Hasil untuk "Metropolitan areas"

Samuel Dekolo, Matthew I. Ekum, Omobolanle K. James et al.

Africa is experiencing unparalleled urbanization, with projections suggesting that by 2030, more than 50% of its inhabitants will live in urban areas. Uncontrolled spatial expansion threatens sustainability, especially in megacities like Lagos. Urban sprawl in peri-urban areas has led to the loss of valuable agricultural lands, food security risks, and breaking the link between rural and metropolitan regions. This study investigates the proximate factors driving urban sprawl on statutory agricultural lands in peri-urban areas of Lagos. An interdisciplinary methodology that employs remote sensing, land change analysis, field surveys, and structural equation modeling was adopted. The findings revealed that built-up areas in the Ikorodu municipality increased by 127% over 32 years, leading to fragmented and uncontrolled development in statutory agricultural zones. The structural equation modeling for 322 homeowners sampled shows a lack of policy awareness and weak development control as major underlying drivers, explaining 37% of peri-urban expansion. Also, declining per capita arable lands indicate risks to regional food self-sufficiency. A strategic land management approach is needed to leverage rural–urban linkages that safeguard food provisioning services and achieve resilient African megacities. Also, rapidly growing African cities should adopt spatial planning incorporating agroecological perspectives and collaborative governance of urban and rural lands for a sustainable future.

Jacqueline H Stephens, Patrick Sharpe, Syeda Hira Fatima et al.

Objective Australian First Nations children bear 8.5 times greater burden of early and recurrent ear and nasopharyngeal infections compared with non-Indigenous children. These disparities are compounded by structural inequities in access to healthcare. To better understand these patterns, we analysed the state-wide epidemiology of childhood myringotomy procedures in South Australia and conducted spatial analysis for its main metropolitan region—Adelaide—to examine the associations with socioeconomic status and distance to healthcare facilities.Design and setting A cross-sectional, population-wide study.Participants All persons who had myringotomy procedures performed between 2007 and 2022.Primary and secondary outcome measures Annual, age and sex-specific incidence was calculated at the local scale (Statistical Area level 2, SA2). We used admitted patient care data from SA Health, providing comprehensive coverage of otitis media procedures across the population, including First Nations. We applied negative binomial regression to assess associations with socioeconomic status and distance to healthcare facilities, accounting for count-based data and overdispersion.Results Myringotomy incidence among First Nations children ranged from 2.2 to 6.1 per 1000 child-years across SA2 regions, compared with 2.4 to 3.7 among non-indigenous children. For the whole population, overall annual incidence ranged from 2.7 to 4.2 for males and 2.0 to 2.9 for females, with higher incidence observed in several suburban areas of Adelaide. Myringotomy procedures were associated with socioeconomic status, with increased socioeconomic advantage associated with a 17% reduction in cases (relative risk 0.83, 95% CI 0.76 to 0.92) among First Nations children. Distance to healthcare facilities was associated with myringotomy for non-indigenous children but not for First Nations children.Conclusions This study found a higher incidence of myringotomy procedures among First Nations children, particularly in later childhood. Socioeconomic disadvantage was a driver, while geographic proximity to healthcare had limited influence. Future initiatives may benefit by prioritising culturally informed, community-led strategies focused on early intervention, prevention and equitable service delivery.

Qianxia Li, Xue Hou, Yuanbin Ye et al.

Due to the increasing demand for accurate and robust GNSS positioning for location-based services (LBS) in urban regions, the impacts prevalent in metropolitan areas, like multipath reflections and various interferences, have become persistent challenges. Consequently, developing effective strategies to address these sophisticated influences has become both a primary research focus and a shared priority. In this paper, the authors explore an approach to identify and mitigate the drawbacks arising from multipath effects in urban positioning. Unlike conventional ways for building complex models, an adaptive data-driven methodology is proposed to identify the fingerprints of a multipath in GNSS observations. This approach utilizes the Fourier transform (FT) to examine code multipath and other error sources in terms of frequency, as represented by the power spectrum. Wavelet decomposition and signal spectrum methods are subsequently applied to seek traces of code multipath in multilayer decompositions. Based on the exhibited multipath features, the impacts of multipath in GNSS observations are detected and mitigated in the reconstructed observations. The proposed method is validated for both static and dynamic positioning scenarios, demonstrating seamless integration with existing positioning models. The feasibility has been verified through a series of experiments and tests under urban environments using navigation terminals and smartphones.

