Hasil untuk "Metropolitan areas"

E. Mills

M. Yeargin-Allsopp, C. Rice, Tanya Karapurkar et al.

F. Baró, I. Palomo, G. Zulian et al.

Sunmin Lee, Jeong-Cheol Kim, Hyung-Sup Jung et al.

ABSTRACT Since flood frequency increases with the impact of climate change, the damage that is emphasized on flood-risk maps is based on actual flooded area data; therefore, flood-susceptibility maps for the Seoul metropolitan area, for which random-forest and boosted-tree models are used in a geographic information system (GIS) environment, are created for this study. For the flood-susceptibility mapping, flooded-area, topography, geology, soil and land-use datasets were collected and entered into spatial datasets. From the spatial datasets, 12 factors were calculated and extracted as the input data for the models. The flooded area of 2010 was used to train the model, and the flooded area of 2011 was used for the validation. The importance of the factors of the flood-susceptibility maps was calculated and lastly, the maps were validated. As a result, the distance from the river, geology and digital elevation model showed a high importance among the factors. The random-forest model showed validation accuracies of 78.78% and 79.18% for the regression and classification algorithms, respectively, and boosted-tree model showed validation accuracies of 77.55% and 77.26% for the regression and classification algorithms, respectively. The flood-susceptibility maps provide meaningful information for decision-makers regarding the identification of priority areas for flood-mitigation management.

Yujing MENG, Jiaxiu CAI, Lu YIN

ObjectiveIn the context of profound demographic change and rapid urban restructuring, the spatial role of university campuses in Japan has undergone a fundamental transformation. Once conceived as inward-looking and self-sufficient “ivory tower” enclaves located on the urban periphery, campuses are increasingly being reconfigured as open and integrated nodes embedded within the metropolitan fabric. This paradigm shift is closely tied to Japan’s declining youth population, intensifying competition among universities, and evolving policy frameworks that regulate land use and higher education. Campus landscapes, in this process, are not merely ornamental green spaces but active agents of transformation that mediate the campus-city relations. The objective of this research is therefore to investigate how campus landscapes, as a spatial and social interface, respond to demographic pressures, policy incentives, and urban redevelopment agendas. By examining the synergistic evolution of universities and their host cities, the research aims to provide insights into the mechanisms that underpin this transformation and to extract lessons relevant to the forthcoming landscape transitions in Chinese higher education institutions.MethodsThe research adopts a multi-scalar approach that combines historical trajectory analysis, case-based comparative study, and theoretical synthesis. First, the historical evolution of Japanese university campuses from 1945 to the present is traced and periodized into three major phases: the expansion phase (1945–1980s), when demographic booms and policy restrictions encouraged suburban relocation and the creation of enclosed, inward-looking campuses; the peak phase (1980s–2000s), marked by intensifying competition, partial return to urban centers, and the emergence of vertical and compact campus typologies; and the contraction phase (2000s to present), characterized by severe demographic decline, urban concentration, and increasing demands for publicness and integration. Second, representative case studies are selected from metropolitan Tokyo, regional cities, and newly developed urban districts. These are analyzed through spatial observation, planning documents, and secondary literature to identify common strategies and contextual variations. Third, the research synthesizes empirical findings into a typological framework of three strategic modes — “catalyst”, “regenerator”, and “stabilizer” — and further generalizes these into a theoretical three-pillar model composed of demographic dynamics, policy instruments, and spatial strategies. This model is used to explain the synergistic evolution mechanism of campus landscapes and urban environments.ResultsThe analysis shows that campus landscape transformation in Japan is not an isolated architectural endeavor but a systemic process shaped by demographic, institutional, and spatial forces. In newly developed urban areas and large-scale redevelopment zones, universities frequently operate as catalysts, strategically positioned to anchor emerging districts. Here, landscape strategies emphasize publicness, multi-functionality, and accessibility. For instance, the Toyosu Campus of Shibaura Institute of Technology integrates open terraces, green staircases, and community-oriented plazas that attract both students and local residents, thereby stimulating district-level vitality. In historic city centers and post-industrial neighborhoods, universities act as regenerators, using landscape interventions to repair urban fabric and reinvigorate cultural identity. Examples include the Kitasenju Campus of Tokyo Denki University, which deploys pedestrian linkages and unified pavement to soften campus — city boundaries, and Kyoto City University of Arts, which integrates riverside ecological restoration with cultural events to generate a “memory landscape”. In smaller regional cities, universities often serve as stabilizers, embedding themselves in local social and demographic structures through service-oriented landscapes and shared facilities. Fukuchiyama Public University, for example, co-locates community dining halls and elderly care facilities within its campus landscape, while university consortia in Kyoto pool resources to create a multi-institutional network of open sports fields, libraries, and cultural spaces accessible to local communities. The proposed three-pillar model explains the underlying mechanism of these transformations. Demographic decline provides the fundamental pressure, reducing the student-age population from over two million in the early 1990s to just above one million in the 2020s, with further decline projected. Policy instruments translate these demographic pressures into spatial outcomes, with such instruments ranging from restrictive measures such as the 1959 Factory Location Law to liberalizing interventions like the 1991 revision of university establishment standards, and most recently, the 2017 enrollment cap in central Tokyo. Spatial strategies, materialized through landscape design, serve as the ultimate vehicles through which demographic and policy drivers are enacted: Open courtyards, pedestrian corridors, cultural event spaces, and service-based green infrastructures become concrete manifestations of institutional adaptation. The interplay of these three pillars — demographics, policies, and spatial strategies — constitutes the synergistic evolution dynamic of campus landscapes and cities.ConclusionJapanese experience shows campus landscapes have moved beyond their traditional role as green buffers to become strategic nodes of governance, cultural renewal, and social inclusion. By adopting roles of catalyst, regenerator, and stabilizer, campuses now shape urban growth, support community services, and sustain regional resilience. The proposed three-pillar model provides a structural lens for interpreting such changes. For China, where higher education faces slowed growth and demographic transition, these findings are highly relevant. Suburban university towns face the risk of under-use, while urban campuses must balance scarcity with public engagement. Japanese precedents suggest strategies of vertical compaction, boundary softening, and service-oriented integration can enhance publicness and urban alignment. Policymakers, meanwhile, should design flexible regulations balancing equity and autonomy. Future research should incorporate quantitative tools such as GIS metrics, user surveys, and cross-national comparison to further validate the three-pillar model and refine its applicability. Ultimately, campus landscapes must be understood not as passive backdrops but as active instruments in reshaping campus – city relations in an era of demographic and urban transformation.

