High-resolution data and continuous monitoring of water quality parameters enable a more accurate characterisation of stormwater pollutants dynamics. This article presents a unique dataset combining real-time online monitoring of turbidity and discharge data with event-based, size-fractionated chemical characterisation of stormwater. Turbidity and discharge were measured with a high temporal resolution at the stormwater outlet of a small urban catchment in Dresden, Germany. Additionally, for selected rainfall-runoff events, the following data were produced: total suspended solids concentrations and their particle-size distribution (<63 µm: fine particles; >63 µm: coarse fraction), elemental composition, and organic content. The online monitoring data covers the period from January 2018 to August 2022, whereas the sampled data were collected from September 2018 to 2021. Turbidity serves as a proxy for particles, organic, and elemental composition of stormwater. Therefore, our dataset is suitable for exploring flush dynamics, particle transport patterns, particle-bound pollutants, as well as for developing and validating particle transport formulations in urban drainage models. This will enable a more effective identification of stormwater treatment and management strategies to address different pollutant flushes, support regulatory decision-making, and minimise the impact of stormwater discharges on receiving water bodies. Hence, intended users of this dataset include, but are not limited to, the urban drainage/urban hydrology/stormwater research community and practitioners, students, decision-makers, policymakers, urban planners, engineers, and other stakeholders interested in water-related issues at the city or urban catchment scale.

The rapid advancement of foundation models has revolutionized visual representation learning in a self-supervised manner. However, their application in remote sensing (RS) remains constrained by a fundamental gap: existing models predominantly handle single or limited modalities, overlooking the inherently multi-modal nature of RS observations. Optical, synthetic aperture radar (SAR), and multi-spectral data offer complementary insights that significantly reduce the inherent ambiguity and uncertainty in single-source analysis. To bridge this gap, we introduce RingMoE, a unified multi-modal RS foundation model with 14.7 billion parameters, pre-trained on 400 million multi-modal RS images from nine satellites. RingMoE incorporates three key innovations: 1) A hierarchical Mixture-of-Experts (MoE) architecture comprising modal-specialized, collaborative, and shared experts, effectively modeling intra-modal knowledge while capturing cross-modal dependencies to mitigate conflicts between modal representations; 2) Physics-informed self-supervised learning, explicitly embedding sensor-specific radiometric characteristics into the pre-training objectives; 3) Dynamic expert pruning, enabling adaptive model compression from 14.7B to 1B parameters while maintaining performance, facilitating efficient deployment in Earth observation applications. Evaluated across 23 benchmarks spanning six key RS tasks (i.e., classification, detection, segmentation, tracking, change detection, and depth estimation), RingMoE outperforms existing foundation models and sets new SOTAs, demonstrating remarkable adaptability from single-modal to multi-modal scenarios. Beyond theoretical progress, it has been deployed and trialed in multiple sectors, including emergency response, land management, marine sciences, and urban planning.

• Evaluates cost-effectiveness of blue-green infrastructure in urban areas. • Cost-effectiveness is sensitive to BGI cost variability and lifetime. • Oslo Blue-Green Factor may be biased towards low-cost, lower-performing BGI. • Provides a transferrable assessment methodology for municipalities. Urban sustainability efforts increasingly rely on blue-green infrastructure (BGI) to deliver essential ecosystem services in response to climate change, urbanisation, and declining public health. However, the ecosystem service outcomes of private developers using cost-effectiveness as a paradigm to design BGI measures remains poorly understood, particularly in operational urban planning contexts. This study evaluated the cost-effectiveness of BGI measures within Oslo’s Blue-Green Factor (BGF), a planning tool that mandates minimum ecological performance requirements for new developments. We combined cost-effectiveness analysis with expert-based weighting of ecosystem services for 12 common BGI measures. Our findings demonstrate substantial heterogeneity in cost-effectiveness across BGI measures in relation to ecosystem services, driven largely by cost variation and expected lifespan. Measures with simple vegetation layers (e.g. lawns, sedums) emerged as most cost-efficient due to low implementation costs and long lifetimes but delivered limited ecosystem service benefits. In contrast, structurally complex measures, such as green walls, intensive green roofs, and rain gardens performed better in regulating air pollution, reducing runoff, and supporting biodiversity, albeit at higher costs. Sensitivity analyses revealed cost variation as the dominant factor influencing cost-effectiveness. Importantly, our cost-effectiveness analysis highlights that the current BGF framework may bias design choices towards low-cost, lower-performing BGI. To more accurately reflect ecosystem service contributions, Oslo’s BGF could benefit from revised weightings and spatially differentiated performance criteria tailored to local socio-ecological priorities. This study provides the first assessment of the BGF’s incentive effects and offers guidance for improving urban BGI planning tools.