Stefan Siedentop, Maximilian Schartmann

In recent years, land prices in Germany have skyrocketed to levels that were hardly thought possible. This has particularly affected prospering cities, where price increases of more than 100 % have often been recorded since the turn of the millennium. The underlying causes are highly controversial. While some scholars point to the scarcity of developable land due to regulatory restrictions, others see the “financialization” of housing markets in the wake of the financial crisis and the massive influx of liquid capital into land and housing markets as the decisive driver. Against this background, this paper investigates the spatial patterns of land price dynamics in North Rhine-Westphalia during a phase of strong demographic and economic reurbanization. We used disaggregated data from the BORIS system for the years 2012 to 2024, which is available state-wide and georeferenced. Our empirical findings point to a significant trend of market polarization, with excessive growth rates in prospering metropolitan areas and real value losses in some rural areas. Overall, the paper offers new insights into the spatial patterns of urban land markets and possible driving factors explaining uneven developments.

Hamza Ehtesham, Ahmed Kamal Siddiqi, Marium Omair Mirza et al.

Background: With increasing age in the United States, the disease burden of chronic kidney disease (CKD) has increased. The CKD-related mortality trends have not been explored for individuals aged ≥ 65 years. The aim of the study was to identify and evaluate the trends in sex, race, and region among CKD-related mortality in older adults. Methods: Death records sourced from the CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) database were used to analyze mortality trends of CKD in individuals aged ≥65 years from 1999 to 2020. We computed age-adjusted mortality rates (AAMRs) per 100,000 population and annual percent changes (APC) using Joinpoint software. The analysis was structured according to year, sex, race/ethnicity, and geographical regions. Results: From 1999 to 2020, there were 1,572,057 CKD-related deaths. The age-adjusted mortality rate (AAMR) rose from 1999 to 2005, declined until 2009, surged from 2009 to 2012, fell in 2015, and increased again in 2020. Men had a higher AAMR (225) than women (136.3). Non-Hispanic Black or African Americans experienced the highest AAMR (319.2), followed by NH American Indian or Alaska Native (229.5), Hispanic (178.5), NH white (154.5), and NH Asian or Pacific Islander (144.1). Regionally, AAMR was highest in the Midwest (184.6) and lower in non-metropolitan areas (133.3) compared to metropolitan areas (126.3). Conclusion: CKD-related mortality is rising among U.S. adults ≥ 65, especially in non-Hispanic African American males in the Midwest and rural areas. Screening high-risk individuals can enable early detection and lower mortality rates.

Darlene J. Dullius, Victor Gabriel Borges, Renzo Vargas et al.

Several countries have encouraged the installation of photovoltaic (PV) systems in urban areas to contribute to the decarbonization goals of the electric power system. At the same time, consumers have adopted PV systems to reduce their electricity bills. While grid-following PV inverters offset active power demand, they can decrease the power factor at the point of interconnection with the grid, subsequently leading to financial penalties imposed by distribution utilities. Additionally, utilities must maintain power factor values above a predefined threshold to maintain acceptable levels of power losses at the transmission level. This paper examines low power factor penalty schemes for distribution utilities and consumers with PV systems. In such an analysis, an optimization approach is used to minimize the costs of penalties associated with low power factor during a consumer’s billing period. This approach makes it possible to reduce the number of low power factor penalties, thus reducing the amount of electricity bills to be paid by consumers. The decision variable in this context is the power factor of the PV inverters. A case study is presented that considers the financial penalties in a city in the metropolitan area of Sao Paulo, Brazil, with various levels of PV penetration in the distribution system. The results show that while the penalties for consumers are low, distribution utilities would incur more significant penalties or require additional investments to maintain the power factor at the values imposed by electric transmission companies. This analysis aims to help regulatory agencies evaluate penalty schemes to reduce electrical losses in the distribution system.

