Journal of Urban Management最新文献

Urban water security is a multi-faceted water, socioeconomic, and governance challenge. The complexity of translating the holistic approach into policies is an important need for improving water resource management to achieve prosperity, equity, sustainability, and good governance. The city of Lamphun is an example of the practice, which faced drought and major challenges in efficiently distributing water to industrial partners and downstream residents. The purpose of this study was to monitor urban water security and formulate a water management-based urban land use policy for Lamphun Municipality to mitigate water conflicts and ensure access to water for all residents. Therefore, the study examined urban water security using 4 indices: urban water resources, access, risks, and governance. A careful urban land use plan responsible for water security was proposed based on potential surface analysis techniques and public participation. The result of this research would not only guarantee water security, but also promote public participation and sustainable communities.

Urban Sprawl, categorized by the city's outward expansion into their adjacent areas, has emerged as a pressing and complex challenge in urban development worldwide. Understanding the urban sprawl drivers becomes essential for efficient and sustainable urban development as cities transform and grow. Only some studies have provided a comprehensive analysis combining local perspectives with international understanding, making it challenging to form policies to prevent urban sprawl. This study is conducted with the primary aim of determining the drivers of urban sprawl. The qualitative analysis of focus group, interviews and document analysis have been done to reveal the multifaceted drivers of urban sprawl. The thematic analysis reveals the main role of economic incentives, government policies, accessibility, zoning regulation, cultural aspects, land use changes, Low Spatial Distribution of Productivity and limited Capacity of Dammam Urban Planning Department in influencing the spatial dynamics of urban sprawl in Dammam, Saudi Arabia. This research study connects the local context to the worldwide urbanization trends, contributing to the broader international perspective on the drivers of urban sprawl. The study findings will be helpful in effectively addressing the urban sprawl challenge. With the local focus and international insight, this research study offers a great knowledge for communities, policy makers and urban planners, enabling more sustainable urban development in Saudi Arabia and beyond.

A significant proportion of the world's population is currently experiencing heat stress. This results from the effects of global warming, urban heat islands (UHIs), and the growth of urban populations. Researchers have investigated multiple strategies to address this problem. It has been found that the outdoor thermal environment (OTE) can be modified by means of vegetation, water surfaces, and urban geometry. Several studies have indicated that certain geometric factors have demonstrated a higher degree of effectiveness in cooling the surrounding environment. OTE studies often employ two commonly utilised factors, known as urban geometry indicating parameters (UGPs)—the sky view factor (SVF) and height-to-width ratio (H/W). This article compares OTE studies focusing on these two factors. The comparison encompasses characteristics such as study methods, places and times of conducting, and thermal indices. The findings indicate that geometric studies have primarily relied on simulation and field measurement methods. These studies were predominantly conducted in tropical or subtropical cities during warm seasons, with a preference for daytime investigations. Complex thermal indices, including the physiologically equivalent temperature and mean radiant temperature, were commonly employed. In addition to UGPs, other physical factors, such as orientation, were also taken into consideration. Studies on H/W and SVF differed slightly although they are both geometrically indicative. This review can provide guidance for future studies in the field of urban geometry, in that researchers may choose to prioritise the examination of practical indicators, such as the energy load, to conduct a more comprehensive analysis while also taking into account other physical aspects, such as the presence of trees.

Rapid urbanization and climate change require a thorough understanding of flood vulnerability in order to assure urban safety and resilience. Understanding the factors that contribute to flood vulnerability, allows us to develop effective initiatives that could mitigate the destructive consequences of flooding, while also protecting communities. The objective of this research is to identify and model the socio-economic and demographic factors that significantly influence flood vulnerability in the floodplains of Jackson, Mississippi, and Birmingham, Alabama, USA. First we analyzed the correlation between socio-economic and demographic factors then employed Principal Component Analysis (PCA) to address multicollinearity, a common challenge in multivariate statistical modeling. Subsequently, PCs-based global regression (PCR) and geographically weighted regression (PCGWR) analysis are used to identify key drivers of flood vulnerability. The findings demonstrate that a significant proportion of the variance (>80%) of these factors can be captured by first two to three Principal Components (PCs). Consistent with existing research, African American, poverty, seniors, and the number of less educated people positively correlate with flood vulnerability, while income and housing prices exhibit a negative correlation. Additionally, PCGWR outperformed the Principal Component Regression (PCR) in most cases, highlighting the spatial heterogeneity of flood vulnerability. This study focuses on two U.S. cities, and the methodology is applicable to other cities with similar characteristics. The identified factors align with global research on flood vulnerability, making the proposed research and findings valuable worldwide. The findings of this research are useful for local governments, policymakers, and urban developers to make detailed location specific flood vulnerability plan to reduce impact of flood and improve urban resilience.

This paper addresses the way in which the expansion zones of the metropolitan areas of Medellín and Rionegro are currently moving from the communal relations that marked their rural life to anonymous relations in which notions of neighborliness are gradually disappearing. Understanding the urban as a social condition and not only as a physical expression of the territory, but the urban is also no longer the opposite of the rural, nor is it synonymous with the city. The urban constitutes a phenomenon where anonymity and individuality are privileged in a space. This process takes place in a rural space where part of its heritage is the landscape and unneighborly relations. We assume the notion of the peri-urban limit as a space of undefinition that extends from the periphery of the Aburrá Valley to some of the rural hamlets of the Territorial Subsystem: Alto Grande - La Ramada, in the San Nicolas Valley; places where the communal is disappearing to give way to new urban dynamics. The article constitutes a theoretical contribution to the interpretation of the new realities observed in the peri-urban fringes of many contemporary metropolises, not only because of the debate it opens on the ways of understanding current urban-rural problems, but also because it suggests other perspectives for territorial planning based on the readings of the new social realities that are established there.