Uncovering nonlinear threshold effects of urban morphology on carbon emissions: Toward optimal low-carbon urban spatial planning

Data-driven urban mobility planning: A GIS-based spatial modeling approach for shared mobility hub placement

Dataset of in-situ meteorological measurements for urban wind energy assessment in the southern region of the Dominican Republic.

The ongoing process of urbanization, coupled with the urgent need for a profound climate transition, underscores the timeliness and necessity of integrating sustainability considerations within the building sector. Real-estate projects are responsible for about 36% of CO2 emissions in the European Union ( European Commission, 2019 ). This study investigates how public and private real-estate developers conceptualize their responsibilities in promoting climate-friendly and socially sustainable urban development, and whether these perceptions differ across actor groups. The analysis is situated within a Nordic context, focusing on Norway—a country characterized by a neoliberal housing market in which substantial responsibility for detailed planning and housing production has been delegated to private real-estate firms. Drawing on a unique quantitative dataset comprising responses from both public and private developers, the findings suggest an emerging, more nuanced understanding of sustainable construction practices. While the dominant focus remains on energy efficiency, technical performance, and functional standards, developers increasingly incorporate broader sustainability principles, such as reuse and circularity. Notably, environmental concerns related to biodiversity and nature preservation appear to be the least developed among the actors. The study also reveals a growing awareness within the building sector regarding its role in fostering socially sustainable urban environments, except ensuring inclusive housing markets. One of the most unexpected findings was the convergence in perspectives between public and private developers, suggesting a shared set of values despite differing formal mandates. • The article surveys public and private real‑estate developers, showing a sustainability responsibility in both groups. • The strongest responsibility awareness is found in energy efficiency and functional requirements, but weaker in circularity. • There is a recognition of the sector’s role in social sustainability; as housing quality and community‑building provisions. • There is a marked similarity in the two groups’ approaches, suggesting shared value orientations despite differing mandates.

Green infrastructure–urban planning nexus: Role, discourse and possibilities in achieving socio-ecological sustainability and resilience

The intersection of energy transition and urban planning for sustainable development: enhancing energy efficiency and sustainability

Urban expansion in areas adjacent to industrial areas presents serious safety challenges, especially in fast developing areas. Nearly between residential and industrial activities increases the risk of accidents, environmental pollution and massive disasters. In response, industrial countries have adopted advanced management systems to reduce these risks. Of these, the Geographical Information System (GIS) provides a powerful tool for analyzing and mapping the areas coming in contact with industrial threats. The purpose of this study is to assess the role of GI in reducing industrial risks and focusing a specific focus on the Algerian context, reducing industrial risks and supporting permanent urban planning. Research adopts a spatial analysis approach using topological maps, geographical datasets and GIS software. Industrial areas and surrounding urban settlements were studied through layered spatial modeling. Supplementary area observation and case studies were included to validate the accuracy of GIS output. The analysis focused on identifying weak areas, assessing industrial threats and assessing the effectiveness of existing land-use and reaction strategies. Conclusions highlight the important weaknesses in current urban risk management systems, especially in terms of preparations and integration with spatial plan. The GIS proved to be effective in detecting high-risk areas, imagining dangerous areas and providing strategic support for the decisions of land-use. The device also featured landscape simulation, which improved the understanding of potential industrial accidents and their impact on nearby communities. The interpretation of these results suggests that GI increases urban flexibility, reduces exposure to industrial threa.

This research assesses theme parks as ideal micro-cities, identifying some of their admirable characteristics relevant to modern urban planning. It argues that theme parks, such as EPCOT and Disneyland, depict controlled aspects of urban design aimed towards a specific goal: human enjoyment. This human-oriented spatial architecture is missing in modern cities such as Los Angeles. Some of the urban challenges identified include car dependency and poor public space. The research New Urbanism and Theme Park Urbanism theoretical frameworks to criticize LA’s Euclidean zoning approach and assess the immersive, narrative-steered settings, respectively. The key research questions are summarized into the lessons modern city planners can pick from theme parks’ regulated spatial aspect and how LA can use these lessons to enhance city experience. The recommended methodology for this study should assess EPCOT and Disneyland theme parks via visitors’ views on these parks. One of the expected outcomes is to derive a framework of design strategies from theme parks that can be adapted to urban settings.

