Peter Kakoma, Penjani Hopkins Nyimbili, Moffat Tembo
et al.
The Constituency Development Fund (CDF) has become a key mechanism for delivering small-scale urban infrastructure in Zambia. However, persistent challenges such as project delays, cost overruns, and quality deficiencies undermine the effectiveness of these interventions. This study addresses a critical gap in the literature and practice by developing a novel performance forecasting model tailored to the unique governance and technical context of CDF-funded projects. The model integrates Adaptive Neuro-Fuzzy Inference Systems (ANFIS) with the Analytic Hierarchy Process (AHP) to forecast performance across five key indicators: cost-effectiveness, schedule adherence, quality compliance, safety performance, and client satisfaction. Using stakeholder data from 196 respondents and historical project records, the model was trained and validated using MATLAB. It achieved strong predictive accuracy, with a coefficient of determination (R²) of 0.92 and a root mean square error (RMSE) of 0.09. These results demonstrate the model’s utility as a decision-support tool for local authorities and urban planners, enabling early detection of underperformance and facilitating proactive interventions. The model contributes to performance-based planning by providing a data-driven, stakeholder-informed forecasting framework that is adaptable to resource-constrained environments. Its application can enhance transparency, optimize resource use, and support inclusive urban development in rapidly growing municipalities.
Urban morphology critically governs residential energy demand, yet empirical evidence from semi-arid, geopolitically constrained cities remains scarce. This study quantifies the influence of neighbourhood form on heating and cooling loads in Hebron, Palestine. Three morphologically distinct districts—Old City (compact), Zeitoun (semi-structured) and Al Sheikh (unplanned sprawl)—were mapped in ArcGIS Pro to derive Floor Space Index, Ground Space Index and Open Space Ratio. Prototype mid-rise dwellings were modelled in DesignBuilder and simulated with EnergyPlus under identical boundary conditions. Pearson correlations and ANOVA assessed relationships between morphological variables and annual loads. Results show cooling demand decreases by 34 % as FSI rises from 0.7 to 1.2, whereas heating demand doubles under the same densification. The moderately dense Zeitoun configuration (FSI≈1.0, OSR≈1.6) achieved the lowest combined energy use, outperforming both extreme forms. Findings demonstrate that mid-rise, medium-density layouts balance summer shading with winter solar access, offering a viable pathway for energy-aware expansion in semi-arid contexts. The integrated spatial-simulation framework provides planners with transferable metrics for zoning and retrofit prioritisation, supporting climate-responsive urban policy across the Middle East. Future research should incorporate behavioural patterns and multiple building typologies to refine these benchmarks under climate-change scenarios.
Mariana Brüning-González, José Ignacio Arroyo, Pablo A. Marquet
et al.
Understanding the quantitative patterns behind scientific disciplines is fundamental for informed research policy. While many fields have been studied from this perspective, Urban Science (USc) and its subfields remain underexplored. As organisms, urban systems rely on materials and energy inputs and transformation (i.e. metabolism) to sustain essential dynamics. This concept has been adopted by various disciplines, including architecture and sociology, and by those focused on metabolic processes, such as ecology and industrial ecology. This study addresses the structure and evolution of Urban Metabolism (UM) and Sustainability research, analyzing articles by disciplines, study subjects (e.g., cities, regions), methodologies, and author diversity (nationality and gender). Our review suggests that UM is an emerging field that grew until 2019, primarily addressed by environmental science and ecology. Common methods include Ecological Network Analysis, and Life Cycle Assessment, and Material Flow Analysis, focusing flows over stocks, ecosystem dynamics and evolutionary perspectives of the urban system. Authors are predominantly from China and the USA, and there are less gender gaps compared to general science research. Our analysis identifies relevant challenges that have become evident in the statistical properties of this scientific field and which might be helpful for the design of improved research policies.
طراحی برای نوآوری اجتماعی بهعنوان رویکردی مؤثر برای مقابله با مسائل پیچیده اجتماعی و ترویج توسعه جامعه پایدار در سراسر جهان ظهور کرده است. این مقاله یافتههای حاصل از یک تحلیل جامع از 14 ابتکار طراحی برای نوآوری اجتماعی را تلفیق میکند که از طریق رویکردها و فرآیندهای مشارکتی متنوع، به مسائل پیچیده اجتماعی ازجمله انسجام اجتماعی، توانمندسازی اقتصادی، پایداری محیطی و سلامت و رفاه میپردازند. این مطالعه از روشهای پژوهش کیفی، ازجمله تحلیل مضمون و تحلیل مطالعات موردی تطبیقی استفاده میکند. دادهها از مستندات پروژه و مقالات مرتبط با آنها جمعآوری شدهاند و درک جامعی از تأثیرات چندوجهی طراحی برای نوآوری اجتماعی در زمینههای مختلف ارائه میدهند. یافتههای کلیدی بر اثربخشی طراحی انسانمحور و سازوکارهای مشارکت جامعه در دستیابی به نتایج پایدار تأکید میکنند. پروژهها، تأثیرات قابلتوجهی مانند تقویت پیوندهای اجتماعی، ارتقاء حفاظت محیطی، بهبود نتایج سلامتی و تقویت اقتصاد محلی از طریق فعالیتهای کارآفرینی را نشان میدهند. این مقاله با ارائه بینشهایی در مورد ظرفیت تحولآفرین طراحی برای نوآوری اجتماعی در مواجهه با چالشهای مختلف اجتماعی، بر اهمیت استراتژیهای تطبیقی، مشارکتهای اجتماعی و مدلهای مقیاسپذیر برای پیشبرد توسعه جامعه پایدار از طریق رویکردهای مبتنی بر طراحی تأکید میکند.
