Traffic accidents impart both economic and social costs upon communities around the world, hence the desire for accident rates to be reduced. For this reduction to occur, the factors influencing the occurrence of accidents must be understood. The role of congestion in modifying accident risk has been widely studied, but consensus has not been reached, with conflicting results leaving open questions. An inverse relationship between accidents and congestion would imply a benefit of congested conditions for road safety, posing a difficult situation for traffic management. This paper assesses articles that reveal the shape of the relationship between traffic accidents and congestion. We find a positive linear response to dominate the literature. However, studies with higher numbers of statistical units tend to show a U-shaped relationship. This suggests an important role of high spatio-temporal traffic data in understanding factors causing accidents and identifying the combination of real-time conditions which may lead to increased accident risk. Modern advancements in traffic measurement systems provide the ability for real-time alleviation of accident-prone conditions before they can fully develop.

Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident occurrence is critical. There is a lack of consensus about how the management of congestion may affect traffic accidents. This paper aims to improve our understanding of this relationship by analysing accidents at 120 intersections in Adelaide, Australia. Data comprised of 1629 motor vehicle accidents with traffic volumes from a dataset of more than five million hourly measurements. The effect of rainfall was also examined. Results showed an approximately linear relationship between traffic volume and accident frequency at lower traffic volumes. In the highest traffic volumes, poisson and negative binomial models showed a significant quadratic explanatory term as accident frequency increases at a higher rate. This implies that focusing management efforts on avoiding these conditions would be most effective in reducing accident frequency. The relative risk of rainfall on accident frequency decreases with increasing congestion index. Accident risk is five times greater during rain at low congestion levels, successively decreasing to no elevated risk at the highest congestion level. No significant effect of congestion index on accident severity was detected.

Degradation from overgrazing of global arid rangelands is of significant concern for this widespread terrestrial ecosystem, and the people who rely on its sustainable use. Addressing this degradation requires a better understanding of how livestock removal and conservation management actions affect the rehabilitation of land condition. However, the dominant effect of climate and meteorological variability on arid vegetation makes isolating management‐induced change a difficult task. We present an analytically simple method for measuring relative land condition by assessing differences in remote‐sensing‐derived persistent fractional vegetation between adjacent stocked and destocked regions over time. The 22‐year observation period focusses on vegetation recovery at a long‐established sheep station after the removal of livestock and the introduction of conservation‐focussed management. The study region, in the southern Australian arid rangelands, comprises sparsely vegetated chenopod shrublands and acacia woodlands across low‐lying plains. Comparison is made to immediately surrounding stocked properties in a spatial design where climate and biogeographic variables remain consistent across the study area. We found an unequivocal relative increase in vegetation cover, and reduction of bare ground cover at the destocked property that became evident approximately 8 years after a reduction in grazing pressure. Distinctly higher persistent vegetation cover was maintained, even during periods of drought. Non‐photosynthetic vegetation cover was most indicative of long‐term change and increased by 1.1% relative to surrounding areas. Photosynthetic vegetation cover increased by 0.5%, while bare ground cover decreased by 2.1%. These cover changes, particularly in the non‐photosynthetic vegetation and bare ground components spatially coincide with the fenced boundary of the destocked property. Synthesis and applications: The ability to quantify management‐related impacts in land condition using freely available remote sensing data could support improved management by all stakeholders in these regions. The method leverages readily available satellite remote sensing data in a study design that is not dependent on large geospatial and climatic datasets that are not necessarily available in remote regions.

Rapid development and uptake in uncrewed aerial vehicles (UAVs) for environmental monitoring, specifically using three-dimensional data from LiDAR and structure from motion (SfM), has enabled improved condition assessment, including fine-scale erosion monitoring. Comparing the precision of LiDAR and SfM for measuring erosion is essential in enabling appropriate method selection. Additionally, knowledge regarding optimal flight heights allows for consideration of the trade-off among survey areas, flight times and precision. We assessed UAV-based LiDAR and SfM for providing high-precision digital surface models (DSM) of substantial gully erosion on a conservation reserve in the southern Australian arid rangelands. The gullies exist in low-slope chenopod shrublands with calcareous soils, and are of significant management concern, with erosion occurring rapidly over short periods following irregular and intense rainfall events. Root mean squared error (RMSE) values for SfM-derived DSMs with resolutions of 2, 4 and 6 cm were lower than comparable LiDAR datasets (SfM = 0.72–1.39 cm; LiDAR = 2.08–3.15 cm). Additionally, 2 cm SfM-derived datasets exhibit notably lower RMSE values than 4 and 6 cm datasets (2 cm = 0.72 cm; 4–6 cm = 2.08–3.15 cm). Change detection over the 1-year study period highlighted erosion in locations of management concern. We propose that, although both methods are of value, SfM is preferred over LiDAR because of its simplicity, reduced cost, and the additional monitoring capabilities of visible-colour imagery, with no notable sacrifice in precision. Visible-colour survey areas and times can be optimised by increasing flight height without dramatic losses in precision. The use of either method will be of great benefit for the monitoring of arid gully erosion and assessing the effectiveness of management interventions, allowing adaptive management and leading to improved condition of arid rangelands into the future.