Omid Mansourihanis, Ayda Zaroujtaghi, Moein Hemmati et al.

This study explores the complex interplay between air pollution, the socioeconomic conditions, and the tourism density within Texas’s urban landscapes, focusing on Dallas, Houston, San Antonio, and Austin. Despite extensive research on environmental justice and urban tourism separately, few studies have integrated these fields to examine how tourism development intersects with environmental and socioeconomic disparities at a neighborhood level. This research addresses this gap by employing advanced geospatial analyses and multi-criteria decision analysis to reveal the pronounced clustering of stressed communities on urban peripheries, often removed from tourism’s economic benefits. The study uniquely quantifies the spatial mismatches between tourist hotspots and areas of environmental stress, a dimension often overlooked in the environmental justice literature. Local spatial statistics and cumulative impact analysis uncover statistically significant correlations between high poverty levels and elevated air pollution in specific locales. The results show varying patterns across cities, with Austin presenting the lowest inequality levels and San Antonio exhibiting significant disparities. This granular, neighborhood-centric approach provides novel insights into the tourism–environment–equity nexus, addressing the lack of comprehensive studies linking these factors in rapidly growing Texan metropolitan areas. The findings underscore the critical need for targeted policy interventions and neighborhood-specific approaches in diagnosing urban environmental disparities and crafting equitable urban development policies that consider tourism’s impact on local communities.

Amar Fadillah, Ching-Lin Lee, Zhi-Xuan Wang et al.

Predicting the future trajectories of pedestrians on the road is an important task for autonomous driving. The pedestrian trajectory prediction is affected by scene paths, pedestrian's intentions and decision-making, which is a multi-modal problem. Most recent studies use past trajectories to predict a variety of potential future trajectory distributions, which do not account for the scene context and pedestrian targets. Instead of predicting the future trajectory directly, we propose to use scene context and observed trajectory to predict the goal points first, and then reuse the goal points to predict the future trajectories. By leveraging the information from scene context and observed trajectory, the uncertainty can be limited to a few target areas, which represent the "goals" of the pedestrians. In this paper, we propose GoalNet, a new trajectory prediction neural network based on the goal areas of a pedestrian. Our network can predict both pedestrian's trajectories and bounding boxes. The overall model is efficient and modular, and its outputs can be changed according to the usage scenario. Experimental results show that GoalNet significantly improves the previous state-of-the-art performance by 48.7% on the JAAD and 40.8% on the PIE dataset.

Hiroaki Minato

This paper presents a Bayesian multilevel modeling approach for estimating well-level oil and gas production capacities across small geographic areas over multiple time periods. Focusing on a basin, which is a geologically and economically distinguishable drilling region, we model the production capacities of its wells grouped by area and time. Regularizing our inferences with priors, we model area-level and time-level variations as well as well-level variations, incorporating lateral length, water usage, and sand usage at each well. The Maidenhead Coordinate System is used to define uniform geographic areas, many of which contain only a small number of wells in a given time period. First, a Bayesian small-area model is built, using data from the Bakken region from February 2012 to June 2024. Then, the model is expanded to contain temporal dynamics in the production capacities. In addition to general time components, water and sand usage intensities are modeled in estimating production capabilities over time. We find the Bayesian multilevel modeling approach provides a flexible and robust framework for modeling and estimating oil and gas production capacities at area and time levels and for informing area-time predictions with uncertainties.

