Search Results (32)

As global climate change intensifies, typhoon disasters pose growing threats to the socio-economic stability of coastal cities. Quantifying urban typhoon resilience and identifying its spatial driving mechanisms are essential for informing targeted disaster risk management and built environment optimization. This study develops an NTL-based framework to quantify urban typhoon resilience across three major typhoon events in Zhuhai from 2017 to 2020, using NTL loss rate and NTL recovery time as the primary resilience indicators and NTL loss as a descriptive measure of absolute disaster impact magnitude. OLS and GWR models are then applied to a 20-factor indicator system to identify the global drivers of resistance and recovery capacity and uncover the spatial heterogeneity of their effects across urbanization gradients, with the aim of providing both a replicable methodological framework and an empirical basis to inform differentiated resilience optimization strategies for coastal cities. The results demonstrate that urban typhoon resilience varies systematically across urbanization gradients in both dimensions. Highly urbanized areas consistently show stronger resistance, with NTL loss rates of 32–46% versus 36–50% in low-urbanized areas, as well as faster recovery, with NTL recovery times of 2.6–3.8 days versus 2.9–5.6 days. Transportation infrastructure emerges as the most consistent global driver. GWR reveals that its effects are most pronounced in less urbanized areas, where the absolute coefficient for transport station density reaches 4.804 (over 4% higher than in other zones). Blue–green infrastructure also plays a significant role, with higher NDVI values being associated with shorter recovery times. These findings provide a replicable NTL-based methodological framework and spatially explicit empirical evidence to support targeted and differentiated resilience optimization in coastal cities. Full article

Amid rapid urbanisation and the associated environmental challenges, such as increased flood risk, the urban heat island effect, and ecosystem degradation, Blue–Green Infrastructure (BGI) has emerged as a vital sustainable development strategy. Some countries have successfully implemented BGI projects, shaped by their unique geographical conditions, socioeconomic contexts, and governance structures. Although the BGI concept is highly relevant worldwide, strategies for integrating BGI into urban environments vary significantly across regions and countries due to their distinct urban structures and spatial planning systems. This study provides a comparative study of BGI implementation into spatial planning systems of Ljubljana (Slovenia) and Kraków (Poland), as Central European cities, and Shanghai and Guangzhou, as Chinese cities. Through a systematic analysis of semi-structured interviews with key stakeholders, the study evaluates how different enablers, i.e., (1) guidelines, strategies, and actions, (2) land-use strategy for BGI, and (3) potential of factors for BGI implementation, including planning scale, financial, technical, and spatial, facilitate BGI implementation. This comparative study reveals contrasting yet complementary BGI paradigms, most notably related to top-down versus bottom-up implementation and different prioritisation of BGI functions. These varying paradigms are shaped by specific urban challenges, governance, and spatial planning systems. Full article

As essential components of the natural environment, urban green and blue spaces (UGBSs) hold significant potential to enhance public health and wellbeing. However, existing research is limited in understanding the spatiotemporal heterogeneity and nonlinear relationships characterizing how built environment (BE) features of UGBSs influence public happiness. This study takes Nanjing, China as a case study. It integrates multisource data (e.g., social media text, remote-sensing imagery, POI data, land use, etc.) and employs machine learning techniques (including sentiment analysis and random forest), to investigate the nonlinear effects and spatiotemporal dynamics of UGBSs’ BE on public happiness. The results show that nonlinear relationships (e.g., S-shaped and inverted U-shaped) commonly exist between UGBSs’ BE indicators and happiness. The influence of UGBSs’ BE on happiness demonstrates significant spatiotemporal dynamics. Diversity and destination accessibility were dominant factors from 2021 to 2023, whereas the importance of the design and density dimensions increased substantially after 2023. The influence varied across UGBS types; except for the diversity dimension, the BE’s density, design, and destination accessibility were significantly associated with happiness across all UGBS types. The study offers empirical evidence to inform planning and management of UGBS infrastructure, with the aim to maximize public health benefits and foster healthy cities. Full article

