Urban Sci., Volume 10, Issue 4 (April 2026) – 44 articles

The rapid inspection of urban road hazards, such as subsurface voids and pipeline damage, demands high efficiency and precision in detection technology. Conventional Ground Penetrating Radar (GPR) systems often face limitations in urban environments, including slow survey speeds, poor channel scalability, and the trade-off between shallow resolution and deep penetration. The proposed system integrates a dual-band antenna array (200 MHz and 400 MHz) to resolve the classical resolution–penetration trade-off, simultaneously capturing high-resolution shallow data and achieving deep subsurface penetration in a single pass. To overcome the sampling rate bottleneck inherent in low-cost microcontrollers, a custom Time-Division Step Multiplexing (TDSM) protocol extends the equivalent sampling period to 0.38 µs across 24 parallel channels while maintaining a 200 kHz pulse repetition rate—enabling real-time data streaming at vehicle speeds up to 70 km/h with 5 cm trace spacing. This capability directly addresses the critical challenge of traffic disruption on urban arterials caused by conventional slow-speed GPR surveys. Complementing this, a master-slave FPGA-MCU hierarchical architecture provides seamless channel scalability from 24 to 36 channels, adapting to diverse swath width requirements without hardware redesign. Laboratory physics model experiments demonstrate a penetration depth exceeding 3 m after convolutional sparse fusion of the dual-band data, covering the typical burial depth of urban utilities. This study provides a deployable high-resolution underground detection solution for rapid urban infrastructure surveys and emergency disease detection by breaking the traditional constraints of channel number, sampling rate, and detection speed, significantly reducing interference with urban main traffic. Full article

Designing sustainable pedestrian infrastructure in hyper-arid cultural landscapes requires balancing visitor experience, heritage protection, and environmental constraints. This study develops a statistically grounded model for planning sustainable walking trails in Al-Ula, Saudi Arabia, using multi-spectral remote sensing data integrated with expert-based evaluation. A GIS-based Multi-Criteria Decision-Making (MCDM) framework was applied to assess topographic slope, vegetation cover (NDVI), built-up density (NDBI), Land Surface Temperature (LST), and solar exposure. Indicator weights were validated through a three-round Delphi survey involving fifteen experts. The results indicate strong consensus among experts, identifying LST (21%) and slope (20%) as the most influential determinants of trail suitability in desert environments. These findings highlight the critical role of thermal stress in shaping safe and sustainable pedestrian mobility in hot climates. The optimized 44.5 km trail network, classified into three difficulty levels, improves energetic efficiency by reducing caloric expenditure by 24% compared to conventional routing. In addition, the proposed network has the potential to reduce carbon emissions associated with heritage-related travel by approximately 75% through modal shift from vehicles to walking. The framework provides a practical decision-support tool for planners seeking to develop low-carbon, climate-responsive tourism infrastructure aligned with the objectives of Saudi Arabia’s Vision 2030. Full article

This systematic review examines the effect of pre-incident information on public preparedness prior to an emergency or disaster. Preparing members of the public for adverse events can improve self-sufficiency and improve health outcomes, particularly during periods when emergency responders are not immediately available. Twenty-three studies were identified, addressing both natural and human-influenced events. All the studies investigated pre-incident training targeting members of the public rather than specialist responders. The synthesis considered training content, delivery approaches and evaluation methods. The studies included preparation, personal safety, triage, first aid and evacuation in scenarios involving terrorism, fire, earthquake, flood and CBRN events. Pre-incident education generally improves knowledge and intention to act, with higher-intensity and interactive training yielding greater engagement and response. Due to the difficulty of simulating emergencies and disasters, several studies used self-reporting and hypothetical testing, while others attempted to create real-life scenarios. The immediate effects of pre-incident education were generally positive, although many studies tested outcomes theoretically or within a classroom environment. It was also noted that few studies considered retention over the medium to long term; this is a concern as temporal decay may reduce preparedness. This review provides a basis for continued development of public-facing pre-incident education to increase resilience to both terrorist attacks and natural disasters. Full article

Port cities represent an interdependent system in which port and urban activities overlap and develop. While ports serve as the gateway for the city, expanding market reach and attracting investments, cities provide the necessary labor and services required for the operation of the ports. However, the mutual relationship between ports and cities is threatened by conflicts such as urban sprawl, which leads to friction by taking the space needed for storing containers at ports. Similarly, ports generate high noise and air pollution, threatening the quality of life in urban centers. Therefore, implementing best practices to manage the port–city dichotomy is essential to ensure the coexistence of the port and city. This study re-examined the port–city relationship in the framework of urban planning to guide redevelopment decisions within the Piraeus city port in Greece. Data were collected through a mixed-methods approach involving secondary research and roundtable discussions. The findings showed that a key design parameter of the Piraeus city port is the development and exploitation of the city’s relationship with water, from a functional, spatial, and aesthetic point of view. Furthermore, a guide was developed to facilitate the redevelopment of the city port and improve decision-making. The recommendations also emphasize the integration of the port city into a global economic forum and highlight its dynamism, ensuring mutual benefits for the city and port. Full article

