Hasil untuk "Metropolitan areas"

Vasileios Volakakis, Hani S. Mahmassani

Airport-bound access and egress trips comprise a significant portion of total ground transportation trips, especially in regions served by large airports. Connecting urban areas with airports under minimal travel delays can be challenging, with traffic congestion along busy connecting corridors being a common phenomenon. Urban Air Mobility (UAM) is a new transportation mode envisioned to reduce travel times using specific aircraft, such as electric (and non-electric) Vertical or Short Take-off and Landing aircraft (e/VTOLs and STOLs, respectively). The operation of these aircraft requires take-off and landing infrastructure known as vertiports. A strategic infrastructure placement framework was introduced, utilizing and adapting the Capacitated Facility Location Problem (a-CFLP) and the Maximal Covering Location Problem (a-MCLP) with capacity constraints. An adapted capacitated k-means algorithm and a greedy heuristic were considered for the solution of the a-CFLP, while the a-MCLP was formulated as a mixed-integer linear programming problem. The proposed framework was applied in the Chicago Metropolitan Area, revealing that various trade-offs regarding coverage and accessibility, versus operational costs (number of facilities, facility capacity, and service radius), exist. The results showed that, depending on vertiport capacity and service radius capabilities, a range of 5 to 12 vertiports can sufficiently address the demand (above 95% demand coverage) and, with respect to accessibility, serve a moderate UAM demand scenario of 6124 daily requests, as identified for this region.

Maria P. Valentini, Valentina Conti, Matteo Corazza et al.

This paper presents a comprehensive methodology to forecast the daily energy demand associated with recharging private electric vehicles in urban areas. The approach is based on plausible scenarios regarding the penetration of battery-powered vehicles and the availability of charging infrastructure. Accurate space and time forecasting of charging activities and power requirements is a critical issue in supporting the transition from conventional to battery-powered vehicles for urban mobility. This technological shift represents a key milestone toward achieving the zero-emissions target set by the European Green Deal for 2050. The methodology leverages Floating Car Data (FCD) samples. The widespread use of On-Board Units (OBUs) in private vehicles for insurance purposes ensures the methodology’s applicability across diverse geographical contexts. In addition to FCD samples, the estimation of charging demand for private electric vehicles is informed by a large-scale, detailed survey conducted by ENEA in Italy in 2023. Funded by the Ministry of Environment and Energy Security as part of the National Research on the Electric System, the survey explored individual charging behaviors during daily urban trips and was designed to calibrate a discrete choice model. To date, the methodology has been applied to the Metropolitan Area of Rome, demonstrating robustness and reliability in its results on two different scenarios of analysis. Each demand/supply scenario has been evaluated in terms of the hourly distribution of peak charging power demand, at the level of individual urban zones or across broader areas. Results highlight the role of the different components of power demand (at home or at other destinations) in both scenarios. Charging at intermediate destinations exhibits a dual peak pattern—one in the early morning hours and another in the afternoon—whereas home-based charging shows a pronounced peak during evening return hours and a secondary peak in the early afternoon, corresponding to a decline in charging activity at other destinations. Power distributions, as expected, sensibly differ from one scenario to the other, conditional to different assumptions of private and public recharge availability and characteristics.

Hyun-Woo Jo, Myoungsoo Won, Florian Kraxner et al.

Climate change-induced heat waves and densely forested areas near urban centers in South Korea create complex challenges for wildfire response systems. Various forest fire models have been developed to address this, each with unique strengths and weaknesses. Process-based models offer high interpretability through human domain knowledge but require extensive optimization, while machine learning models automatically identify important features but have limited interpretability. To leverage the strengths of both models, this study aimed to integrate human domain knowledge into a machine learning framework. IIASA's wildfire cLimate impacts and Adaptation Model (FLAM)&#x2014;a process-based model incorporating biophysical and human impacts&#x2014;was developed as a neural network called FLAM-Net. Enhancements included improving backpropagation for optimization and introducing algorithms for national-specific fire ignition dynamics. FLAM-Net was applied at multiple scales and integrated through U-Net-based architecture, named deep neural FLAM (DN-FLAM), to produce downscaled predictions. The optimization revealed spatial concentration of fires near metropolitan areas and the east coast, with temporal concentration in spring due to agricultural burning. Integration of multiscale features through DN-FLAM achieved optimal performance with Pearson's <italic>r</italic> values of 0.943, 0.840, and 0.641 for temporal, spatial, and spatio-temporal validations. Future projections based on shared socioeconomic pathways indicated increasing fire frequencies until 2050, followed by a decrease due to increased precipitation. This study demonstrates the benefits of the hybrid approach, providing interpretability, accuracy, and efficient optimization. These hybrid models offer scientific evidence to guide locally tailored decision-making for climate change-induced forest fires and lay the groundwork for global application through their optimization capabilities.