Augustine Chiga Awolorinke, Stephen Appiah Takyi, Owusu Amponsah

The complexities involved in the urbanization process and its effect on environmental sustainability and city aesthetics has been extensively researched in the conventional literature. The rapid urban growth in countries in the global south coupled with weak development control has led to the encroachment of environmentally sensitive areas. Yet, little is known among scholars on whether regulatory agencies have given up on the encroachment of ecologically sensitive areas to continue or they are powerless. This paper through a qualitative research approach explores the factors that influence non-compliance with land use and ecosystem regulations from the perspective of relevant stakeholders. Through face-to-face interviews, 19 participants from eleven (11) regulatory institutions in the Greater Kumasi Metropolitan Area were interviewed. The findings of the study showed that several factors ranging from political, social, and economic adversely affect the ability of the regulatory agencies to effectively enforce the regulations that protect environmentally sensitive areas such as freshwater and wetlands. For example, in terms of political factors, the study showed that, the powerful nature of political actors in Ghana's democratic dispensation coupled with their continuous interference in the enforcement of regulations and the lack of sustained political will continue to threaten the sustainable management of environmentally sensitive areas. Socially and culturally, there is a shift from communal management of ecological resources to a formal public institutional management approach. Inadequate financial support, logistical constraints, and unavailability of technical experts and technology were economic factors that influence institutional non-compliance with land use and ecosystem regulations in Ghana The researchers conclude that the inability of the policymakers and the relevant authorities to address these political, social, and economic barriers confronting the regulatory agencies will continue to make them powerless when it comes to the enforcement of the regulations that protect environmentally sensitive areas.

Songyang Zhang, Tianhang Yu, Brian Choi et al.

Providing rich and useful information regarding spectrum activities and propagation channels, radiomaps characterize the detailed distribution of power spectral density (PSD) and are important tools for network planning in modern wireless systems. Generally, radiomaps are constructed from radio strength measurements by deployed sensors and user devices. However, not all areas are accessible for radio measurements due to physical constraints and security consideration, leading to non-uniformly spaced measurements and blanks on a radiomap. In this work, we explore distribution of radio spectrum strengths in view of surrounding environments, and propose two radiomap inpainting approaches for the reconstruction of radiomaps that cover missing areas. Specifically, we first define a propagation-based priority and integrate exemplar-based inpainting with radio propagation model for fine-resolution small-size missing area reconstruction on a radiomap. Then, we introduce a novel radio depth map and propose a two-step template-perturbation approach for large-size restricted region inpainting. Our experimental results demonstrate the power of the proposed propagation priority and radio depth map in capturing the PSD distribution, as well as the efficacy of the proposed methods for radiomap reconstruction.

Weiying Lin, Che Liu, Xin Zhang et al.

Implementing precise detection of oil leaks in peak load equipment through image analysis can significantly enhance inspection quality and ensure the system's safety and reliability. However, challenges such as varying shapes of oil-stained regions, background noise, and fluctuating lighting conditions complicate the detection process. To address this, the integration of logical rule-based discrimination into image recognition has been proposed. This approach involves recognizing the spatial relationships among objects to semantically segment images of oil spills using a Mask RCNN network. The process begins with histogram equalization to enhance the original image, followed by the use of Mask RCNN to identify the preliminary positions and outlines of oil tanks, the ground, and areas of potential oil contamination. Subsequent to this identification, the spatial relationships between these objects are analyzed. Logical rules are then applied to ascertain whether the suspected areas are indeed oil spills. This method's effectiveness has been confirmed by testing on images captured from peak power equipment in the field. The results indicate that this approach can adeptly tackle the challenges in identifying oil-contaminated areas, showing a substantial improvement in accuracy compared to existing methods.

J. Bound, H. Holzer

Isabel P. De Ramos, Amy H. Auchincloss, Usama Bilal

Background/Objective: Investigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019. Methods: Using vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990–1994 to 2015–2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables. Results: In 2015–2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time. Conclusion: Despite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.

Yajing Liu, Ahmed S. Zamzam, Andrey Bernstein

This paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system.

Yuting Xie

Christine Baumgärtner

André Luís Acosta, PhD, Fernando Xavier, PhD, António Saraiva, PhD et al.

