Urban vibrancy reflects the dynamic human activity within urban spaces and is often measured using mobile data that captures floating population trends. This study proposes a novel approach to derive Urban Vibrancy embeddings from real-time floating population data to enhance traffic prediction models. Specifically, we utilize variational autoencoders (VAE) to compress this data into actionable embeddings, which are then integrated with long short-term memory (LSTM) networks to predict future embeddings. These are subsequently applied in a sequence-to-sequence framework for traffic forecasting. Our contributions are threefold: (1) We use principal component analysis (PCA) to interpret the embeddings, revealing temporal patterns such as weekday versus weekend distinctions and seasonal patterns; (2) We propose a method that combines VAE and LSTM, enabling forecasting dynamic urban knowledge embedding; and (3) Our approach improves accuracy and responsiveness in traffic prediction models, including RNN, DCRNN, GTS, and GMAN. This study demonstrates the potential of Urban Vibrancy embeddings to advance traffic prediction and offer a more nuanced analysis of urban mobility.
This study investigates the ethno-sustainability of Itawit architecture as a distinctive indigenous practice in the Cagayan province of Northern Philippines. Employing a qualitative grounded theory approach, data were gathered through ethnographic interviews, field observations, and archival research with building owners, carpenters, shamans, and elders from Middle and Southern Cagayan. Using coding, memoing, and thematic analysis, the research thematised vernacular construction practices and knowledge systems, framing them as integral components of cultural heritage and community resilience. Findings demonstrate that Itawit architecture embodies sustainable principles through locally sourced materials, ritual practices, and collective labour systems such as ivvet (community construction). Despite modernisation pressures and the adoption of permanent materials, traditional ecological knowledge and oral transmission continue to sustain building practices and cultural identity. The study highlights “ethno-sustainability” as a framework wherein spiritual beliefs, environmental sensitivity, and social contracts interconnect to preserve community resilience. Documentation of terms, visual records, and rituals provides a baseline reference for conservationists, policymakers, and urban planners. Integrating these indigenous practices into contemporary planning contributes to culturally inclusive and environmentally sustainable development in the Philippines and beyond.
To uncover the city's fundamental functioning mechanisms, it is important to acquire a deep understanding of complicated relationships among citizens, location, and mobility behaviors. Previous research studies have applied direct correlation analysis to investigate such relationships. Nevertheless, due to the ubiquitous confounding effects, empirical correlation analysis may not accurately reflect underlying causal relationships among basic urban elements. In this paper, we propose a novel urban causal computing framework to comprehensively explore causalities and confounding effects among a variety of factors across different types of urban elements. In particular, we design a reinforcement learning algorithm to discover the potential causal graph, which depicts the causal relations between urban factors. The causal graph further serves as the guidance for estimating causal effects between pair-wise urban factors by propensity score matching. After removing the confounding effects from correlations, we leverage significance levels of causal effects in downstream urban mobility prediction tasks. Experimental studies on open-source urban datasets show that the discovered causal graph demonstrates a hierarchical structure, where citizens affect locations, and they both cause changes in urban mobility behaviors. Experimental results in urban mobility prediction tasks further show that the proposed method can effectively reduce confounding effects and enhance performance of urban computing tasks.
Generative AI, large language models, and agentic AI have emerged separately of urban planning. However, the convergence between AI and urban planning presents an interesting opportunity towards AI urban planners. Existing studies conceptualizes urban planning as a generative AI task, where AI synthesizes land-use configurations under geospatial, social, and human-centric constraints and reshape automated urban design. We further identify critical gaps of existing generative urban planning studies: 1) the generative structure has to be predefined with strong assumption: all of adversarial generator-discriminator, forward and inverse diffusion structures, hierarchical zone-POI generative structure are predefined by humans; 2) ignore the power of domain expert developed tools: domain urban planners have developed various tools in the urban planning process guided by urban theory, while existing pure neural networks based generation ignore the power of the tools developed by urban planner practitioners. To address these limitations, we outline a future research direction agentic urban AI planner, calling for a new synthesis of agentic AI and participatory urbanism.
