This paper proposes a methodology for using mobile telephone-based sensor data for detecting spatial and temporal differences in everyday activities in cities. Mobile telephone-based sensor data has ...great applicability in developing urban monitoring tools and smart city solutions. The paper outlines methods for delineating indicator points of temporal events referenced as 'midnight', 'morning start', 'midday', and 'duration of day', which represent the mobile telephone usage of residents (what we call social time) rather than solar or standard time. Density maps by time quartiles were also utilized to test the versatility of this methodology and to analyze the spatial differences in cities. The methodology was tested with data from cities of Harbin (China), Paris (France), and Tallinn (Estonia). Results show that the developed methods have potential for measuring the distribution of temporal activities in cities and monitoring urban changes with georeferenced mobile phone data.
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BFBNIB, DOBA, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Although cold hardiness is known to be a major determinant of tree species distribution, its dynamics and the factors that regulate it remain poorly understood. Variation in cold hardiness and ...carbohydrate concentration, from dormancy induction until bud burst, were investigated in populations of two deciduous (Quercus robur L. and Quercus pubescens Willd.) and one evergreen (Quercus ilex L.) European oak. Mean cold hardiness values in January were -56, -45 and -27 °C for Q. robur, Q. pubescens and Q. ilex, respectively. Soluble carbohydrate concentrations were closely related to instantaneous cold hardiness, estimated by the electrolyte leakage method, whereas total carbohydrate concentration was related to maximum cold hardiness. Both cold hardiness and carbohydrate concentration showed a close linear relationship with temperatures at the location of the sampled population. Our results show that temporal variation in both the inter- and intraspecific cold hardiness in European oaks can be related to variations in the concentrations of soluble carbohydrates and that these relationships appear to be driven by temperature.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Changes in European spring phenology Ahas, R.; Aasa, A.; Menzel, A. ...
International journal of climatology,
30 November 2002, Volume:
22, Issue:
14
Journal Article
The need to examine the entire scope of everyday activities of individuals in segregation studies has recently been recognized by social scientists and policy makers. To bring forth new insights into ...ethnic segregation through investigating the activities and movement undertaken by different population groups, we used mobile phone positioning data to compare the activity spaces of out-of-home nonemployment activities over a one-year period in Estonia and abroad. The results show that ethnicity has a significant influence on the activity spaces of individuals. The biggest differences between the two population groups occur in Estonia outside the respondents' home city of Tallinn, where the Russian-speaking minority was found to visit 45 percent fewer districts than Estonians. Moreover, they exhibit a preference for districts that are more heavily populated by a Russian-speaking population. With respect to international travel, the Russian-speaking minority visits fewer countries and are 3.6 times more likely to visit former Soviet Union countries than Estonians. The activity spaces of out-of-home nonemployment activities have fewer differences between the two groups in the respondents' home city of Tallinn. Overall, our results show that ethnic differences have less effect on the everyday activity space and a greater influence on the choices made regarding long-distance travel.
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BFBNIB, DOBA, INZLJ, IZUM, KILJ, NMLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK, ZRSKP
•We examine monthly human spatial behaviour over a 12-month period.•We use mobile phone call detail records as a novel data source.•Our proposed approach is able to capture longitudinal human spatial ...behaviour.•We provide a set of new insights on monthly variances in human spatial behaviour.