Green infrastructure has emerged as an opportunity to balance sociocultural and ecological benefits, alongside the potential for biodiversity conservation in cities. However, key design challenges that remain unsolved including 1) how to effectively balance biodiversity conservation and sociocultural benefits, and 2) how user's perception and knowledge may affect the acceptance of conservation interventions in parks. In this study, we used a mixed methods approach in which focus groups were used to explore users' perceptions of landscape attributes, their benefits, biodiversity, climate change, and conservation interventions in parks. This was followed by face-to-face interviews with the broader general public to quantitatively assess perceptions and acceptability for conservation interventions in parks. While plant density and functional diversity were identified as key landscape attributes, trade-offs may occur with other attributes such as multi-functionality and the order of the vegetation. Most conservation interventions had high acceptance levels, where the decrease of grass in parks was the most controversial attribute. All interventions were correlated with the importance of landscape attributes and climate change concerns, but poorly associated with knowledge of native biodiversity. The results support 1) increasing the functional diversity of plants in parks as a way to balance environmental and sociocultural benefits and promote the acceptability of conservation interventions, however such an increase should be linked to designs that respect notions of order and other park uses, and 2) environmental education based on climate change may be the key to improving acceptability of these initiatives.

The negative impacts of greenhouse gas emissions, particularly CO₂ emissions, have garnered widespread attention. Various old residential areas in China, built more than 20 years ago, have been undergoing urgent transformation to improve citizens’ quality of life, which may significantly reduce carbon emissions. This study developed a carbon emissions accounting framework for residential areas to account the emissions impact of residential transformation. The framework addressed the inventory classifications of landscape greening, residential buildings, water resources, solid waste, infrastructure and transportation. The consumption-based calculation model and bottom-up data collection methods were used. The results show that the transformation of two old residential areas achieved considerable carbon reductions of 17.16% and 33.37% in South and North China, respectively. The macro guidance of local policies, specifically those regarding local urban infrastructure construction, significantly aided the carbon emissions reductions. Based on the calculation results, a list of recommended technologies was proposed to reduce carbon emissions, and four measures (adding greening, improving the garbage recovery rate, separating rain and sewage and transforming envelope structures for energy savings in northern China) were recommended to promote low carbon development in residential areas.

This study focuses on developing and evaluating predictive models for bus travel times adaptable to any transit network, or to new roadway segments without prior travel time data. Most prior work relies on non-standardized features such as road traffic forecasts or closed-source datasets to test predictions on a single route or network. We leverage standardized and open-source data from GTFS and GTFS-RT feeds to gather four months of realtime bus position data from Seattle and Trondheim's transit networks. We then test and refine strategies for generalizing model predictions across both locations. To achieve this, we first develop a data pipeline to process and clean the raw data, then extract features from the standardized sources. We then evaluate the performance of several deep learning and heuristic models in predicting bus travel times between source and target bus networks. Holdout data is taken from selected routes in the source city to validate the internal generalization of the models. Data from the target city is used to evaluate the external generalization of the models. An ablation study explores the impact of different open data sources on model generalization (GPS, static timetables, OpenStreetMap and other realtime trips). We then extend the analysis to 33 international bus networks, placing the results in broader context and testing fine-tuning strategies for generalization. Results show that deep learning methods generalize well within the source network, with as little as 1% loss in MAPE on holdout routes. With minimal fine-tuning generalization is significantly improved on the target network. Model features built on static schedule data, realtime positions or OpenStreetMap embeddings improved generalization performance (up to 10% reduction in MAPE). This was more pronounced for networks with a greater initial quantity of training data. As a route-planning tool for roadways without prior data, geospatial data mining can provide reasonable bus travel time estimates. For cross-sectional bus network analysis, fine tuning on at least 100 trajectory samples for each target network is required to significantly outperform baseline heuristics. This necessitates a GTFS-RT or other standardized realtime data feed in the target city.

Urban form contributes to crime prevention. However, most studies not only simplify the relationship between urban form and crime, they also fail to reflect the geographic structure of urban areas. This study first measured a comprehensive multidimensional urban form indicator for 1486 counties in the United States, which was used to characterize the size and geospatial structure of urban areas. Specifically, it described urban form as consisting of three components: 1) size and population distribution; 2) built environment; and 3) landscape environment. Then, generalized additive mixed models were then used to explore linear or nonlinear associations between urban form indicators and different crime types (violent and property crime). This study's main findings were that 1) the relationship between urban form and crime is not only linear but may also be nonlinear; 2) urban size, fragmentation, connectivity, forest mixing, and shrub mixing are associated with all crime types; 3) population distribution and agricultural mixing are associated with violent crime; and 4) urban patch complexity and water mixing are associated with property crime. Overall, the results of this study can provide guidance for long-term planning of urban geographic structures, contributing to the safe and sustainable development of urban areas.