Manassé Drabo, Horatio M. Morgan

Innovation is a central engine of economic growth, technological advancement and urban resilience. In an increasingly interconnected and competitive global economy, cities and regions must sustain innovative activity to remain productive and attractive. Among the most debated sources of urban innovation is diversity. Notably, cultural diversity and industrial diversity have been studied as distinct drivers of innovation. This paper examines the impact of cultural and industrial diversity on innovation across 152 Canadian urban areas from 2001 to 2021.

Tina BENFERHAT, Abdelmadjid BOUDER

: Transport in the metropolitan area of Algiers is very complicated, so we used the powerful tools of geographic information systems in the analysis of transport in the study area. Through the utilization of network analysis and GIS capabilities, our study focuses on optimizing transportation networks and enhancing port accessibility in the metropolitan regions of Boumerdes, Blida, Tipaza, and Algiers. Our methodology involves data collection, GIS analysis, and mapping to generate databases and maps of metropolitan networks. Through assessing port accessibility, road connectivity, and population-based hotspots analysis. Our study reveals Algiers as the most accessible municipality, attributed to its strong centralization. The roadbased analysis and population-based hotspot analysis provide valuable insights into port accessibility, road connectivity, and high-density townships, facilitating informed urban planning and infrastructure development.

Dedsy Yajaira Berbesí-Fernández, Sara Milena Ramos-Jaraba, Sebastián Bedoya-Mejía

Introduction: Worldwide, around 33.10 million to 45.70 million individuals are infected with HIV, with men who have sex with men (MSM) constituting a significantly affected demographic. Objective: To determine the prevalence of HIV among MSM in three major cities of Colombia and to describe the characteristics of this population, including HIV risk behaviors. Materials and methods: Cross-sectional observational study conducted using secondary data collected from 3 171 adult MSM residing in Bogotá D.C. and the metropolitan areas of Cali and Medellín, as reported in 3 studies conducted at 3 different points in time: 2010, 2016 and 2019. In all studies, participants were recruited by respondent-driven sampling (RDS). HIV prevalences were calculated for the 3 cities/metropolitan areas and the 3 study years, while the chi-square test of independence was used to compare the 3 years in each city/metropolitan area. Results: HIV prevalence over the 3 years ranged from 15.00% to 26.40%, 9.10% to 21.00%, and 15.00% to 23.40 in Bogotá and the metropolitan areas of Medellín and Cali, respectively. Between 27.53% and 58.03% of MSM in the 3 cities/metropolitan areas were younger than 24 years and between 79.28% and 87.68% had a low socioeconomic level (strata 0-3); less than 40.48% reported having a stable male partner; more than 76.81% reported having sex with casual male partners; less than 45.78% claimed to participate in HIV/AIDS information or education activities; less than 33.03% stated having had STIs; and more than 84.45% reported using psychoactive substances, with alcohol and marijuana being the most consumed (92.03-98.53% and 25.1-45.07%). Conclusion: The prevalence of HIV in this population was high in the 3 cities/metropolitan areas during the 3 years analyzed. Furthermore, risk behaviors included a significant use of psychoactive substances and high proportions of MSM who reported not using a condom with their regular partner (male or female) or the last time they had anal intercourse with a casual male partner.

Park JH, Lee MJ, Tsai MH et al.

