Hasil untuk "Metropolitan areas"

Karl E. Case, Robert J. Shiller, Robert J. Shiller et al.

R. Farley, W. Frey

B. Stone, J. Hess, H. Frumkin

Background Extreme heat events (EHEs) are increasing in frequency in large U.S. cities and are responsible for a greater annual number of climate-related fatalities, on average, than any other form of extreme weather. In addition, low-density, sprawling patterns of urban development have been associated with enhanced surface temperatures in urbanized areas. Objectives In this study. we examined the association between urban form at the level of the metropolitan region and the frequency of EHEs over a five-decade period. Methods We employed a widely published sprawl index to measure the association between urban form in 2000 and the mean annual rate of change in EHEs between 1956 and 2005. Results We found that the rate of increase in the annual number of EHEs between 1956 and 2005 in the most sprawling metropolitan regions was more than double the rate of increase observed in the most compact metropolitan regions. Conclusions The design and management of land use in metropolitan regions may offer an important tool for adapting to the heat-related health effects associated with ongoing climate change.

Kiki Adhinugraha, Yusuke Gotoh, David Taniar

Access to large-scale public transport journey data is essential for analysing accessibility, equity, and urban mobility. Although digital platforms such as Google Maps provide detailed routing for individual users, their licensing and access restrictions prevent systematic data extraction for research purposes. Open-source routing engines such as OpenTripPlanner offer a transparent alternative, but are often limited to local or technical deployments that restrict broader use. This study evaluates the feasibility of deploying a publicly accessible, open-source routing platform based on OpenTripPlanner to support large-scale public transport route simulation across multiple cities. Using Australian metropolitan areas as a case study, the platform integrates GTFS and OpenStreetMap data to enable repeatable journey queries through a web interface, an API, and bulk processing tools. Across eight metropolitan regions, the system achieved itinerary coverage above 90 percent and sustained approximately 3000 routing requests per minute under concurrent access. These results demonstrate that open-source routing infrastructure can support reliable, large-scale route simulation using open data. Beyond performance, the platform enables public transport accessibility studies that are not feasible with proprietary routing services, supporting reproducible research, transparent decision-making, and evidence-based transport planning across diverse urban contexts.

Shima Hamidi, Sadegh Sabouri, R. Ewing

R. Pampalon, Denis Hamel, P. Gamache et al.

Tasuku Okui

Dingyi Jia, Weiguo Qiu, Rongpeng Guo et al.

Balancing socio-economic development with ecological protection amid rapid urbanization is a pressing global issue. The ecological security pattern (ESP) follows the reciprocal relationship between pattern and function to conserve ecological processes, providing an effective approach to address this problem. However, most studies have adopted a single subjective assignment method for resistance factors, lacking the exploration of the impact of various assignment methods on the ESP. Taking the Fuzhou metropolitan area as a case, this study proposes different resistance assignment methods: favorable, moderate, and unfavorable. By applying circuit theory, it constructs the ESP and identifies critical areas for protection and restoration. The findings show that (1) as the cumulative resistance threshold increases, the area of ecological corridors expands from 171.36 km² to 1439.24 km², with the moderate method identified as the optimal resistance assignment approach; (2) significant differences exist in the identification of key corridors under different resistance assignment methods. The moderate method identifies 26 key corridors, spanning a total length of 41.29 km; (3) the key ecological protection areas cover 2469.79 km², including 13 patches and 26 pinch points, while the key ecological restoration areas cover 14.55 km², including 7 barriers and 21 breaking points. By pinpointing key ecological areas and proposing targeted strategies, this study can facilitate practical ecological protection efforts, thereby achieving the sustainable development goal of minimizing economic costs while maximizing ecological benefits.