Michele Pezzagno, Anna Richiedei, Barbara Maria Frigione
et al.
The study advocates for a qualitative research design to address knowledge gaps regarding Collective Energy Initiatives (CEIs), utilising evidence-based research and a maximum variation principle. Focused on EU countries, the study employs desk research and surveys to identify stages of CEI development and explore impactful practices. It examines initiatives aligned with EU Directives and broader energy transition efforts, categorising them by complexity. Through surveys, the study identifies drivers and barriers to coalition phenomena, aiming to enhance understanding of energy policies’ impact. This approach responds to the need for comprehensive investigations into energy initiatives’ impediments and facilitators, aligning with recent calls for research in this area.
This paper analyzes the concept of affordable housing and urban planning instruments that incentivize its development, especially in city centers. Considering the shortage of affordable housing in Zagreb, the research aims to identify contemporary urban planning practices that focus on the social function of housing and the role that local urban and housing policies have in ensuring access to it. By comparing the strategic documents for the housing development of the cities of Lyon and Barcelona and models of their implementation in the local urban plans for the areas of city centers and contact brownfield areas, the provisions incentivizing the development of the affordable housing (right of pre-emption, category of subsidized housing, inclusionary zoning, density bonus, and protection of residential use) are singled out. In the context of urban renewal of the historic center of Zagreb and of brownfield redevelopment in the contact zone of the city center, inclusion of the aforementioned provisions in local urban plans is examined, demonstrating the potential that such instrument has for the development of affordable housing in the city center.
Social segregation in cities, spanning racial, residential, and income dimensions, is becoming more diverse and severe. As urban spaces and social relations grow more complex, residents in metropolitan areas experience varying levels of social segregation. If left unaddressed, this could lead to increased crime rates, heightened social tensions, and other serious issues. Effectively quantifying and analyzing the structures within urban spaces and resident interactions is crucial for addressing segregation. Previous studies have mainly focused on surface-level indicators of urban segregation, lacking comprehensive analyses of urban structure and mobility. This limitation fails to capture the full complexity of segregation. To address this gap, we propose a framework named Motif-Enhanced Graph Prototype Learning (MotifGPL),which consists of three key modules: prototype-based graph structure extraction, motif distribution discovery, and urban graph structure reconstruction. Specifically, we use graph structure prototype learning to extract key prototypes from both the urban spatial graph and the origin-destination graph, incorporating key urban attributes such as points of interest, street view images, and flow indices. To enhance interpretability, the motif distribution discovery module matches each prototype with similar motifs, representing simpler graph structures reflecting local patterns. Finally, we use the motif distribution results to guide the reconstruction of the two graphs. This model enables a detailed exploration of urban spatial structures and resident mobility patterns, helping identify and analyze motif patterns that influence urban segregation, guiding the reconstruction of urban graph structures. Experimental results demonstrate that MotifGPL effectively reveals the key motifs affecting urban social segregation and offer robust guidance for mitigating this issue.
With rapid urbanisation and the accompanying increase in traffic density, traffic noise has become a major concern in urban planning. However, traditional grid noise mapping methods have limitations in terms of time consumption, software costs, and a lack of parameter integration interfaces. These limitations hinder their ability to meet the need for iterative updates and rapid performance feedback in the early design stages of street-scale urban planning. Herein, we developed a rapid urban traffic noise mapping technique that leverages generative adversarial networks (GANs) as a surrogate model. This approach enables the rapid assessment of urban traffic noise distribution by using urban elements such as roads and buildings as the input. The mean values for the mean squared error (RMSE) and structural similarity index (SSIM) are 0.3024 dB(A) and 0.8528, respectively, for the validation dataset. The trained model is integrated into Grasshopper as a tool, facilitating the rapid generation of traffic noise maps. This integration allows urban designers and planners, even those without expertise in acoustics, to easily anticipate changes in acoustics impacts caused by design in the early design stages.