This paper presents a comparative analysis of unconventional roundabouts, commonly referred to as third-generation roundabouts, based on case studies from the United States and Europe, specifically Croatia and Italy. These intersection designs deviate from traditional circular geometries to overcome limitations in safety, capacity, and spatial integration, especially in constrained or high-demand environments. The study focuses on three major typologies: raindrop, turbo, and two-geometry roundabouts (TGRs), examining their geometric characteristics, operational principles, and context-specific implementations. Based on real-world examples and qualitative assessments, each national section investigates design rationale and performance considerations in relation to local traffic dynamics. The paper contributes to the understanding of adaptive and context-sensitive intersection design, offering a conceptual framework for comparing unconventional roundabout typologies across different regulatory environments. The comparative analysis reveals that each typology responds to specific operational and spatial constraints rather than representing a universally optimal solution. In particular, raindrop and dog-bone roundabouts are most effective in interchange contexts, turbo roundabouts enhance safety and capacity in regulated multilane environments, while TGRs provide greater adaptability in constrained and irregular urban settings. These findings highlight the importance of context-dependent design strategies and support the need for flexible and context-sensitive evaluation frameworks. Full article

Cities are increasingly expected to achieve environmentally sustainable outcomes while simultaneously adapting to rapid technological transformation and growing governance complexity. However, sustainability performance in urban systems cannot be explained by technological infrastructure alone. Institutional capacity and algorithmic governance capabilities play a critical role in shaping coherent environmental policy implementation and green urban performance, particularly in transition city contexts. This study proposes the ISAG-G Governance Framework (Institutional and Smart Algorithmic Governance for Green Performance), a governance-oriented analytical framework designed to assess green urban governance capacity. The framework integrates four governance dimensions: institutional governance capacity, algorithmic and digital governance enablement, green urban governance performance, and citizen sustainability interaction. Methodologically, the study develops a composite governance index based on a structured indicator system. Indicator weights are determined using the Best–Worst Method (BWM) through expert consultation, while Min–Max normalization and weighted aggregation are applied to construct the composite index. The framework is empirically applied through a comparative analysis of five transition municipalities (evidence from Armenia) representing different levels of administrative capacity and urban development. The findings reveal distinct governance profiles across municipalities and highlight the importance of institutional coherence and algorithmic governance capacity in shaping green urban performance. By moving beyond infrastructure-centric approaches, the proposed framework provides both an analytical and policy-oriented tool for evaluating urban sustainability governance in transition city contexts. Full article

Urban heritage structures are most commonly understood as memorial artifacts, tourism assets, or redevelopment resources. While this common view acknowledges cultural and economic value, it overlooks a deeper function of heritage within the long evolution of human settlements. This paper advances a counter thesis: in addition to its historic contingencies and power relationships—which are real, but only part of the picture—urban heritage embodies valuable but often hidden intelligence that is highly relevant to contemporary urban challenges. Specifically, heritage environments encode useful structured information about spatial configurations that have gained adaptive value over time in a process known as stigmergy. Drawing on complexity science, network theory, the mathematics of symmetry, and theories of extended cognition, the paper argues that enduring urban forms persist not only for symbolic or historical reasons, but because they embed structural properties conducive to resilience, legibility, social interaction, climatic adaptation, and human well-being. Recurring characteristics include fine-grained network connectivity, fractal scaling hierarchies, organized symmetry, articulated thresholds, and biophilic integration. Evidence from environmental psychology, public health, and urban morphology suggests that such properties correlate with reduced stress, increased walkability, stronger social capital, and improved ecological performance. The paper proposes a methodological framework—what we call the Adaptive Patterns Model—for identifying, evaluating, and translating this embedded intelligence into contemporary regeneration practice. The Model is presented as a four-phase, conceptually synthesized framework—integrating insights from complexity science and stigmergy, urban morphological analysis, and pattern-language methodology—comprising documentation, pattern extraction, encoding, and performance correlation. It concludes by challenging a still-prevalent assumption that contemporary conditions invalidate accumulated spatial knowledge. Instead, urban heritage is understood as adaptive capital within an ongoing evolutionary process, offering a structurally grounded foundation for resilient urban transformation. Full article

Unauthorized occupation of parking spaces designated for individuals with disabilities remains a persistent challenge in urban environments, limiting accessibility and inclusive mobility. This paper proposes an integrated UAV-assisted enforcement framework that combines drone-based imaging, onboard license plate recognition (LPR), IoT connectivity, and a staged optimization strategy for energy-aware surveillance. The framework employs a two-phase approach: first, it derives energy-efficient UAV activation patterns via sleep–active scheduling, followed by coverage maximization under energy constraints. The inherently multi-objective problem—balancing energy consumption, coverage, and redundancy—is addressed via a weighted-aggregation formulation, enabling efficient optimization with classical metaheuristic algorithms. Seven algorithms—Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Differential Evolution (DE), Artificial Bee Colony (ABC), and a Greedy baseline—are implemented in both conventional and staged variants to enable comprehensive evaluation. Experimental results demonstrate 32–45% reductions in energy consumption, over 95% coverage effectiveness, and 50–60% faster convergence compared to single-phase approaches, with all improvements statistically significant (p < 0.001). The proposed framework provides a scalable, practically deployable solution for intelligent enforcement of disability parking regulations while also enabling energy-efficient UAV coordination in smart urban monitoring systems. Full article