Anugrah Aditya INSANI, Eko HARYONO, Didit Hadi BARIANTO

This research assesses geodiversity hotspots to identify areas needing regional geoconservation, focusing on the Jogja Geopark and its geosites-geodiversity sites. Previous studies have modified threat indices by adding, removing, or replacing sub-threat components. Here, population density, representing demographic pressure, and anthropogenic intervention, indicating anthropogenic geomorphology dynamics, are included as sub-threat indices. Geodiversity and threat data were assessed at a 1:50,000 scale with a 0.5 km2 grid respectively. Involved data includes geopark and geosites outer boundary, lithology, tectonics and structures, landform systems, surface hydrology, hydrogeology, soil order, population density per km2 , and anthropogenic intervention. Feature calculation method was used to calculate geodiversity and threat from those datas. Geodiversity hotspots within the Jogja Geopark, highlighting areas urgently needing regional geoconservation. The Kartamantul (Yogyakarta - Sleman - Bantul) metropolitan area and surrounding three geosites: Kalibawang Eocene-age Nanggulan Formation; Mengger Hills Opak Fault; and Parangtritis Sand Dunes require the most attention. Meanwhile, geodiversity sites in Jogja Geopark generally show low to medium sensitivity. This indicates that the processes and outcomes of socio-economic systems actively threaten geoecosystems, particularly in the relatively passive geodiversity element on Jogja Geopark area and its geosites. Meanwhile, geodiversity sites are threatened by socio-economic systems although in a different intensity from geosites because of the narrow area and the scale of the study that has not been able to accommodate all geodiversity phenomena and threats in it. This study confirms the substantial impact of human activities on geodiversity. By integrating geodiversity and threat indices, critical sites for immediate geoconservation have been identified. The findings stress the urgency of implementing effective conservation policies to protect the geopark from further degradation.

R. Hunter, Leandro Garcia, T. H. de Sá et al.

The COVID-19 pandemic is causing mass disruption to our daily lives. We integrate mobility data from mobile devices and area-level data to study the walking patterns of 1.62 million anonymous users in 10 metropolitan areas in the United States. The data covers the period from mid-February 2020 (pre-lockdown) to late June 2020 (easing of lockdown restrictions). We detect when users were walking, distance walked and time of the walk, and classify each walk as recreational or utilitarian. Our results reveal dramatic declines in walking, particularly utilitarian walking, while recreational walking has recovered and even surpassed pre-pandemic levels. Our findings also demonstrate important social patterns, widening existing inequalities in walking behavior. COVID-19 response measures have a larger impact on walking behavior for those from low-income areas and high use of public transportation. Provision of equal opportunities to support walking is key to opening up our society and economy. Mobility restrictions implemented to reduce the spread of COVID-19 have significantly impacted walking behavior. In this study, the authors integrated mobility data from mobile devices and area-level data to study the walking patterns of 1.62 million anonymous users in 10 US metropolitan areas.

Albert Saiz

Is there a local economic impact of immigration? Immigration pushes up rents and housing values in US destination cities. The positive association of rent growth and immigrant inflows is pervasive in time series for all metropolitan areas. I use instrumental variables based on a “shift-share” of national levels of immigration into metropolitan areas. An immigration inflow equal to 1% of a city’s population is associated with increases in average rents and housing values of about 1%. The results suggest an economic impact that is an order of magnitude bigger than that found in labor markets.

Zhengde Fan, Chengdong Yi, Yourong Wang et al.

The ability of the cross-city commuting labor force to obtain housing has a profound impact on the development of the housing market and the enhancement of social welfare, but whether cross-city commuting has facilitated housing purchases remains to be verified However, the research on whether cross-city commuting behavior promotes labor force housing purchase in metropolitan areas is still lacking, especially in China, where the culture of buying houses is relatively special. This article used field survey data from the 2023 China Metropolitan Area Occupation and Housing Status Sampling Survey to empirically analyze whether cross-city commuting has facilitated housing purchases within metropolitan areas. The analysis was conducted by constructing a baseline model, a mediation effect model, and a subsample regression model. The results show that the cross-city commuting facilitated housing purchase within metropolitan areas, and the location preference is to purchase a house with a distance of 20–40 km from the workplace, but the contribution of the cross-city commuting to multi-suite purchases is relatively low. Mechanism analysis shows that compared to the workers who work and live in peripheral areas or the workers who work and live in cores, intercity commuters are promoted to purchase housing by relatively higher income and inducement of the housing price gap. The above conclusions still hold after controlling potential endogeneity issues and in robustness tests. The research of this paper can provide a new perspective for alleviating the housing inequality in the metropolitan area.