Grant Buster, Jordan Cox, Brandon N. Benton
et al.
As urbanization and climate change progress, urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in urban heat can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, estimating the effects of urban heat is an ongoing field of research typically burdened by an imprecise description of the built environment, significant computational cost, and a lack of high-resolution estimates of the impacts of climate change. Here, we present open-source, computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to residential buildings in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50%. The corresponding increase in heating demand complicates this narrative, but total annual energy use from combined heating and cooling with electric heat pumps in the Los Angeles urban climate is shown to benefit from the engineered cooling strategies under both current and future climates.
This study proposes an exploratory urban morphology agent-based model (ABM) to simulate the combined impact of the establishment of hub facilities that urban residents can conveniently access, policies for promoting human interactions around them, and the introduction of trams amidst dispersed habitations in peripheral urban areas. The proposed model offers a new perspective on ways to improve the urban environment. It describes a shift from dispersed habitation to concentrated habitation in a bottom-up manner through behavioural changes at the micro level, which lead to productive human interactions in an urban setting. Specifically, the model experimentally demonstrates a trade-off between increased human interactions caused by the introduction of hub facilities that attract a diverse range of activities, and policies that promote such interactions and development amongst dispersed habitation. Additionally, the model suggests that the direction of urban growth is a consequence of collective action, implying that collaborative efforts can facilitate its improvement.
The shopping mall has emerged as an important component of many cities. While the rapid development of malls and the increasing patronage show their viability and acceptance by the populace, respectively, there is a dearth of studies that examine the impact of its physical and behavioural attributes on attachment. This study examines the effect of physical characteristics, activities, and socioeconomic characteristics on place attachment to the first standalone mall in Ibadan, Nigeria. From a sampling frame of 7, 115 shoppers, quantitative data was obtained from 350 respondents using systematic sampling on April 29, 2017, through a structured questionnaire. The data was analysed using mean, factor analysis, cross-tabulation, correlation, and categorical regression. The findings show that the most prevalent activities are meeting others (α = 0.77); leisure (α = 0.75); and, parties and hanging out (α = 0.70). The important physical attributes are circulation, wayfinding, and aesthetics (α = 0.87); access to mechanical conveyors, mall decoration, and quality materials (α = 0.80); and, ambience (α =0.79). However, the regression results show that the most important factors of attachment are access to mechanical conveyors, mall decoration, and quality materials (β = 0.334); leisure (β = 0.279); purchasing activities (β = 0.236); and, meeting others (β = 0.165). Hence, these factors should be considered in creating new malls in the city. In the context of urbanism, this is key to the social and economic revitalization of cities.
Adheena Kottappurath Aliyar, Mark David Major, Heba O Tannous
et al.
In the late 20th century, Doha’s rapid urbanization and globalization led to the loss of housing and the compact, traditional urban fabric in the old city center. The Qatari government and Msheireb Properties developed Msheireb Downtown Doha to bring urban living back with a contemporary re-interpretation of the traditional urban fabric and modern life conveniences. Our study's primary objective is to investigate the relationship between urban form and the rental value of residential units, identifying factors that might influence rental asking prices. The paper examines morphological characteristics through field surveys and the real-estate variables such as location, floor area, number of bedrooms/bathrooms, and asking price collected from publicly available real estate websites. The findings indicate that the residential units' layout and adjacent streets' morphological characteristics clearly define specific targeted user groups. Larger residential units target Qatari families via more bedrooms/bathrooms and quieter urban settings, emphasizing Islamic cultural values. Smaller units target ex-pat workers (especially Westerners) using open-plan layouts in more lively urban environments of the development. The price per square meter also increases for residential units closer to the Doha Metro station. The study reiterates the success of compact living for improving urban living in other neighborhoods of old Doha.
The present study delves into the decision-making processes pertaining to housing among young professionals residing in urban areas, focusing particularly on their preferences for sustainable housing options. Understanding the factors influencing the housing preferences of this demographic is critical for promoting sustainable urban development, given the ongoing challenges of urbanisation and environmental issues faced by cities. This study aims to explore the decision-making process pertaining to housing among young professionals in Malaysian urban areas and its correlation with sustainability. This study employs a mixed-methods approach, encompassing surveys and in-depth interviews, to analyse the significant factors and decision-making criteria of young professionals residing in urban settings concerning housing. This study primarily focuses on the economic aspect of housing decisions, specifically home affordability, without dismissing the social and environmental factors that may also influence these decisions. The present study contributes to the ongoing discourse on urban sustainability by elucidating the dynamic and evolving preferences of young professionals residing in urban areas. The findings provide valuable insights for politicians, urban planners, and developers who aim to construct housing options that are both sustainable and appealing to this influential demographic group. Ultimately, this contributes to the overall sustainability and resilience of urban communities.