Urban shrinkage, driven by demographic and socioeconomic changes, has become a pressing issue across Europe, particularly in small peripheral towns and semi-urban settlements that have historically relied on a single industry or company. This study investigates the demographic and socioeconomic factors contributing to the multi-dimensional decline, encompassing population loss, economic contraction, and deteriorating socioeconomic conditions in Latvian mono-towns, thereby filling a void in empirical research on urban development in post-socialist contexts. Principal component analysis (PCA) was applied to a set of key demographic and socioeconomic indicators derived from census and administrative data to identify the principal dimensions that drive urban shrinkage. The analysis reveals three principal components explaining 87% of the variance: socioeconomic vitality (57.1%), population change and peripherality (17.2%), and aging society dynamics (12.6%). The results contribute to a nuanced understanding of how mono-functional urban contexts shape the intensity and character of shrinkage. These results establish a basis for specific policy measures designed to promote resilience in small-settlement settings and contribute to the understanding of spatial planning and regional development approaches in the post-socialist urban transition context. This research underscores the need for context-specific approaches to address the multifaceted challenges of urban shrinkage. Full article

Urban rooftop photovoltaic systems represent a substantial yet still underutilized renewable energy resource, particularly in high-density residential environments. Accurate large-scale assessment of rooftop solar potential, however, remains challenging due to the complex geometry of urban morphology and the limited availability of high-resolution geospatial data. This study presents a large-scale methodological framework for estimating the theoretical photovoltaic potential of urban rooftop spaces using Unmanned Aerial System (UAS)-based digital photogrammetry and GIS-based spatial analysis. The approach integrates centimeter-resolution Digital Surface Models (DSMs) and orthophotos derived from fixed-wing UAS surveys with detailed rooftop vectorization and solar radiation modeling implemented in a GIS environment. The methodology accounts for rooftop geometry, surface orientation, slope, shading effects, and rooftop-mounted obstacles. The methodology consists of data collection of high-resolution RGB imagery suitable for detailed three-dimensional reconstruction. The images are captured with a UAS equipped with a S.O.D.A. 3D photogrammetric camera, creating a dense, georeferenced three-dimensional point cloud based on UAS imagery. Based on the point cloud, a high-resolution Digital Surface Model (DSM) was produced. Rooftop boundaries and rooftop-mounted structures were digitized on the basis of an orthophoto created from UAS imagery. The analysis workflow consists of solar modeling using ArcGIS Pro, including calculating the solar radiation. The next methodological step is to filter low radiation rooftops, steep slopes, and northern-oriented rooftops. Finally, we calculate the potential electricity production. The framework was applied to high-density residential districts in Sofia, Bulgaria, dominated by prefabricated panel buildings with predominantly flat rooftops. Drone applications in such studies are typically restricted to modeling individual roofs, which severely limits their scalability for district-wide evaluations. To overcome this, the study employs a specialized fixed-wing UAS uniquely certified for legal operations over densely populated urban environments. This platform rapidly maps large territories, ensuring consistent lighting and shading conditions that significantly enhance the accuracy of subsequent rooftop digitization. Furthermore, the resulting centimeter-level precision enables the exact vectorization of micro-rooftop obstacles. Capturing these intricate details is a critical innovation that effectively prevents the overestimation of solar energy potential commonly observed in conventional large-scale models. Solar radiation was modeled at the pixel level for a full annual cycle and filtered using photovoltaic suitability criteria, including minimum annual radiation thresholds, slope, and aspect constraints. Theoretical electricity production was subsequently estimated using zonal statistics and system performance parameters representative of contemporary photovoltaic installations. The results indicate a total theoretical annual electricity potential of approximately 76.7 GWh for the analyzed rooftop spaces, with an average production of about 34 MWh per rooftop and pronounced spatial variability driven by rooftop geometry and exposure conditions. The findings demonstrate the significant renewable energy potential embedded in existing urban rooftop infrastructure and highlight the applicability of UAS-based photogrammetry for high-resolution, large-area solar potential assessments. The proposed framework provides actionable information for urban energy planning, municipal solar cadaster development, and the strategic integration of photovoltaic systems into dense urban environments, particularly in regions lacking open-access high-resolution geospatial datasets. Full article