Human activity-travel behaviour (ATB) is a complex pattern of paths and activities in space and time. Studies indicate that ATB is the construction of daily habitual, weekly, monthly and seasonal routines together with strong variety seeking behaviour. Daily habitual travel patterns are usually taken as a basis, but for transportation planners more knowledge is needed on longitudinal trends in human ATB. Empirical data on prolonged perspective are hard to come by while mobile phone based call detail records could be one means of narrowing this research gap. By implementing this method, the present study attempts to provide new insights on individual monthly spatial travel behaviour. Using call detail records obtained from a set of anonymous mobile phone users, we examined their activity locations and activity spaces for 12 consecutive months. We found modest monthly variation in the number of activity locations, whereas there were great variations in the sizes of individual activity spaces. The monthly variation in individual spatial behaviour is explained up to 17% by seasonality, although the variance is predominantly attributed to individual factors and results indicate significant intrapersonal monthly variability. Findings suggest new avenues for future work on ATB from a longitudinal perspective.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The paper introduces methods and applications of the mobile positioning-based social positioning method in geography. The social positioning method (SPM) studies space-time behavior by analyzing the ...location coordinates of mobile phones and the social characteristics of the people carrying them. We describe the experience gained from the SPM pilot studies carried out in Estonia from 2003 to 2006. The results demonstrate that mobile positioning-based tracing is applicable in different geographical studies, as an analysis of temporal movement patterns and activity spaces. The biggest advantage of mobile positioning-based methods is that mobile phones are widespread, positioning works inside buildings, and collection of movement data is done by a third party at regular intervals. The disadvantage of mobile positioning today is relatively low spatial accuracy and surveillance fears. The boom in the generation of phones with A-GPS will improve positioning accuracy in networks.
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Recent warming of Northern Hemisphere (NH) land is well documented and typically greater in wintersolidusspring 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 decadesuperscript -1), late spring warmth (SI first bloom date, -1.0 days decadesuperscript -1; last spring day below 5°C, -1.4 days decadesuperscript -1), and last spring freeze date (-1.5 days decadesuperscript -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.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In this paper the spatial and temporal variability of climatic seasons and phenological phases in Estonia are estimated, and the correlation between them is analysed. The start dates and durations of ...8 climatic seasons at 23 stations and of 16 spring and summer phenological phases in Estonia between 1946 and 1998 were used for data analysis. The homogeneity of long-term series of climatic seasons was tested using an SNHT (standard normal homogeneity test). The time series can be considered nearly homogeneous. The phenological calendar method was applied. Significant spatial and temporal variability of climatic seasons was detected. The thermal influence of the Baltic Sea is the main factor in the formation of spatial differences. Due to the comparatively cold sea surface, the spring season lasts longer in coastal regions. On average, beginning of summer is observed first in southeast Estonia, at the end of May. In North Estonia summer starts at the beginning of June, and in coastal areas in the middle of June. The onset of the springtime phenological phases has a pattern similar to that of the start dates of spring and summer. The onset migrates over Estonia from southeast to northwest. In coastal areas, climatic seasons during the autumn period start 1 to 5 wk later than in continental Estonia. This spatial difference increases from the beginning of autumn to the beginning of winter. Climatic seasons in the spring period have tended to start earlier over the period between 1891 and 1998. At the same time, seasons in the autumn period tended to start later. In conclusion, the summer season has lengthened significantly (by 11 d), while winter has contracted by 30 d. Correlation between start dates of climatic seasons and phenological phases is moderate in Estonia. In most cases, correlation coefficients are statistically significant at the 0.05 confidence level. The highest values are typical for seasons and phases that occur nearly at the same time. In general, the space-time variability of phenological phases is much lower than that of climatic seasons in the same period.
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A phenological calendar with 24 phenological phases was compiled for three meteorological stations in Estonia for the period 1948-1996. We analysed the length of the vegetation period, the order of ...the phenological phases, and the variability and possible changes for two incremental climate change scenarios (+/-2 degrees C), and compared the results with examples of extreme years. The statistically significant linear trends show that the spring and summer-time phenological phases occurred earlier and the autumn phases moved later during the study period. The study of extreme (minimum and maximum) years shows that 70% of the earliest dates of the 24 phases studied have occurred during the last 15 years with an absolute maximum in 1990 with 8 extreme phases. The phenological spring has shortened (slope -0.23), the summer period has lengthened (slope 0.04), and the autumn has lengthened too. The length of the growing season, determined by the vegetation of rye, has shortened (slope -0.09), which could be the result of changing agricultural technology. The correlation between the starting dates of the phenological phases with the air temperature of the previous 2-3 months is relatively high (0.6-0.8). Studying the +2 degrees C and -2 degrees C scenarios and values for the extreme years shows that, in the case of short variations of air temperature, the phenological development remains within the limits of natural variation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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