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The novel coronavirus pneumonia (COVID-19) pandemic has caused enormous impacts around the world. Characterizing the risk dynamics for urgent epidemics such as COVID-19 is of great benefit to epidemic control and emergency management. This article presents a novel approach to characterizing the space-time risks of the COVID-19 epidemic. We analyzed the heavy-tailed distribution and spatial hierarchy of confirmed COVID-19 cases in 367 cities from 20 January to 12 April 2020, and population density data for 2019, and modelled two parameters, COVID-19 confirmed cases and population density, to measure the risk value of each city and assess the epidemic from the perspective of spatial and temporal changes. The evolution pattern of high-risk areas was assessed from a spatial and temporal perspective. The number of high-risk cities decreased from 57 in week 1 to 6 in week 12. The results show that the risk measurement model based on the head/tail breaks approach can describe the spatial and temporal evolution characteristics of the risk of COVID-19, and can better predict the risk trend of future epidemics in each city and identify the risk of future epidemics even during low incidence periods. Compared with the traditional risk assessment method model, it pays more attention to the differences in the spatial level of each city and provides a new perspective for the assessment of the risk level of epidemic transmission. It has generality and flexibility and provides a certain reference for the prevention of infectious diseases as well as a theoretical basis for government implementation strategies. [ABSTRACT FROM AUTHOR]

Attribution of compound events informs preparedness for emerging hazards with disproportionate impacts. However, the task remains challenging because space-time interactions among extremes and uncertain dynamic changes are not satisfactorily addressed in the well-established attribution framework. For attributing the 2020 record-breaking spatially compounding flood-heat event in China, we conduct a storyline attribution analysis by designing simulation experiments via a weather forecast model, quantifying component-based attributable changes, and comparing with historical flow analogs. We quantify that given the large-scale circulation, anthropogenic influence to date has exacerbated the extreme Mei-yu rainfall in the mid-lower reaches of the Yangtze River during June-July 2020 by ~6.5% and warmed the co-occurring seasonal extreme heat in South China by ~1°C. Our projections show a further intensification of the compound event by the end of this century, with moderate emissions making the rainfall totals ~14% larger and the season ~2.1°C warmer in South China than the 2020 status. [ABSTRACT FROM AUTHOR]

For spatially dependent functional data, a generalized Karhunen-Loève expansion is commonly used to decompose data into an additive form of temporal components and spatially correlated coefficients. This structure provides a convenient model to investigate the space-time interactions, but may not hold for complex spatio-temporal processes. In this work, we introduce the concept of weak separability, and propose a formal test to examine its validity for non-replicated spatially stationary functional field. The asymptotic distribution of the test statistic that adapts to potentially diverging ranks is derived by constructing lag covariance estimation, which is easy to compute for practical implementation. We demonstrate the efficacy of the proposed test via simulations and illustrate its usefulness in two real examples: China PM 2.5 data and Harvard Forest data. for this article are available online. [ABSTRACT FROM AUTHOR]

Huanglongbing (HLB) is the most harmful bacterial disease in citrus production in the world, and has been seriously ravaging the citrus groves of South China since the 1930s. The surveillance of the epidemiological characteristics of HLB is of utmost priority for citrus production in this region. In order to explore the effects of disease control measures, analyses on the space–time statistical features of the HLB epidemic, from 2019 to 2021, within six orchards in the Guangdong province are presented. Overall, the number of citrus plants in the orchards usually slightly decreased year by year. The reduction was mainly related to the level of plant susceptibility, which is correlated with citrus varieties. The maximum disease severity (incidence and race increment) was correlated with the awareness of this disease and the management intensity applied by the manager. A higher disease index was found in the conventional management orchards than in the comprehensive prevention and control orchards. Proper insect-protective screen houses can effectively prevent the epidemic of HLB, without affecting the fruit quality, and can also aid with higher yields. A high correlation was found between the geometry and topography of orchards and the HLB epidemic due to the wind direction from May to September and the Asia citrus psyllid activity characteristics. For flat orchards, the incidence of HLB in the north and entrance areas was higher than that in the southwest. In the mountain area, the incidence of the windward side in the south was higher than that of the leeward side in the north. Diseased trees tended to have an edge effect in the grove, whereas the trees of the same disease scale were found clustered in their distribution. These results allow a better understanding of HLB epidemiology and provide guidance for the early warning of HLB in new groves in areas that are severely affected by this disease. Furthermore, they also provide a scientific basis for the comprehensive prevention and control of HLB in old groves. [ABSTRACT FROM AUTHOR]

The rapid development of high-speed rail has markedly shortened the travel time from one city to another. However, the impact of space–time compression brought about by high-speed rail on city innovation has not received sufficient attention. This paper examines the space–time compression phenomenon produced by high-speed railway networks and its impact on city innovation from 2000 to 2019 using a sample of 279 Chinese prefecture-level cities. The empirical results show that there was a strong space–time compression during this period. The development of high-speed rail can promote city innovation. However, the construction of high-speed rail also produces a siphon effect, which accelerates the convergence of innovative elements in cities with stronger innovation capabilities. Nevertheless, it has a negative spillover effect on cities with weaker innovation capabilities. Finally, policy recommendations for promoting the balanced development of city innovation and recommendations for future research are presented. [ABSTRACT FROM AUTHOR]

Classical Chinese gardens have a distinct layout structure. By studying the traditional Chinese conception of space–time and its characteristics, this article explores the spatiotemporal narrative structure and typological patterns of the Lingering Garden, which is highly representative of Souzhou gardens in China. While existing literature addresses the sagittal and cyclical concepts of space–time, this paper advances a separate and interactive view of space–time using Yin-Yang transformation logic. Field research revealed that three space–time natures emerge as three spatiotemporal narratives in the Lingering Garden (sagittal, cyclical, and separate-and-interactive) with different characteristics. These modes intertwine in different ways in the garden's five areas to form the Lingering Garden's holistic spatiotemporal narrative structure, which nurtures dynamic experiences and infinite imagination. This result helps us better understand other Chinese gardens and supplements the theory of gardening art; however, more case studies should be done to determine its generalisability. [ABSTRACT FROM AUTHOR]

Copyright of Geography & Geographic Information Science is the property of Geography & Geo-Information Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The problem of urban crashes brings huge challenges and threats to local police and governments, especially in many cities in developing countries such as China. To reduce the frequency and severity of urban crashes, the local government in China has gradually taken interest in conducting detailed actions of traffic safety improvement at the microzone-level. Therefore, the primary goal of this study is to try a new method in spatiotemporal data mining techniques, the space-time cube method, to find high-risk crash spots at the spatiotemporal level and to obtain their spatiotemporal evolution patterns. The cumulative frequency curve method was performed to identify high-risk crash spots, and the contributory factors of forming these spots were analyzed by the latent class analysis method. The results showed that: (1) key parameters' selection is crucial in the space-time cube construction; (2) the exit ramp gore point in interchanges, intersections, and entrances of neighborhoods were prone to have many high-risk crash spots at the spatiotemporal scale; and (3) locations with consecutive, persistent, and sporadic hotspots patterns need different risk monitoring strategies and traffic safety improvement. The feasibility and advantages of the space-time cube method in hotspots identification at the microzone-level were confirmed. [ABSTRACT FROM AUTHOR]