Urban regeneration has traditionally focused on large-scale developments that aim at increasing the livability and vitality of disadvantaged areas. Alternative views of urban regeneration have emerged to challenge such a structural approach. These novel ideas reflect contextual changes in progressive and innovative Western countries that embrace the culture of experimentation, prefer sharing to ownership, and emphasize participation and inclusion as fundamental aspects of public governance. This article elaborates the idea of lean urban regeneration in the progressive welfare society context, with a special view of citizen and stakeholder involvement through inclusion, sharing, and co-creation. Empirical research utilizes mini cases of the largest cities in the growth triangle of Finland. This article identifies the manifestations of lean urban regeneration and discusses its preconditions and ability to tackle urban development challenges. The results emphasize the framing nature of inclusion, the underutilization of sharing, and the key role of co-creation in lean urban regeneration. A particular potential of lean interventions is based on co-creation as the core of multimodal or hybrid regenerative projects that are firmly anchored on economic inclusion. By utilizing the input of residents, entrepreneurs, and other local stakeholders, it is possible to open up a path to integrated high-leverage activities with a potential to alleviate structural urban problems. Full article

We estimate the causal impact of a high-frequency bus upgrade on neighborhood labor-market outcomes using the August 2019 launch of Pace’s Pulse Milwaukee Line in the Chicago region. We use public data-Pace GTFS schedules (stops/headways), ACS tract-level socioeconomic measures, and LEHD/LODES workplace counts. Using this database, we build a tract-level panel combining annual workplace employment outcomes with multi-year household outcomes, and then we implement a transparent difference-in-differences design that compares tracts within 0.5 miles of new Pulse stops to a 0.5–2 mile control ring before and after service begins. We find no detectable short-run effects, but we estimate a positive and economically sizable increase in workplace jobs per resident ($0.066;\approx 14\%$ of the pre-treatment mean). Under conventional tract-clustered inference, this estimate is marginal (p = 0.073); thus, we interpret it as suggestive rather than definitive evidence. Our results are highly robust. Event-study estimates show flat pre-trends and post-treatment gains persisting into years +1 and +2; our placebo corridors yield null effects; and our buffer-width tests show monotonic strengthening. Finally, our population-weighted estimates remain positive, though smaller. To conclude, the results suggest that frequency improvements can reallocate jobs toward upgraded corridors even when resident employment and incomes do not move immediately. Our results may highlight a likely sequencing of impacts and the potential need for complementary land-use and workforce policies to translate accessibility gains into household-level benefits. Full article

Casablanca, Morocco’s most populous and economically dynamic metropolis, is undergoing rapid and unregulated expansion, leading to accelerated agricultural land artificialization, landscape fragmentation, and growing socio-environmental vulnerability in peri-urban territories. This study investigates the spatio-temporal dynamics of urban expansion within a 40 km buffer around the city, using multi-temporal Landsat imagery (2015–2025), a GIS-based framework, and supervised classification. Four land-cover classes were extracted (urban, vegetation, forest and water) enabling a diachronic comparison of land transformation processes. Two spatial indicators were mobilized to quantify urban dynamics: the Average Urban Expansion Rate (AUER) and the Urban Expansion Intensity Index (UEII). Results reveal that urban areas expanded by up to 387.9% in some communes, with 15 exceeding an AUER of 25% and 17 falling within the “very high development” category based on UEII thresholds. Land artificialization was most intense along southern and southeastern peripheries, notably Deroua, Tit Mellil, Had Soualem, and Sidi Moussa Ben Ali, resulting in severe fragmentation of agricultural land. The classification of communes into four profiles (fast, slow, consolidated, and stable) highlights varying degrees of territorial vulnerability. By integrating demographic trends (2014–2024), the study exposes mismatches between population growth and land consumption, underscoring the urgent need for integrated spatial diagnostics and governance reforms toward sustainable peri-urban land management. Full article

Kuwait faces mounting challenges in municipal solid waste (MSW) management alongside continued dependence on fossil-fuel-based electricity generation. Per capita waste generation in Kuwait is approximately 1.7 kg/person/day, exceeding the global average of 0.74 kg/person/day, indicating substantial potential for resource recovery and energy conversion. This study evaluates public perceptions of waste-to-energy (WtE) in Kuwait’s residential sector and estimates the potential electricity that could be generated from household waste. A structured online household survey (n = 470) was administered to assess socio-demographic characteristics and key perception constructs, including awareness, perceived risks, perceived benefits, and overall attitudes toward WtE. In parallel, a quantitative estimation was undertaken using literature-based parameters for monthly per capita waste generation and electricity consumption to derive household-level waste quantities, corresponding energy potential, and generated-to-consumed energy ratios. Survey findings indicate generally favourable attitudes toward WtE and recognition of its potential to reduce landfill dependence and contribute to electricity supply, although respondents showed stronger support for locating WtE facilities away from residential neighbourhoods. Perceived risks—particularly related to health and environmental impacts—remained salient, while perceived benefits associated with waste reduction and local economic value were also acknowledged. The technical assessment indicates that higher waste generation increases theoretical energy recovery potential; however, high residential electricity demand reduces the relative contribution of WtE, with a generated-to-consumed energy ratio of approximately 2, compared with a global benchmark ratio of 4.1. This study highlights the need for targeted public engagement, improved source segregation, and more detailed Kuwait-specific technical and economic evaluations to support evidence-based WtE policy and investment decisions. Full article

