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Despite an improvement in worldwide numbers, road traffic crashes still cause social, psychological, and financial damage and cost most countries 3% of their gross domestic product. However, none of the current commercial or open-source navigation systems contain spatial information about road traffic crash hot spots. By developing an algorithm that can adequately predict such spatial patterns, we can bridge these still existing gaps in road traffic safety. To that end, geographically weighted regression and regression tree models were fitted with five uncorrelated (environmental and socioeconomic) road traffic crash predictor variables. Significant regional differences in adverse weather conditions were identified; Slovenia lies at the conjunction of different climatic zones characterized by differences in weather phenomena, which further modify traffic safety. Thus, more attention to speed limits, safety distance, and other vehicles entering and leaving the system could be expected. In order to further improve road safety and better implement globally sustainable development goals, studies with applicative solutions are urgently needed. Modern vehicle-to-vehicle communication technologies could soon support drivers with real-time traffic data and thus potentially prevent road network crashes. [ABSTRACT FROM AUTHOR]

The human population is increasing. The ongoing urbanization process, in conjunction with climate change, is causing larger environmental footprints. Consequently, quality of life in urban systems worldwide is under immense pressure. Here, the seasonal characteristics of Maribor's urban thermal environment were studied from the perspectives of surface urban heat island (SUHI) and urban heat island (UHI) A remote sensing thermal imagery time series and in-situ measurements (stationary and mobile) were combined with select geospatial predictor variables to model this atmospheric phenomenon in its most intensive season (summer). Finally, CMIP6 climate change scenarios and models were considered, to predict future UHI intensity. Results indicate that Maribor's UHI intensity maximum shifted from winter to spring and summer. The implemented generalized additive model (GAM) underestimates UHI intensity in some built-up parts of the study area and overestimates UHI intensity in green vegetated areas. However, by the end of the century, UHI magnitude could increase by more than 60% in the southern industrial part of the city. Such studies are of particular concern, in regards to the increasing frequency of heat waves due to climate change, which further increases the (already present) heat stress in cities across the globe. [ABSTRACT FROM AUTHOR]

The use of weather satellite recordings has been growing rapidly over the last three decades. Determining the patterns between meteorological and topographical features is an important scientific job. Cloud cover analysis and properties can be of the utmost significance for potential cloud seeding. Here, the analysis of the cloud properties was conducted by means of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite recordings. The resolution of used data was 1 km2 within the period of 30 years (1989–2019). This research showed moderate changing of cloudiness in the territory of Serbia with a high cloudiness in February, followed by cloudiness in January and November. For the past three decades, May has been the month with the highest cloudiness. The regions in the east and south-west, and particularly in the west, have a high absolute cloudiness, which is connected with the high elevation of the country. By means of long term monitoring, the whole territory of Serbia was analyzed for the first time, in terms of cloudiness. Apart from the statistical and numerical results obtained, this research showed a connection between relief and clouds, especially in the winter season. Linear regression MK (Mann-Kendall test) has proven this theory right, connecting high elevation sides with high absolute cloudiness through the year. [ABSTRACT FROM AUTHOR]