Participatory urban sensing leverages human mobility for large-scale urban data collection, yet existing methods typically rely on centralized optimization and assume homogeneous participants, resulting in rigid assignments that overlook personal preferences and heterogeneous urban contexts. We propose MAPUS, an LLM-based multi-agent framework for personalized and fair participatory urban sensing. In our framework, participants are modeled as autonomous agents with individual profiles and schedules, while a coordinator agent performs fairness-aware selection and refines sensing routes through language-based negotiation. Experiments on real-world datasets show that MAPUS achieves competitive sensing coverage while substantially improving participant satisfaction and fairness, promoting more human-centric and sustainable urban sensing systems.
Abstract This paper will argue that the study of morphological processes has lagged behind the identification and classification of morphological patterns. Examples from Newcastle upon Tyne will be used to illustrate this argument, ranging from mediaeval burgage plots, through a typology of nineteenth-century working-class terraced housing that emerged in the west end of the city, and more recent twentieth-century social housing. It is concluded that a deeper understanding of urban forms is dependent on a stronger focus on the processes operating at a variety of scales.
In the context of land scarcity and high-density urban areas, the adaptive reuse of abandoned historical industrial buildings plays a critical role in achieving sustainable development goals. This study proposes a sustainability assessment framework for the adaptive reuse of industrial buildings as exhibition spaces within the context of high-density urban development, addressing multiple dimensions of sustainability, including the building’s physical structure, economic factors, environmental impact, social considerations, and governance. The framework consists of 55 design indexes, categorized into 15 subcategories and 5 main categories. We conducted a survey of experts with experience in high-density urban renewal design and implemented a weighting analysis to identify priority intervention measures for industrial building redevelopment in the era of urban stock. Finally, a fuzzy comprehensive evaluation was carried out on ten cases in Shenzhen where industrial buildings were converted into exhibition spaces over the past 12 years. The findings reveal the following: (1) “Reuse of old architectural spaces” is the most critical category to prioritize, and, at the indicator level, “adaptability and efficiency of building reuse”, “public participation in the renewal process”, “cooperative operation structures”, and “planning vision” are identified as the four key influencing factors. (2) The functional layout, historical value, and richness of public amenities in the transformed industrial buildings have a significant positive impact on the evaluation results, while the building’s construction time and floor area do not significantly affect public post-evaluation. (3) Younger and more highly educated groups tend to view the transformed exhibition spaces as tourist attractions, particularly expressing satisfaction with the repurposing of the Kinwei Brewery and OCAT B10 New Hall, and consider the adaptive reuse of industrial buildings to promote sustainable urban renewal (SUR). This study provides concrete policy recommendations and practical guidance for the adaptive reuse of both new and existing industrial buildings, contributing to the creation of sustainable urban environments.
Alfred Toku, Owusu Amponsah, Stephen Appiah Takyi
et al.
Large-scale government land acquisitions in Ghana continue to face significant challenges, despite the existence of regulatory frameworks, policy initiatives, and normative guidelines intended to govern the process. This study examines these challenges in four communities through the theoretical lenses of social contract and justice. A convergent parallel mixed-methods design was employed, combining a cross-sectional survey of 324 landowners and users with interviews and focus group discussions involving key stakeholders. The analysis, using thematic, spatial, and descriptive techniques, revealed critical gaps in constitutional and institutional frameworks. The acquisition processes were marked by overlapping land claims, unclear boundaries, non-payment of compensation, and lack of resettlement, resulting in land-related disputes. These findings highlight the complexity and contested nature of land governance in Ghana. The study emphasizes the importance of clearly defined stakeholder roles and recommends the creation of a national governance body to oversee large-scale acquisitions, with attention to livelihoods and marginalized groups.
Urban food production is becoming an increasingly significant topic in the context of climate change and food security. Conducting research on this subject is becoming an essential element of urban development, deepening knowledge regarding the benefits, challenges, and potential for the development of urban agriculture as an alternative form of food production. Responding to this need, this monograph presents the results of a project study developing innovative socio-technological solutions for sustainable food production and consumption. The idea behind this unique project was to install twenty hydroponic cabinets in the corridors of the selected block of flats, where residents would grow edible plants. The presented research aimed to understand the people who joined this unique initiative. The qualitative study employed purposive sampling and in-depth interviews conducted in two waves. The study comprised 42 participants drawn from two communities of residents in Łódź and Warsaw, Poland. The findings outline the reasons that motivate urban residents to implement sustainable food production solutions, their farming experiences and the educational activities that led to their decision to join an innovative urban food production project. The results obtained will be relevant for those involved in the urban education process, including city authorities, urban educators, pro-environmental associations, and grassroots activists.