Monitoring of the indicator Sustainable Development Goal (SDG) 11.3.1 is important for understanding the coordination between land consumption rate (LCR) and population growth rate (PGR). However, the spatiotemporal indicator SDG 11.3.1 changes at the urban agglomeration (UA) level, and the relationship between LCR and PGR in the prefecture-level cities from different UAs remains unclear. In this study, we monitored the spatiotemporal indicator SDG 11.3.1 in the Yangtze River Economic Belt (YREB) and its three major UAs (i.e., Chengdu–Chongqing (CC), the Middle Reaches of the Yangtze River (MRYR), and the Yangtze River Delta (YRD)) for the periods 2000–2010, 2010–2015, and 2015–2018, using the space–time interaction (STI) method and Pearson's method. Our major findings were as follows: (1) Compared with the world average of 1.28 for LCRPGR (i.e., ratio of LCR to PGR), except for the LCRPGR of the YRD (2000–2018) and CC (2000–2010), the LCRPGR of CC, the MRYR, and the YREB was lower than 1.28 during 2000–2018. (2) The gaps in both population and built-up area between the YREB and the three UAs did not narrow, but widened. (3) Compared with the LCRPGR in China, except for the LCRPGR of the YRD (2000–2018) and CC (2000–2010), the LCRPGR of the YREB increased from 1.21 to 1.23 between 2000–2010 and 2010–2015, and then decreased to 1.16 in 2015–2018, indicating that the relationship between LCR and PGR in the YREB is relatively stable. (4) A significant positive relationship (p < 0.001) was found between LCR and PGR in CC, the MRYR, the YRD, and the YREB. We conclude that the indicator SDG 11.3.1 is a helpful tool for evaluating land-use efficiency caused by the LCR and PGR at the UA level. Our results provide information support for promoting sustainable and coordinative development between LCR and PGR. [ABSTRACT FROM AUTHOR]

Copyright of New Architecture is the property of New Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Guangxi is a high prevalence area of tuberculosis (TB) in China, urgent needing of further TB reduction. Our purpose is to analyze the epidemiological characteristics of TB in Guangxi and analyze the relationship between socioeconomic factors and TB from the dimensions of time and space to provide evidence to effectively prevent and control TB. Patients and Methods: We performed a retrospective analysis of the epidemiology of TB. Moran's index (I) was used for spatial autocorrelation analysis, and space-time scanning was used to detect temporal, space, and space-time clusters of TB. A Bayesian space-time model was used to analyze related factors of the TB epidemic at the county level in Guangxi. Results: From 2015 to 2019, a total of 233,623 TB cases were reported in Guangxi. The majority of TB cases were in males; the reported incidence of TB was the highest in people aged ≥ 65 years. By occupation, farmers were the most frequently affected. The overall reported incidence of TB decreased by 4.95% during this period. Tuberculosis occurs all year round, but the annual reporting peak is usually from March to July. Spatial autocorrelation analysis showed that the reported incidence of TB in 2015– 2019 was spatially clustered (Moran's I > 0, P < 0.05); Kulldorff's scan revealed that the space-time cluster (log-likelihood ratio = 2683.76, relative risk = 1.60, P < 0.001) was mainly concentrated in northern Guangxi. Using Bayesian space-time modeling, socioeconomic and healthcare factors are related to the high prevalence of TB. Conclusion: The prevalence of TB is influenced by a space-time interaction effect and is associated with socioeconomic and healthcare status. It is necessary to improve the economic development and health service in areas with a high TB prevalence. Graphical [ABSTRACT FROM AUTHOR]

Accumulating evidence suggests that people's sense of the spatial location of events in time is flexible across cultures, contexts, and individuals. Yet few studies have established whether time spatialization is correlated with traumatic experiences. Based on findings that people tend to demonstrate a past time orientation when suffering from disasters, the present research investigated how earthquake experience is associated with temporal focus and time spatialization. Study 1 compared responses of residents in an earthquake-hit area with those of residents in a non-disaster area about two weeks after the disaster had occurred. The results showed that participants in the disaster area were more past-focused and produced more past-in-front responses than participants in the non-disaster area. In Study 2, a follow-up survey was conducted in the same areas ten months after the earthquake to examine whether the impact of disasters on spatial conceptions of time would decay as time elapsed. The findings indicated that participants in these two areas showed no differences in temporal focus and implicit space–time mappings. Taken together, these findings provide support for the Temporal Focus Hypothesis. They also have implications for understanding fluctuation in temporal focus and the high malleability of temporal mappings across individuals. [ABSTRACT FROM AUTHOR]

Drought is a common natural disaster that greatly affects the crop yield and water supply in China. However, the spatiotemporal characteristics of drought in China are not well understood. This paper explores the spatial and temporal distributions of droughts in China over the past 40 years using multiscale standardized precipitation evapotranspiration index (SPEI) values calculated by monthly precipitation and temperature data from 612 meteorological stations in China from 1980 to 2019 and combines the space–time cube (STC), Mann–Kendall test, emerging spatiotemporal hot-spot analysis, spatiotemporal clustering, and local outliers for the analysis. The results were as follows: 1) the drought frequency and STC show that there is a significant difference in the spatiotemporal distribution of drought in China, with the most severe drought in Northwest China, followed by the western part of Southwest China and the northern part of North China. 2) The emerging spatiotemporal hot-spot analysis of SPEI6 over the past 40 years reveals two cold spots in subregion 4, indicating that future droughts in the region will be more severe. 3) A local outlier analysis of the multiscale SPEI yields a low–low outlier in western North China, indicating relatively more severe year-round drought in this area than in other areas. The low–high outlier in central China indicates that this region was not dry in the past and that drought will become more severe in this region in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • The mean latent/removed periods of the COVID-19 epidemic in China were 5.40/2.13 days. • There were 1.72 latent/infected persons per 10,000 Wuhan travelers up to January 20th. • Space-time R 0 estimates indicated an initial value between 2 and 3.5 in most cities. • There were 196 cities that had an estimated R 0 < 1 on February 29th. • A clear descent in temporal R 0 started one week after the outbreak and lasted for two weeks. The novel coronavirus (COVID-19) epidemic is reaching its final phase in China. The epidemic data are available for a complete assessment of epidemiological parameters in all regions and time periods. This study aims to present a spatiotemporal epidemic model based on spatially stratified heterogeneity (SSH) to simulate the epidemic spread. A susceptible-exposed/latent-infected-removed (SEIR) model was constructed for each SSH-identified stratum (each administrative city) to estimate the spatiotemporal epidemiological parameters of the outbreak. We estimated that the mean latent and removed periods were 5.40 and 2.13 days, respectively. There was an average of 1.72 latent or infected persons per 10,000 Wuhan travelers to other locations until January 20th, 2020. The space-time basic reproduction number (R 0) estimates indicate an initial value between 2 and 3.5 in most cities on this date. The mean period for R 0 estimates to decrease to 80%, and 50% of initial values in cities were an average of 14.73 and 19.62 days, respectively. Our model estimates the complete spatiotemporal epidemiological characteristics of the outbreak in a space-time domain. These findings will help enhance a comprehensive understanding of the outbreak and inform the strategies of prevention and control in other countries worldwide. [ABSTRACT FROM AUTHOR]