Urban ecological recreation space (UERS), as a crucial component of urban blue–green infrastructure, plays a pivotal role in supporting daily recreational activities and enhancing urban ecological resilience. However, existing equity studies often focus on supply–demand matching outcomes while neglecting the structural allocation of green space provision. Against this backdrop, this study constructs a dual-layer analytical framework of “structural supply–supply–demand matching” and introduces a quality factor to improve the Gaussian two-step floating catchment area method (G2SFCA). Focusing on Urumqi as an empirical case, the accessibility and equity of its UERS are analyzed. The results indicate: 1. The accessibility of UERS exhibits a “core–periphery” differentiation, with the old urban area demonstrating higher accessibility levels in terms of structural supply. However, due to the competitive effects of high population density, its accessibility advantage in the supply–demand matching layer is significantly diminished. 2. Population competition amplifies spatial imbalances, resulting in significantly higher inequality at the supply–demand matching layer than at the structural supply layer. 3. After considering the quality factors of UERS, its fairness has improved, which is more pronounced in the supply–demand matching layer. Optimizing the quality of UERS in high-density built-up areas contributes to the enhancement of fairness. This study emphasizes that UERS accessibility should be understood as a coupled outcome of structural supply and competitive redistribution. The proposed dual-layer framework provides a more comprehensive basis for diagnosing spatial inequalities and formulating differentiated blue–green infrastructure planning strategies. Full article

Urbanisation and climate change are intensifying heat risks in cities worldwide through the combined effects of global warming and the urban heat island (UHI) phenomenon. Elevated urban temperatures threaten human health, strain infrastructure, increase energy demand and exacerbate socio-spatial inequalities. While architectural and urban design decisions are central to the formation and mitigation of UHI, moving from UHI mitigation to heat-resilient cities requires linking physical interventions with governance capacity, equity, and adaptive learning over time. This paper, therefore, develops a conceptual framework for resilient and sustainable urban environments that embeds built-environment strategies within a broader resilience-oriented governance context. The study combines a narrative review of UHI mechanisms, impacts and mitigation approaches with a systematic review of local-government strategies implemented between 2015 and 2025. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and a population, intervention, comparison, and outcome (PICO)-based search strategy, 100 studies were selected from Scopus and Web of Science and analysed thematically. The review identifies four main domains of local action: green infrastructure; cool and permeable materials; water-based and blue–green infrastructure; and policy, governance and technology. Within these domains, the paper highlights architectural and design-relevant interventions, including shade-oriented streetscapes, climate-responsive building envelopes, ventilation-sensitive urban form, and blue–green corridors, while also examining institutional, financial and social factors that shape implementation and effectiveness. The findings show that combinations of green infrastructure, cool materials and blue–green systems can reduce surface and near-surface air temperatures and improve thermal comfort, with co-benefits for public health, energy efficiency, biodiversity and liveability. However, implementation is frequently constrained by limited financial and technical capacity, fragmented institutions, context-specific trade-offs, and insufficient attention to equity. Building on these insights, the paper proposes a conceptual framework comprising ten components that connect context and drivers; assessment and diagnosis; intervention strategies; implementation mechanisms; enablers; barriers; equity operationalisation; outcomes and effectiveness; monitoring and evaluation; and feedback and iteration. The paper concludes that advancing from urban heat islands to resilient cities requires design innovation supported by enabling governance, equity-centred prioritisation, and iterative monitoring and learning. Full article

Blue–green infrastructure (BGI) is an important nature-based solution for mitigating urban overheating, and machine learning (ML) techniques offer strong potential in capturing the complex, nonlinear relationships between influencing factors and BGI cooling effects. This study presents a systematic review of 54 journal articles published between 2015 and 2025 that applied ML to assess the cooling performance of BGI. We classified BGI into seven types across three spatial scales, evaluated the metrics and indicators used to characterize the BGI cooling effects, and examined the ML algorithms, model performance, and data sources adopted in reviewed studies. We found that 2D BGI morphology metrics and BGI physical and biological metrics are most frequently used as model inputs, whereas 3D morphology metrics are used less. Surface temperature-related indicators dominate model outputs, while air temperature and human heat stress indicators, which better reflect heat health hazards, remain underutilized. In terms of methodology, ML applications are primarily based on artificial neural networks for temporal regression and tree ensemble algorithms for spatial regression. Building on these findings, we identify key research gaps and advocate that future research should develop comprehensive multi-source and multi-scale BGI databases, improve model transparency and generalizability, and integrate energy-balance information into BGI-ML studies. Finally, we propose a systematic BGI-ML modeling framework to guide future research in this field. Full article

