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The global pandemic of COVID-19 has had a significant influence on public transportation usage and service provision. As many countries begin to return to normality, new public transportation planning standards are being developed. Considering these new standards, there is a critical shortage of understanding the possible impact of the pandemic on public transportation systems and models that can help service planning face these challenges. This paper analyzes data collected in Cluj-Napoca (Romania), from late- February 2020 to late-March 2021. As local authorities began to remove restrictions aimed at limiting the propagation of the SARSCoV-2 virus, the study investigates the travel changes in various modes of transportation, travel plans, and user categories. Results confirm that low-income groups depend on public transit the most; consequently, they had considerably lower declines in usage during the COVID-19 pandemic. This study also identifies various daily average patterns of demand for public transportation in Cluj-Napoca throughout each stage of the pandemic. All of these data contribute to extending the global understanding about COVID-19's influence on transport usage by comparing these outcomes with the ones from other cities. They offer pertinent information for transportation authorities to develop adaptation policies to a major event like this pandemic. Although there is still apprehension about using public transportation, the collected data show that the regular public transport users from before the pandemic have been gradually returning to their transport of choice once the restrictions have been relaxed (March-May 2020). [ABSTRACT FROM AUTHOR]

Urban sprawl and population growth are the main triggers of land use reconversion around big cities. Due to the expansion of metropolitan areas, many land use categories (grasslands, arable lands, forests, pastures) have been transformed in living spaces. Determining the built-up area growth rate from satellite images, in correlation with demographics and dwellings data, leads to a better comprehension of sustainable urban development and the negative effects of chaotic urbanization. This study analyses the built-up area expansion growth rate in Cluj Metropolitan Area in 1991-2017 using the normalized difference built-up index and soil-adjusted vegetation index applied on Landsat imagery. Results highlight different spatial patterns within the studied area, based on the correlation between the growth rates of built-up area expansion and demographic data. The land use types most impacted by the urban sprawl are meadows and arable lands near the metropolitan centre and grassland in areas located at the periphery of the metropolitan area. [ABSTRACT FROM AUTHOR]

Abstract Snow avalanches are some of the most important geomorphic processes that disturb the forests at treeline in the Romanian Carpathians. The occurrence of multiple snow avalanches in the same area leads to the development of the avalanche paths. In Parâng Mountains, the spatial extent and the frequency of past avalanche events are poorly documented. In this study we combined remote sensing approach and natural archives based on tree-rings to reconstruct the spatial extent of a past snow avalanche. Dendrogeomorphic reconstruction of past avalanche activity was performed in two avalanche paths based on the following growth anomalies: traumatic resin ducts, compression wood, callus tissue associated with scars and growth suppression. Remote sensing reconstruction was performed in nine avalanche paths including the above mentioned two and relies on the sudden variations of four spectral indices (Normalized Burn Ratio, Normalized Difference Moisture Index, Moisture Stress Index and Disturbance Index) between images acquired yearly from 1984 till 1988. The results of dendrogeomorphic reconstruction pinpoint a severe avalanche event occurred in 1985–1986 winter that affected both avalanche paths. The results of remote sensing reconstruction validate the dendrogeomorphic reconstruction and suggest four other avalanche paths affected by the same avalanche event. The combination of both methods provided a powerful approach to analyze the impact of a snow-avalanche event a regional scale. We consider both powerful methods to further asses the spatial extent of more avalanche events over the entire surface of Parâng Mountains. Highlights • Dendrogeomorphological reconstruction of past snow-avalanche activity was performed. • Remote sensing of spatial extent for a snow-avalanche event was performed. • The results of the two methods validate reciprocally. • The spatial extent of the snow avalanche was assessed in Parâng Mountains (Romania). [ABSTRACT FROM AUTHOR]