Background: With the continuous spreading of SARS-CoV-2 globally, the probability for interactions between humans who are infected and wildlife tends to grow intensely, as well as the likelihood of viral spillover from humans to biodiversity. This aspect is of great concern for wildlife conservation and human health, because the list of highly susceptible animal groups that have contracted SARS-CoV-2 (bats, mustelids, and primates) is large and, once infected, these groups can act as vectors and reservoirs, becoming a substrate for viral mutations and recombinations and boosting the risk of new strains emerging, which can return to humans as new diseases. Little is known about the inducing factors facilitating coronavirus spillover from one species to another, but it can be argued that interface zones between wild fauna and humans, which are narrow edges between anthropic (cities, roads, parks, ecotourism sites, and agricultural frontiers) and sylvatic habitat, are zones of increased interaction between humans and wild animals, and thus have a higher probability of viral spillover events than other areas. In a similar context, the habitat compression by forest fragmentation also brings species and infected beings closer, reducing their home ranges and intensifying the risk of spillover among wild populations. Therefore, on the basis of the premise for zoonosis—the greater human–animal interaction, the greater risk of viral spillover—we aimed to identify the most and least susceptible areas to viral spillover in Brazil. Methods: We developed an approach combining ecological modelling (Biomod2: modelling habitat suitability for 158 bat and 49 primate species) and geographical information systems (by using demographic indicators, roads, and related variables) to map the most and least susceptible areas to spillover in Brazil. This map indicates priority areas for serological surveillance of fauna for monitoring the spillover and circulation of SARS-CoV-2 strains and variants in Brazilian biodiversity. Findings: Among our most relevant preliminary results, we found that forested areas surrounding the São Paulo Metropolitan Area are among the most susceptible areas for spillover. This resulted from the combination of high contaminated human density and high density of non-human primates interacting with humans in these transitional areas. Interpretation: Because of the high resolution of the results, the map can be useful for action planning and decision making in conservation and health, since susceptible areas denote not only a greater risk of virus jumping from humans to animals, but also of coronaviruses returning from fauna to humans in new viral strains. Funding: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP; 2019/12988-7 and 2018/14389-0).

E. J. G. Merin, A. L. F. Yute, C. J. S. Sarmiento et al.

Natural disasters incur many fatalities and economic losses for vulnerable and developing countries such as the Philippines. It is crucial that during calamities, on-ground surveillance is supplemented by low-cost and time-efficient methods such as satellite remote sensing. Diwata-2 is a Philippine microsatellite specifically equipped for disaster assessment. In this study, the capabilities of this satellite in ashfall detection were explored by closely examining the case of the Taal volcano eruption on January 12, 2020. Satellite images covering parts of CALABARZON and Metropolitan Manila before and after the phreatomagmatic eruption were compared. The presence and extent of heavy ash over the study area were identified after the image classification using the Support Vector Machine (SVM) algorithm. A decrease in vegetation cover and built-up areas was also observed. Upon validation, an overall accuracy of 91.4562 and Kappa coefficient of 0.8833 were achieved for the post-eruption ashfall extent map, exhibiting the potential of Diwata-2 imagery in monitoring volcanic eruptions and similar phenomena.

Maurilio Matracia, Mustafa A. Kishk, Mohamed-Slim Alouini

Despite coverage enhancement in rural areas is one of the main requirements in next generations of wireless networks (i.e., 5G and 6G), the low expected profit prevents telecommunication providers from investing in such sparsely populated areas. Hence, it is required to design and deploy cost efficient alternatives for extending the cellular infrastructure to these regions. A concrete mathematical model that characterizes and clearly captures the aforementioned problem might be a key-enabler for studying the efficiency of any potential solution. Unfortunately, the commonly used mathematical tools that model large scale wireless networks are not designed to capture the unfairness, in terms of cellular coverage, suffered by exurban and rural areas. In big cities, in fact, cellular deployment is essentially capacity driven and thus cellular base station densities are maximum in the town centers and decline when getting far from them. In this paper, a new stochastic geometry-based model is implemented in order to show the coverage spatial variation among urban, suburban, and exurban settlements. Indeed, by implementing inhomogeneous Poisson point processes (PPPs) it is possible to study the performance metrics in a realistic scenario where terrestrial base stations (TBSs) are clustered around the urban center while outer aerial base stations (ABSs) are uniformly distributed outside an urban exclusion zone. Based on this, our simulation results can quantify the improvement, in terms of coverage probability, that even a surprisingly low density of ABSs can bring to peripheral regions depending on the extension of the exclusion zone, enabling us to draw insightful considerations.