While increased tourist demand has brought economic benefits to tourist destinations, it has also put tremendous pressure on tourism-related ecological environments. Therefore, the relationship between regional urban tourism's economic benefits and tourism ecologies must be considered by increasing the ecological security levels of regional urban tourism and promoting sustainable tourism development. This paper defines the ecological security of regional urban tourism, constructs an indicator system of said ecological security based on a pressure-state-response social-economic-environment (PSR-SEE) model, uses the entropy method to objectively assign weights to the indicator system, constructs a dynamic multi-scenario simulation model to assess ecological security under continuous, economic priority and various ecological protection scenarios, employs ArcGIS software to analyze the spatial distribution patterns of the ecological security of regional urban tourism, and uses a standard deviation ellipse method to analyze the space–time evolutionary track of the ecological security of regional urban tourism. The index system is applied to 16 cities in Hubei Province to measure the ecological security levels and test the viability of the system. The present research focuses on the space–time evolution of the ecological security of regional urban tourism, addresses the contradictions between socioeconomic development and the ecological security of regional urban tourism, provides an important reference for tourism destination planning, and can assist in improving the levels of the ecological security of regional urban tourism to promote sustainable tourism development. [ABSTRACT FROM AUTHOR]

COVID-19 outbreaks in China in late December 2019, then in the United States (US) in early 2020. In the initial wave of diffusion, the virus respectively took 14 and 33 days to spread across the provinces/states in the Chinese mainland and the coterminous US, during which there are 43% and 70% zero entries in the space-time series for China and US respectively, indicating a zero-inflated count process. A logistic growth curve as a function of the number of days since the first case appeared in each of these countries accurately portrays the national aggregate per capita rates of infection for both. This paper presents two space-time model specifications, one based upon the generalized linear mixed model, and the other upon Moran eigenvector space-time filtering, to describe the spread of COVID-19 in the initial 19 and 58 days across the Chinese mainland and the coterminous US, respectively. Results from these case studies show both models shed new light on the role of spatial structures in COVID-19 diffusion, models that can forecast new cases in subsequent days. A principal finding is that describing the spatio-temporal diffusion of COVID-19 benefits from including a hierarchical structural component to supplement the commonly employed contagion component. [ABSTRACT FROM AUTHOR]

City service demand fluctuates across space and time. Although various data, such as 311 hotline data and social media data, have been used to explore the spatiotemporal patterns of city services, data uncertainty and the uneven distribution of service demand are overlooked to some extent and thus could result in bias. To overcome these shortcomings, top‐down collected city service data that fully cover urban areas are used as an emerging data source in this article. A visual analytical approach that employs a three‐dimensional model based on a space‐time cube combined with the Mann–Kendall algorithm is developed and applied in Xicheng District, Beijing, China. The results show that in comparison to other methods, the emerging data and visualization methods have more power to explain city services in terms of overall trends and micro‐scale details. For instance, city service cases demonstrate a significant downward trend. Meanwhile, the distribution of hotspots/coldspots is found to be related to the built environment and population density. For example, high‐incidence cases are located in some communities that are the key governance areas, indicating a demand to increase the staffing of grid administrators. The findings of this work can potentially benefit other cities in China and worldwide. [ABSTRACT FROM AUTHOR]

The spatiotemporal heterogeneity of b values has great potential for helping in understanding the seismogenic process and assessing seismic hazard. However, there is still much controversy about whether it exists or not, and an important reason is that the choice of subjective parameters has eroded the foundations of much research. To overcome this problem, we used a recently developed non-parametric method based on a data-driven concept to calculate b values. The major steps of this method include (1) performing a large number of Voronoi tessellations and Bayesian information criterion (BIC) value calculation, selecting the optimal models for the study area, and (2) using the ensemble median (Q2) and median absolute deviation (MAD) value to represent the final b value and its uncertainty. We investigated spatiotemporal variations in b values before and after the 2019 Changning MS=6.0 earthquake in the Sichuan Basin, China. The results reveal a spatial volume with low pre-mainshock b values near the mainshock source region, and its size corresponds roughly with the rupture area of the mainshock. The anomalously high pre-mainshock b values distributed in the NW direction of the epicenter were interpreted to be related to fluid invasion. The decreases in b values during the aftershock sequence along with the occurrences of several strong aftershocks imply that b values could be an indicator of the stress state. In addition, we found that although the distribution characteristics of b values obtained from different methods of investigation are qualitatively consistent, they differ significantly in terms of their specific values, suggesting that the best way to study the heterogeneous pattern of b values is in the joint dimension of space-time rather than separately in time and space. Overall, our study emphasizes the importance of b -value studies in assessing earthquake hazards. [ABSTRACT FROM AUTHOR]

Fine particulate matter with a diameter of less than 2.5 µm (PM2.5) has been used as an important atmospheric environmental parameter mainly because of its impact on human health. PM2.5 is affected by both natural and anthropogenic factors that usually have strong diurnal variations. Such information helps toward understanding the causes of air pollution, as well as our adaptation to it. Most existing PM2.5 products have been derived from polar-orbiting satellites. This study exploits the use of the next-generation geostationary meteorological satellite Himawari-8/AHI (Advanced Himawari Imager) to document the diurnal variation in PM2.5. Given the huge volume of satellite data, based on the idea of gradient boosting, a highly efficient tree-based Light Gradient Boosting Machine (LightGBM) method by involving the spatiotemporal characteristics of air pollution, namely the space-time LightGBM (STLG) model, is developed. An hourly PM2.5 dataset for China (i.e., ChinaHigh PM2.5) at a 5 km spatial resolution is derived based on Himawari-8/AHI aerosol products with additional environmental variables. Hourly PM2.5 estimates (number of data samples = 1 415 188) are well correlated with ground measurements in China (cross-validation coefficient of determination, CV- R2 = 0.85), with a root-mean-square error (RMSE) and mean absolute error (MAE) of 13.62 and 8.49 µgm-3 , respectively. Our model captures well the PM2.5 diurnal variations showing that pollution increases gradually in the morning, reaching a peak at about 10:00 LT (GMT + 8), then decreases steadily until sunset. The proposed approach outperforms most traditional statistical regression and tree-based machine-learning models with a much lower computational burden in terms of speed and memory, making it most suitable for routine pollution monitoring. [ABSTRACT FROM AUTHOR]

The spatiotemporal heterogeneity of b values has great potential for understanding the seismogenic process and assessing the seismic hazard. However, there is still much controversy about whether it exists or not, and an important reason is that the choice of subjective parameters has eroded the foundations of many researches. To overcome this problem, we used a recent developed non-parametric method based on the data-driven concept to calculate b values. The major steps of this method include: 1) perform a large number of Voronoi tessellation, Bayesian information criterion (BIC) value calculation and selection of the optimal models for the study area, and 2) use the ensemble median (Q2) and median absolute deviation (MAD) value to represent the final b value and its uncertainty. We investigated spatiotemporal variations of b values before and after the 2019 Changning MS 6.0 earthquake in Sichuan Basin, China. The results reveal a spatial volume with low pre-mainshock b values near the mainshock source region, and its size corresponds roughly with the rupture area of the mainshock. The anomalously high pre-mainshock b values distributed in the NE direction of the epicenter was interpreted to be related with fluid invasion or increased pore pressure. The decreases of b values during the aftershock sequence along with the occurrences of several strong aftershocks imply that b values could be an indicator of stress state. In addition, we found that although the distribution characteristics of b values obtained from different way of investigating are qualitatively consistent, they differ significantly in terms of their specific values, suggesting that the best way to study the heterogeneous pattern of b values is in the joint dimension of space-time rather than alone in time and space. Overall, our study emphasizes the importance of b value studies on assessing the earthquake hazards. [ABSTRACT FROM AUTHOR]