ABSTRACT Promoting healthy and sustainable cities through urban design and planning is essential to improving the urban environment and overall population well-being. The Global Healthy and Sustainable City Indicators (GHSCI) initiative is a collaborative effort that provides open-source tools to support the development of spatial indicators for urban health promotion. This study used GHSCI software to analyze spatial indicator data for the Jakarta region. The collected data were evaluated and compared with the median values of the 25 initial cities from GHSCI’s first collaboration project. The research findings highlight Jakarta’s comparative position among other cities within the GHSCI framework. An analysis of GHSCI reveals both strengths and weaknesses in Jakarta’s efforts to achieve a healthy and sustainable urban status. Key findings include limited access to fresh food markets; high intersection density in most neighborhoods, which may serve as a potential marker for promoting walkability; and widespread access to public transportation, with the majority of residents living within proximity to bus stops. While these indicators provide valuable information, this study suggests that future refinements of GHSCI could benefit from expanded indicators that incorporate lessons from recent public health crises to better predict urban health.

ABSTRACT In rapidly urbanising low and middle-income countries where access to formal leisure facilities is limited, informal public spaces play a critical role in supporting leisure-time physical activity (LTPA). Using a mixed-methods citizen science approach in Lagos, Nigeria, and Yaoundé, Cameroon, this study examined how sex, socio-economic status (SES), and perceived risks shape the use of public spaces for LTPA. Sex and SES disparities were observed: men were more likely to use vacant plots for LTPA, while women predominantly engaged in walking and running; walking was most prevalent in high-SES neighbourhoods, whereas organised activities were more common among women in Yaoundé and spontaneous activities among women in Lagos. Perceived injury risk was highest in areas with low socio-economic status (SES), where safety features were least available. These findings demonstrate that informal public spaces function as socially and economically stratified environments for physical activity, rather than neutral settings. The study advances understanding of equity in active living in African cities and provides evidence to inform sex- and equity-responsive urban and public health planning.

ABSTRACT Developing countries are urged to adopt fit-for-purpose land administration (FFPLA) to address global land administration challenges under rapid urbanisation. The FFPLA has proven cost-effective in initialising the formalisation of land tenure as a key input into planning and land development. However, its long-term ability to support planning, particularly its suitability for high-value, rapidly changing urban contexts remains uncertain. This study assesses Rwanda’s FFP implementation, focusing on contextual factors, methods used, and current capacity to address urban planning needs. Findings highlight gaps between policy ambitions and practical outcomes, calling for adjustments to better support planning and sustainable urban development.

ABSTRACT During the late 1960s and 1970s, traffic-planners across Europe adopted an ideology of traffic separation – as the optimal way to address traffic hazards and risks. According to this ideology, pedestrian underpasses allowed cars to cross paths with pedestrians without conflict or interruption. Around 1970, the City of Copenhagen made large investments but these investments dwindled towards the end of the 1970s and underpasses diminished. This paper examines the rise and fall of pedestrian underpasses as a solution to perceived and real challenges in urban mobility. Using Actor-Network Theory (ANT) approach, the paper follows the interessement that traffic planners, politicians, and the press engaged in as well as the degree of pre-inscription of children, the elderly, and other imagined users during the construction of pedestrian underpasses. It shows how children were put forward as the main argument for these infrastructural investments. Vulnerable children were framed as the problem that the underpasses were meant to solve. However, as the underpasses became a fixture in the city, the public, politicians, and planners realized that children did not subscribe to this problematization, and Copenhagen-planners gradually abandoned the technology. The article reveals the ambiguous potency-yet-fragility of using children as a rhetorical tool in urban planning.

Urban food insecurity in African cities reflects deep structural gaps in planning, governance, and service delivery. This review examines how guerrilla agro-urbanism, the (in)formal community-led socio-economic use of vacant urban land, can be strategically integrated into resilient urban planning in Harare, Zimbabwe. Its low-cost, adaptive practices outside formal regulation, guerrilla agrourbanism, is critical in enhancing food security, generating income, and delivering environmental benefits. However, it remains largely invisible in policy as it is seen as a threat to what is viewed as “modern cities” landscapes. The paper identifies both opportunities and constraints based on historical analysis, global and African case studies, and Zimbabwe’s legal and planning frameworks. Key barriers include insecure land tenure, inadequate legal recognition, and environmental risks. The review proposes reforms centred on formal policy recognition, secure and equitable land access, safe agricultural practices, and community participation, aligned with the African Union’s Agenda 2063, the SDGs, and devolved governance systems. By reframing informality as an asset rather than a threat, this study offers a pathway for transforming guerrilla agro-urbanism from a survival strategy into a pillar of inclusive, climate-resilient urban food systems. The findings intrigue further debates on sustainable urban planning, putting into perspective the realities of urban residents. It also provides actionable insights for policymakers, planners, and stakeholders committed to sustainable urban development in the Global South