This study addresses the challenges of adaptive reuse in heritage buildings in Jordan. Despite the importance of preserving heritage buildings, particularly given their cultural and historical significance, there is a lack of scholarly investigation into the specific challenges faced in their adaptive reuse in Jordan. This research aims to identify and analyse these challenges to provide insights for policymakers, preservationists, and urban planners. Using they Fuzzy Delphi Method, 10 conservationists specialising in heritage buildings in Jordan were consulted to identify six critical obstacles: scarcity of skilled contractors, financial burdens, lack of awareness among building owners, investment risks, legal constraints, and management challenges. Recognising and ameliorating these identified barriers emerge as imperative prerequisites for fostering the sustainable development of Jordan’s architectural heritage and catalysing the proliferation of adaptive reuse practices within the regional milieu.
Luca Maria Aiello, Anastassia Vybornova, Sándor Juhász
et al.
Urban highways are common, especially in the US, making cities more car-centric. They promise the annihilation of distance but obstruct pedestrian mobility, thus playing a key role in limiting social interactions locally. Although this limiting role is widely acknowledged in urban studies, the quantitative relationship between urban highways and social ties is barely tested. Here we define a Barrier Score that relates massive, geolocated online social network data to highways in the 50 largest US cities. At the unprecedented granularity of individual social ties, we show that urban highways are associated with decreased social connectivity. This barrier effect is especially strong for short distances and consistent with historical cases of highways that were built to purposefully disrupt or isolate Black neighborhoods. By combining spatial infrastructure with social tie data, our method adds a new dimension to demographic studies of social segregation. Our study can inform reparative planning for an evidence-based reduction of spatial inequality, and more generally, support a better integration of the social fabric in urban planning.
Understanding the causes and determinants of development and underdevelopment has emerged as a crucial focus within the realm of social and economic studies over the past five decades. Regional development, as a fundamental requirement for progress, encompasses diverse dimensions aimed at achieving regional equilibrium, reducing infrastructural disparities, and addressing structural and territorial gaps. This developmental model not only exhibits exceptional efficiency in terms of resource management and harnessing regional potential, but also strives to narrow or eradicate disparities within and between regions through the spatial organization of socio-economic and structural activities, capitalizing on local capacities unique to each region. This particular study seeks to conduct a comprehensive structural analysis of the drivers influencing regional development in the Chaharmahal and Bakhtiari province. Employing an applied theoretical framework, the research employs a descriptive-analytical survey approach. Data and information were gathered through an extensive examination of relevant academically-sound sources alongside field observations, including interviews and questionnaires. Quantitative analysis, employing cross-impact analysis and Micmac software, was employed to analyze the collected data. Twenty key factors were thus extracted and identified as crucial drivers influencing regional development in the province of Chaharmahal and Bakhtiari.
Introduction
Regional development is driven by the objectives of reducing socio-economic disparities among different regions and promoting spatial decentralization, ultimately aiming for sustainable socio-economic progress. By recognizing and understanding the factors that contribute to regional development and formulating plans for achieving sustainable development, regions can take essential steps towards closing the gap between them. These disparities manifest as a reflection of various elements, such as environmental factors, political economy, shortcomings in spatial planning systems, insufficient integrated territorial management, and a lack of coordination among responsible organizations involved in spatial and regional development. The Chaharmahal and Bakhtiari province, encompassing a significant territorial extent in Iran, benefits from extensive capacities within economic, social, cultural, and natural resource domains, indicating a favorable environment for growth, development, and overcoming challenges. Nonetheless, despite numerous programs designed and implemented to foster infrastructure development and enhance social services, unfavorable conditions persist in major economic, social, and infrastructure indicators. Inefficient management practices, operational inadequacies, and insufficient attention towards harnessing the province's potentials have led to diverse issues and challenges impeding its development. Consequently, it becomes evident that regional imbalances and the neglect of development drivers within the province are reflected across economic, social, cultural, and infrastructure indicators. Thus, recognizing the influential factors and drivers that underpin regional development in the province and establishing a solid foundation for regional development planning based on these drivers becomes critically significant. Such an approach serves as a gateway to addressing and alleviating the problems and shortcomings associated with underdevelopment and deprivation. Thus, the primary objective of this research centers on conducting a structural analysis of the drivers shaping regional development. Specifically, it seeks to address the following question: What are the key driving forces influencing regional development in the Chaharmahal and Bakhtiari province?