Human adenovirus (HAdV-7) is a highly contagious pathogen that causes severe respiratory illnesses. However, the epidemic patterns and genetic variability of HAdV-7 circulating in mainland China have not been well elucidated. In this study, we used Chinese HAdV sentinel surveillance data obtained from 2012–2015 to investigate the clinical features of 122 HAdV-7-positive cases and performed amplification and sequence determination of three capsid genes (penton base, hexon, and fiber) from 69 isolated viruses covering from seven provinces of China. Additionally, we compared with data from representative sequences of 21 strains covering seven more provinces in China and 32 international HAdV-7 strains obtained from GenBank database to determine the phylogenetic, sequence variations, and molecular evolution of HAdV-7. The results indicated that HAdV-7 infection occurred throughout the year, and a high proportion of severe cases (27 cases, 22.1%) exhibited infantile pneumonia. Moreover, phylogenetic analysis showed that all HAdV-7 strains could be divided into two major evolutionary branches, including subtype 1 and subtype 2, and subtype 3 was also formed according to analysis of the penton base gene. Subtypes 1 and 2 co-circulated in China before 2008, and HAdV-7 strains currently circulating in China belonged to subtype 2, which was also the predominant strain circulating worldwide in recent years. Further sequence variation analysis indicated that three genes of HAdV-7 were relatively stable across time and geographic space, particularly for viruses within subtypes, which shared almost the same variation sites. Owing to continuous outbreaks caused by HAdV-7, resulting in increased illness severity and fatality rates in China, the establishment of a national HAdV surveillance system is urgently needed for the development of effective preventive and infection-control interventions for adenovirus respiratory infections in China. [ABSTRACT FROM AUTHOR]

According to the existing researches of aerosol optical depth （AOD） spatial coverage improve⁃ ment, the spatial⁃temporal correlation of multi⁃source products is not fully considered in the fusion process, and the uncertainty of the estimated results is not considered. This paper proposes an AOD spatial coverage improvement method based on spatio ⁃ temporal random effects （STRE） modeling with the uncertainty constraint. And this method is applied to the spatial coverage improvement of daily Moderate ⁃ resolution Imaging Spectroradiomete （MODIS） AOD products in eastern China from January 2013 to December 2017. The results show that the STRE model AOD spatial coverage improvement method can effectively improve the spatial coverage and temporal completeness of AOD by considering the temporal and spatial correlation of AOD data. And the introduction of uncertainty analysis in the STRE model AOD spatial coverage improvement can effectively reduce the accuracy of the overall coverage improvement results, es⁃ pecially for the region with serious missing original AOD data on time and space. [ABSTRACT FROM AUTHOR]

Political actors communicate strategic narratives to shape the meaning of place-images in the past, present and future. Whether narratives about the past are persuasive depends on the translation of historical ideas embedded in these narratives across time and space. Moreover, the imagination and re-imagination of historical place-images in foreign policy communication are contentious, because they stand for specific power relations and identity narratives. Therefore, actor's selective uses of history require disambiguation to increase positive perception. This abstract argument is theorised in an investigation of China's Belt and Road Initiative, specifically the communication of a New Silk Road. China's promotion of the Silk Road legacy is frequently contested with Great Game interpretations. Through the novels of Marco Polo and Rudyard Kipling, which present historical imaginations of the Silk Road and the Great Game, this study shows the contentiousness of historical place-images across time and space. [ABSTRACT FROM AUTHOR]

To investigate the genetic diversity, time origin, and evolutionary history of the 2019‐nCoV outbreak in China and Thailand, a total of 12 genome sequences of the virus with known sampling date (24 December 2019 and 13 January 2020) and geographic location (primarily Wuhan city, Hubei Province, China, but also Bangkok, Thailand) were analyzed. Phylogenetic and likelihood‐mapping analyses of these genome sequences were performed. On the basis of our results, the star‐like signal and topology of 2019‐nCoV may be indicative of potentially large "first generation" human‐to‐human virus transmission. We estimated that 2019‐nCoV likely originated in Wuhan on 9 November 2019 (95% credible interval: 25 September 2019 and 19 December 2019), and that Wuhan is the major hub for the spread of the 2019‐nCoV outbreak in China and elsewhere. Our results could be useful for designing effective prevention strategies for 2019‐nCoV in China and beyond. Highlights: On the basis of our results in the present study, the star‐like signal and topology of 2019‐nCoV may be indicative of potentially large "first generation" human‐to‐human virus transmission. We estimated that 2019‐nCoV likely originated in Wuhan on 9 November 2019 (95% Bayesian credible interval: 25 September 2019 and 19 December 2019). Future study should include comparative analyses of between‐host and within‐host transmission of 2019‐nCOV, and finer scale epidemiology to elucidate the transmission dynamics of different hosts through time and space. However, we acknowledge that the estimates presented here relate only to a limited number of 2019‐nCOV genome sequences and our results are estimated with some uncertainty. Therefore, our conclusions should be considered preliminary and explained with caution. Our results could be useful for designing effective prevention strategies for 2019‐nCoV in China and beyond. [ABSTRACT FROM AUTHOR]

Lamproites and kimberlites are natural probes of the subcontinental lithospheric mantle providing insights into the Earth's continental lithosphere. Whole-rock major-, trace-element and Sr–Nd–Pb isotopic compositions of the Paleozoic (~ 253 Ma) lamproite dikes from the Baifen zone of the Zhenyuan area in southeastern Guizhou Province (in the southern Yangtze Block, South China) are presented. The Baifen lamproites are characterized by high MgO (7.84–14.1 wt%), K2O (3.94–5.07 wt%) and TiO2 (2.69–3.23 wt%) contents, low SiO2 (41.3–45.7 wt%), Na2O (0.21–0.28 wt%) and Al2O3 (6.10–7.20 wt%) contents. All lamproites have elevated Cr (452–599 ppm) and Ni (485–549 ppm) abundances, as well as high Ba (1884–3589 ppm), La (160–186 ppm), Sr (898–1152 ppm) and Zr (532–632 ppm) concentrations. They show uniform REE distribution patterns that are strongly enriched in light REEs relative to heavy REEs [(La/Yb)N = 71.1–87.6], and exhibit OIB-like geochemical features with obvious enrichment of both LILEs and HFSEs in the primitive mantle-normalized multi-element distribution diagram. Moderately radiogenic Sr (87Sr/86Sri = 0.706336–0.707439), unradiogenic Nd (143Nd/144Ndi = 0.511687–0.511704 and εNd(t) = − 12.2 to − 11.9), and low initial Pb (206Pb/204Pbi = 16.80–16.90, 207Pb/204Pbi = 15.34–15.35 and 208Pb/204Pbi = 37.43–37.70) isotopic compositions are obtained from the rocks. They yield old model ages of TDM(Nd) = 1.48–1.54 Ga. These signatures suggest that the Baifen lamproite magmas are alkaline, ultrapotassic and ultramafic in character and mainly represent mantle-derived primary melts, which have undergone insignificant crustal contamination and negligible fractional crystallization. The Baifen lamproites originated from a veined metasomatized lithospheric mantle source. We envisage that they were derived by partial melting of old, mineralogically complex metasomatic vein assemblages in the subcontinental lithospheric mantle beneath the southern Yangtze Block. The source region experienced ancient mantle metasomatism with complex modification by enriched fluids and melts. The metasomatic agents are most likely to originate from pre-existing slab subduction beneath the southeastern margin of the Yangtze Block. Tectonically, the Baifen lamproites were emplaced at the southern margin of the Yangtze Block, and they formed in an intraplate extensional setting, showing an anorogenic affinity. In terms of time and space, the genesis of Baifen lamproites is presumably related to the Emeishan large igneous province. The Emeishan mantle plume is suggested as an effective mechanism for rapid extension and thinning of the lithosphere, followed by decompression melting of the subcontinental lithospheric mantle. Combined with the thermal perturbation from asthenospheric upwelling induced by the Emeishan mantle plume, the lamproite magmas, representing small volume and limited partial melts of ancient enriched mantle lithosphere, arose. We propose that the generation of the Baifen lamproite dikes probably was a consequence of the far-field effects of the Emeishan mantle plume. [ABSTRACT FROM AUTHOR]