In the context of global climate change and rapid urbanization, integrating urban blue-green infrastructure into the built environment is essential for mitigating the urban heat island effect and enhancing climate resilience. Focusing on urban riparian corridors as vital natural cooling systems, this study aims to: (1) quantify their cooling performance in terms of intensity and distance; (2) identify the key landscape drivers and their relative importance; (3) uncover nonlinear relationships and determine ecological thresholds for optimal thermal regulation; and (4) translate these findings into science-based guidelines for climate-adaptive design and sustainable management. Taking 27 representative riparian green spaces in Zhengzhou, China (average area: 17,539 m², range: 10,027–42,690 m²) as a case study, nine key factors characterizing vegetation structure and composition, corridor morphology, and blue-green spatial pattern were used as predictors in a Boosted Regression Tree (BRT) model to analyze their contributions and marginal-effect thresholds. Results show that these corridors provide substantial cooling, with an average intensity of 5.43 °C extending over 215.56 m. Canopy Density, 3D Green Volume per Unit Area, and Green Cover Ratio emerged as the three core drivers, jointly explaining >86% of the cooling performance. The key innovation lies in identifying explicit, design-oriented ecological thresholds—for example, cooling efficacy stabilizes when Green Cover Ratio reaches ~77%, Canopy Density attains 0.7, and the Blue-Green Space Width Ratio approaches 1:1. These thresholds can be directly translated into performance benchmarks for sustainable urban planning and landscape engineering, providing evidence-based parameters for optimizing vegetation structure and spatial configuration. This study demonstrates that applying quantified ecological thresholds can transform riparian corridors into efficient climate-resilient infrastructure, thereby synergistically improving thermal comfort, enhancing ecosystem services, and promoting sustainable land use in urban environments. Full article

University students face rising mental health pressures, making restorative environmental perception (REP) in campus forests critical for psychological recovery. While environmental factors are recognized contributors, Socio-Ecological Systems (SES) theory emphasizes that environmental and social processes are interdependent. Within this context, informal social interaction (ISI)—low-effort encounters such as greetings or small talk—represent a key social dimension that may complement environmental restoration by fostering comfort and embedded affordances. However, most studies examine these factors separately, often using coarse measures that overlook heterogeneity in restorative mechanisms. This study investigates how environmental-exposure and social–environmental context dimensions jointly shape REP in campus forests, focusing on distributional patterns beyond average effects. Using a Public Participation Geographic Information Systems (PPGIS) approach, 30 students photographed 1294 tree-dominant scenes on a forest-rich campus. Environmental features were quantified via semantic segmentation, and ISI was rated alongside REP. Quantile regression estimated effects across the REP distribution. Three distributional patterns emerged. First, blue exposure and ISI acted as reliable resources, consistently enhancing REP with distinct profiles. Second, green exposure functioned as a threshold-dependent resource, with mid-quantile attenuation but amplified contributions in highly restorative scenes. Third, anthropogenic and demographic factors created conditional barriers with distribution-specific effects. Findings demonstrate that campus forest restoration operates through differentiated socio-ecological mechanisms rather than uniform pathways, informing strategies for equitable, restoration-optimized management. More broadly, the distributional framework offers transferable insights for urban forests as socio-ecological infrastructures supporting both human well-being and ecological resilience. Full article