Methodology
The present research adopts an "applied-theoretical" approach in terms of its purpose, while employing a "descriptive-analytical" methodology that aligns with its nature and methodological framework. The research methodology for this study combines both quantitative-survey and qualitative techniques, in accordance with the research objectives. In addition to gathering insights from experts through the Delphi method, documentary analysis of various sources such as the provincial spatial planning document, reports, plans, and development plans of the province has been utilized as part of the research methodology. The statistical population for this study consists of academic experts, professionals, and institutional-organizational managers who possess ample knowledge and experience in the field of regional development within the study area. These experts were purposefully selected and included in the research sample, following the method of purposive sampling. To analyze the structure of regional development drivers in the Chaharmahal and Bakhtiari province, a total of 21 academic experts, institutional-organizational experts, and managers were chosen as representative samples. Selection criteria were based on the experts' expertise, willingness to participate, as well as the complexity of the methods, stages, and implementation conditions associated with the Delphi technique. This study encompasses various dimensions and drivers of regional development, including economic, social, infrastructural, environmental, agricultural, and institutional-organizational aspects, in addition to urban and rural development considerations. These drivers were prioritized based on the expert opinions' importance, and the identification of key drivers was accomplished through the utilization of the Cross-impact analysis method along with Micmac software.
Discussion and Results
Aligned with the primary objective of the present research, the structural analysis and identification of key drivers that impact regional development in Chaharmahal and Bakhtiari province were carried out using the Cross-impact analysis (CIA) method. This method facilitated the identification and assessment of the influence exerted by these drivers on the region. Through a comprehensive analysis that involved examining the relationship between variables, assessing the stability and instability of the studied system, constructing a matrix of direct influences (MDI), a matrix of indirect influences (MII), ranking variables, and calculating the coefficient of displacement for each variable under varying conditions, a total of 20 factors were extracted and selected as the key drivers influencing the regional development of Chaharmahal and Bakhtiari provinces. Table 1 presents the ranking of drivers affecting the regional development of Chaharmahal and Bakhtiari province, based on their direct and indirect dependencies and influences.
Table 1. Key drivers influencing the regional development of Chaharmahal and Bakhtiari province
Code
Drivers
Final score
Rank
MDI
MII
MDI
MII
V1
Employment and labor market
227
226
1
1
V20
Human resource management and the use of local and expert manpower in the development management of the province
222
221
2
3
V54
Migration management (rural-urban and outside the province)
220
220
3
2
V49
Coordination and constructive inter-organizational interaction
216
212
4
4
V22
Coherence in social management of the province
211
209
5
5
V4
Deprivation policies and poverty reduction
203
202
6
6
V41
Development of infrastructure and urban and rural water supply networks
202
200
7
7
V39
Utilization of tourism capacities and tourism development infrastructures
200
196
8
9
V11
The optimal distribution system of investment and economic resources between different regions of the province
197
195
9
11
V51
The existence of comprehensive crisis management plans and programs
197
194
10
8
V12
Economic competitiveness at the national and transnational level
194
194
11
10
V60
Management of urban and rural population spatial distribution system
194
194
12
12
V55
Appropriate distribution of infrastructure, services, and balancing to the urban and rural residential network
192
193
13
13
V25
Protection, exploitation, and management of water resources (organizing and development of water resources, containment and transfer of surface water, and improvement of efficiency in exploitation of water resources)
191
190
14
17
V28
Management and exploitation of agricultural resources
191
190
15
15
V47
Development and equipping of infrastructures, and facilities related to the field of crisis management
189
189
16
14
V62
Resilience of settlements
187
187
17
18
V64
Evaluating the effects of urban and rural development plans
187
185
18
16
V33
Environmental and social management of water transfer projects
184
182
19
22
V34
Management of environmental hazards and pollution (polluting sources of water, soil, and air and the emerging phenomenon of dust storm with extra-regional origin)
181
178
20
19
Conclusions
The present study has been conducted with the primary objective of conducting a comprehensive analysis and identification of indicators and drivers that contribute to regional development in Chaharmahal and Bakhtiari province. To achieve this goal, an examination of spatial planning and development documents specific to the province, as well as consultations with academic and organizational experts, were conducted. Through this process, a prioritization of 20 drivers was accomplished, highlighting the key drivers that significantly influence regional development. It is crucial to attain a correct comprehension of these key drivers within the development dimensions of the province in order to effectively implement regional development policies in Chaharmahal and Bakhtiari province. By doing so, integrated management, sustainable planning, and collaboration at national and provincial levels can be fostered. This collaborative effort aims to overcome obstacles to development and capitalize on opportunities in alignment with the province's capabilities.
