In order to assess the rainfall erosivity in the Pannonian basin, several parameters which describe distribution, concentration and variability of precipitation were used, as well as 9 extreme precipitation indices. The precipitation data is obtained from the European Climate Assessment and Dataset project for the period 1961-2014, for 8 meteorological stations in northern Serbia, 5 in Hungary and 1 in eastern Croatia. The extreme values of precipitation were calculated following the indices developed by the ETCCDI. RclimDex software package was used for indices calculation. Based on statistical analysis and the calculated values, the results have been presented with Geographic Information System (GIS) to point out the most vulnerable parts of the Pannonian basin, with regard to pluvial erosion. This study presents the first result of combined rainfall erosivity and extreme precipitation indices for the investigated area. Results of PCI indicate presence of moderate precipitation concentration (mean value 11.6). Trend analysis of FI (mean value 22.7) and MFI (mean value 70.2) implies a shift from being largely in the low erosivity class, to being completely in the moderate erosivity class in the future, thus indicating an increase in rainfall erosivity for most of the investigated area (except in the northwestern parts). Furthermore, the observed precipitation extremes suggest that both the amount and the intensity of precipitation are increasing. The knowledge about the areas affected by strong soil erosion could lead to introducing effective measures in order to reduce it. Long term analysis of rainfall erosivity is a significant step concerning flood prevention, hazard mitigation, ecosystem services, land use change and agricultural production.

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This study investigates travel behavior and psychosocial factors that influence it during the COVID-19 pandemic. In a cross-sectional study, using an online survey, we examined changes in travel behavior and preferences after lifting travel restrictions, and how these changes were influenced by exposure to COVID-19, COVID-19 travel-related risk and severity, personality, fear of travel, coping, and self-efficacy appraisals in the Romanian population. Our results showed that participants traveled less in the pandemic year than the year before—especially group and foreign travel—yet more participants reported individual traveling in their home county during the pandemic period. Distinct types of exposure to COVID-19 risk, as well as cognitive and affective factors, were related to travel behavior and preferences. However, fun-seeking personality was the only major predictor of travel intention, while fear of travel was the only predictor of travel avoidance. Instead, people traveled more cautiously when they perceived more risk of infection at the destination, and had higher levels of fear of travel, but also a high sense of efficacy in controlling the infection and problem-solving capacity. The results suggest that specific information about COVID-19, coping mechanisms, fear of travel, and neuropsychological personality traits may affect travel behavior in the pandemic period.

The practice of producing drone videos for hobby or commercial purposes has already created a vast amount of open and free video datasets. When these videos are properly authored, time-stamped and geo-referenced, they receive characteristics of volunteered geographic information (VGI). As alternative forms to user-generated content (UGC), these visually appealing footages attract significant attention, but their production faces different practical and motivational issues that could impose limitation on the value of this kind of VGI. In order to better understand volunteered geographic drone videos (VGDV) from the social media and VGI perspective we conceptualize and discuss prospects and problems that could be explored in further research. This paper contributes to the development of theory about aerial drone videos, exploration of aerial drone video UGC characteristics and to the applicability of drone videos in Digital Earth systems.

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.