Jeong-Hui Park,1,&ast; Min Jee Lee,2,&ast; Meng-Han Tsai,3,4 Huan-Ju Shih,5 Jongwha Chang6 1Department of Health Behavior, School of Public Health, Texas A&M University, College Station, TX, USA; 2Population Science and Policy, School of Medicine, Southern Illinois University, Springfield, IL, USA; 3Georgia Prevention Institute, Augusta University, Augusta, GA, USA; 4Cancer Prevention, Control, & Population Health Program, Georgia Cancer Center, Augusta University, Augusta, GA, USA; 5Department of Health Administration and Policy, School of Public Health, George Mason University, Fairfax, VA, USA; 6Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX, USA&ast;These authors contributed equally to this workCorrespondence: Jongwha Chang, Email jc2345@tamu.eduObjective: The primary objective of this study is to conduct a comparative analysis of telemedicine utilization patterns among adult populations residing in both rural and urban areas and evaluate the probability of telemedicine adoption among adults dwelling in both rural and urban areas amid the backdrop of the COVID-19 pandemic.Methods: Our study has attained sample populations (n = 279,260, National Weighted Estimates = 2,391,188,373) through the secondary analysis of the National Health Interview Survey (NHIS) for the year 2021. We examined the relationship between the rural, regional, and racial variables using chi-square tests and binary logistic regression associated with telemedicine use in our multivariable analysis.Results: Telemedicine use by population decreased with decreasing urbanization level, from 40.2% among adults living in large central metropolitan to 29.7% among adults living in rural area (p< 0.0001). Regarding household income, adults with 400% or more of the federal poverty level (FPL) were significantly more likely to use telemedicine than adults with less than 100% of the FPL. Females were more likely than males to utilize telemedicine. In terms of region, adults living in the West were 1.25 times more likely to use telemedicine than adults living in the Northeast, and minority race/ethnicity groups (eg, Non-Hispanic Black, Hispanic, and other) are less likely to use the telemedicine rather than Non-Hispanic White.Conclusion: Health equity is attained when all demographic groups enjoy uniform access to healthcare services, but disparities emerge when there are discernible variations in access to treatment. Considering this study’s findings, it becomes evident that the distinctions in poverty rates, median income levels, and healthcare utilization patterns across racial and regional lines may serve as indicators of potential health equity concerns.Keywords: telemedicine, COVID-19, NHIS sample, healthcare utilization

Ann Owens, Peter Rich

Suburbs were once a haven for advantaged, White families to avoid city life and access high-status schools. This urban-suburban divide, however, has changed in recent decades as suburban communities (and their school districts) have diversified. This study provides an updated cross-sectional portrait of recent racial-ethnic segregation and inequality between and within urban and suburban school districts in U.S. metropolitan areas. We find that the urban-suburban divide remains an important stratifying force—a substantial portion of racial-ethnic residential and school segregation, as well as racial-ethnic inequality in school poverty and test scores, occurs between urban and suburban school districts. Significant segregation and inequality also occur between and within suburban school districts. Suburban stratification is a key feature of the geography of inequality, warranting theoretical and methodological attention.

Alexandros Bartzokas-Tsiompras, Efthimios Bakogiannis

ABSTRACTThe disruptions associated with health and energy crisis have emphasized the need for hyperlocal cities. However, in Europe, a tool to measure the efficiency of land use and accessibility planning for localizing urban mobility is missing. In this paper, we construct a comparable 15-Minute-Walking City (15-MWC) index that assesses the walking performance of 121 European metropolitan areas and seven amenity types. The data are combined equally following the PROMETHEE II multicriteria approach to assign a final score and to present a ranking of 15-Minutes cities. The main visualization demonstrates European-level disparities and indicates that most of leading cities are in Germany, while most of the worst performers are in the UK. We also reveal a statistically significant difference in 15-MWC performance due to their GDP per capita disparities. The empirical results may serve as a referencing tool for cross-city comparisons and may support policymakers when designing transport and city-planning strategies.

Natalia Verde, Petros Patias, Giorgos Mallinis

As urbanized areas continue to expand rapidly across all continents, the United Nations adopted in 2015 the Sustainable Development Goal (SDG) 11, aimed at shaping a sustainable future for city dwellers. Earth Observation (EO) satellite data can provide at a fine scale, essential urban land use information for computing SDG 11 indicators in order to complement or even replace inaccurate or invalid existing spatial datasets. This study proposes an EO-based approach for extracting large scale information regarding urban open spaces (UOS) and land allocated to streets (LAS) at the city level, for calculating SDG indicator 11.7.1. The research workflow was developed over the Athens metropolitan area in Greece using deep learning classification models for processing PlanetScope and Sentinel-1 imagery, employing freely-available cloud environments offered by Google. The LAS model exhibited satisfactory results while the best experiment performance for mapping UOS, considering both PlanetScope and Sentinel-1 data, yielded high commission errors, however, the cross-validation analysis with the UOS area of OpenStreetMap exhibited a total overlap of 67.38%, suggesting that our workflow is suitable for creating a “potential” UOS layer. The methodology developed herein can serve as a roadmap for the calculation of indicator 11.7.1 through national statistical offices when spatial data are absent or unreliable.

George Mnatzaganian, Mark Woodward, H. David McIntyre et al.