This article explores the connection between Smart Growth and the decolonization of urban growth management in Egypt, examining the impact of former colonial influence on present urban policy and practices. Drawing insights from the urbanization of Egyptian desert areas before and after the New Urban Communities Program (NUCP), it scrutinizes how historical influences adversely affect contemporary approaches, inducing socio-economic impacts. The primary objective is to identify the root causes of misguided urban growth management practices, arguing that mono-institutional and sectoral development is rooted in Egypt's quasi-colonial history preceding the NUCP. The research employs a comprehensive methodological approach, using descriptive qualitative methods to investigate the growth of emerging cities based on Smart Growth principles and quantitative analysis to assess population decongestion resulting from the NUCP. It evaluates the implementation of Smart Growth principles during the NUCP and pre-NUCP, offering insights into adverse management practices. Despite the NUCP's goal to alleviate congestion, only 1.6 percent of the population was decongested by 2017. The research highlights the need for a new municipally guided growth model, emphasizing indigenous and locally validated approaches. This model aims to rectify inefficiencies in current urban management practices, fostering a responsive and sustainable approach aligned with local community needs.
Trees play a crucial role in urban environments, offering various ecosystem services that contribute to public health and human well-being. China has initiated a range of urban greening policies over the past decades, however, monitoring their impact on urban tree dynamics at a national scale has proven challenging. In this study, we deployed nano-satellites to quantify urban tree coverage in all major Chinese cities larger than 50 km2 in 2010 and 2019. Our findings indicate that approximately 6000 km2 (11%) of urban areas were covered by trees in 2019, and 76% of these cities experienced an increase in tree cover compared to 2010. Notably, the increase in tree cover in mega-cities such as Beijing, and Shanghai was approximately twice as large as in most other cities (7.69% vs 3.94%). The study employs a data-driven approach towards assessing urban tree cover changes in relation to greening policies, showing clear signs of tree cover increases but also suggesting an uneven implementation primarily benefiting a few mega-cities.
Different social backgrounds and planning policies give rise to diverse urban morphologies. These morphologies influence urban microclimate factors and contribute to the formation of unique local microclimates, particularly in terms of outdoor temperature. In recent times, the heat island effect has gained increasing significance during the summer season. Therefore, this study aims to explore the correlation between urban microclimate simulation and urban morphology within the context of the heat island effect. Specifically, we investigate how the outside temperature varies across different types of residential buildings in Yeongdeungpo-gu, Seoul, South Korea, during the summer period. We compare temperature conditions using a multi-dimensional system of building clusters' morphological indices and employ ENVI-met software for simulation purposes. The results of the urban microclimate simulation are comprehensively analyzed, revealing a significant finding: high-rise residential buildings exhibit considerably higher outdoor temperatures compared to low-rise residential buildings. Furthermore, the presence of open spaces plays a crucial role in mitigating high neighborhood temperatures. By deriving insights from these findings, we aim to provide valuable conclusions to support city managers in making informed decisions.
