The LW and LWC were greater during the wet season when VIs were higher compared to the dry season (\(p<0.001\)). Results suggest that the remote monitoring of pasture availability, the LWC and LW is possible under extensive grazing conditions. Further, the use of VIs and other readily available data such as rainfall can be used to predict the LWC of a breeding herd in extensive conditions. Such information could be used to increase the productivity and land management in extensive beef production. The integration of these data streams offers great potential to improve the monitoring, management, and productivity of grazing or cropping enterprises. average daily gain; pasture availability; NDVI Article  
1 Sydney Institute of Agriculture, School of Life and Environmental Science, Faculty of Sciences,  
The University of Sydney, Camden, NSW 2570, Australia; [EMAIL_ADDRESS]  
The live weight gain of cattle in extensive grazing conditions is directly linked to pasture quantity and quality [1]. The distinct wet and dry seasons affect pasture growth throughout the year, being highest during and immediately following the wet season (December to March in the tropics of the Southern Hemisphere) [2]. A cow's live weight (LW) and body condition score (BCS) reflect this, typically being highest at the end of the wet season, with declines in the LW occurring as pasture quantity and quality decline throughout the dry season [1]. Satellite imagery with high a spatial and temporal resolution allows the calculation of VIs, which can be correlated to pasture quantity and quality [3, 4]. The growth and weight of cows are of interest because they impact cows' reproductive efficiency, including their ability to conceive, gestate, and raise a calf to weaning [5, 6]. Cow and calf loss in extensive systems is responsible for large productivity losses, with the live weight of cows believedto impact the extent of calf loss in these systems [6]. Cattle live weight change (LWC) can also be measured using remote automatic weighing systems [7; 8]. This information could be useful to integrate with remotely sensed VIs. However, no studies have been published integrating data streams from the remote monitoring of both vegetation and cattle LWC in extensive systems. Such information could then be used to assess the relationship between these variables throughout the seasons. It could also be used to manage animals in regard to nutrition, through paddock change, and feed supplementation. Mating and weaning strategies, amongst others [8], could also benefit from this information. VIs can assist in understanding the greenness and digestibility of a pasture [9].