Search Results (160)

This study investigates strategies for urban-scale renewable energy integration through a photovoltaic-centric approach, with a case study of a district in Barcelona. The methodology integrates spatial and morphological data using a geographic information system (GIS)-based and clustering framework to address challenges of CO₂ emissions, air pollution, and energy inefficiency. Rooftop availability and photovoltaic (PV) design constraints are analysed under current urban regulations. The spatial analysis incorporates building geometry and solar exposure, while an evolutionary optimisation algorithm in Grasshopper refines shading analysis, energy yield, and financial performance. Clustering methods (K-means and 3D proximity) group PV panels by solar irradiance uniformity and spatial coherence to enhance system efficiency. Eight PV deployment scenarios are evaluated, incorporating submodule integrated converter technology under a solar power purchase agreement model. Results show distinct trade-offs among PV scenarios. The standard fixed tilted (31.5° tilt, south-facing) scenario offers a top environmental and performance ratio (PR) = 66.81% but limited financial returns. In contrast, large- and huge-sized modules offer peak financial returns, aligning with private-sector priorities but with moderate energy efficiency. Medium- and large-size scenarios provide balanced outcomes, while a small module and its optimised rotated version scenarios maximise energy output yet suffer from high capital costs. A hybrid strategy combining standard fixed tilted with medium and large modules balances environmental and economic goals. The district’s morphology supports “solar neighbourhoods” and demonstrates how multi-scenario evaluation can guide resilient PV planning in Mediterranean cities. Full article

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article

Smart city research often emphasises technology while neglecting how governance structures and resources influence outcomes. This study compares Tier 1 (Sydney, Melbourne, Brisbane, Adelaide) and Tier 2 (Geelong, Newcastle, Hobart, Sunshine Coast) Australian cities to evaluate how urban scale, economic capacity, governance complexity, and local priorities influence smart-enabled resilience. We analysed 22 official strategy documents using a two-phase qualitative approach: profiling each city and then synthesising patterns across technological integration, community engagement, resilience objectives and funding models. Tier 1 cities leverage extensive revenues and sophisticated infrastructure to implement ambitious initiatives such as digital twins and AI-driven services, but they encounter multi-agency delays and may overlook neighbourhood needs. Tier 2 cities deploy agile, low-cost solutions—sensor-based lighting and free public Wi-Fi—that deliver swift benefits but struggle to scale without sustained support. Across the eight cases, we identified four governance archetypes and six recurring implementation barriers—data silos, funding discontinuity, skills shortages, privacy concerns, evaluation gaps, and policy changes—which collectively influence smart-enabled resilience. The results indicate that aligning smart technologies with governance tiers, fiscal capacity, and demographic contexts is essential for achieving equitable and sustainable outcomes. We recommend tier-specific funding, mandatory co-design, and intergovernmental knowledge exchange to enable smaller cities to function as innovation labs while directing metropolitan centres towards inclusive, system-wide transformation. Full article

Rapid urbanisation in Sub-Saharan Africa demands innovative land management strategies that promote sustainable, inclusive, and resilient urban development. This study investigates the potential of land readjustment (LR) to foster neighbourhood-scale social–ecological urban resilience (SEUR) through a case study of the Nunga LR project in Kigali, Rwanda. Grounded in the social–ecological system (SES) theory and operationalised through the social–ecological land readjustment model for resilient neighbourhoods, the research evaluates LR practices against an integrated benchmark framework combining LR aspects, neighbourhood design standards, and resilience attributes. The study uses secondary data, project shapefiles, and key informant interviews to assess how Rwanda’s emerging LR model contributes to resilient neighbourhood development. Findings demonstrate strong community mobilisation and adaptive governance capacity. However, critical resilience dimensions—including modularity, green infrastructure integration, land-use diversity, and adaptive feedback mechanisms—were only partially operationalised. Consequently, while LR improved spatial formalisation and basic infrastructure provision, it fell short of creating a truly resilient, multifunctional neighbourhood ecosystem. These findings highlight the need to reframe LR from a purely technical land management tool into a systemic resilience-building mechanism. Policy recommendations include mandating green/blue infrastructure in LR plans, establishing innovative financing mechanisms, institutionalising adaptive monitoring, strengthening affordability safeguards, and promoting multifunctional spatial layouts. The study contributes to urban resilience and land governance scholarship by offering a context-sensitive, empirically tested model for integrating SEUR principles into LR practice in rapidly urbanising African cities. Future research should pursue longitudinal analyses and dynamics modelling of land readjustment impacts to deepen understanding of urban resilience pathways in the Global South. Full article