In order to monitor progress towards malaria elimination, it is crucial to be able to measure changes in spatio-temporal transmission. However, common metrics of malaria transmission such as parasite prevalence are under powered in elimination contexts. China has achieved major reductions in malaria incidence and is on track to eliminate, having reporting zero locally-acquired malaria cases in 2017 and 2018. Understanding the spatio-temporal pattern underlying this decline, especially the relationship between locally-acquired and imported cases, can inform efforts to maintain elimination and prevent re-emergence. This is particularly pertinent in Yunnan province, where the potential for local transmission is highest. Using a geo-located individual-level dataset of cases recorded in Yunnan province between 2011 and 2016, we introduce a novel Bayesian framework to model a latent diffusion process and estimate the joint likelihood of transmission between cases and the number of cases with unobserved sources of infection. This is used to estimate the case reproduction number, Rc. We use these estimates within spatio-temporal geostatistical models to map how transmission varied over time and space, estimate the timeline to elimination and the risk of resurgence. We estimate the mean Rc between 2011 and 2016 to be 0.171 (95% CI = 0.165, 0.178) for P. vivax cases and 0.089 (95% CI = 0.076, 0.103) for P. falciparum cases. From 2014 onwards, no cases were estimated to have a Rc value above one. An unobserved source of infection was estimated to be moderately likely (p>0.5) for 19/ 611 cases and high (p>0.8) for 2 cases, suggesting very high levels of case ascertainment. Our estimates suggest that, maintaining current intervention efforts, Yunnan is unlikely to experience sustained local transmission up to 2020. However, even with a mean of 0.005 projected up to 2020, locally-acquired cases are possible due to high levels of importation. Author summary: Although malaria is still responsible for a great deal of death and illness in many parts of the world, many national control programmes have made great strides in controlling malaria and now are in a position to aim for elimination. However, in order to monitor progress towards elimination and plan interventions, it is crucial to measure malaria transmission and how it varies over space and time. However, traditional metrics used to measure malaria transmission are not suitable in elimination settings. China is one example of a country approaching elimination, with aims to eliminate the disease by 2020. Using a detailed individual level dataset of the times and locations of people showing symptoms of malaria, we use approaches adapted from the study of how information spreads through social networks to estimate the likelihood of transmission occurring between cases. This information is used to estimate how many people we expect each case to go on to infect. In elimination settings, this number is an indication of how quickly elimination will be reached and how likely we are to see a resurgence in cases once elimination is achieved. Our results show a decline in this metric over time, as well as seasonal changes in transmission which are different to the patterns in when the most cases were observed. [ABSTRACT FROM AUTHOR]

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Aims Morphological variation of leaves is a key indicator of plant response to climatic change. Leaf size and shape are associated with carbon, water and energy exchange of plants with their environment. However, whether and how leaf size and shape responded to climate change over the past decades remains poorly studied. Moreover, many studies have only explored inter- but not intraspecific variation in leaf size and shape across space and time. Methods We collected >6000 herbarium specimens spanning 98 years (1910–2008) in China for seven representative dicot species and measured their leaf length and width. We explored geographical patterns and temporal trends in leaf size (i.e. leaf length, leaf width and length × width product) and shape (i.e. length/width ratio), and investigated the effects of changes in precipitation and temperature over time and space on the variation in leaf size and shape. Important Findings After accounting for the effects of sampling time, leaf size decreased with latitude for all species combined, but the relationship varied among species. Leaf size and shape were positively correlated with temperature and precipitation across space. After accounting for the effects of sampling locations, leaf size of all species combined increased with time. Leaf size changes over time were mostly positively correlated with precipitation, whereas leaf shape changes were mostly correlated with temperature. Overall, our results indicate significant spatial and temporal intraspecific variation in leaf size and shape in response to climate. Our study also demonstrates that herbarium specimens collected over a considerable period of time provide a good resource to study the impacts of climate change on plant morphological traits. [ABSTRACT FROM AUTHOR]

The FAO-56 Penman-Monteith estimates that the ET0 method is widely used, but multiple meteorological data are required for calculation. Developing an alternative method that can provide accurate or at least close to the FAO-56 Penman-Monteith ET0 estimate is one of the research hotspots in the field with as little meteorological data as possible. In this paper, combined with Canonical Correlation Analysis (CCA) and k nearest neighbor algorithm (k-NN), the potential evapotranspiration calculation method (CCA-k-NN) of self-optimizing nearest neighbor algorithm is proposed, and the potential evapotranspiration is realized by using less meteorological data. Estimate. The core idea is to use the CCA algorithm to find the meteorological data most relevant to the potential evapotranspiration, to realize the dimensionality reduction of the meteorological data when the ET0 is estimated later, and then use the k-NN algorithm to estimate the ET0. The Northwest China region was selected as a use case. The regional meteorological data were divided into training dataset, verification dataset and test dataset from time and space scales. The ET0 was estimated by the method in the three types of datasets respectively, and the FAO-56 Penman-Monteith as a reference, evaluated the estimation accuracy and applicability of the CCA-k-NN method. The results show that the CCA-k-NN method has a high correlation with the FAO-56 Penman-Monteith (correlation coefficient greater than 0.9), and has good estimation accuracy. The root mean square error and Mean Absolute Error are both less than 1 mm·d-1. On the spatial scale, the Nash-Sutcliffe coefficient of efficiency is greater than 0.5, and the Nash-Sutcliffe coefficient of efficiency on the time scale is greater than 0.8, the CCA-k-NN method is applicable at both space and time scales. At the same time, compared with other alternative methods, the algorithm has low time complexity O(n), which can effectively reduce the time cost when calculating large amounts of data. The FAO-56 Penman-Monteith estimates that the ET0 method is widely used, but multiple meteorological data are required for calculation. Developing an alternative method that can provide accurate or at least close to the FAO-56 Penman-Monteith ET0 estimate is one of the research hotspots in the field with as little meteorological data as possible. In this paper, combined with Canonical Correlation Analysis (CCA) and k nearest neighbor algorithm (k-NN), the potential evapotranspiration calculation method (CCA-k-NN) of self-optimizing nearest neighbor algorithm is proposed, and the potential evapotranspiration is realized by using less meteorological data. Estimate. The core idea is to use the CCA algorithm to find the meteorological data most relevant to the potential evapotranspiration, to realize the dimensionality reduction of the meteorological data when the ET0 is estimated later, and then use the k-NN algorithm to estimate the ET0. The Northwest China region was selected as a use case. The regional meteorological data were divided into training dataset, verification dataset and test dataset from time and space scales. The ET0 was estimated by the method in the three types of datasets respectively, and the FAO-56 Penman-Monteith as a reference, evaluated the estimation accuracy and applicability of the CCA-k-NN method. The results show that the CCA-k-NN method has a high correlation with the FAO-56 Penman-Monteith (correlation coefficient greater than 0.9), and has good estimation accuracy. The root mean square error and Mean Absolute Error are both less than 1 mm·d-1. [ABSTRACT FROM AUTHOR]

