V.M. Marshall, M.M. Lewis and B. Ostendorfhttp://www.journals.elsevier.com/journal-of-arid-environments

Native vegetation around the world is under threat from historical and ongoing clearance, overgrazing, invasive species, increasing soil and water salinity, altered fire regimes, poor land management and other factors, resulting in a degradation of natural ecosystem services. Consequently, maintaining and improving native vegetation condition is a target frequently adopted by natural resource managers and government agencies world-wide. Adequate monitoring of vegetation condition remains a prerequisite for environmental decision-making and for tracking progress towards management goals. Throughout we consider vegetation condition to include the compositional, structural and functional attributes of vegetation relative to undisturbed vegetation of the same type.Site-based methods have long been used to assess compositional, structural and functional attributes as indicators of vegetation condition, and these methods continue to be used widely today. With developing technologies, remote sensing methods are being employed increasingly for monitoring a range of remotely detectable properties of vegetation, and there is now a growing demand to explicitly integrate the two approaches for mapping and monitoring vegetation condition across a range of scales.Here we review the attributes of vegetation identified as important for monitoring vegetation condition, those indicators that are best measured using traditional site-based methods and those that are more readily detectable using remote sensing methods, including their application in operational programmes within Australia. Further to this we review recent literature on the integration of the two approaches for monitoring indicators of vegetation condition.We find that remote sensing methods have the advantage of offering broad scale automated and repeatable methods for monitoring indicators of vegetation condition, but when combined with detailed ecological site-based data, together can improve monitoring for answering ecological questions across a range of scales. Further work, however, is required to effectively integrate the two approaches for mapping and monitoring vegetation condition

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.