Land cover and spatial variation of seasonal temperature may contribute to different evapotranspiration rates between the European regions. In order to assess the integral effect of land cover and climate on water resources, we implemented a procedure which allows defining favorability areas to high rate of evapotranspiration. Seasonal mean air temperature for the present (2011-2040) and future (2041-2070) combined with the seasonal crop coefficients of current future projections of land cover for the 2040s have been used to evaluate the various degrees of evapotranspiration at European scale. Extremely high and very high degree of evapotranspiration tendency were verified for Southern, Eastern, Western and Central of Europe during the mid-season period. The low and very low evapotranspiration favorability were found in the Scandinavian Peninsula and in the Alps, Dinarics, and Carpathian during the present period in all the seasons. In the cold season, the land cover favorability to evapotranspiration (LCFE) is low and very low in almost the whole Europe. These findings indicate that the southern and western regions of Europe are facing low water availability, decrease in surface water flow, and possible long periods of drought in the summers. [ABSTRACT FROM AUTHOR]

This paper compares the spatial structure of accessibility in Romania before and after the implementation of some major national and/or European road infrastructure projects. This study suggests a new index for accessibility measurement by combining gravity-based models with Place Rank and adapting it to the Romanian system of settlements. Based on the GIS estimation of travel time, this index evaluates not only the geographical position of a specific community relative to the road network, but also the level of accessibility of rural and urban communities to the social services located in central places. The GIS-based maps indicate the existing disparities (between well-connected and isolated regions in terms of accessibility to the central places) and the impact of new infrastructure projects on these disparities. The resulting maps can be used as efficient tools for transport planning and development at different scales (international, national, regional and local). [ABSTRACT FROM AUTHOR]

Many rural villages in Eastern Europe are severely impacted by aeolian smelter dust/deposits. Commonly, elemental studies in Romania have suffered from limited sampling numbers (n = 5–10) and/or incomplete digestion offering only semi-total quantification of elements using traditional, laboratory-based techniques. These approaches are simply inadequate for evaluating potentially hazardous soils and their spatial extent, particularly at urban/rural interfaces of variable land use. Portable x-ray fluorescence (PXRF) spectroscopy can accurately quantify contamination rapidly, in-situ with a wide dynamic range and little to no sample preparation for analysis of regulated elements (e.g., As, Cd, Cu, Mn, Pb, V, Zn) and other common soil elements such as Ca, Fe, K, Rb, Sr, Ti, and Zr. A contemporary PXRF spectrometer was used to scan 61 soil samples across multiple land use types in urban/rural interfaces on-site. Each site was georeferenced with elemental data inputted into a geographic information system for high resolution kriging interpolation. These models were superimposed over modern aerial imagery to evaluate the extent of pollution for each government-regulated element with simultaneous consideration and quantification of spatial variability in naturally occurring soil elements. Pb exceeded governmental action limits across 100% of the area, while V, Mn, Cu, and Zn were exceeded in 2.2, 2.1, 39.6, and 9.8% of the area. Furthermore, many regulated elements were closely correlated to natural soil elements. In short, georeferenced PXRF data proved a powerful new tool for on-site assessment of contaminated soils; one which has rarely been utilized in Eastern Europe to date. [ABSTRACT FROM AUTHOR]

Based on previous works on the connectivity index applied to the settlements of Banat (Rusu, 2007; Rusu, 2008), the paper assesses the road connectivity index for the same settlements using a slightly different approach, based on the road distance from every settlement to the nearest central places, ranked on nine levels. Therefore, it is not the position on a certain road that counts, but the means by which specific groups of people (either urban or rural communities) might access a set of services or facilities deemed socially necessary and located in the above-mentioned central places. The welfare of the communities depends mainly on the standards of connectivity and accessibility to such services or facilities. We considered that the most valid measure of connectivity would then be the assessment of the space (distance) needed to be crossed for the population of every settlement to reach specific destinations. The overall values for each settlement have been interpolated using GIS in order to produce a map of the road connectivity index in Banat. The map clearly shows the existing disparities between well-connected regions, especially around the main cities, and isolated areas, usually in the mountains, the hills or along the borders. [ABSTRACT FROM AUTHOR]