This study investigates the relationship between neighbourhood walkability, recreational walking, and physical activity and well-being outcomes in Bangkok, Thailand. A cross-sectional survey was conducted with 881 residents from 50 districts in Bangkok. The Neighbourhood Environment Walkability Scale-Abbreviated (NEWS-A) was employed to assess neighbourhood walkability and its association with recreational walking behaviour. The Global Physical Activity Questionnaire (GPAQ) and WHO-5 Well-Being Index were used to explore the links between recreational walking, physical activity, and well-being. The findings reveal that neighbourhood environment characteristics significantly influence recreational walking behaviour, with high-rise and planned neighbourhoods showing higher odds of recreational walking compared to unplanned neighbourhoods. Additionally, recreational walking was positively associated with both achieving sufficient physical activity and better well-being scores. These findings suggest that neighbourhood-level interventions aimed at promoting recreational walking could be effective strategies for encouraging physical activity and enhancing well-being in urban residents. The study recommends that targeted, neighbourhood-level interventions focused on creating supportive walking environments may be more effective in promoting health outcomes compared to broader city-wide urban design strategies. Our results also provide evidence-based support for shifting from tourism-centric to neighbourhood-focused walking infrastructure development in Bangkok. Full article

A smoothed M-estimator is derived from Hampel’s three-part redescending estimator for location and scale. The estimator is shown to be weakly continuous and Fréchet differentiable in the neighbourhood of the normal distribution. Asymptotic assessment is conducted at asymmetric contaminating distributions, where smoothing is shown to improve variance and change-of-variance sensitivity. Other robust metrics compared are largely unchanged, and therefore, the smoothed functions represent an improvement for asymmetric contamination near the rejection point with little downside. Full article

Domestic workers represent an essential yet invisible workforce within urban economies, especially in developing countries. Predominantly women in low-income, single-headed households, they often work informally and rely on buses or minibus taxis for suburb-to-suburb travel. Despite their contributions, their transport needs are overlooked in traditional planning, which prioritises CBD-centric routes over the suburb-to-suburb journeys that define their invisible commute. The purpose of this study is to examine the transport mobility patterns of live-out domestic workers in urban areas, focusing on Centurion, one of the affluent neighbourhoods in the Metropolitan City of Tshwane, South Africa. To assess the transport challenges faced by domestic workers during their commutes, a Likert scale was utilised. The data were analysed using descriptive statistics facilitated by the SPSS software package to identify key trends and patterns in the responses. The key challenges of domestic workers are high transport costs, lack of access to affordable transport modes like rail and long commute times. Minibus taxi is the most commonly used mode accommodating both standard and non-standard working hours. The study also found that most of the domestic workers working in Centurion are migrant workers. To reduce the need to travel to work, mixed-income developments, and inclusionary housing are some of the concepts that can be adopted in affluent suburbs like Centurion. These two concepts not only address the need to travel to work but also spatial inequality and promotion of social integration whereby affordable housing are created within higher income areas. Full article

Gated communities have been widely examined as a contemporary urban phenomenon, yet their emergence in the Middle East reflects broader socioeconomic and cultural transformations rather than a direct continuation of historical spatial practices. Historically, Arabian cities featured compact, human-scaled urban layouts with walled perimeters, narrow streets, and shared courtyards, fostering social cohesion, security, and communal interaction. These spatial characteristics evolved organically, balancing privacy with integration to meet communal needs. This article examines the historical evolution of enclosed neighbourhoods in Arabian cities and their sociospatial connections to modern gated communities, assessing their impact on urban sustainability. By employing historical inquiry, this study investigates how traditional principles, such as privacy, community resilience, and spatial hierarchy, have been inherited, reinterpreted, or redefined in contemporary developments. Findings indicate that historical Arabian cities reinforced internal cohesion and self-governance, whereas modern gated communities introduce deliberate spatial and social segregation, disrupting urban connectivity and weakening social sustainability. The study highlights critical implications for urban planning, suggesting that integrating historical spatial principles can create inclusive and adaptable contemporary developments. Full article

