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This study analyses long‐term changes in drought indices (Standardised Precipitation Index—SPI, Standardised Precipitation–Evapotranspiration Index—SPEI) at 1 and 3 months scales at 182 stations in 11 central and eastern European countries during 1949–2018. For comparative purposes, the necessary atmospheric evaporative demand (AED) to obtain SPEI was calculated using two methods, Hargreaves‐Samani (SPEIH) and Penman‐Monteith (SPEIP). The results show some relevant changes and tendencies in the drought indices. Statistically significant increase in SPI and SPEI during the cold season (November–March), reflecting precipitation increase, was found in the northern part of the study region, in Estonia, Latvia, Lithuania, northern Belarus and northern Poland. In the rest of study domain, a weak and mostly insignificant decrease prevailed in winter. Summer season (June–August) is characterized by changes in the opposite sign. An increase was observed in the north, while a clear decrease in SPEI, reflecting a drying trend, was typical for the southern regions: the Czech Republic, Slovakia, Hungary, Romania, Moldova and southern Poland. A general drying tendency revealed also in April, which was statistically significant over a wide area in the Czech Republic and Poland. Increasing trends in SPI and SPEI for September and October were detected in Romania, Moldova and Hungary. The use of SPEI instead of SPI generally enhances drying trends. [ABSTRACT FROM AUTHOR]

Mobile positioning is recognised to be one of the most promising new sources of data for the production of fast and cost-effective statistics regarding population and mobility. Considerable interest has been shown by government institutions in their search for a way to use mobile positioning data to produce official statistics, although to date there are only few examples of successful projects. Apart from data access and sampling, the main challenges relate to the spatial interpolation of mobile positioning data and extrapolation of recorded data to the level of the entire population. This area of work has to date received relatively little attention in the academic discussion. In the current study, we compare five different methods of spatial interpolation of mobile positioning data. The best methods of describing population distribution and size in comparison with Census data are the adaptive Morton grid and the Random forest model (R2 > 0.9), while the more widely used point-in-polygon and areal-weighted methods produce results that are far less satisfactory (R2 = 0.42; R2 = 0.35). Careful selection of spatial interpolation methods is therefore of the utmost importance for producing reliable population statistics from mobile positioning data. [ABSTRACT FROM AUTHOR]

Similar to every process involving quantitative research, the study of migration heavily depends on the data available for analysis. The available movement data limit the type of questions that can be asked, and as a result, certain aspects of human spatial mobility have yet to be examined. The development of information and communication technologies and their widespread adoption offers new datasets, methods and interpretations that make it possible to study social processes at a new level. For example, mobile positioning data can aid in overcoming certain constraints embedded in traditional data sources (such as censuses or questionnaires) for study of the connections between daily mobility and change of residence. This study presents a framework for mapping changes of residence using data from passive mobile positioning and an anchor point model to better understand the limits of these methods and their contribution to understanding long-term mobility. The study concludes that the most important considerations in monitoring change of residence using passive mobile position data include the continuity of the time-series data, the varying structure of the mobile tower network and the diversified nature of human mobility. The fine spatial and temporal granularities of passive mobile positioning data allow us to study human movement at a detailed scale. [ABSTRACT FROM PUBLISHER]

Abstract: The objective of this study is to analyse the diurnal rhythms of city life and its spatial differences in Tallinn, using mobile telephone positioning data. The positioning experiment was carried out in April 2006 over an 8-day period and 15-min intervals, with a random sample of 277 respondents living in new residential areas outside the city of Tallinn. The investigation of the space–time movements and daily distances of respondents showed that the majority of respondents had a similar temporal rhythm related to work, school, services and leisure in the city. Because of the different timing of those activities, the mobile positioning data made it possible to map functional differences in the city. The advantages and disadvantages of mobile positioning data in mapping urban life are discussed in the final section of the study. [Copyright &y& Elsevier]

Temporal and spatial variabilities of heat waves in the three eastern Baltic countries – Lithuania, Latvia and Estonia – in 1951–2021 were studied. Three heat wave definitions – daily maximum temperature (CTX), daily minimum temperature (CTN) and excess heat factor (EHF) at 90 and 95 percentile levels – were used for the calculation of five heat wave indices – heat wave factor (HWF), heat wave number (HWN), heat wave duration (HWD), heat wave amplitude (HWA) and heat wave magnitude (HWM) – at 40 stations. Additionally, numbers of extremely warm days (Tmax > 27 °C) were analysed. Linear regression and Mann-Kendall tests were applied for trend analysis. The mean spatial distribution of the number of extremely warm days has clear regularities. Lower values are typical for the coastal zone and for the northern part of the study area while higher values are located in the continental region and in the southern part. Extremely warm days are mostly concentrated to the mid-summer period, from 6 July to 9 August. The results of the trend analysis indicate the presence of statistically significant increasing trends in the majority of heat wave indices. The number of extremely warm days has approximately doubled during 1951–2021 while the trend has been statistically significant at all stations. The strongest increasing trends were revealed in the case of HWF (total number of heat wave days). This increase has nearly doubled while the trend was significant at all stations. The increase is stronger also for other heat wave indices measured in days (number of heat waves HWN, duration of heat waves HWD). The indices showing temperature anomalies (HWA, HWM) have notably slower growth trends, which are mostly insignificant. [ABSTRACT FROM AUTHOR]

