1. Spatial modelling of modal shift due to COVID-19Simona Šinko, Klemen Prah, Tomaž Kramberger, 2021, original scientific article Abstract: The outbreak of COVID-19 caused many changes in people's life. One of the most significant is the travel behaviour and transport mode choice. This study focus on the changes that the inhabitants of Vienna made in their travel choices because of the virus. The same research about spatial modelling the transport mode choice of commuters in Vienna was completed in 2019 and is a topic addressed in our previous work. Based on our developed methodology, this article indicates that public transport is not a dominant transport mode choice as it was before the virus outbreak.The main result of this paper is geographically defined areas of application of individual alternatives shown on the final map of modal shift in Vienna, which could provide theoretical support for policy-makers and transportation planners. For the city of Vienna, we found that the area of the city where cars are now used has increased, which certainly has a negative impact on air quality and life in the city. The advantage of the methodology is that it can also be applied to other cities in the world.
Keywords: coronavirus, city traffic, urban mobility, transport mode choice, passenger transport, geographical methods, spatial modelling, city logistics, Vienna
Published in DKUM: 14.10.2024; Views: 0; Downloads: 17
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2. Revealing the spatial pattern of weather-related road traffic crashes in SloveniaDanijel Ivajnšič, Nina Zver, Igor Žiberna, Eva Konečnik Kotnik, Danijel Davidović, 2021, original scientific article Abstract: 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.
Keywords: GIS, hot spot analyses, traffic safety, spatial modelling, weather patterns
Published in DKUM: 20.08.2024; Views: 92; Downloads: 8
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3. The Lyme borreliosis spatial footprint in the 21st century : a key study of SloveniaDaša Donša, Jaša Veno Grujić, Nataša Pipenbaher, Danijel Ivajnšič, 2021, original scientific article Abstract: After mosquitoes, ticks are the most important vectors of infectious diseases. They play an important role in public health. In recent decades, we discovered new tick-borne diseases; additionally, those that are already known are spreading to new areas because of climate change. Slovenia is an endemic region for Lyme borreliosis and one of the countries with the highest incidence of this disease on a global scale. Thus, the spatial pattern of Slovenian Lyme borreliosis prevalence was modelled with 246 indicators and transformed into 24 uncorrelated predictor variables that were applied in geographically weighted regression and regression tree algorithms. The projected potential shifts in Lyme borreliosis foci by 2050 and 2070 were calculated according to the RCP8.5 climate scenario. These results were further applied to developing a Slovenian Lyme borreliosis infection risk map, which could be used as a preventive decision support system.
Keywords: CART, climate change, MGWR, Lyme disease, infection risk, spatial modelling
Published in DKUM: 12.08.2024; Views: 69; Downloads: 10
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