Abstract Background Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes in Australia with rates trebling over the past decades partially explained by rising obesity rates and maternal age among childbearing women. Percentage of GDM attributable to obesity has been documented, mostly focusing on metropolitan populations. In parts of regional (areas outside capital cities) and rural Australia where overweight, obesity and morbid obesity are more prevalent, intertwined with socioeconomic disadvantage and higher migrant communities, trends over time in adjusted percentages of GDM attributed to obesity are unknown. Methods In this population-based retrospective panel study, women, without pre-existing diabetes, delivering singletons between 2010 and 2017 in a tertiary regional hospital that serves 26% of Victoria’s 6.5 million Australian population were eligible for inclusion. Secular trends in GDM by body mass index (BMI) and age were evaluated. The percentage of GDM that would have been prevented each year with the elimination of overweight or obesity was estimated using risk-adjusted regression-based population attributable fractions (AFp). Trends in the AFp over time were tested using the augmented Dickey-Fuller test. Results Overall 7348 women, contributing to 10,028 births were included. The age of expecting mothers, their BMI, proportion of women born overseas, and GDM incidence significantly rose over time with GDM rising from 3.5% in 2010 to 13.7% in 2017, p <  0.001, increasing in all BMI categories. The incidence was consistently highest among women with obesity (13.8%) and morbid obesity (21.6%). However, the highest relative increase was among women with BMI < 25 kg/m2, rising from 1.4% in 2010 to 7.0% in 2017. Adjusting for age, country of birth, socioeconomic status, comorbidities, antenatal and intrapartum factors, an estimated 8.6% (confidence interval (CI) 6.1–11.0%), 15.6% (95% CI 12.2–19.0%), and 19.5% (95% CI 15.3–23.6%) of GDM would have been prevented by eliminating maternal overweight, obesity, and morbid obesity, respectively. However, despite the rise in obesity over time, percentages of GDM attributable to overweight, obesity, and morbid obesity significantly dropped over time. Scenario analyses supported these findings. Conclusions Besides increasing prevalence of obesity over time, this study suggests that GDM risk factors, other than obesity, are also increasing over time.

Joseph Gyourko, Joseph S. Tracy

Işılay Kavadarlı, Melek Mutlu

Objectives:To assess the effects of the coronavirus disease-2019 (COVID-19) pandemic on Turkish ophthalmologists.Materials and Methods:In this survey study, an online questionnaire consisting of 40 questions was directed to actively working ophthalmologists. The questions asked about demographic characteristics, working conditions and schedule, follow-up of ophthalmology patients, and levels of knowledge and anxiety about the pandemic.Results:This study included 161 ophthalmologists (78 women and 83 men). They were predominantly consultant ophthalmologists (71%), with 128 living in metropolitan areas. More than half (54.4%) reported decreased weekly working hours, 52.5% were attending routine outpatient clinics, 52.8% were working in COVID-19-related units, 67.1% were performing only emergency operations, and 52% reported disrupted follow-up of chronic eye patients. Sixty-four percent thought that ophthalmologists were in the high-risk group, and nearly all participants used masks while working (99%). Additionally, 91% expressed high anxiety regarding the pandemic, most commonly due to the risk of transmitting the disease to family (83%), and 12.5% considered their level of knowledge about the pandemic to be insufficient. Forty-six percent of the participants thought that daily life conditions would normalize in 2 to 5 months.Conclusion:Close proximity during patient examination causes ophthalmologists concern about their risk. The increasing number of COVID-19 cases resulted in a proportional decrease in the number of patients and surgeries in ophthalmology clinics in our country. As a result, ophthalmologists are unwillingly appointed to high-risk units. The COVID-19 pandemic has caused a substantial increase in anxiety levels among Turkish ophthalmologists.

A. Goodman, T. Thibodeau

Rafik Arfaoui

Based on the example of the territory of Ambert (France), this article analyses how non-metropolitan fragile areas, faced with problems of isolation and shrinking populations, affect the reception dynamics. The characteristics of the territory of Ambert are both a potential resource and a risk for the reception of newcomers that appears paradoxical and unequal. This article also highlights how the heterogeneity of volunteers’ representation spaces leads to the emergence of heterogeneous reception dynamics. These reception dynamics are following a duty to welcome and a right to be welcomed. Even though they are heterogeneous, these reception dynamics are complementary and demonstrate a social innovation capacity in non-metropolitan areas. In return, these reception dynamics reconfigure the territory of Ambert by the emergence of a “territoire solidaire” that is part of a legitimist temporality and a “territoire révolté” that is part of a contesting temporality.

A. Kulshreshtha, Abhinav Goyal, Kaustubh C Dabhadkar et al.

Rudiger Ahrend, A. Schumann

S. Musterd, R. Ostendorf

G. Borjas, V. Ramey

M. Hall