This study presents a comprehensive analytical-applied framework for the revitalization of historic urban centers through the application of an urban injection strategy guided by the results of spatial structure analysis. The historic Rusafa district of Baghdad serves as a case study. Field surveys, digital maps, and Depth map X analysis were employed to measure indices of integration, clarity, intensity, and selection. This allowed for the identification of areas with high structural coherence, visually prominent axes, and centers of urban activity. The results reveal a dual urban structure within the historic core. This structure is characterized by highly integrated and spatially dominant main axes, such as Al Khulafa Street and Al-Khilani Square, contrasted with secondary streets and pathways suffering from weak coherence and functional performance, particularly sections of Al Rashid Street. Activity is clearly concentrated along the Al-Rashid-Al-Khulafa axis. Based on this diagnosis, the study proposes the Urban Injection strategy as a precise intervention approach. It draws inspiration from therapeutic and aesthetic intervention patterns in the medical field (intravenous, intramuscular, subcutaneous, intraosseous, cosmetic, preventative, and spiritual injections) and repurposes them within the field of architecture and urban planning, adapting them to the spatial functioning of the historic fabric. This approach allows for targeted interventions that revitalize urban areas while preserving heritage values. It provides planners and decision-makers with an evidence-based and replicable tool that supports the achievement of the Sustainable Development Goals, particularly Goal 11 (Sustainable Cities and Communities) and Goal 13 (Climate Action). The study is constrained by limited socio-economic data and restricted access to parts of the study area. Moreover, the analysis focuses mainly on spatial structure, with limited consideration of social and environmental variables. Future research should incorporate behavioral and environmental indicators to broaden the framework’s analytical scope.

While housing price prediction is well-studied, the prediction of large-scale housing conditions remains underexplored due to data limitations. This paper addresses this gap by developing a machine-learning model to predict housing conditions across the United States. We integrated property-level data from the Warren Group with neighborhood characteristics from the U.S. Census Bureau's American Community Survey and trained three gradient-boosting algorithms: CatBoost, LightGBM, and XGBoost. Despite XGBoost's slightly higher balanced accuracy, CatBoost was selected as the best model due to its superior resistance to overfitting. The final model's predictions were aggregated to census tracts, ZIP code tabulation areas, and a 36.13 km2 resolution hexagonal grid for national-scale spatial analysis. The resulting comprehensive dataset can serve as a valuable resource for researchers and practitioners to analyze the geography of housing quality with applications in urban planning, disaster management, community resilience, public health, and more.

Abstract The current U.S. federal administration has sought to intervene into every aspect of academic life, university functioning, and the research enterprise including by attacking academic freedom and integrity and canceling and retreating from publicly funded research. Such actions have profound adverse effects on the U.S. public, especially its most marginalized communities, and on science, itself. This perspective provides a telling example of such impacts through our own experience of funding cancellation, the disruptions it causes and the effects it has on urban systems and the communities they support. By focusing on our project that sought to center environmental justice communities in urban transportation and climate planning we offer insights into the wide-ranging effects of such disinvestment, including on sustainability and air quality efforts, with recommendations for moving forward to advance sustainable, equitable, and resilient cities.

ABSTRACT This study investigates the factors influencing public transport acceptance in Egyptian cities using advanced machine learning techniques, including Optimal Regression Forest (ORF) and Variance-Based Sensitivity Analysis (VBSA). We analyze data from a survey of 2,511 respondents using a stated preference experiment to identify key drivers of acceptance and quantify their impact. VBSA was applied, quantifying both direct and interaction effects of fourteen explanatory variables. The results show that socioeconomic variables, perceived benefits, and service reliability are the most influential factors, with significant implications for policymakers seeking to improve public transport adoption. By integrating ORF and VBSA, our model achieves strong predictive performance, providing actionable insights for enhancing transport policy and service design. These findings contribute to the literature on public transport planning and offer practical recommendations for urban planners and policymakers in Egypt and in other Middle East and North Africa (MENA) cities with comparable socioeconomic and institutional conditions.