Haixin Huang, Jiageng Yang

Optimizing urban land use is of significant practical importance for promoting economic development, enhancing the standard of living for individuals residing in metropolitan areas, enhancing urban infrastructure and public services, driving urban transformation and upgrading, and attaining synchronized progress of the economy, society, and environment. This paper uses the super-efficiency SBM model to measure the urban land use efficiency (ULUE) of 13 cities in the Beijing–Tianjin–Hebei (BTH) urban agglomeration from 2005 to 2020 and explores the spatiotemporal evolution characteristics and influencing factors of ULUE in this urban agglomeration using analysis of spatial data and application of geographic detector methods. The results show that (1) from 2005 to 2020, the ULUE of the BTH urban agglomeration had an initial rise followed by a decline; however, the overall efficiency score is above 1, suggesting an overall effective state; (2) a distribution pattern with Beijing as its core was established, exhibiting greater ULUE in the northern region and poorer efficiency in the southern region, with significant correlation characteristics in efficiency values between adjacent cities; and (3) capital input, labor input, social welfare, and ecological environment are all influencing factors that promote the improvement in ULUE in the BTH region, and the interaction of any two factors explains the ULUE in this region better than a single factor. The empirical research results can provide useful references for improving the input–output ratio of land units and further spatial planning and policy formulation in the BTH region.

Guyue Li, Hongyi Luo, Jiabao Yu et al.

With the rapid growth of handheld devices in the internet of things (IoT) networks, mobile applications have become ubiquitous in everyday life. As technology is developed, so do also the risks and threats associated with it, especially in the forthcoming quantum era. Existing IoT networks, however, lack a quantum-resistant secret key sharing scheme to meet confidential message transmission demands in wide-area mobile applications. To address this issue, this article proposes a new scheme, channel reciprocity (CR) based quantum key distribution (QKD) CR-QKD, which accomplishes the goal of secret key sharing by combining emerging techniques of QKD and CR-based key generation (CRKG). Exploiting laws of quantum physics and properties of wireless channels, the proposed scheme is able to ensure the secrecy of the key, even against computationally unbounded adversaries. The basic mechanism is elaborated for a single-user case and it is extended into a multi-user case by redesigning a multi-user edge forwarding strategy. In addition, to make CR-QKD more practical, some enhancement strategies are studied to reduce the time delay and to improve the secret key generation rate in a secure manner. A prototype of CR-QKD is demonstrated in a metropolitan area network, where secret keys are shared between two remote IoT devices that are roughly fifteen kilometers apart from each other. The experimental results have verified that CR-QKD allows a secret key rate of 424 bits per second with a retransmission rate of 2.1%.

Xiangqi Wang, Dilinuer Aishan, Qi Liu

The effectiveness of graphical recommender system depends on the quantity and quality of negative sampling. This paper selects some typical recommender system models, as well as some latest negative sampling strategies on the models as baseline. Based on typical graphical recommender model, we divide sample region into assigned-n areas and use AdaSim to give different weight to these areas to form positive set and negative set. Because of the volume and significance of negative items, we also proposed a subset selection model to narrow the core negative samples.

Andressa Garcia Fontana, Victor Fernandez Nascimento, Jean Pierre Ometto et al.