To advance the Sustainable Development Goals, it is essential to correct imbalances in how the benefits of urban trees are distributed across different demographic and socioeconomic groups. Environmental justice studies have frequently overlooked assumptions regarding the data-generating process and have not considered spatial confounding. This oversight potentially misestimates patterns of inequity. This study evaluates the sensitivity of inequity to model assumptions using urban tree inventories from Málaga and Sevilla and Bayesian hierarchical models. City-level differences dominated the inequity patterns, and model specification influenced the magnitude, precision, and credibility of estimated effects, though directionality remained consistent. Patterns were highly consistent across the four ecosystem services, indicating that model assumptions affected all services equivalently. Málaga and Seville exhibited divergent inequity patterns, indicating that local urban context mediates these relationships. In Seville, inequity patterns were inconsistent with the luxury hypothesis and occurred primarily across age-based demographic strata, whereas in Málaga they manifested predominantly along ethnicity, with weaker evidence of income inequities. We advocate for explicitly modeling spatial data-generating processes and comparing conventional versus confounding-mitigated approaches. This city-specific rigor is essential for urban planners to prevent resource misallocation, ensuring that tree-planting strategies address genuine inequities rather than methodological biases. Full article

In the last two decades, the utilization of solar energy has been growing rapidly worldwide, mainly due to the increasing adoption of photovoltaic (PV) systems. Since solar energy is one of the most weather-dependent renewable energy sources, an increasing number of meteorological studies have focused on PV potential (PV_pot) and its projected changes under global warming. GCM outputs disseminated through the Coupled Model Intercomparison Project (CMIP) are often applied in energy-related urban climate studies, as they can be downscaled either statistically or dynamically. It is essential to evaluate raw (not bias-corrected) GCM data, which helps to determine the uncertainties in the GCM simulations before downscaling. Despite their coarse resolution, some studies even rely directly on the GCM grid cell time series to represent individual locations. Accordingly, this study evaluates 10 CMIP Phase 6 (CMIP6) GCMs with respect to some atmospheric variables (air temperature, solar radiation, and wind speed, which are the primary drivers of PV_pot) in four lowland grid cells representing four major urban areas in Central and Southeast Europe: Belgrade (Serbia), Budapest (Hungary), Vienna (Austria), and Prague (Czechia). The use of solar energy has increased significantly in most of these regions in recent years; however, it remains less studied than in Western Europe. ERA5 reanalysis is used as the reference dataset. We analyzed the boreal summer (JJA) days of three overlapping 30-year time periods: 1971–2000, 1981–2010, and 1991–2020. Our main findings are as follows: GCMs tend to overestimate solar radiation and underestimate maximum near-surface air temperature relative to ERA5 in all time periods and in all the four urban areas, which leads to a significant overestimation of the number of JJA days with high PV_pot (PV_pot,90). PV_pot,90 is increasing from 1971–2000 to 1991–2020 in the vast majority of GCMs, in all the four regions. EC-Earth3 and its different configurations (EC-Earth3-Veg, EC-Earth3-CC) are considered the most accurate GCMs relative to ERA5. Full article

Globally, sustainability indicators have become increasingly important in the building construction sector. While contractors play a critical role in advancing sustainability during the construction phase, there is limited guidance on the specific practices they should adopt. This study aims to address that gap by identifying sustainable practices relevant to building construction and developing an initial set of practical guidelines to support contractors in enhancing their sustainability performance. Based on a literature review and the author’s experiences in New Zealand, a list of 49 sustainable practices for building construction has been developed, addressing the three pillars of sustainability: environmental, economic, and social. The research focuses on the building construction phase and emphasises contractor-level key implementation challenges, such as regulatory barriers and the need for enhanced waste management during construction. The proposed list of practices can serve as a valuable tool to guide contractors’ commitment to sustainability and may inform contractor selection for future tender projects. Full article

Deep decarbonization strategies at the local level have been extensively documented for cities in the Global North, yet little is known about how cities in Sub-Saharan Africa (SSA) pursue climate mitigation amid infrastructure constraints, limited fiscal autonomy, and pressing developmental needs. Local governments worldwide are recognized as critical actors in addressing urban greenhouse gas (GHG) emissions. However, SSA cities’ decarbonization efforts remain underexplored in academic and policy discourse, despite the region’s acute climate vulnerability and rapid urbanization. However, SSA cities’ decarbonization efforts remain underexplored in academic and policy discourse, despite the region’s acute climate vulnerability and rapid urbanization. This study examines how deep decarbonization pathways in four leading SSA cities (Accra, Addis Ababa, Lagos, and Nairobi) compare with those in the Global North. Using qualitative methods including document analysis and semi-structured interviews, we examine the technical pathways, institutional strategies, governance mechanisms, and actors involved in these cities’ climate mitigation efforts. Our findings reveal that while SSA cities pursue similar technical priorities to Global North cities (renewable energy, building efficiency, sustainable transport), their approaches diverge significantly in implementation. SSA cities innovate through decentralized waste-to-energy systems adapted to informal contexts, rely heavily on donor funding rather than municipal bonds, and uniquely leverage traditional institutions for community engagement. Governance structures are predominantly top-down and centralized, contrasting with the polycentric, multi-level governance observed in the Global North. These findings demonstrate that deep decarbonization in SSA must be reconceptualized not only as a form of climate mitigation but as an integrated strategy that addresses infrastructure gaps and building institutional capacity. This research contributes new knowledge on urban climate governance in developing regions and offers transferable lessons for cities facing similar constraints. Full article