The main objective of this study was to analyze the perception of the influence of various weather conditions on patients with rheumatic pathology. A group of 394 patients, aged between 39 and 87 years and diagnosed with degenerative rheumatic diseases, were interviewed individually by using a questionnaire created specifically for this study. Further on, to assess the relationship between pain intensity and weather conditions, a frequency analysis based on Pearson's correlation matrix was employed. The most important results are as follows: the great majority of the participants (more than 75%) believe that their rheumatic pain is definitely or to a great extent influenced by different weather conditions; most of the patients reported intensification of their pain with weather worsening, especially when cloudiness and humidity suddenly increase (83.8% and 82.0%, respectively), air temperature suddenly decreases (81.5%), and in fog or rain conditions (81.2%). In our research, alongside simple meteorological variables, we established that complex weather variables such as atmospheric fronts, in particular, the cold ones and winter anticyclonic conditions, greatly intensify the rheumatic pain, whereas summer anticyclonic conditions usually lead to a decrease in pain severity. In terms of relationships between pain intensity and weather conditions, we found the strongest correlations (ranging between 0.725 and 0.830) when temperature, relative humidity, and cloudiness are constantly high. [ABSTRACT FROM AUTHOR]

The study examines the spatial and economic characteristics of commuting to work in one of the most dynamic areas of Romania, Cluj County. Based on the 2011 census data, the study reveals a strong connection between accessibility and commuting intensity, while the urban network determines the spatial orientation of the dominant commuting flows. However, we found no significant relation between dynamic economic performance and commuting intensity. [ABSTRACT FROM AUTHOR]

Mobility practices have changed dramatically in Romanian towns over the last 25 years, following the collapse of socialist mobility restrictions. Urban areas like Cluj-Napoca are facing both increasing immigration and car mobility, and therefore increasing levels of road traffic crashes. The analysis of traffic crashes is one of the most important elements for improving the road safety policy. This paper is divided in two parts. In the first one, the authors focus on identifying the traffic crash hotspots along the street network, while in the second part they discuss the social background of road traffic crash occurrence. The first step in analyzing traffic crashes is to determine crash hotspots. A four-year record (2010–2013) provided by the Traffic Department of the General Inspectorate of Romanian Police (GIRPTD) was used. As a method of hotspot determination, the Kernel Density Estimation tool was employed, in the frame of the spatial analysis along network (SANET). The outcome was the hotspot map of traffic crashes in Cluj-Napoca. The results have revealed 4 categories of street segments: not-dangerous , low-dangerous , medium-dangerous and high-dangerous . Based on this classification, at least 4 dangerous areas were identified, located at the city entrances-exits (in the West, North-West and East) and the city center (the most dangerous zone). The second part of the paper focuses on social groups involved in car crashes. The following are considered: age, gender and blood alcohol concentration of the person (driver or pedestrian) found guilty for every individual crash. [ABSTRACT FROM AUTHOR]

Soil reaction (pH) is one of the most commonly measured soil characteristics. Traditionally, soil pH measurements have been made either colorimetrically or electrometrically. These approaches, while accurate, are destructive in nature and require sample modification to form soil pastes or extracts. The use of portable X-ray fluorescence (PXRF) spectrometry for pH determination was investigated using elemental data as a proxy for soil pH. Two datasets representing a wide variety of soil pH (4.17-8.70) were first evaluated via PXRF followed by standard laboratory techniques. Datasets were divided into modeling and validation datasets. Simple and multiple linear regressions were used to develop models associating both pure elemental data from PXRF as well as PXRF elemental data with auxiliary input data (clay content, sand content, organic matter content). Multiple linear regression with auxiliary input data provided the best predictive model (R²: 0.825; RMSE: 0.541); multiple linear regression with pure PXRF elemental data provided a quality model (R²: 0.772; RMSE: 0.685); simple linear regression was ineffective as producing significant model predictions. Validation via correlation analysis confirmed the significance of the developed models. Summarily, PXRF shows considerable promise in providing rapid pH predictions in soils with reasonable accuracy, especially for unusual circumstances where non-destructive sampling is required. [ABSTRACT FROM AUTHOR]