Infrastructure and amenities have an evident effect on differentiated urban structures and house prices. However, few studies have taken into account the spatial heterogeneity of large-scale urban areas. Regarding this issue, the present study proposes a novel spatial framework to quantify the impacts of built environment factors on the housing market. We aim to answer: how does a specific factor impact house prices across different spatially autocorrelated neighbourhood clusters? The city of Shanghai, the economic centre of China, is examined through the transaction data from the China Real-estate Information Center (CRIC) are analysed. Firstly, spatially autocorrelation clusters were explored to identify high/low housing prices in concentrated areas in Shanghai. Secondly, using the development-scale house prices as the dependent variable, we employed ordinary least squares (OLS) linear regression and geographically weighted regression (GWR) models to examine the impact of built environment facilities on the house prices across these spatial autocorrelation regions and Shanghai more generally. The results suggest the following: (1) There are significant spatially autocorrelated clusters across Shanghai, with high-value clusters concentrated in the city core and low value concentrated in the suburban fringes; (2) Across Shanghai and its spatially autocorrelated clusters, transportation accessibility and service amenities factors can affect house prices quite differently, especially when focusing on the city centre and the suburban areas. Our results highlight the importance of optimising the city’s polycentric structural framework to foster a more balanced regional development. Differentiated approaches to the distribution of public service facilities should be adopted to address the diverse needs of residents across various regions. Full article

This paper addresses the need to decarbonize built environments by altering community planning and home design. By employing principles of Circular Economy at the community and dwelling levels, the paper argues that having flexible design strategies can contribute to the reduction of the carbon footprint of urban areas by minimizing the need for demolition and, as a result, material waste. Currently, depending on location and cultural and economic conditions, large-scale developments might take many years to approve and construct. Moreover, when changes are to be introduced to an initially approved masterplan, the process of obtaining municipal planning approval can be lengthy. By using a case study-based methodology for community and home design, this research argues that, given the rapidly emerging new social challenges, neighbourhoods can be designed to adapt and accommodate changes they may encounter throughout their development and in subsequent years. The proposed approval procedure that this research introduces provides a step-by-step approach to planning that can be readily adjusted based on market demand and newly developing economic and social conditions. To demonstrate his research in partnership with a private developer and the municipality, the author utilized these techniques in the design of a community in La Prairie, a town near Montreal, in Quebec, Canada. The paper also introduces the concepts of adaptability and circularity at the dwelling unit level to minimize demolition and waste. The energy efficient design incorporates demountable partitions and specialized conduits for the installation and improvement of utility lines. By investigating the macro and micro levels, the author concludes that changes to the current system, while considering the needs of key stakeholders, stand to reduce demolition and waste. Full article

The degrowth movement is gradually gaining recognition within North American urban planning, but its influence and application remain limited. Most degrowth-oriented initiatives have remained at a small scale, mostly pertaining to communities and neighbourhoods. This study explores whether it is possible to incorporate degrowth principles into larger planning institutions and policies. The paper reviews existing studies on zoning policies and the degrowth movement, employing a qualitative research approach, and utilising secondary data analysis through document and critical discourse analysis. Through this exploration, this study aims to contribute to upscaling and institutionalising degrowth principles and to provide a clear outlook on the movement and its characteristics. Drawing on 32 key sources on zoning and degrowth, alongside two policy documents and a case study of Texas, this study applies coding, content analysis, and GIS mapping to explore the intersections of zoning regulations and degrowth principles in urban planning. The six key principles found to be essential to the degrowth movement—decoupling economics, fostering stronger communities, self-sufficiency, equity, political autonomy/collaboration, and ecological/environmental protection—were analysed in the context of the Texas municipal code for zoning to see whether current zoning ordinances follow the degrowth ideology. The findings reveal that while aspects of degrowth, such as affordable housing initiatives and environmental sensitivity, are present in Texas’ zoning regulations, these remain minimal and often constrained by the overarching focus on economic profitability. To integrate degrowth principles more effectively, significant reforms are required, including disengaging zoning ideologies from economic growth, fostering autonomy and self-sufficiency, and reimagining zoning practices to prioritise equity, ecology, and collective resource management. Full article

This article presents STEAM Architecture, a STEAM project for all educational levels, from pre-school to high school, a project that links the learning of subjects with architectural concepts, thus trying to generate meaningful learning in students. The project is the result of an ERASMUS+ project (DART4City (2020-1-ES01-KA227-SCH-095545) Empowering Arts and creativity for the cities of tomorrow) in which a methodology was developed to extract STEAM projects from European curricula. This methodology has two variants: “forward” and “backward”. The “forward” variant analyzes the curriculum and found the areas of opportunity with more connections among the contents while the “backward” methodology proposes a specific theme to look for the connections. The “backward” variant allows finding a topic that may be of social interest. This is the variant we use in this article. We explore the “backward” methodology in order to find an area of opportunity in society, in particular related to architecture. A questionnaire is distributed to different sectors of people in society to find out whether the learning of different architectural concepts at pre-university levels is interesting. The results of these tests show the potential of a STEAM project related to architecture. The design of the STEAM architecture project shows how the subdivision is carried out from an educational point of view, and also from an architectural point of view. Both worlds agree on dividing space into micro-, meso- and macro-space depending on the scale of what is being treated. For this reason, the STEAM architecture project is subdivided into Room, House, Neighbourhood and City for each educational level: pre-school, primary school and high school (which is 4 years of secondary school (ESO) and the last 2 years of high school). At the end of the article, we show the different workshops that were held in order to analyze the goodness of the proposal. Full article