Underground infrastructure systems are typically managed as discrete technical assets rather than as integrated, adaptive systems. This paper develops the Body Underground framework, a structured biological analogy that synthesizes prior clinical and epidemiological metaphors into a multiscale conceptual model linking materials, facilities, networks, and governance. Building on Little’s clinical framing of infrastructure health and Bardet and Little’s epidemiological analysis of network failure clustering, the framework extends biological interpretation to anatomical, physiological, and homeostatic scales. The approach maps structural, hydraulic, sensing, protective, and regulatory functions to functional equivalents in living systems using explicit criteria of feedback, regulation, and measurability. The central objective of the study is to determine whether biological regulatory concepts—particularly homeostasis and hierarchical organization—can provide a coherent interpretive structure for understanding infrastructure health across material, facility, network, and governance scales. The resulting framework reframes resilience as dynamic regulatory balance rather than static robustness alone. It clarifies the methodological basis for constructing biological–infrastructure analogies, identifies measurable “vital signs” for infrastructure health, and outlines pathways toward operational translation through integrated monitoring and governance feedback. While conceptual in nature, the framework provides a structured synthesis linking material science, infrastructure engineering, systems resilience theory, and policy coordination. By organizing resilience concepts through cross-scale regulatory logic, the Body Underground model offers a coherent structure for integrating monitoring, diagnosis, and governance in the proactive management of underground infrastructure systems. Full article

Urban demographic dynamics—including migration, aging, fertility change, and population redistribution—are central to sustainable urban development, urban resilience, and long-term well-being. In many small and transition economies, rapid urbanization combined with sustained emigration and population aging poses significant challenges for urban planning, labor markets, housing systems, and public services. The purpose of the paper is to evaluate urban sustainability-related demographic risks by a composite index and assess long-term demographic dynamics with different trajectories of migration flows and fertility. Since migration flows are more intense among urban population, depopulation is very high in peripheral rural areas, and urbanization is about 64% in Armenia, the results of the research will inform national and urban policy makers to reshape policy frameworks to enhance long-term urban resilience. This study develops a demographic threat index (DTI) to assess demographic risks relevant to urban sustainability in Armenia over the period 2000–2023. The index integrates 20 indicators grouped into three pillars—population change, population health, and socio-economic vulnerability—with indicator weights derived using principal component analysis (PCA). The results reveal a persistent increase in demographic risks, marked by accelerated population aging, declining youth cohorts, and rising socio-economic vulnerability, particularly in urban contexts. A decomposition of population change demonstrates that net migration has been the dominant driver of demographic dynamics, outweighing the combined effects of fertility and mortality. Scenario-based population projections further indicate that even optimistic increases in fertility are insufficient to stabilize population trajectories without sustained positive migration. By linking demographic security to urbanization, migration, and socio-economic vulnerability, the study highlights the importance of integrated urban and demographic policy frameworks. The proposed index offers a replicable tool for evaluating demographic risks in countries facing similar urban and demographic transitions and provides evidence-based insights for urban planning, migration management, and sustainable city strategies. Full article

After major disruptive events, particularly natural and human-made disasters, community leaders face the challenge of rebuilding societal infrastructure and managing the allocation of funds, which can affect the duration of recovery periods. Decision-makers must quickly determine how to allocate financial resources while minimizing population distress. Conventional methods of assessing damage and evaluating relief requirements fall short of meeting the urgent recovery needs after a disaster, potentially leading to negative effects on communities, such as involuntary relocation and neighborhood gentrification. The study evaluates current methods and technologies to propose a new approach that leverages low-cost consumer drones and modern image analysis techniques to support initial damage assessments and track recovery progress, thereby promoting the dynamic allocation of limited resources. Using low-cost drone imagery enables rapid, cost-effective data collection and dynamic analysis through iterative reviews during the disaster response and recovery phases that can adjust baseline disaster funding allocations. The study investigates the potential of temporary blue tarp roofs (“blue roofs”) as a metric for recovery progress during the 2020 tornado in Middle Tennessee and conducts an R-squared and error analysis. The goal of this research is to evaluate an affordable and efficient data analysis method (e.g., modern image analysis; artificial intelligence; low-cost drones) that can improve post-disaster resource allocation and inform decision-making for governmental and planning officials. Full article