Andreu Salcedo-Bosch, Lian Zong, Yuanjian Yang et al.

Abstract This study applies machine learning techniques, specifically stacked generalization, to develop a 1-day-ahead air pollution forecasting model for Shanghai, one of the largest metropolitan areas in the world, taking advantage of the essential information on air quality that can be inferred from a small but long-term dataset of meteorological and pollutant concentration variables ( $$\text{PM}_{10}$$ PM 10 and $$\text{PM}_{2.5}$$ PM 2.5 ), consisting of only 4240 samples. We conducted a comprehensive analysis of daily-averaged meteorological observation data, including temperature (T), relative humidity (RH), wind speed (WS) and direction (WD) and precipitation (P) from 74 automatic weather stations over a 12-year period, from 2011 to 2021, and satellite-retrieved aerosol optical depth (AOD) at 550 nm and planetary boundary layer height (PBLH) for the same time interval. In addition, principal component analysis (PCA) was used to identify the most prevalent synoptic weather patterns in the Shanghai region to assess the origin of pollution advection sources. Thanks to the long-term trends information used for model training, combined with machine learning stacking generalization techniques, the developed model improved the prediction results of alternative methods for pollution forecasting with limited observations, obtaining RMSE and $$R^2$$ R 2 values of 11.93 $$\upmu \text{g}\, \text{m}^{-3}$$ μ g m - 3 and 0.72, respectively. Moreover, it was able to forecast most of the pollution peaks, such as those in January 2019 and November 2020, showing itself as a useful tool for policy making and alerting for health risks. The results of this study highlight the need for cohesive strategies that tackle both air quality and climate change to promote sustainable urban growth and environmental robustness.