This research investigates Land Use and Land Cover (LULC) changes in the Porto Alegre Metropolitan Region (RMPA). A 30-year historical analysis using Landsat satellite imagery was made and used to develop LULC scenarios for the next 20 years using a Multilayer Perceptrons (MLP) model through an Artificial Neural Network (ANN). These maps analyze the urban area’s expansion over the years and project their potential development in the future. This research considered several critical factors influencing urban growth, including shaded relief, slope, distances from main roadways, railway stations, urban centers, and the state capital, Porto Alegre. These spatial variables were incorporated into the model’s learning processes to generate future urbanization scenarios. The LULC historical maps precision showed excellent performance with a Kappa index greater than 88% for the studied years. The results indicate that the urbanization class witnessed an increase of 236.78 km2 between 1990 and 2020. Additionally, it was observed that the primary concentration of urbanized areas since 1990 has predominantly occurred around Porto Alegre and Canoas. Lastly, the future forecasts for LULC changes in 2030 and 2040 indicate that the urban area of the RMPA is projected to reach 1,137.48 km2 and 1,283.62 km2, respectively. In conclusion, based on the observed urban perimeter in 2020, future projections indicate that urban areas are expected to increase by more than 443.29 km2 by 2040. The combination of remote sensing data and Geographic Information System (GIS) enables the monitoring and modeling the metropolitan area expansion. The findings provide valuable insights for policymakers to develop more informed and conscientious urban plans, as well as enhance management techniques for urban development.

Morgan L. Rhodes, T. Brandt Ryder, Brian S. Evans et al.

In urban and human-modified landscapes, animals face novel selection pressures resulting from differences in habitat structure and increased anthropogenic noise. Urban noise pollution can negatively impact songbirds because low-frequency noise often masks portions of birds’ mating signals and reduces signal transmission. Previous research has demonstrated that the songs of birds in more urban habitats have structural differences that can enhance signal transmission when noise is present. The majority of these studies have focused on species that deliver short, stereotyped songs and have limited repertoires. Gray catbirds (Dumetella carolinensis, family: Mimidae) sing long bouts containing imitated, improvised, and invented song elements, and therefore may have an increased ability to vary songs in response to noise. We hypothesized that aspects of developed habitats including loud anthropogenic noise and changes to land cover would impact catbirds’ song structural parameters, including song minimum, peak, and maximum frequency, frequency bandwidth, and entropy. We recorded and processed songs from 42 male catbirds and analyzed over 18,000 song elements from sites along an urban gradient from western Virginia to the Washington, DC metropolitan region. We quantified the urban intensity at each site-centroid based on percent canopy cover, percent impervious surface, and noise level. Song features such as minimum, maximum, and peak frequency increased significantly as noise levels increased, demonstrating that catbirds in noisier areas sing higher frequency songs compared to individuals in quieter habitats. Land cover variables also significantly predicted certain song features such as maximum frequency (impervious surface) or entropy (canopy cover). These structural differences in catbird song can limit the negative effects of environmental noise-masking, even for their long song bouts, and suggest that vocal mimics respond to anthropogenic noise. Future studies could investigate repertoire size and composition along an urban gradient and if these structural differences lead to functional consequences for the songs of vocal mimics.

Leyre Encío, César Díaz, Carlos R. del-Blanco et al.

Along with society’s development, transportation has become a key factor in human daily life, increasing the number of vehicles on the streets. Consequently, the task of finding free parking slots in metropolitan areas can be dramatically challenging, increasing the chance of getting involved in an accident and the carbon footprint, and negatively affecting the driver’s health. Therefore, technological resources to deal with parking management and real-time monitoring have become key players in this scenario to speed up the parking process in urban areas. This work proposes a new computer-vision-based system that detects vacant parking spaces in challenging situations using color imagery processed by a novel deep-learning algorithm. This is based on a multi-branch output neural network that maximizes the contextual image information to infer the occupancy of every parking space. Every output infers the occupancy of a specific parking slot using all the input image information, unlike existing approaches, which only use a neighborhood around every slot. This allows it to be very robust to changing illumination conditions, different camera perspectives, and mutual occlusions between parked cars. An extensive evaluation has been performed using several public datasets, proving that the proposed system outperforms existing approaches.

Maikell Segovia, Philipp Schwabl, Salem Sueto et al.