Although urban resilience is a complex concept, several initiatives have made it more tangible. Urban public authorities and policymakers are of utmost importance, as they influence multiple neighbourhoods, stakeholders and aspects of urban resilience. Nevertheless, the role of individual facilities—such as sports fields—should not be overlooked. While their impacts are smaller in scale, they can significantly enhance local resilience and serve as inspirational pilots for broader initiatives. To assess resilience at the facility scale, an existing assessment framework was adapted, aligned with ESG (environmental, social and governance) criteria and climate action pillars and valuing ecosystem services. In the sports field case study, stormwater was reframed from a burden into a resource and integrated with other scheduled resilience-enhancing interventions: water conservation, installation of photovoltaic panels, enhanced tree shading, and circularity through sports equipment reuse. Together, these interventions strengthen urban sustainability, resilience, and climate adaptation while delivering ecological and social benefits. The stormwater drainage system was modelled to simulate naturalization actions. The assessment framework is described, and its application at both neighbourhood and facility scales is discussed. Comparisons between the existing and improved situations show clear resilience gains, and opportunities for extending these measures to the city scale are explored. Full article

Wood biomass ash (WBA) from thermal power plants is often landfilled despite its potential as a secondary raw material. This study adopts a circular economy perspective to assess the physicochemical properties, valorization potential, and environmental risks of WBA, aiming to support its use in agriculture and environmental management. Comprehensive characterization included pH, cation exchange capacity (CEC), proximate and elemental composition, and selected organic contaminants, including polycyclic aromatic hydrocarbons (PAHs). The WBA exhibited a strongly alkaline pH (10.55), moderate CEC (4.36 cmol kg⁻¹), and high ash content (78.32%), with lower nutrient content than other biomass ashes. Major elements included Ca (6.84%), K (2.90%), and Si (3.19%), while nitrogen was absent. Potentially toxic elements (PTEs) such as As, Cd, and Ni were below detection limits; Cr, Cu, Pb, and Zn remained within most regulatory thresholds, although Zn exceeded some limits. ΣPAHs were low (0.05 mg·kg⁻¹), indicating minimal environmental concern. Despite reduced nutrient richness, the ash demonstrated suitability as a liming agent and supplementary nutrient source, provided that Zn levels are managed and nitrogen is supplemented. These results support the redirection of WBA from disposal to beneficial use, advancing circular economy goals and contributing to more sustainable and resilient agricultural systems. Full article

As global temperatures rise, cities struggle with heat stress and the limitations of traditional cooling strategies. This study introduces “seasonal urban exodus”—temporarily relocating urban residents to cooler areas during summer—as a behavioral climate adaptation strategy driven by the need for thermal comfort. To assess social feasibility, a survey was conducted among 163 urban residents in Romania. The dataset was analyzed using linear regression and machine learning algorithms (Random Forest and K-Means clustering). The results show that 77.9% of respondents would relocate for 1–2 months if they had adequate destination infrastructure, while a 2 °C temperature increase would cause 46% to migrate temporarily. Predictive modeling identified barriers related to heat (p = 0.009) and transportation (p = 0.016) as the most significant predictors of relocation intention. These results suggest that seasonal mobility is a viable social response to urban heat islands. However, while this adaptation strategy improves individual thermal comfort, further interdisciplinary research—including life-cycle assessments, travel emission calculations, and the evaluation of rural energy systems—is absolutely necessary to determine the net carbon balance and environmental viability of these relocation patterns. Full article

This article presents an analysis of cross-border cooperation over the mountains. This research stems from a European project that investigated the difficulties and opportunities to form research and innovation (R&I) partnerships in the European Alps, a geographically challenging yet highly developed region bordering seven countries at the heart of Europe. The investigation highlights the role of orchestrator platforms for coordinating and matching partners in peripheral and complex areas such as the Alps, where the characteristics of a border region combine with small and peripheral urban areas. The analysis combines second-hand studies with surveys and interviews of 114 participants in innovative partnership projects from 2019 to 2022. The evidence highlights the challenges in forming effective partnerships and presents policy proposals for managing mountain entrepreneurial ecosystems. This research contributes by providing policy prescriptions that point to digital platforms for R&I collaborations in a disadvantaged and poorly explored context, such as the smaller urban areas in the Alps. Full article

Sóller, a highly touristic town in Mallorca, has been affected by gentrification problems related to the tourism industry. Recently, another gentrification process has appeared, affecting the retail fabric and leading to the disappearance of traditional locally owned shops and their substitution with tourist-focused stores. Using data from different sources, such as the City Hall documentary data, the Commerce Association archives and Google Street View images, this research highlights the gentrification process affecting two of the main commercial areas of the town. The results confirm that a commercial gentrification process, already identified in large cities such as Barcelona or Venice, can also affect medium-sized towns, creating a retail mutation that impacts local residents and their shopping capabilities. Full article