Data-driven approaches, including deep learning, have shown great promise as surrogate models across many domains. These extend to various areas in sustainability. An interesting direction for which data-driven methods have not been applied much yet is in the quick quantitative evaluation of urban layouts for planning and design. In particular, urban designs typically involve complex trade-offs between multiple objectives, including limits on urban build-up and/or consideration of urban heat island effect. Hence, it can be beneficial to urban planners to have a fast surrogate model to predict urban characteristics of a hypothetical layout, e.g. pedestrian-level wind velocity, without having to run computationally expensive and time-consuming high-fidelity numerical simulations. This fast surrogate can then be potentially integrated into other design optimization frameworks, including generative models or other gradient-based methods. Here we present the use of CNNs for urban layout characterization that is typically done via high-fidelity numerical simulation. We further apply this model towards a first demonstration of its utility for data-driven pedestrian-level wind velocity prediction. The data set in this work comprises results from high-fidelity numerical simulations of wind velocities for a diverse set of realistic urban layouts, based on randomized samples from a real-world, highly built-up urban city. We then provide prediction results obtained from the trained CNN, demonstrating test errors of under 0.1 m/s for previously unseen urban layouts. We further illustrate how this can be useful for purposes such as rapid evaluation of pedestrian wind velocity for a potential new layout. It is hoped that this data set will further accelerate research in data-driven urban AI, even as our baseline model facilitates quantitative comparison to future methods.
Monitoring urban structure and development requires high-quality data at high spatiotemporal resolution. While traditional censuses have provided foundational insights into demographic and socioeconomic aspects of urban life, their pace may not always align with the pace of urban development. To complement these traditional methods, we explore the potential of analyzing alternative big-data sources, such as human mobility data. However, these often noisy and unstructured big data pose new challenges. Here we propose a method to extract meaningful explanatory variables and classifications from such data. Using movement data from Beijing, which are produced as a byproduct of mobile communication, we show that meaningful features can be extracted, revealing, for example, the emergence and absorption of subcentres. This method allows the analysis of urban dynamics at a high spatial resolution (here, 500m) and near real-time frequency, and high computational efficiency, which is especially suitable for tracing event-driven mobility changes and their impact on urban structures.
Jürgen Bruns-Berentelg, Luise Noring, Adam Grydehøj
This paper considers the cases of urban redevelopment at waterfront and brownfield sites in Copenhagen (Denmark) and Hamburg (Germany) to explore how two municipal governments have pursued divergent kinds of entrepreneurial governance, even as they have aimed to create similar kinds of new-build neighbourhoods. Copenhagen and Hamburg have both engaged in large-scale speculative development projects, simultaneously raising urban land values and adding urban public good. The cities follow a long tradition of using land value capture to raise funds for municipal activities, yet their scopes of action and tools for achieving progress have been shaped by local economic and political conditions. Although both cities began redevelopment at similar kinds of sites in the 1990s, Copenhagen’s municipal government was relatively impoverished, while Hamburg’s municipal government was relatively wealthy. As a result, even though both cities deployed state-owned enterprises (SOEs) and revolving funds models to reinvest revenues in future development, they possessed different potential strategies for increasing intercity competitiveness: Copenhagen’s immediate aim in redeveloping its Ørestad and harbour districts was to fund a citywide mass transit system and thereby enhance competitiveness through infrastructure development, while Hamburg sought to use its HafenCity waterfront redevelopment to boost competitiveness through port modernisation, increased in urban quality and commercial expansion in the city centre. By comparing these two cases, we can better understand the contingent nature of entrepreneurial governance and urban redevelopment processes.
Evelyn A Adade, Lewis R Elliott, Lora E Fleming
et al.
Building on evidence of the links between bluespace and public health, this study explores the governance of bluespace infrastructure to promote human health and well-being in Plymouth (UK). Using in-depth retrospective interviews and document analysis, this study focused on the role of governance in urban planning and development, specifically, the implementation phase of a bluespace infrastructure intervention. A deductive qualitative approach categorised content into themes related to pre-established water governance frameworks. Key findings from this study emphasise: the importance of health and welfare concerns around blue spaces as an incentive to getting started; collaborative stakeholder participation and engagement; the necessity of adequate funding; and the importance of continued monitoring and maintenance of urban blue space infrastructure. Based on reflective accounts of stakeholder experiences, the successes of the implementation process of the redevelopment are highlighted. More successful and sustainable bluespace interventions can be realised through ongoing considerations of effective water governance.