Results indicate a different degree of clergy involvement in the electoral process, depending on the impact of the political event on church reliability. thus, Romania's church-based electoral capital is assessed using spatial and statistical analysis, resulting in territorial patterns based on voter turnout results. Performing Democracy An Analysis of Church-Based Electoral Capital in Romania e len A-m Anuel A b îr Sã nuc, e m Anuel A-Adin A c oci ª, v iorel Gli Gor, t itu S-c ri Sti An m An, Alex Andru-SAbin n icul A, m ihne A-Simion Stoic A Introduction R esearching politics has always been a laborious task, mostly due to the complexity of the subject as well as to the geographic, social, and economic implications. With results that rely on the election rates and statistics made at the level of 603 administrative units hosting the 863 monastic sites identified, spatial patterns of voter turnout are derived and the relation between electoral behavior and the clergy political implications is modeled. the results of two electoral events (one with political implications compared against one with social valences) from Romania are analyzed in order to assess the level of church and clergy influence on the electoral proceedings. [Extracted from the article]

This article aims to analyse, both spatially and numerically, the protests that occurred in Romania between January 2016, immediately after the 2016 Parliamentary Elections and the attempt of the new elected party to change Romania's constitution and legislations, and October 2017, triggered by several consecutive corruption acts. Methodologically, the analysis is based on a set of data provided by the Public Relations Department of the Romanian Gendarmerie. The statistical and cartographical analysis are focused on the main characteristics of the protests: place and triggering factors. Most protests (97%) take place in urban areas, and, during the analysed time frame, the following typologies are identified: Political System (59%), Economic Justice (37%), Human Rights (3%), Social Events (1%). The statistical model that resulted from the logistical regression is a strong predictor of the studied events, with a determination factor of 0.98, the main factors being the share of population with university studies, public expenses on healthcare, culture and education, as well as the unemployment rate, showing a high participation rate for the population with higher education that are living in areas where the authorities investment in culture and healthcare is significant. The results obtained through an interdisciplinary approach (geography, politics, statistics) improve the methodological matrix of mono-disciplinary studies and facilitate the inclusion in the same topic of experts from diverse domains. [ABSTRACT FROM AUTHOR]

Proximal sensors have rapidly developed in-situ analysis of soil and sediment. Two systems in particular, portable X-ray fluorescence (PXRF) spectrometry and visible near infrared diffuse reflectance spectroscopy (VisNIR DRS), have gained widespread acceptance for agronomic, pedological, and environmental quality assessment, but have scarcely been utilized to investigate mine tailings in South Africa. This study investigated 419 samples across four mines in South Africa using both PXRF and VisNIR DRS. Specifically, the PXRF was used to provide elemental data for comparison to X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDAX) coupled with scanning electron microscopy (SEM) for confirmation of tailings mineralogy. Next, PXRF data was used to model first derivative (1D) VisNIR reflectance spectra. Results revealed many satisfactory calibrations (R 2 > 0.70) relative to PXRF analysis with VisNIR DRS predictive models showing fair (RPD 1.4–2.0) to stable, accurate (RPD > 2.0) prediction of multiple elements. Use of better data partitioning methods and considering the target variability is likely to improve model accuracy further. Summarily, this study has established the effectiveness of using VisNIR DRS for the evaluation of mine tailings, justifying further application development with mine-specific models. [ABSTRACT FROM AUTHOR]

As countries of Eastern Europe look to advance their agricultural markets through large scale agronomic production, high resolution mapping of soil resources will be essential. Portable X-ray fluorescence (PXRF) spectrometry and diffuse reflectance spectroscopy (DRS) are non-invasive, proximal sensing techniques which provide quantitative data germane to physicochemical soil properties in seconds. While these techniques have been widely used to characterize individual soil samples, sample sets, or variability across individual fields, less work has been done at the catena scale (even less so in Eastern Europe), where variability due to topographic differences substantively affects a wide number of soil properties. The present study was conducted on three catenas of the Transylvanian Plain, Romania, each with 100 sampling points randomly established in ArcGIS. Laboratory analysis (particle size analysis, total carbon, total nitrogen, soil organic matter) was conducted at Texas Tech University, USA. Following Savitzky–Golay first derivative transformation, DRS spectra were used to predict soil physicochemical parameters of interest via support vector regression. The whole dataset was randomly divided into a 70% training (n = 210) and 30% test set (n = 90). Across all catenas, a combined PXRF + DRS approach showed better parameter prediction relative to either sensor independently as evidenced by higher R 2 , lower RMSE, higher RPD, and higher RPIQ values. For each parameter, the 100 points per catena were used as input data to develop a PXRF + DRS predictive model, and the output data from each model was kriged using ArcGIS 10.3.1. Spatial analysis strongly reflected management and landscape dynamics across the catenas. Combined proximal sensor approaches show considerable advantages over traditional laboratory approaches, allowing for high sample throughput, greater analytical density, and less expensive data, with minimal fall off in data quality. The combined PXRF + DRS approach showed excellent potential for providing the data needed to support optimized soil resource mapping and land management decisions in Eastern Europe or worldwide. [ABSTRACT FROM AUTHOR]