امروزه با رشد روزافزون شهرنشینی و شکلگیری ابعاد جدیدی از رشد شهری در طی چند دهه اخیر، موجب شده است که شهر و شهرسازی معاصر با چالشهای جدیدی روبرو شود. احداث صنایع و استقرار فعالیتهای کارگاهی- صنعتی در قالب شهرکها در نواحی پیراشهری ازجمله پدیدههایی است که پیامدهای گوناگونی در برداشته است. لذا هدف پژوهش حاضر، تحلیل اثرات کالبدی-اقتصادی خوشههای صنعتی-کارگاهی در نواحی پیراشهری چابهار میباشد. این پژوهش به لحاظ هدف کاربردی و از نظر ماهیت و روش توصیفی- تحلیلی است. دادههای موردنیاز تحقیق به روش اسنادی- میدانی (پرسشنامه و مشاهده) گردآوریشده است. به منظور تجزیهوتحلیل اطلاعات از نرمافزار SPSS (آزمون تی) و مدلهای آراس خاکستری و آراس فازی استفاده شد. نتایج آزمون تی تک نمونهای نشان داد در همه گویههای مورد بررسی با توجه به میانگین بالای (3) و سطح معناداری (000/0)، خوشههای صنعتی - کارگاهی بر ابعاد (کالبدی و اقتصادی) نواحی پیراشهری تأثیر بسزایی دارند. نتایج مدل آراس فازی، نشان داد در بعد کالبدی، شاخص دسترسی به خدمات شهری با مقدار وزن 453/0 و در بعد اقتصادی، شاخص شغل با مقدار وزن 426/0، بالاترین وزن را به خود اختصاص دادهاند. درنهایت نتایج تحلیل فضایی مناطق پیراشهری با تأکید بر نقش خوشههای صنعتی-کارگاهی با محوریت توسعه اقتصادی و کالبدی با استفاده از مدل آراس خاکستری نشان داد، روستای زمین، در اولویت قرار دارد.
Sentiment analysis methods are rapidly being adopted by the field of Urban Design and Planning, for the crowdsourced evaluation of urban environments. However, most models used within this domain are able to identify positive or negative sentiment associated with a textual appraisal as a whole, without inferring information about specific urban aspects contained within it, or the sentiment associated with them. While Aspect Based Sentiment Analysis (ABSA) is becoming increasingly popular, most existing ABSA models are trained on non-urban themes such as restaurants, electronics, consumer goods and the like. This body of research develops an ABSA model capable of extracting urban aspects contained within geo-located textual urban appraisals, along with corresponding aspect sentiment classification. We annotate a dataset of 2500 crowdsourced reviews of public parks, and train a Bidirectional Encoder Representations from Transformers (BERT) model with Local Context Focus (LCF) on this data. Our model achieves significant improvement in prediction accuracy on urban reviews, for both Aspect Term Extraction (ATE) and Aspect Sentiment Classification (ASC) tasks. For demonstrative analysis, positive and negative urban aspects across Boston are spatially visualized. We hope that this model is useful for designers and planners for fine-grained urban sentiment evaluation.
Manmeet Singh, Subhasis Ghosh, Harsh Kamath
et al.
Urbanization is advancing rapidly, covering less than 2% of Earth's surface yet profoundly influencing global environments and experiencing disproportionate impacts from extreme weather events. Effective urban management and planning require high-resolution, temporally consistent datasets that capture the complexity of urban growth and dynamics. This study presents NDUI+, a novel global urban dataset addressing critical gaps in urban data continuity and quality. NDUI+ integrates data from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS), VIIRS Nighttime Light, and Landsat 7 NDVI using advanced remote sensing and deep learning techniques. The dataset resolves sensor discontinuity challenges, offering a seamless 30-meter spatial and annual temporal resolution time series from 1999 to the present. NDUI+ demonstrates high precision and granularity, aligning closely with high-resolution satellite data and capturing urban dynamics effectively. The dataset provides valuable insights for urban climate studies, IPCC assessments, and urbanization research, complementing resources like UT-GLOBUS for urban modeling.
Shengjie Hu, Zhenlei Yang, Sergio Andres Galindo Torres
et al.
Urban land growth presents a major sustainability challenge, yet its growth patterns and dynamics remain unclear. We quantified urban land evolution by analyzing its statistical distribution in 14 regions and countries over 29 years. The results show a converging temporal trend in urban land expansion from sub-country to global scales, characterized by a coherent shift of urban area distributions from initial power law to exponential distributions, with the consequences of reduced system stability and resilience, and increased exposure of urban populations to extreme heat and air pollution. These changes are attributed to the increased influence from external economies of scale associated with globalization and are predicted to intensify in the future. The findings will advance urban science and direct current land urbanization practices toward sustainable development, especially in developing regions and medium-size cities.