E-waste production increase in the industrialised countries of the Global South follows the worldwide trend in the early 21st century. In large urban centres of these territories, e-waste disposal occurs in more significant quantities, and the need to implement a reverse logistics system within a proper regulatory and technical conditions has become a challenge. To the extent that most researches on the e-waste recycling in the developing world are dedicated to the analysis of informal stakeholders – especially in the waste collection and processing stages –, this article aims to contribute to the scientific debate by analysing the organisation of formal recyclers in Sao Paulo Macrometropolis, the most expressive consumer market of Brazil, encompassing more than 30 million inhabitants. Through a comparative case study of formal recyclers operating before the enforcement of national e-waste management regulation (2020), it was revealed some logistics limitations related to the low/irregular flow of e-waste collected, and the lack of technologies to enable the final stages of recycling. Research also points to possible synergies between the demands of these formal companies and the instruments that will be enforced by the recently approved regulation as a way to overcome these limitations in the short term partially..
Urban green space has been regarded as contributing to citizen happiness by promoting physical and mental health. However, how urban green space and happiness are related across many countries of different socioeconomic conditions has not been explained well. By measuring urban green space score (UGS) from high-resolution Sentinel-2 satellite imagery of 90 global cities that in total cover 179,168 km$^2$ and include 230 million people in 60 developed countries, we reveal that the amount of urban green space and the GDP can explain the happiness level of the country. More precisely, urban green space and GDP are each individually associated with happiness; happiness in the 30 wealthiest countries is explained only by urban green space, whereas GDP alone explains happiness in the 30 other countries in this study. Lastly, we further show that the relationship between urban green space and happiness is mediated by social support and that GDP moderates the relationship between social support and happiness, which underlines the importance of maintaining urban green space as a place for social cohesion in promoting people's happiness.
Sarah Mokhtar, Matthew Beveridge, Yumeng Cao
et al.
Urban planners and policy makers face the challenge of creating livable and enjoyable cities for larger populations in much denser urban conditions. While the urban microclimate holds a key role in defining the quality of urban spaces today and in the future, the integration of wind microclimate assessment in early urban design and planning processes remains a challenge due to the complexity and high computational expense of computational fluid dynamics (CFD) simulations. This work develops a data-driven workflow for real-time pedestrian wind comfort estimation in complex urban environments which may enable designers, policy makers and city residents to make informed decisions about mobility, health, and energy choices. We use a conditional generative adversarial network (cGAN) architecture to reduce the computational computation while maintaining high confidence levels and interpretability, adequate representation of urban complexity, and suitability for pedestrian comfort estimation. We demonstrate high quality wind field approximations while reducing computation time from days to seconds.
Nas últimas décadas, tem havido um crescimento expressivo do número de atrações turístico-culturais, dentre as quais atrações principais, centros de interpretação patrimonial e trilhas e roteiros patrimoniais. Objetiva-se apresentar, discutir e exemplificar diversas maneiras de criar, formatar, gerir e promover atrações turístico-culturais, isoladamente ou em conjunto, de modo a tornar a oferta turístico-cultural de uma cidade, região ou país mais atrativa para determinados públicos-alvo. O presente artigo aborda o seguinte: a) a criação de uma nova e original atração turístico-cultural; b) o pacote de atrações e outros elementos turísticos e de lazer; c) o desenvolvimento de trilhas e roteiros patrimoniais; d) eventos – destinos turísticos; e) centro de interpretação patrimonial; e f) eventos – atração turístico-cultural. Enquanto no exterior há o fenômeno do encerramento de atrações turístico-culturais, em virtude de um crescimento acelerado superior ao da demanda, tem ocorrido no Brasil, por parte do poder público e da iniciativa privada, um desinteresse em abrir centros de interpretação patrimonial e desenvolver trilhas e roteiros patrimoniais, dentre outras atrações, mesmo em nossas principais cidades patrimoniais. A “importação” de novos modelos e tipos de atrações turístico-culturais seria algo inovador para o mercado de turismo cultural no Brasil, mesmo que alguns desses já estejam sendo implantados no exterior, desde pelo menos os anos 1980.