Yan Wang, Ziyi Guo

Abstract Social infrastructure plays a critical role in shaping neighborhood well-being by fostering social and cultural interaction, enabling service provision, and encouraging exposure to diverse environments. Despite the growing knowledge of its spatial accessibility, time use at social-infrastructure places is underexplored due to the lack of a spatially resolved national dataset. We address this gap by developing scalable Social-infrastructure Time Use (STU) measures that capture length and depth of activity engagement, diversity, and spatial inequality, supported by the first-of-their-kind datasets spanning multiple geographic scales—from census tracts to metropolitan areas. Our datasets leverage anonymized and aggregated foot traffic data collected between 2019 and 2024 across 49 continental U.S. states. The data description reveals variances in STU across time, space, and differing neighborhood socio-demographic characteristics. Validation demonstrates generally robust population representation, consistent with established national survey findings while revealing more nuanced patterns. Future analyses could link STU with public health outcomes and environmental factors to inform targeted interventions aimed at enhancing population well-being and guiding social infrastructure planning and usage.

Fakhar Latif, Muhammad Moiz Nasir, Wajeeh Ur Rehman et al.

<h4>Background</h4>Ischemic heart disease (IHD) has a significant impact on public health and healthcare expenditures in the United States (US).<h4>Methods</h4>We used data from the CDC WONDER database from 1999-2020 to identify trends in the IHD-related mortality of patients ≥ 75 years in the US. AAMRs per 100,000 population and APC were calculated and categorized by year, sex, race, and geographic divisions.<h4>Results</h4>Between 1999 and 2020, a total of 8,124,568 IHD-related deaths were recorded. Notable declines in AAMR were observed from 1999 to 2014 (APC: -3.86) and from 2014 to 2018 (APC: -2.55), with an overall increase from 2018 to 2020 (APC: 3.76). Older men consistently demonstrated higher AAMRs than older females, with AAMRs for both sexes decreasing steadily from 1999 to 2018 and increasing in 2020. When stratified by race/ethnicity, Whites (1931.7) had the highest AAMR, followed by Blacks (1836.5), American Indians (1510.5), Hispanics (1464.4), and Asians (1093.6). Furthermore, nonmetropolitan areas (2015.2) showed greater AAMRs than metropolitan areas (1841.8). The ≥ 85-year group consistently exhibited higher IHD-related mortality rates compared to the 75-84 years group. In comparison, the older group [≥75 years] (1873.0) consistently exhibited higher IHD-related AAMRs than the younger group [<75 years] (64.0) throughout the study, showing a significant disparity. Chronic IHD (1552.0) consistently showed the highest AAMRs throughout the study, surpassing myocardial infarction (515.6), other ischemic heart diseases (24.0), and angina pectoris (5.6).<h4>Conclusion</h4>Targeted interventions and resource allocation are crucial for areas with high IHD-related mortality. Public health policies should address demographic and geographical disparities, with further research for effective strategies.

Xiao Sun, J. Crittenden, Feng Li et al.

Yong Zhu, Dong Liang, Jingrui Zou

Objectives This study was conducted to examine urban–rural differences in the real-world prescribing pattern of oral anticoagulants and geographic variations in the prescribing pattern among clinicians serving Medicare beneficiaries in the USA.Design A cross-sectional study.Setting A real-world setting.Participants 232 665 clinicians who prescribed oral anticoagulants for Medicare beneficiaries from the 2020 Medicare Provider Utilisation and Payment Data were classified as warfarin only, direct oral anticoagulants (DOACs) only or warfarin+DOAC prescribers.Main outcome measures Urban–rural differences in the prescribing patterns were examined using multivariate multinominal logistic regression analysis. A geospatial analysis was conducted to estimate standardised prescriber ratios (SPR) for DOAC only or warfarin only prescribers versus warfarin+DOAC prescribers to illustrate hot and cold spots for DOAC adoption in the USA.Results 92% of clinicians who prescribed oral anticoagulants prescribed DOAC in 2020. Clinicians from rural regions were more likely to prescribe warfarin only (adjusted OR=1.335, 95% CI=(1.281 to 1.391)) and DOAC only (adjusted OR=2.052, 95% CI=(1.999 to 2.106)), compared with clinicians from urban regions. Hot spots for SPR of DOAC only versus warfarin+DOAC prescribers were mostly found in California, southern and southeastern states; cold spots were mostly found in Minnesota and Iowa. Hot spots for SPR of warfarin only versus warfarin+DOAC prescribers were mostly found in several metropolitan areas on the west coast and in Midwest; cold spots were mostly found on the east coast.Conclusions Urban–rural status of clinicians was associated with their prescribing patterns of oral anticoagulants. The study identifies geographical heterogeneity in DOAC adoption and highlights gaps that may need to be addressed for increased accessibility of DOAC for patients in need.