Ecological wisdom in traditional nomadic societies is formed in the process of production, life and spiritual belief. Nomadic settlements are multidimensional cultural heritage and cultural landscape types in post-modern society. This research takes Qiongkushitai village as the research object, and referring to the research methods and achievements of human geography and temporal geography, this paper discusses the spatiotemporal features and evolution of the traditional nomadic settlements under the process of rapid urbanisation. Taking local wisdom as the breakthrough point, two characteristics of the traditional nomadic spatiotemporal picture are condensed: ❶ self-adaptability of nomadic spatiotemporal picture restricted by alpine resources, ❷ multi-level nesting law of nomadic spatiotemporal picture. By extracting the typical fragments on the spatiotemporal axis, this paper attempts to propose a periodic activity model on the multi-level spatiotemporal scale in the nomadic space and time trajectory. This paper explores the evolution mechanism of traditional nomadic settlements driven by national policies, individual demands, technology, and market. The results of this study can provide information for the study of resilience construction in the construction of ecological civilisations in alpine pastoral areas in Western China. [ABSTRACT FROM AUTHOR]

China has experienced persistent fine particulate matter (PM 2.5) pollution for the past few years, which adversely affects both physical and mental health. The availability of high-accuracy and full-coverage PM 2.5 products will be of substantial value in formulating effective policies to combat and regulate PM 2.5 pollution. Therefore, we have developed a similarity distance-based space-time random forest (SDSTRF) model to estimate daily PM 2.5 concentrations over China by integrating surface measurements, satellite aerosol products, meteorological data, and auxiliary information. The proposed model not only accounts for spatial-temporal heterogeneity, but also uses the similarity distance to avoid errors caused by outliers. It has undergone rigorous validation through three different cross-validation (CV) approaches and has shown high and stable accuracy, particularly in the site-based CV with a coefficient of determination (R2) of 0.87, and a root mean square error (RMSE) of 10.68 μg/m3, along with a relative RMSE (rRMSE) of 27.48%. In addition, the leave-out data are predicted to determine if the SDSTRF model is accurate in its predictive power, which achieves an impressive site-based CV R2 of 0.80 and an RMSE of 12.89 μg/m3, along with an rRMSE of 33.01%. The results from a variety of validation approaches strongly indicate that the SDSTRF model can provide accurate estimation of PM 2.5 concentrations at different time scales and outperform many other space-time models by incorporating similarity distance. The proposed model would be a promising application in air pollution studies with remote sensing. • A similarity distance-based space-time random forest is used for PM 2.5 estimation. • The similarity distance indicator contributes to improving the estimation accuracy. • The model outperforms other widely used regression models in predictive power. • PM 2.5 concentrations at 0.1° are generated based on the latest MODIS AOD (C6.1). [ABSTRACT FROM AUTHOR]

Copyright of Tourism Tribune / Lvyou Xuekan is the property of Tourism Institute of Beijing Union University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Droughts are regional phenomena that dynamic varied along the time; however, the spatiotemporal dynamic processes of drought were usually ignored in the drought identification methods. To better understand the space-time structure of drought, a space-time continuum drought identification method was used to identify drought intensity, duration, and area in Huai River basin, and their multiple dependences were modeled by copulas. The Intensity-Area-Frequency (IAF) curves were used to model the regional variation of drought in this study. Without identified space-time structure of drought, the construction of IAF curves is usually focusing on the decreasing drought intensity with increasing areal extent. However, stronger drought intensity was found to be followed by larger areal extent when considering the space-time structure of drought, and a copula-based method was introduced to better constructive IAF curves. Conditional probabilities of several drought characteristics taking extreme values were further analyzed. Compared to probabilities estimated by univariate frequency analysis, results indicate that occurrence frequency of drought was underestimated when neglecting any natural characteristic of drought, and underestimation was more serious for the more extreme situations of drought. Furthermore, owing to stronger dependences of drought characteristics from short-term to long-term, more serious underestimations of occurrence frequency of drought were found for the drought from short-term to long-term when neglecting any natural characteristic of drought. [ABSTRACT FROM AUTHOR]

Human activities interacting with coastal waters lead to large amounts of nutrient loading and severe water pollution in China's near Seas. In this context, a comprehensive quantitative characterization of the spatiotemporal variation of nutrient pollutant concentrations is a key component of any reliable seawater quality assessment and integrated coastal management plan. The present work combines the Bayesian maximum entropy method with stochastic site indicators to estimate monthly nitrate and phosphate concentrations in China's near seas during 2015, explore their spatiotemporal variation, and provide an explicit quantitative assessment of seawater quality in conditions of in situ uncertainty. This makes it the first study of space‐time nutrient pollutant characterization at a national‐scale in a coastal seawater environment. The results showed that nitrate and phosphate distributions exhibit the same spatial trends along China's near seas, whereas high nutrient pollution levels are found in the Yangtze River, Liaohe River, and Pearl River estuaries. Local differences of temporal trends exist between nitrate and phosphate distributions, which suggest that distinct remediation strategies are needed to properly satisfy the required seawater quality standards. The average nitrate and phosphate concentrations across space‐time were found to be equal to 0.271 and 0.015 mg/L, respectively. The nitrate and phosphate concentrations exceeding the fourth grade seawater quality standard during 2015 were about 11% and 2.6%, respectively. The study of both the seasonal changes in human activities along the coastal cities and the temporal marine hydrodynamics can offer a better understanding of the seawater quality and the biogeochemical process of nutrient transport and distribution. Key Points: Bayesian maximum entropy maps showed that nitrate and phosphate concentrations had similar spatial distributionsNitrate and phosphate distributions exhibited different seasonal patterns that may have been affected by coastal hydrodynamics and human activitiesStochastic site indicators showed that nitrate pollution was much more serious than phosphate pollution [ABSTRACT FROM AUTHOR]

Copyright of Online Journal Mundo Asia Pacífico is the property of Universidad EAFIT and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the increase of mining depth, the high gassy coal mine confronts with a variety of gas problems, such as gas concentration exceeding the limit in the working face, gas outburst and gas explosion. According to the situation of gas drainage in Qinshui Basin (South of Shanxi Province, China) and enlightened by horizontal directional drillings (HDD) and multi‐branched horizontal wells, a new gas drainage pattern that inverted π‐shape km borehole layout was proposed. Verified in Yuwu Coal Mine, the gas drainage data were standardized via the unified theory of standardization. It could dropped the coal seam gas content to 7.71 m3/t, and increased the gas drainage rate to 34.2%, which conformed to the Chinese regulation (<8 m3/t, >30%, respectively). This pattern has a significant effect on coal mines with a single seam, where protective seam mining technology was unsuitable to prevent gas outburst and gas explosion. A double pressure relief circle model of gateway and borehole was proposed. Combined with traditional gas drainage technology, a new gas drainage scheme came up with – inverted π shape km boreholes group model. The novel gas drainage scheme of inverted π‐shape km boreholes arrangement has the advantage of reducing gas drainage time and expanding coverage area. It is a new tri‐dimensional space‐time gas drainage system for underground coal mines. [ABSTRACT FROM AUTHOR]