Urban research involves a wide range of scenarios and tasks that require the understanding of multi-modal data. Current methods often focus on specific data types and lack a unified framework in urban field for processing them comprehensively. The recent success of multi-modal large language models (MLLMs) presents a promising opportunity to overcome this limitation. In this paper, we introduce $\textit{UrbanLLaVA}$, a multi-modal large language model designed to process these four types of data simultaneously and achieve strong performance across diverse urban tasks compared with general MLLMs. In $\textit{UrbanLLaVA}$, we first curate a diverse urban instruction dataset encompassing both single-modal and cross-modal urban data, spanning from location view to global view of urban environment. Additionally, we propose a multi-stage training framework that decouples spatial reasoning enhancement from domain knowledge learning, thereby improving the compatibility and downstream performance of $\textit{UrbanLLaVA}$ across diverse urban tasks. Finally, we also extend existing benchmark for urban research to assess the performance of MLLMs across a wide range of urban tasks. Experimental results from three cities demonstrate that $\textit{UrbanLLaVA}$ outperforms open-source and proprietary MLLMs in both single-modal tasks and complex cross-modal tasks and shows robust generalization abilities across cities. Source codes and data are openly accessible to the research community via https://github.com/tsinghua-fib-lab/UrbanLLaVA.
The modelling of human mobility is vital for the understanding of the complexity of urban dynamics and guiding effective interventions to improve quality of life. Traditional modelling approaches focus on `average citizens,' which overlook the multitude of experiences from distinct sociodemographic groups. Recent studies have unveiled significant variations in mobility patterns related to gender and socioeconomic status, yet the impact of parenthood remains under-explored. Parenthood brings profound changes to daily routines, influenced by factors such as increased caregiving responsibilities, altered work-life balance, and the need for family-friendly environments. Parents often prioritise considerations such as cost of living, social wellbeing, environmental quality, and safety. Quantifying how `friendly' a city is becomes more and more important for parents, especially in the context of rising remote work opportunities which, in turn, reverberate on the choices on where to settle. This work investigates whether these considerations lead to distinct mobility patterns between parents and non-parents, also accounting for the impact of partnership. Using extensive census data across American cities, we analyse how parenthood and partnership reshape their urban experiences. Our findings indicate that cities can indeed be classified by their level of friendliness towards parents and partners. For example, Dallas and Nashville can be more suited for single individuals, New York and Chicago can be more accommodating to parents, while Washington and Baltimore favour married people. These insights contribute to the growing body of research advocating for more nuanced and equitable urban planning. By recognising the diverse needs of different demographic groups, particularly parents, our study underscores the importance of tailored urban design strategies over universal solutions.
This study offers a comprehensive evaluation of urban renewal efforts in Shandong Province, China, by employing the entropy method combined with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). An evaluation index system was constructed to assess the weights of key factors influencing urban renewal, including the renovation of old residential areas, improvement in sewage treatment quality, development of sponge cities, adoption of clean heating, and enhancement of air quality. Analysis of 16 prefecture-level cities in 2019 reveals significant disparities in performance, with Jinan achieving the highest ranking due to notable improvements in infrastructure and environmental management. Meanwhile, other cities displayed varying levels of success, reflecting different developmental stages and capacities. The findings underscore the necessity for tailored strategies to optimize urban renewal outcomes, focusing on high-weight factors such as sewage treatment, clean heating, and residential renovation. This study provides actionable insights for policymakers, advocating adaptive renewal strategies that align with local contexts and encourage continuous innovation. The results highlight the importance of targeted policy interventions to enhance urban renewal quality across Shandong Province, promoting sustainable urban development and better living standards.