Da-Som Park, Yongjoo Choi, Young Sunwoo et al.

This study presents an improved wet scavenging process for particles in air quality modeling, focusing on the Korean Peninsula. New equations were incorporated into the air quality chemical transport model (CTM) to enhance the simulation of particulate matter (PM) concentrations. The modified air quality CTM module, utilizing size-dependent scavenging formulas, was applied to simulate air quality for April 2018, a month characterized by significant precipitation. Results showed that the modified model produced more accurate predictions of PM₁₀ and PM_2.5 concentrations compared to the original air quality CTM model. The maximum monthly average differences were 5.46 µg/m³ for PM₁₀ and 2.87 µg/m³ for PM_2.5, with pronounced improvements in high-concentration regions. Time-series analyses for Seoul and Busan demonstrated better agreement between modeled and observed values. Spatial distribution comparisons revealed enhanced accuracy, particularly in metropolitan areas. This study highlights the importance of incorporating region-specific, size-dependent wet scavenging processes in air quality models. The improved model shows promise for more accurate air quality predictions, potentially benefiting environmental management and policy-making in the region. Future research should focus on integrating more empirical data to further refine the wet scavenging process in air quality modeling.

Cosmina-Daniela Ursu, Jozsef Benedek

Following the collapse of the communist regime, Romania underwent significant economic, territorial, and social transformations that exacerbated inequality. To help policymakers create effective economic strategies, it is necessary to pinpoint the areas with the largest disparities. Thus, using spatial statistics available in ArcGIS, the primary goal of this study is to identify spatial clusters/outliers of income per capita. The findings indicate a strong concentration of high incomes at the regional level in Bucharest-Ilfov, West, Centre, and North-West regions. Conversely, low-income groups are concentrated in every other region, and their circumstances do not appear to improve over the course of the analysis period (2007-2021). At the metropolitan level, large cities are particularly home to high-value clusters and their influence within metropolitan areas is outlined.

Denis Mongin, Clement P. Buclin, Stephane Cullati et al.

(1) Background: France implemented a COVID-19 certificate in July 2021 to incentivize the population to uptake COVID-19 vaccines. However, little is known about the variation in its impact across age groups and its dependence on socio-demographic, economic, logistic, or political factors. (2) Methods: Using France’s weekly first dose vaccination rate, a counterfactual trend approach allowed for the estimation of the vaccination rate across age groups at a small geographical level before and after the implementation of the health pass. The effect of the health pass was operationalized as the vaccination rate among those who would not be vaccinated without it. (3) Results: Vaccination before the health pass varied greatly among age groups and was mainly influenced by territory (lower in rural and overseas territories when compared to urban and metropolitan ones), political beliefs, and socio-economic disparities. Vaccine logistics played a minor but significant role, while the impact of COVID-19 did not affect the vaccination rate. The health pass increased the vaccination overall but with varying efficiency across groups. It convinced mainly young people politically close to the governmental vaccination strategy and living in urban metropolitan areas with low socio-economical discrepancies. The selected variables explained most of the variability of the vaccination rate before the health pass; they explained, at most, a third of the variation in the health pass effect on vaccination. (4) Conclusions: From a public health perspective, the French health pass increased the overall vaccination, but failed to promote preventive behaviours in all segments of society, particularly in vulnerable communities.

Yifang Wang, Linlin Cheng, Yang Zheng

Because the relationship between cultivated land and the surrounding land types is not taken into account, there existed a deviation in the assessment of cultivated landscape ecological security. A novel methodology assessing the cultivated landscape ecological security is presented in this study, in the grid scale adjusted cultivated landscape ecological security index by the cultivated land disturbance index and the surrounding environment index. This method was applied in Xintai City, Shandong Province. The results demonstrate that (1) between 1985 and 2015, there was a constant loss of 173.2 km² cultivated land, the bulk of which was converted to building land, primarily on the outskirts of cities. (2) The landscape ecological security of cultivated land has decreased; the bulk of high-risk grids are located in central metropolitan areas and mining districts, and have a tendency to spread out over time. (3) We applied a three–dimensional model to generate a spatial combination of cultivated land and presented zoning suggestions for regional cultivated land use and management. This assessment technique reduces errors that may occur when relying solely on landscape features for cultivated ecological security evaluation. The evaluation’s results more accurately reflect the impact of human activity and urban growth, are more consistent with local features, and have a higher quality of reference value.