Urban mobility is a central challenge for sustainable and inclusive cities, as climate change, congestion, and spatial inequality increasingly reveal mobility patterns as expressions of deeper social and spatial structures. Inclusive urban mobility examines whether transport systems equitably support the everyday movements and accessibility needs of historically marginalized and underserved populations. The integration of artificial intelligence with geographic information science, combined with multimodal geospatial data fusion, provides powerful tools to diagnose and address these disparities by integrating heterogeneous data sources such as satellite imagery, GPS trajectories, transit records, volunteered geographic information, and social sensing data into scalable, high-resolution urban mobility analytics. This paper presents a systematic survey of recent GeoAI studies that fuse multiple geospatial data modalities for key urban mobility tasks, including accessibility mapping, demand forecasting, and origin–destination flow prediction, with particular emphasis on inclusive and equity-oriented applications. The review examines 18 multimodal GeoAI studies identified through a PRISMA-ScR screening process from 57 candidate publications between 2019 and 2025. The survey synthesizes methodological trends across data-, feature-, and decision-level fusion strategies, highlights the growing use of deep learning architectures, and examines emerging techniques such as knowledge graphs, federated learning, and explainable AI that support equity-relevant insights across diverse urban contexts. Building on this synthesis, the review identifies persistent gaps in population coverage, multimodal integration, equity optimization, explainability, validation, and governance, which currently constrain the inclusiveness and robustness of GeoAI applications in urban mobility research. To address these challenges, the paper proposes a structured research roadmap linking these gaps to concrete methodological and governance directions including equity-aware loss functions, adaptive multimodal fusion pipelines, participatory and human-in-the-loop workflows, and urban data trusts to better align multimodal GeoAI with the goals of inclusive, just, and sustainable urban mobility systems. Full article

Mapping urban tree species supports green infrastructure planning. An essential issue refers to the monitoring of exotic species that may become invasive. Street-level imagery provides a complementary perspective to aerial images for species identification that are difficult to distinguish from above. In this context, our study aimed to evaluate deep learning-based object detection and image segmentation approaches to identify a potentially invasive tree species known as Leucaena leucocephala in an urban environment in Brazil, using 422 street-level images acquired from Google Street View (SV) and mobile phones (MPs). Object detection models (YOLOv8 and DETR) and a foundation segmentation model (SAM, zero-shot) were applied to assess how deep learning paradigms perform under heterogeneous urban imaging conditions. YOLOv8 achieved detection performance with mAP50 above 0.83 and recall up to 0.76. DETR showed domain sensitivity, with mAP50 of 0.45 in SV images and 0.84 in MP imagery. For segmentation, SAM zero-shot achieved 0.92 accuracy and 0.93 F1-score in SV images, decreasing to 0.63 accuracy and 0.66 F1-score in MP images. Overall, this study demonstrates that combining detection and segmentation approaches provides complementary information for urban vegetation monitoring, supporting decision-making related to invasive species management and sustainable urban landscape planning. Full article

The ongoing rise in temperatures due to climate change is one of the most critical considerations in the design of outdoor recreational spaces. Thermal conditions can affect people’s visitation patterns, satisfaction, health and well-being. In many developing countries, including Jordan, rapid urbanisation often occurs without sufficient planning for public outdoor spaces, thereby diminishing their quality. This study is the first to investigate the effects of temperature on visitor patterns and user satisfaction in Jordanian urban parks. A mixed-methods approach was employed, combining continuous measurements of outdoor temperature (Ta) and relative humidity (Rh) with a survey assessing users’ thermal sensation, satisfaction, and preferences across six urban parks in Amman, Jordan. Data were collected from 718 respondents in summer 2025. Visitation records for the surveyed parks were also obtained from local authorities for the monitored period. The results show that the mean Ta exceeded 30 °C in all surveyed parks during the monitoring period, with peak readings exceeding 41 °C. This resulted in a warm-to-hot thermal sensation among participants, with many preferring cooler conditions. A significant inverse relationship between temperature and park visitation rates (R² = 0.67, p = 0.001) was observed, with a 1 °C increase in outdoor temperature associated with approximately a 2.03 visitor decrease. Participants’ satisfaction was higher in parks with adequate amenities, such as shading, disability access, and green zones, than in parks with fewer amenities (p = 0.01, d = 0.63). The most reported areas for improvement included facilities, shaded seating areas, and perceived safety. The findings highlight the importance of considering outdoor thermal conditions when designing urban parks, as they shape public outdoor activity patterns, particularly in hot climates. Full article

Financial channels only redistribute existing wealth rather than generating new wealth. Consequently, financialized gains for one person inevitably mean losses for others. However, the prevailing literature on housing financialization often emphasizes how investors earn excessive profits while neglecting how ordinary households bear corresponding losses. This study seeks to initiate a conceptual and empirical exploration of financialized loss within housing consumption. This study first clarifies what constitutes these losses. It then employs a comparative case study of Japan and Canada to highlight how certain housing characteristics are linked to major financialized losses for housing consumers. The findings can guide the design of more targeted housing policies to reduce housing consumers’ losses and, thereby, improve housing affordability for ordinary households. Ultimately, this study lays the groundwork for a new research agenda focused on financialized loss in housing consumption, thereby providing a novel perspective for understanding housing financialization. Full article