The traditional A* algorithm faces the challenges of low search efficiency and large node extension range in the field of path planning. These directly restrict the overall performance of the algorithm. In this study, we aimed to improve the search efficiency and path planning quality of the A* algorithm in complex and large-scale environments through a series of optimisation measures, including the innovation of weight design, flexible adjustment of the search neighbourhood, improvement of the heuristic function, and optimisation of the node selection strategy. Specifically, this study innovatively introduces the local obstacle rate as the core index of weight design, and it dynamically adjusts the weights according to the change of the obstacle rate during the node movement process, which effectively reduces the search space and significantly improves the search speed. At the same time, according to the real-time change of the local obstacle rate, this study dynamically adjusts the range of the search neighbourhood, so that the algorithm can choose the optimal search strategy according to different environmental information. In terms of the improvement of the heuristic function, this study adopted the diagonal distance as the benchmark for cost estimation, and it innovatively introduces the angle coefficient to reflect the complexity of path turning, thus providing the algorithm with a more accurate guidance for the search direction. In addition, this study optimises the node selection method by drawing on the idea of simulated annealing, which eliminates the need to calculate and compare all possible surrogate values during the node selection process, thus significantly reducing the running time of the algorithm. The results of the simulation experiments fully verify the effectiveness and practicality of the improved algorithm. Compared with the traditional A* algorithm, the improved algorithm achieved significant optimisation in terms of the average running time, the number of expansion nodes, and the path length, with the average running time shortened by 84%, the number of expansion nodes reduced by 94%, and the path length also shortened by 2.3%. Full article

Understanding energy demand and supply flow at a large urban scale is an essential step for urban designers, planners and policymakers in investigating how buildings within an existing urban context could be designed as a whole to support the future sustainable built environment. The contemporary approach is to model energy use activities at various building and urban scales. This, albeit a practical approach, poses significant challenges in acquiring good quality data concerning buildings and their interactions at an urban scale at an affordable price. This paper presents a streamlined benchmarking methodology with a parametric modelling workflow to complement the mainstream urban building energy modelling (UBEM) approach. The proposed building energy benchmarking workflow integrates multiple databases concerning building energy consumption, energy generation and underlying grid infrastructure. Parametric modelling serves as a tool for integrating databases through the underlying sortable geometric characteristics. This is envisaged to afford stockholders, such as policymakers or urban planners, greater flexibility to investigate energy demand and supply scenarios at an urban neighbourhood scale and further explore potential applications. Using the proposed workflow, we look at renewable solar energy to experiment with offsetting urban building energy consumption through reconfiguring existing electricity microgrids in the Sheffield city centre. The result of this study demonstrates how the presented urban building energy benchmarking (UBEB) workflow would afford capabilities and flexibility to support stakeholders, e.g., urban planners, policymakers, and end-users, to better understand existing barriers and explore actionable opportunities via re-configurable electricity microgrids. Full article

The concept of segregation analyses the unequal distribution of social groups between neighbourhoods. It rests on two assumptions: that of homogeneous neighbourhoods and of a market liberal housing system. Both assumptions are applicable the context of American cities, but they display severe limitations when applied to the European context. Vienna’s housing market is particularly highly segmented, not only throughout the city as a whole but also within neighbourhoods. In the densely built-up area, residential buildings of different segments with different underlying rent regulations and entry barriers can be found side by side. Therefore, buildings are expected to show varying tenant and owner structures, which undermines the idea of a homogeneous neighbourhood. Against this background, we analyse at the micro scale small neighbourhoods defined by 100 m grid cells in a case study of two inner-city Viennese districts (districts 6 and 7) characterised by a particularly vivid housing-transformation and commodification dynamic. Using a novel and fine-grained dataset combining building information with the socio-economic data of households, we investigate the patterns and dynamics of income inequality and income segregation, as well as the relationship between housing market segments and socio-economic patterns. As data comprise two cross-sections for the years 2011 and 2020/21, changes in the neighbourhoods during the house-price boom period are also considered. This leads us to ask the question: How do housing market segmentation and its related changes affect income inequality and segregation at the micro scale? Our analysis delivers two main results: Firstly, we show the existence of marked social variation and related dynamics at the micro scale, even within a small urban area. Secondly, we show that the spatial distribution of housing market segments has a strong impact on income inequality in the neighbourhood. Full article