In order to consider the time delay caused by signalized intersections, toll stations, etc. In the definition of the airport economic zone, the advantages and disadvantages of the three methods of spatial circle, time circle and improved time circle were first compared and analyzed. Meanwhile, the proportion change and distribution rules of the surrounding companies' aviation hub-orientation function in Beijing Capital International Airport by using the third method were analyzed. The basic circling of the airport economic zone was also defined. In addition, the final scope of the airport economic area was determined according to the hotspot analysis, land use type and existing planning layout. It can be concluded that the time span of space circling was large, which was not suitable as the regional division index With added time delayed points, t was more in line with the actual situation. The aviation hub-orientation function companies distribution was clustered, and companies having strong functions were mainly distributed in the airport development zone, integrated bonded area, logistics base and China aviation industry zone. The base layer of the airport economic zone is 9 minutes accessible area. The final identified airport economic zone was determined to be north to Sixth Rings Road and Shun Ping Road, east to Shun Bai Road and Airport East Road, south to Jing Ping high way, west to Yu An Road and Jing Shen Road. The expansion of the airport economic zone was mainly in the west and north directions. [ABSTRACT FROM AUTHOR]

Lower accessibility to transit services may lead to more constraints, making travel less flexible in space and time. By using information and communication technologies (ICT), travelers can obtain additional travel information on transit stations and transfer routes, possibly attenuating the negative effects of low transit accessibility on the space-time flexibility (SPF) of travel. Based on data from 612 interviews in Chengdu (China), this study delves into the impact of transit accessibility on the SPF of shopping travel for non-daily goods, as well as the moderating role of ICT use. Binomial logistic regression models suggest that both bus accessibility and metro accessibility are significantly and positively associated with the SPF. Nonetheless, this association is not statistically significant for those who frequently use ICT for searching transit information, suggesting an attenuating effect of ICT use. Therefore, the frequent use of ICT may mitigate the social inequality in the SPF posed by the uneven distribution of transit facilities. [ABSTRACT FROM AUTHOR]

The history of the popularization and research of psychodrama in the west has spanned more than 80 years since it was founded by J. L. Moreno in the 1930s. However, it was only in the 1990s that psychodrama was systematically introduced in mainland China. The historical process of the spread and development of psychodrama in China is complex; therefore, this study approached it from the perspectives of space and time and theoretical development. Considering four events as the critical time points, the history of psychodrama in China can be divided into four periods from a spatiotemporal perspective: pre-contact period, preparatory period, period of prosperity, and the period of new development. Based on the theoretical classification, three major branches of psychodrama in mainland China are represented by Gong Shu’s Yi Shu psychodrama, Katherine Hudgins’ therapeutic spiral model, and campus psychodrama developed by Chinese psychologists. [ABSTRACT FROM AUTHOR]

The evolution of the Palaeo-Tethys Ocean played an important role in the Palaeozoic tectono-metallogenesis in Southeast Asia, in which diverse blocks amalgamated due to its closure. Previous researches focused mostly on endogenic metallogenesis related to the evolution of the Palaeo-Tethys Ocean. However, the tectonic control on the numerous Mn ore deposits in the southwestern South China Block (SCB) developed during Palaeo-Tethys evolution is largely unknown. In this article, we review Palaeo-Tethys evolution and define its four evolutionary stages from initial opening, maturity, incipient subduction, to post-closure. This study further investigated the geology and palaeogeography of Mn ore deposits in Upper Devonian, lower Carboniferous, middle Permian, and Lower-Middle Triassic formations in the southwestern SCB. We show that each of the four Mn metallogenic episodes was a response to each of the four evolutionary stages of the Palaeo-Tethys Ocean. Wall rocks of orebodies transitioned from chert-mudstone-carbonate in the Devonian, Carboniferous, and Permian to siltstone-mudstone in Lower-Middle Triassic. The ores of the four episodes of Mn mineralization are composed primarily of rhodochrosite, manganocalcite, and rhodonite. The carbonate C–O isotope and ore trace element composition data suggest that ore-forming fluids were dominated by seafloor water with involvement of magmatic hydrothermal fluids and organic matter as well. Palaeogeography reconstructions indicate the Mn-ore deposits formed along the margins or in the centre of the abyssal basins. Despite the diverse tectonic settings of the four Mn mineralization episodes, it is proposed that the crustal sagging, restricted seafloor environment, and hydrothermal activities that occurred in the southwestern margin of SCB contributed to Mn mineralization. [ABSTRACT FROM AUTHOR]

Urbanization reflects the overall behavior of human society; thus, characterization of its associated spatial and temporal trends has been extensively researched. This study examines the process of urban expansion in the Huaihe River Basin (HRB) which is a key transition region within China’s urban system. In order to grasp the urban expansion process in different temporal sequences objectively, rapidly, and accurately, we used remote sensing data to assess the urban expansion in time and space. Urban expansion rules were defined for the urban area, urbanization intensification, extended dynamic degree, and spatial pattern. The research findings show that the urban area expansion speed was at medium level throughout the entire HRB and within each province. Presently, the formation of a whole urban agglomeration or urban system is not complete in the HRB; urban expansion in the HRB displayed space-time disequilibrium tendencies during 1998–2013. [ABSTRACT FROM AUTHOR]

Municipal district adjustment and built-up area expansion are two main forms of urban spatial expansion. Using geometric methods, this study constructed a space-time path method to characterize the space-time relationship between municipal district adjustment and built-up area expansion, and drew the space-time path sets of major prefecture level cities from 2000 to 2010 by constructing a coordinate system of the standardized built-up areas and municipal district areas. This divided them into four quadrants, namely, H-H, L-H, L-L, and H-L, based on the relative mean value to evaluate overall and individual stability by three indexes of the trajectory vectors, namely, direction, length, and slope. Results provide the following conclusions. 1) Municipal district adjustment is an effective spatial expansion way for city-scale promotion in China. Since 2000, municipal district adjustments have been mainly distributed in the eastern coastal regions and mid-western capital cities along with their surrounding cities. 2) Municipal district adjustment affects the scale and status of a city in China. Many cities that have expanded municipal districts behave stably and cross quadrants. 3) Great majority second-tier cities have effectively promoted their scale and status through municipal district adjustment. The municipal district adjustment of medium and small cities in the mid-west area is relatively advanced compared with city development. 4) Municipal district adjustment with minimal magnitude is severely restricted from upgrading the scale and status of a city. The transformation from entirely incorporated counties or cities to municipal districts should be the mainstream in future municipal district adjustment. [ABSTRACT FROM AUTHOR]

Traditional villages are the carriers of tangible cultural heritage and intangible cultural heritage, as well as China's non-renewable cultural resources and valuable tourism resources. With Sina travel blogs as the data platform, taking the number of page views as an evaluation indicator of network attention, the dynamics of network attention to the 91 traditional villages in Hunan Province that have been included in the first three batches of Chinese Traditional Village List were analyzed from two aspects of time and space. Based on this, development strategies were put forward for tourism of Chinese traditional villages so as to promote the development of the tourism economy in Hunan Province. [ABSTRACT FROM AUTHOR]