هدف از این پژوهش واکاوی نقش مکانهای سوم شهری در کیفیت محیطی شهر اهواز است. این پژوهش با رویکردی کمَی، به روش پیمایشی و متکی بر مطالعات کتابخانهای- اسنادی در سال 1402 در شهر اهواز انجام شد. جامعه آماری کلیه شهروندان اهوازی (885000 نفر) در سال 1395 میباشند که بهوسیله فرمول کوکران تعداد 390 نفر بهعنوان حجم نمونه و بهصورت تصادفی بهوسیله پرسشنامه محقق ساخته مورد ارزیابی قرار گرفتند. برای تجزیهوتحلیل اطلاعات از آزمونهای ANOVA، تحلیل رگرسیون، T تک نمونهای، تحلیل مسیر و... استفاده شد. یافتهها نشان میدهد، تمامی 10 شاخص بررسیشده بالاتر از میانگین مبنا (3) بودند. همچنین در مدل رگرسیونی مشخص شد، متغیرهای پیشبین حدود (741/0= R2) از واریانس متغیر ملاک (کیفیت محیط) را تبیین میکنند؛ و منطقه 6 (میانگین 08/4) برتری بیشتری نسبت به سایر مناطق 8 گانه اهواز ازلحاظ کیفیت محیطی داشت. نتایج نشان داد؛ کیفیت محیط و میزان رضایت شهروندان اهوازی از مکانهای سوم شهری با توجه به فرهنگ بومی ساکنین این شهر، ارتباطی تنگاتنگ با وضعیت مکانهای سوم این شهر (با بار عاملی 722/0) دارد.
The substantial rise in automobile ownership and expansion of metropolitan areas in recent decades, especially in emerging nations, has resulted in a severe shortage of parking spaces. This problem not only causes significant traffic congestion and an increase in accidents but also places a considerable financial burden on individuals and worsens air pollution. Despite extensive research on addressing the parking issue, there is still a notable deficiency in effective approaches for selecting the best locations for multi-story parking structures, particularly in major cities in Iran. Hence, acknowledging the significance of effective parking management in addressing these problems, This study aimed to provide a comprehensive framework for choosing parking locations in Shiraz's business district. This study combined the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) with a Geographic Information System to make fuzzy multi-criteria decisions. To determine suitable locations, factors such as proximity to business hubs, key roads, land prices, population density, and construction feasibility were assessed. The findings identified districts 13, 14, 15, 16, 17, and 18 in Shiraz's core as having the highest potential for multi-story parking facilities among the 30 central districts. Additionally, the findings showed that accessibility to major roads, population density, and proximity to trip generators were the most relevant factors in deciding where parking facilities should be located in Shiraz. Policymakers and urban planners can use the insights provided by the outcomes of these models to make well-informed decisions on parking infrastructure expenditures.
This study examines the dynamics of Urban Land Use Succession (ULUS) in Upper Hill, Nairobi, highlighting the impact of neoliberal policies and private sector-led urban redevelopment. It investigates how land tenure, public infrastructure, and planning controls shape urban landscapes, leading to patchwork land use patterns and environmental misalignments. The case of Upper Hill, transitioning from a serene residential area to a bustling commercial hub, is explored to understand the determinants of ULUS and propose strategies for streamlined urban development. Employing Neoliberal Theory and hypothesis testing, the research identifies spatial policy as the primary driver of ULUS. The study suggests innovative approaches, including land assembly and the establishment of an Urban Redevelopment Authority, to harmonize urban development. These strategies aim to bridge the gap between private and public land development, ensuring coherent urban growth. The research contributes to the understanding of urban redevelopment, particularly in Kenyan contexts, by offering a model that integrates public and private interests. This model serves as a blueprint for managing urban transformation in Nairobi and other similar urban settings, promoting sustainable and equitable urban development.
Gustavo Moreira, Maryam Hosseini, Carolina Veiga
et al.
Over the past decade, several urban visual analytics systems and tools have been proposed to tackle a host of challenges faced by cities, in areas as diverse as transportation, weather, and real estate. Many of these tools have been designed through collaborations with urban experts, aiming to distill intricate urban analysis workflows into interactive visualizations and interfaces. However, the design, implementation, and practical use of these tools still rely on siloed approaches, resulting in bespoke applications that are difficult to reproduce and extend. At the design level, these tools undervalue rich data workflows from urban experts, typically treating them only as data providers and evaluators. At the implementation level, they lack interoperability with other technical frameworks. At the practical use level, they tend to be narrowly focused on specific fields, inadvertently creating barriers to cross-domain collaboration. To address these gaps, we present Curio, a framework for collaborative urban visual analytics. Curio uses a dataflow model with multiple abstraction levels (code, grammar, GUI elements) to facilitate collaboration across the design and implementation of visual analytics components. The framework allows experts to intertwine data preprocessing, management, and visualization stages while tracking the provenance of code and visualizations. In collaboration with urban experts, we evaluate Curio through a diverse set of usage scenarios targeting urban accessibility, urban microclimate, and sunlight access. These scenarios use different types of data and domain methodologies to illustrate Curio's flexibility in tackling pressing societal challenges. Curio is available at https://urbantk.org/curio.