Chagas disease is a significant public health risk in rural and semi-rural areas of Venezuela. Triatomine infection by the aetiological agent Trypanosoma cruzi is also observed in the Metropolitan District of Caracas (MDC), where foodborne T. cruzi outbreaks occasionally occur but active vector-to-human transmission (infection during triatomine bloodmeal) is considered absent. Citizen science-based domiciliary triatomine collection carried out between 2007 and 2013 in the MDC has advanced understanding of urban T. cruzi prevalence patterns and represents an important public awareness-building tool. The present study reports on the extension of this triatomine collection program from 2014 to 2019 and uses mitochondrial metabarcoding to assess feeding behavior in a subset of specimens. The combined, thirteen-year dataset (n = 4872) shows a high rate of T. cruzi infection (75.2%) and a predominance of Panstrongylus geniculatus (99.01%) among triatomines collected in domiciliary areas by MDC inhabitants. Collection also involved nymphal stages of P. geniculatus in 18 of 32 MDC parishes. Other collected species included Triatoma nigromaculata, Triatoma maculata, Rhodnius prolixus, and Panstrongylus rufotuberculatus. Liquid intestinal content indicative of bloodmeal was observed in 53.4% of analyzed specimens. Dissection pools representing 108 such visually blooded P. geniculatus specimens predominantly tested positive for human cytochrome b DNA (22 of 24 pools). Additional bloodmeal sources detected via metabarcoding analysis included key sylvatic T. cruzi reservoirs (opossum and armadillo), rodents, and various other synanthropic and domesticated animals. Results suggest a porous sylvatic-domiciliary transmission interface and ongoing adaptation of P. geniculatus to the urban ecotope. Although P. geniculatus defecation traits greatly limit the possibility of active T. cruzi transmission for any individual biting event, the cumulation of this low risk across a vast metropolitan population warrants further investigation. Efforts to prevent triatomine contact with human food sources also clearly require greater attention to protect Venezuela's capital from Chagas disease.

Adugnaw Zeleke Alem, Fantu Mamo Aragaw, Daniel Gashaneh Belay et al.

Objectives This study aimed to assess the spatial distribution, wealth-related inequality and determinants for delayed initiation of antenatal care (ANC) visits among reproductive-age women in Ethiopia.Design Cross-sectional study design.Setting Ethiopia.Participants A total of 2924 reproductive-age women who had given birth in the 5 years preceding the survey.Outcome measure Delayed initiation of ANC visits.Results The magnitude of delayed initiation of ANC visits among reproductive-age women in Ethiopia was 62.63% (95% CI 60.86%, 64.37%). Women aged 35–49 (AOR=1.42; 95% CI 1.04, 1.94), being protestant religion followers (AOR=1.43; 95% CI 1.06, 1.94), being in higher wealth index (AOR=0.53; 95% CI 0.41, 0.69), living in rural residence (AOR=1.50; 95% CI 1.02, 2.19) and living in the metropolitan region (AOR=0.45; 95% CI 0.26, 0.77) were significantly associated with delayed initiation of ANC visit. Southern Nations Nationalities and Peoples Region (SNNPR), Somalia, Benishangul Gumuz, Southern Addis Ababa and Gambella regions were hot spot regions for delayed initiation of ANC visits. The SaTScan analysis result identified 107 primary clusters of delayed initiation of ANC visits located in regions of SNNPR, Gambella, Southern Addis Ababa, Eastern Oromia and Benishangul Gumuz.Conclusions Significant spatial clustering of delayed initiation of ANC visits was observed in Ethiopia. More than half of women had delayed initiation of ANC visits in Ethiopia. Women’s age, religion, wealth index, residence and region were significant predictors of delayed initiation of ANC visits. There is a disproportional pro-poor distribution of delayed initiation of ANC visits in Ethiopia. Therefore, interventions should be designed in the hot spot areas where delayed initiation of ANC visits was high to enhance the timely initiation of ANC visits.