M. Jokela, W. Bleidorn, M. Lamb et al.

Ah-Ra Kim, Dohsik Minn, Su Hwan Kim et al.

OBJECTIVES The Korea National Health and Nutrition Examination Survey (KNHANES) is a nationwide cross-sectional surveillance system that assesses the health and nutritional status of the Korean population. To evaluate the occurrence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the community, we investigated the prevalence of anti-SARS-CoV-2 antibodies in the sera of KNHANES participants. METHODS Subjects were recruited between April 24 and December 12, 2020. In total, 5,284 subjects aged 10-90 years from 17 regions participated. SARS-CoV-2 antibodies were screened using the Elecsys Anti-SARS-CoV-2 assay. Positive samples were verified using 4 different SARS-CoV-2 antibody assays and the plaque reduction neutralizing test. The final seropositivity criteria were a positive screening test and at least 1 positive result from the 5 additional tests. RESULTS Almost half (49.2%; 2,600/5,284) of participants were from metropolitan areas, 48.9% were middle-aged (40-69 years), and 20.5% were in their 20s or younger. The seropositivity rate was 0.09% (5/5,284). Three of the 5 antibody-positive subjects had a history of infection, of whom 2 were infected abroad and 1 was infected in a local cluster outbreak. CONCLUSIONS The low SARS-CoV-2 antibody seroprevalence in Korea indicates that there have been few coronavirus disease 2019 (COVID-19) cases due to successful COVID-19 management measures (e.g., diagnostic tests for overseas arrivals, national social distancing, and strict quarantine measures). Moreover, asymptomatic infections were uncommon due to active polymerase chain reaction testing. However, hidden infections may exist in the community, requiring the continuation of quarantine and vaccination measures.

Suresh Chavhan, Deepak Gupta, B. Chandana et al.

The public transportation system (PTS) in a metropolitan area is a nonlinear, dynamic, and complex system. Managing and providing suitable public transportation services are difficult. In this article, we propose an Internet of Things-based intelligent PTS (IoT-IPTS) in a metropolitan area. An IoT is used to interconnect transportation entities, such as vehicles, commuters (mobile phones), routes (sensors), roadside units (RSUs), etc., in a metropolitan area. The IoT provides the seamless connectivity between different networking technologies whenever the commuters or vehicles move from one location to another location. Hence, IoT provides the suitable seamless public transportation services in the metropolitan area. In addition, we have used context information of transportation entities, such as routes condition, traffic density, number of routes available, traffic congestion, vehicles’ movement, and their mobility, which are stored in the cloud. The stored context information in cloud along with the IoTs are used to find the relevant routes, alternative modes, departure times, and many more for providing public transportation services in a metropolitan area. The proposed IoT-IPTS makes use of static and mobile agents with the emergent intelligence technique (EIT) for collecting, analyzing, and sharing context information. The analyzed context information is used to form the policies to provide the best available public transportation services to the commuters in a metropolitan area. The software-defined network is used to enable the cloud computing and EI network to manage the public transportation services to the commuters.

D. Passaretti, V. Candela, P. Sessa et al.

C. Bryan, K. L. Reynolds

Karna Dahal, S. Juhola, J. Niemelä

Abstract Renewable energy policies are necessary for achieving carbon neutrality which is the main goal for climate change mitigation. The cities in the Helsinki Metropolitan area have committed themselves to significantly reducing carbon emissions through various climate measures including some measures for renewable energy utilization. We use multilevel perspective (MLP) and renewable energy frameworks to examine the role of renewable energy policies to carbon neutrality in the Helsinki Metropolitan area and base our analysis on various policy documents and semi-structured interviews. Our findings show that current renewable energy policies in the Helsinki Metropolitan area are weak and many challenges exist. Nevertheless, many options are available for improving existing policies. The cities have many opportunities to adopt various energy policy measures, including small-scale renewable energy production in building premises, renewable energy integration to district heating, demand-side solutions for energy utilization, and increasing budgets and subsidies to renewable energy production and enhancement of the social acceptance of renewable energy. Such additional policies are needed to reach carbon neutrality in the Helsinki Metropolitan area.