Pablo Valgañón, Andrés Felipe Useche, Felipe Montes
et al.
We introduce a surveillance strategy specifically designed for urban areas to enhance preparedness and response to disease outbreaks by leveraging the unique characteristics of human behavior within urban contexts. By integrating data on individual residences and travel patterns, we construct a Mixing matrix that facilitates the identification of critical pathways that ease pathogen transmission across urban landscapes enabling targeted testing strategies. Our approach not only enhances public health systems' ability to provide early epidemiological alerts but also underscores the variability in strategy effectiveness based on urban layout. We prove the feasibility of our mobility-informed policies by mapping essential mobility flows to major transit stations, showing that few resources focused on specific stations yields a more effective surveillance than non-targeted approaches. This study emphasizes the critical role of integrating human behavioral patterns into epidemic management strategies to improve the preparedness and resilience of major cities against future outbreaks.
The explosion of massive urban data recently has provided us with a valuable opportunity to gain deeper insights into urban regions and the daily lives of residents. Urban region representation learning emerges as a crucial realm for fulfilling this task. Among deep learning approaches, graph neural networks (GNNs) have shown promise, given that city elements can be naturally represented as nodes with various connections between them as edges. However, many existing GNN approaches encounter challenges such as over-smoothing and limitations in capturing information from nodes in other regions, resulting in the loss of crucial urban information and a decline in region representation performance. To address these challenges, we leverage urban graph structure information and introduce a hierarchical graph pooling process called Coarsened Graph Attention Pooling (CGAP). CGAP features local attention units to create coarsened intermediate graphs and global features. Additionally, by incorporating urban region graphs and global features into a global attention layer, we harness relational information to enhance representation effectiveness. Furthermore, CGAP integrates region attributes such as Points of Interest (POIs) and inter-regional contexts like human mobility, enabling the exploitation of multi-modal urban data for more comprehensive representation learning. Experiments on three downstream tasks related to the UN Sustainable Development Goals validate the effectiveness of region representations learned by our approach. Experimental results and analyses demonstrate that CGAP excels in various socioeconomic prediction tasks compared to competitive baselines.
This paper addresses the pressing challenge of urban mobility in the context of growing urban populations, changing demand patterns for urban mobility, and emerging technologies like Mobility-on-Demand (MoD) platforms and Autonomous Vehicle (AV). As urban areas swell and demand pattern changes, the integration of Autonomous Mobility-on-Demand (AMoD) systems with existing public transit (PT) networks presents great opportunities to enhancing urban mobility. We propose a novel optimization framework for solving the Transit-Centric Multimodal Urban Mobility with Autonomous Mobility-on-Demand (TCMUM-AMoD) at scale. The system operator (public transit agency) determines the network design and frequency settings of the PT network, fleet sizing and allocations of AMoD system, and the pricing for using the multimodal system with the goal of minimizing passenger disutility. Passengers' mode and route choice behaviors are modeled explicitly using discrete choice models. A first-order approximation algorithm is introduced to solve the problem at scale. Using a case study in Chicago, we showcase the potential to optimize urban mobility across different demand scenarios. To our knowledge, ours is the first paper to jointly optimize transit network design, fleet sizing, and pricing for the multimodal mobility system while considering passengers' mode and route choices.
Chengxin Wang, Gary Tan, Swagato Barman Roy
et al.
Urban spatio-temporal (ST) forecasting is crucial for various urban applications such as intelligent scheduling and trip planning. Previous studies focus on modeling ST correlations among urban locations in offline settings, which often neglect the non-stationary nature of urban ST data, particularly, distribution shifts over time. This oversight can lead to degraded performance in real-world scenarios. In this paper, we first analyze the distribution shifts in urban ST data, and then introduce DOST, a novel online continual learning framework tailored for ST data characteristics. DOST employs an adaptive ST network equipped with a variable-independent adapter to address the unique distribution shifts at each urban location dynamically. Further, to accommodate the gradual nature of these shifts, we also develop an awake-hibernate learning strategy that intermittently fine-tunes the adapter during the online phase to reduce computational overhead. This strategy integrates a streaming memory update mechanism designed for urban ST sequential data, enabling effective network adaptation to new patterns while preventing catastrophic forgetting. Experimental results confirm DOST's superiority over state-of-the-art models on four real-world datasets, providing online forecasts within an average of 0.1 seconds and achieving a 12.89% reduction in forecast errors compared to baseline models.