Growing studies suggest that air pollution exposure is an emerging driver for neurological diseases, but existing evidence on the association between air pollution and epilepsy is scarce. Here, we aimed to quantitatively estimated the short-term effects of various air pollutants on childhood epilepsy hospitalizations in China. We obtained daily electronic health records on childhood epilepsy hospitalizations and air pollutants (PM 2.5 , PM 10-2.5 , PM 10 , SO 2 , NO 2 , O 3) from 2016 through 2018 in 10 cities of Anhui Province in China. In the first stage, a space–time-stratified case-crossover analysis was employed to evaluate the short-term association of childhood epilepsy hospitalizations with each air pollutant in Anhui Province. In the second stage, short-term effect of air pollution on childhood epilepsy morbidity reported in Anhui Province and in previous studies was pooled with a random-effect meta -analysis model to get the overall effect of different air pollutants in eastern China. This study included 8,181 childhood epilepsy patients from 10 cities in Anhui province of China. The first stage case-crossover analysis in Anhui province found significant associations between higher concentrations of all air pollutants (except O 3) and increased risk of childhood epilepsy hospitalizations. Each 10 μg/m3 increase in PM 2.5 , PM 10-2.5 , PM 10 , SO 2 , and NO 2 concentrations was associated with an increase of 1.1 % [95 % confidence interval (CI): 0.1 %-2.1 %], 1.7 % (95 %CI: 0.5 %-2.9 %), 0.8 % (95 %CI: 0.1 %-1.4 %), 8.5 % (95 %CI: 1.5 %-16.0 %), and 4.3 % (95 %CI: 2.3 %-6.3 %) in epilepsy hospitalizations, respectively. We also observed greater effects of particulate matter in cold season. The second stage meta -analysis that additionally included two prior studies with 43,002 patients from other 11 cities found a marginally significant increase in childhood epilepsy attacks associated with PM 2.5 , PM 10 , and NO 2 in eastern China. Short-term exposure to both particulate matter and gaseous air pollution was associated with an increased risk of childhood epilepsy exacerbation in eastern China. Our findings suggest that air pollution exposure especially in cold season needs to be considered by children's parents or guardians to prevent epilepsy attacks. [ABSTRACT FROM AUTHOR]

• People living near metro stops do not always perceive easy access to metro services. • People with access to metro stations within 800m have high space-time flexibility. • High perceived metro accessibility positively impacts space-time flexibility. • The importance of metro accessibility is highlighted from the perspective of time geography. • Increasing the density of metro stations may be an effective planning strategy. Space-time flexibility is defined as the extent to which individuals can participate in activities at different locations and different times. High space-time flexibility of travel enables people more freedom to choose when and where to make trips and assists in achieving both environmental and social sustainability. Applying a quasi-experimental approach – propensity score matching – to data obtained from 624 interviews in Chengdu (China), this paper aims to examine the effects of metro accessibility on space-time flexibility of shopping travel for non-daily goods. The results show that people residing around metro stations (i.e., high calculated accessibility) have a higher level of space-time flexibility of shopping travel than those living elsewhere. Meanwhile, people who perceive easy access to metro services (i.e., high perceived accessibility) are also likely to have a higher level of space-time flexibility. The findings highlight the importance of metro accessibility from the perspective of time geography. In practice, improving calculated and perceived accessibility to metro services may be an effective urban planning strategy to increase residents' space-time flexibility of shopping travel and inform policy recommendations for the design of sustainable cities. [ABSTRACT FROM AUTHOR]

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Through applying exploratory spatial data analysis ( ESDA) and confirmatory spatial data analysis ( CSDA), this paper examines the space-time dynamics of innovation at the provincial level in China from 2000 to 2011. We first investigate the trend of regional inequality in innovation in China and then use ESDA methods to visualize the space-time relationship between patent applications and innovation determinants. Impacts of innovation determinants on the space-time dynamics of innovation are also examined by analyzing the knowledge production function with the spatial panel Durbin model. Knowledge spillovers from both the R&D and the innovation outcome perspectives are highlighted in CSDA. We have found an increasingly intensified coastal-interior divide with growing spatial clusters and more innovative activities in the coastal region. We have also found a close space-time relationship between innovation and its determinants. Lastly, innovation spillovers cross province boundaries, and knowledge from a province's neighboring provinces has substantial effects on innovation activities of the province. This paper highlights positive knowledge spillover effects between regions, the close relationship between innovation and its determinants, and the importance of spatial externalities in innovation activities. [ABSTRACT FROM AUTHOR]

Hydro-morphological processes (HMP; any process in the spectrum between debris flows and flash floods) threaten human lives and infrastructure; and their effects are only expected to worsen under the influence of climate change. Limiting the potential damage of HMPs by taking preventive or remedial actions requires the probabilistic expectation of where and how frequently these processes may occur. The information on where and how frequently a given earth surface process may manifest can be expressed via susceptibility modeling. For the whole Chinese territory, a susceptibility model for HMP is currently not available. To address this issue, we propose a yearly space-time model built on the basis of a binomial Generalized Linear Model. The target variable of such model is the annual presences/absences of HMP per catchment across China, from 1985 to 2015. This information has been accessed via the Chinese catalogue of HMP, a data repository the Chinese Government has activated in 1950 and which is still currently in use. This binary spatio-temporal information is regressed against a set of time-invariant (catchment shape indices and geomorphic attributes) and time-variant (urban coverage, rainfall, vegetation density and land use) covariates. Furthermore, we include a regression constant for each of the 31 years under consideration and also a three-years aggregated information on previously occurred (and not-occurred) HMP. We consider two versions of our modeling approach, an explanatory benchmark where we fit the whole space-time HMP data, including a multiple intercept per year. Furthermore, we also extend this explanatory model into a predictive one, by considering four temporal cross-validation schemes. As a result, we portrayed the annual susceptibility models into 30 maps, where the south-east of China is shown to exhibit the largest variation in the spatio-temporal probability of HMP occurrence. Also, we compressed the whole spatio-temporal prediction into three summary maps. These report the mean, maximum and 95% confidence interval of the spatio-temporal susceptibility distribution per catchment, per year. The information we present has a dual value. On the one hand, we provide a platform to interpret environmental effects controlling the occurrence of HMP over a very large spatial (the whole Chinese country) and temporal (31 years of records) domain. On the other hand, we provide information on which catchments are more prone to experience a HMP-driven hazard. Hence, a step further would be to select the most susceptible catchments for detailed analysis where physically-based models could be tested to estimate the potentially impacted areas. For transparency, the results generated in this work are shared in the supplementary material as GIS (geopackage) files. • We build a space-time susceptibility model for hydromorphological (HMP) processes. • The spatio-temporal domain covers the Chinese territory from 1985 to 2015. • The temporal validation routines we tested suitably predict HMP occurrences. • The frequency of HMPs increases with time. • Susceptible catchments can be extracted for more detailed physically-based simulations. [ABSTRACT FROM AUTHOR]

Against the background of increased interest in subjectively experienced well-being in economics, psychology, and the social sciences, this article analyzes how such well-being is associated with geographical context, social contacts, and life circumstances. The empirical analysis of data collected in Hong Kong is used to elaborate and support two main claims. The first is that geography matters to not only overall well-being but also momentary well-being and that researchers should be careful to specify the influence of geographical context correctly. We therefore employ an approach that is informed by various strands of time–geographical thought and find that life satisfaction is associated more strongly with geographical context than is momentary well-being. Second, we confirm positive relations between social contacts and experienced well-being but extend earlier research by showing that these relations stretch across multiple timescales and depend to some extent on the duration of an activity episode and with whom the activity episode is undertaken. This means that the use of simple indicators of social capital is inadequate for making the complex linkages between well-being and people's social contacts understandable in empirical research. [ABSTRACT FROM AUTHOR]