Understanding segregation plays a significant role in determining the development pathways of a country as it can help governmental and other concerned agencies to prepare better-targeted policies for the needed groups. However, inferring segregation through alternative data, apart from governmental surveys remains limited due to the non-availability of representative datasets. In this work, we utilize Call Data Records (CDR) provided by one of Estonia's major telecom operators to research the complexities of social interaction and human behavior in order to explain gender segregation. We analyze the CDR with two objectives. First, we study gender segregation by exploring the social network interactions of the CDR. We find that the males are tightly linked which allows information to spread faster among males compared to females. Second, we perform the micro-analysis using various users' characteristics such as age, language, and location. Our findings show that the prime working-age population (i.e., (24,54] years) is more segregated than others. We also find that the Estonian-speaking population (both males and females) are more likely to interact with other Estonian-speaking individuals of the same gender. Further to ensure the quality of this dataset, we compare the CDR data features with publicly available Estonian census datasets. We observe that the CDR dataset is indeed a good representative of the Estonian population, which indicates that the findings of this study reasonably reflect the reality of gender segregation in the Estonian Landscape. [ABSTRACT FROM AUTHOR]

Objectives: The Estonian National Mental Health Study (EMHS) was conducted in 2021–2022 to provide population‐wide data on mental health in the context of COVID‐19 pandemic. The main objective of this paper is to describe the rationale, design, and methods of the EMHS and to evaluate the survey response. Methods: Regionally representative stratified random sample of 20,000 persons aged 15 years and older was drawn from the Estonian Population Register for the study. Persons aged 18 years and older at the time of the sampling were enrolled into three survey waves where they were invited to complete an online or postal questionnaire about mental well‐being and disorders, and behavioral, cognitive, and other risk factors. Persons younger than 18 years of age were invited to fill an anonymous online questionnaire starting from wave 2. To complement and validate survey data, data on socio‐demographic, health‐related, and environmental variables were collected from six national administrative databases and registries. Additionally, a subsample was enrolled into a validation study using ecological momentary assessment. Results: In total, 5636 adults participated in the survey wave 1, 3751 in wave 2, and 4744 in wave 3. Adjusted response rates were 30.6%, 21.1%, and 27.6%, respectively. Women and older age groups were more likely to respond. Throughout the three survey waves, a considerable share of adult respondents screened positive for depression (27.6%, 25.1%, and 25.6% in waves 1, 2, and 3, respectively). Women and young adults aged 18 to 29 years had the highest prevalence of depression symptoms. Conclusions: The registry‐linked longitudinal EMHS dataset comprises a rich and trustworthy data source to allow in‐depth analysis of mental health outcomes and their correlates among the Estonian population. The study serves as an evidence base for planning mental health policies and prevention measures for possible future crises. [ABSTRACT FROM AUTHOR]

The paper presents initial steps into the research of commuting patterns and functional regions using mobile phone location data. The main aim is to introduce and discuss the potential of mobile phone location data as an alternative data sources to censuses for mapping commuting flows and subsequent functional regionalization. A set of analytical maps covering various aspects of regular daily movements of population and functional regionalization is provided. Estonia is serving as a pilot laboratory for analyses based on commuting flows derived from mobile phone location data. The maps give to reader a synthetic overview of contemporary settlement system in Estonia and introduce the potential of mobile phone location data for research in this field. [ABSTRACT FROM AUTHOR]

Recent warming of Northern Hemisphere (NH) land is well documented and typically greater in winter/spring than other seasons. Physical environment responses to warming have been reported, but not details of large-area temperate growing season impacts, or consequences for ecosystems and agriculture. To date, hemispheric-scale measurements of biospheric changes have been confined to remote sensing. However, these studies did not provide detailed data needed for many investigations. Here, we show that a suite of modeled and derived measures (produced from daily maximum–minimum temperatures) linking plant development (phenology) with its basic climatic drivers provide a reliable and spatially extensive method for monitoring general impacts of global warming on the start of the growing season. Results are consistent with prior smaller area studies, confirming a nearly universal quicker onset of early spring warmth (spring indices (SI) first leaf date, −1.2 days decade−1), late spring warmth (SI first bloom date, −1.0 days decade−1; last spring day below 5°C, −1.4 days decade−1), and last spring freeze date (−1.5 days decade−1) across most temperate NH land regions over the 1955–2002 period. However, dynamics differ among major continental areas with North American first leaf and last freeze date changes displaying a complex spatial relationship. Europe presents a spatial pattern of change, with western continental areas showing last freeze dates getting earlier faster, some central areas having last freeze and first leaf dates progressing at about the same pace, while in portions of Northern and Eastern Europe first leaf dates are getting earlier faster than last freeze dates. Across East Asia last freeze dates are getting earlier faster than first leaf dates. [ABSTRACT FROM AUTHOR]

Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high-temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single-site or single-species studies are particularly open to suspicion of being biased towards predominantly reporting climate change-induced impacts. No comprehensive study or meta-analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade−1 in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species' phenology is responsive to temperature of the preceding months (mean advance of spring/summer by 2.5 days°C−1, delay of leaf colouring and fall by 1.0 day°C−1). The pattern of observed change in spring efficiently matches measured national warming across 19 European countries (correlation coefficient r=−0.69, P<0.001). [ABSTRACT FROM AUTHOR]