North African cities have been undergoing major transformation over the past two decades following protracted instability, civic uprising, and conflicts, changing their perception from havens to territories of displacements with social, psychological, and physical problems. Historic public spaces in those cities, in particular, form a critical part of urban environments as they have the identity, livelihoods and cross-community engagement in a healthy and fulfilling urban fabric and culture. Whilst there have been several studies on the characteristics of open spaces in urban environments, there is very limited work on the changing perceptions, use and engagement of public spaces in historic cities especially in the post-Arab Spring and its relative instability. This study aims to deploy investigative and creative methods to map, analyse and navigate through the transformation in the perceptions of historic public spaces in Post-Conflict Libya and its divided cities. It will study the users' (locals and visitors) attitudes, movements, and reflections on how those spaces have changed over time. visitors' behaviour in open historical public spaces in Tripoli, Libya. The study explores the relationships between the characteristics of historical public spaces, physical activity, and psychological behaviour. The paper argues that safety and security in public spaces are critical and inherent qualities that inform much of the users’ attitudes in historic cities, which has continued to be the case in post-conflict Tripoli.
Revitalization is an important process in action area planning, especially in the heritage sites located within urban area contexts. Varied techniques and tools of revitalization are applied at various spatial levels, some are suitable for the urban scope, and others suit the architectural building scope. Urban DNA is a term used academically to reflect social, economic, and urban characteristics but has a different interpretation that depends on the spatial scale and context. In action areas, urban DNA refers to the essential visual, social, economic, and physical characteristics that preserve the vital structure of an urban area. Heritage areas are vital in a city structure, in the journey of maximizing the urban DNA chrematistics of heritage sites, sometimes the urban DNA is lost in the process. This paper identifies and encapsulates the importance of Urban DNA in heritage site considerations in the revitalization process within heritage urban context to maximize the socio-economic and visual impacts, especially in declined cities such as Foah City the case study in the Nile Delta region in Egypt. The results pinpoint the most effective urban DNA structure for the declined Foah Heritage Center, despite the city's importance as a ranked third of heritage cities in the country.
Percut Sei Tuan District is one of the sub-districts in Deli Serdang Regency. The position of this sub-district is between Medan City and Batang Kuis District to Kuala Namu Airport. In addition, this sub-district is also one of the centers for the Medindingro development project (Medan - Binjai - Deli Serdang - Karo) as stipulated in RI Presidential Regulation Number 62 of 2011 concerning Medindingro Vision 2027 and is included in the National Strategic Area (KSN).Social and economic problems will arise as the population increases, this requires the development of office facilities, education, health, housing and so on. The challenge is quite complex for the regional government concerned in an effort to build and improve the standard of living and welfare of its people. With the increasing number of activities and dense population, a city can no longer meet the needs of its citizens optimally, so it is necessary to have supporting cities that can accommodate activities that cannot be fulfilled in urban areas. [2] This is done to prevent the development and growth of cities naturally, in other words developing without programmed direction and planning. For this reason, it is necessary to carry out a Study on the Regional Arrangement of Percut Sei Tuan Subdistrict as a guideline for the direction of development for the future, and to avoid uncontrolled forms of development. Creating an integrated urban environment that can increase the efficiency of land use and the carrying capacity of land and can improve the physical quality and appearance of the city.The results of this study are expected to be able to provide directions for regional arrangement in terms of architecture, landscape, regional design in Percut Sei Tuan District, as a guideline for the development and arrangement of urban areas. As a guide for all development actors, both in the design process, space utilization, physical development and in controlling spatial use in Percut Sei Tuan District, Deli Tengah Regency.
Details in building design and construction. Including walls, roofs, Urban renewal. Urban redevelopment
Mohammad Lavajoo, Abbas Arghan, Mohammadreza Zand Moghadam
The extreme spatial disparity and heterogeneity between Tehran city and other settlements in its urban area have led to a decline in spatial justice and amplified differences within the Tehran metropolitan area. This study aims to identify the key factors that influence the realization of the Tehran Metropolitan Plan objectives in the metropolitan area management system using an institutional approach and meta-synthesis method. A systematic review of scientific research articles published between 1390 to 1400 was conducted, and the meta-synthesis method was used to analyze the findings of 23 studies. The results indicate that the reformation of Tehran Metropolitan's organizational structure is the most crucial step toward institutional change, as per the proposed indicators. At the variable level, the study emphasizes the need for the adoption of a multi-centered development model that aligns with institutional change in planning systems, comprehensive and integrated management of the metropolitan area, shifting towards governance of the metropolitan area, centralization, creating a multifaceted functional network, transparency, accountability, and collaborative efforts.