• Proximal sensors were used to determine calcic horizons in-situ. • PXRF in isolation was adept at differentiating chernozems and phaeozems. • Combined VisNIR-PXRF models modestly increased predictive model stability. The Transylvanian Plain (TP), Romania is widely used for agronomic production. The Chernisol soil class covers a vast majority of the TP as defined by the Sistemul Roman De Taxonomie A Solurilor (SRTS). Chernisols are fertile, dark soils similar to Mollisols in the United States. Chernisols have four key soil types, two of them occur in the TP: chernozems and phaeozems. While these two classifications appear similar to those found in the World Reference Base (WRB) for Soil Resources , only the Romanian system (SRTS) is applied in this paper. Chernozems require a chroma of ≤2 in the Am horizon when moist and a calcic horizon or secondary CaCO 3 within 125 cm. Phaeozems require chroma of ≤3.5 when wet and a calcic horizon or secondary CaCO 3 deeper than 125 cm. Traditionally, morphological assessment in combination with laboratory data has been used to assess the depth of secondary CaCO 3 , thus establishing the taxonomic classification. Herein, the efficacy of portable X-ray fluorescence (PXRF) and visible near infrared spectroscopy (VisNIR) were evaluated to make such determinations in lieu of laboratory data on 25 soil cores collected across five toposequences. Cores were scanned on-site with both sensors at 10 cm increments to determine depth to CaCO 3 accumulation. Comparing Ca percentages from only PXRF with traditional laboratory pressure calcimetry via simple linear regression (SLR), the following model validation data (based on whole core splitting, Core val) were obtained: R2 = 0.92; root mean squared error (RMSE) = 0.81%; residual prediction deviation (RPD) = 3.27: ratio of performance to interquartile range (RPIQ): 5.34. Thus, most of the Ca in soils of the TP is associated with secondary CaCO 3. Using the three most prominent latent variables, VisNIR spectra (smoothed to 10 nm bands) were combined with PXRF data via partial least squares regression (PLSR) to determine if any improvements could be achieved by the combined approach. Combined Core val models produced the following: R2 = 0.89; RMSE = 0.98%; RPD = 2.73; RPIQ = 4.46. Boosted regression tree Core val modeling produced similar results (R2 = 0.90; RMSE = 0.89%; RPD = 2.99; RPIQ = 4.87). With deference to the law of parsimony, use of PXRF data without VisNIR for calcic horizon identification and quantification in conjunction with morphological assessment and interpretation appears preferable for most Pedological applications given its robust, strong performance. Minimal differences were observed using two different sample splitting schemes (whole core vs. full sample set) relative to PXRF data predictive models for CaCO 3 prediction, especially for PXRF with no VisNIR contribution. Of the sites investigated, PXRF identified six phaeozems (P) and nineteen chernozems (C). Specifically, the following were identified on different slope profiles: summits (1P/4C), shoulders (1P/2C), backslopes (3P/7C), footslopes (0P/4C), and toeslopes (1P/2C). Localized landslides and erosion precluded the identification of a common landscape model differentiating P/C on landscapes. Nonetheless, proximal sensors were adept at informing soil properties needed for taxonomic classification on-site, with minimal need for traditional pressure calcimetry. [ABSTRACT FROM AUTHOR]