The Yellow River Basin faces severe challenges in water security and ecological protection: at the basin scale, complex hydrological processes and fragile ecosystems undermine the water security pattern; at the local scale, waterlogging risks have intensified in Zhengzhou—a core city in the lower reaches—impacting the city itself and also exerting negative effects on the basin’s water security. To address this, mapping the scientific layout of green infrastructure (GI) is urgent. However, existing studies on GI layout at the basin-urban scale have certain limitations: neglect of underlying surface spatial heterogeneity, insufficient integration of natural, hydrological and social factors’ synergies, and lack of research on large-scale basins and cities, especially ecologically sensitive areas with complex hydrological processes. To fill these gaps, this study proposes an integrated framework (SCS–GIS–MCDM) combining the SCS hydrological model, GIS spatial analysis, and multi-criteria decision making (MCDM). The SCS hydrological model is refined via localized parameter calibration for better accuracy; indicator weights are determined through the MCDM framework; and green infrastructure (GI) suitability maps are generated by integrating ArcGIS spatial analysis with fuzzy logic. Results show that (1) 6.8% of Zhengzhou is highly suitable for GI, mainly in riparian areas and the Yellow River alluvial plain; (2) sensitivity analysis confirms flooded areas and runoff corridors as key drivers; (3) spatial validation against government-issued ecological control zone plans demonstrates the model’s value in balancing flood safety and socio-economy. This framework provides a replicable application model for GI construction in cities along the Yellow River Basin, thereby supporting urban planners in making evidence-based decisions for sustainable blue–green space planning. Full article

Urban riparian areas serve as vital blue-green infrastructure for climate adaptation, yet mechanisms governing energy exchange remain underexplored. This study aims to quantify the spatiotemporal patterns of sensible heat flux (H) and latent heat flux (LE) across riparian plant communities on daily and annual scales, and to disentangle the interactive effects of vegetation structure and water bodies on these fluxes. Using year-long field monitoring (September 2020–August 2021) across seven riparian plant communities along the Danshui River in Shanghai, environmental parameters were collected at multiple distances from the river. Interpretable machine learning models (Random Forest with SHAP analysis) were employed to identify key drivers. Results reveal significant diurnal and seasonal dynamics: LE amplitude exceeded H in summer but reversed in winter, with spatial gradients in H and LE strongly influenced by proximity to water bodies in grasslands and broadleaf forests but weakened in conifers. Meteorological factors such as photosynthetically active radiation and sunshine duration dominated daily-scale fluxes, while vegetation structures such as canopy height and leaf area index (LAI) contributed >50% to annual-scale variability. These findings underscore vegetation’s role in modulating energy partitioning, providing a theoretical basis for optimizing riparian plant configurations to enhance microclimate regulation in urban riparian. Full article

With rapid global aging, the community environment has become a critical factor influencing cognitive health in older adults. However, most existing studies focus on single environmental attributes and rely on linear analytical methods, which fail to capture the complex and synergistic effects of community features. Guided by an integrated theoretical perspective on environmental psychology, aging, and cognitive health, this study examines how multiple community environmental factors jointly affect cognitive function in elderly people. A case study was conducted among 215 older residents in Shanghai, China. An exploratory factor analysis (EFA) identified the following five key dimensions of community environment: pedestrian friendliness, blue–green spaces, infrastructure, space attractiveness, and safety. We then applied both Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA) to reveal linear and configurational relationships. The findings showed that pedestrian friendliness, blue–green spaces, and space attractiveness significantly enhance cognitive health, while fsQCA highlighted multiple pathways that underscore the non-linear and synergistic interactions among environmental features. These results provide theoretical insights into the mechanisms linking community environments and cognitive function and offer practical guidance for designing age-friendly communities. Full article

As important urban green spaces, rivers enhance cooling island effects significantly by leveraging environmental factors. This study selected Suzhou River in Shanghai as the subject to explore how to improve blue–green–gray infrastructure to optimize the river cooling island effect on the riparian zone for outdoor activities in summer. A total of 77 samples, including 36 control groups and 41 experimental groups, were categorized into 12 types of blue–green–gray infrastructure composite features. ENVI-met was used to simulate summer thermal comfort, while redundancy analysis and boosted regression trees were used to identify significant factors and thresholds influencing the river’s cooling island effect. The results showed that for Suzhou River, the green–blue–green–gray–green composition most effectively optimizes the river cooling island effect. It is recommended to select construction sites where the river width is 55 m and the percentage of green infrastructure exceeds 40% and keep the distance between green infrastructure and the water body to within 3 m. Additionally, limiting gray infrastructure to less than 10%, with an average building height of 37 m and a building undulation of 25 m, is recommended to achieve the optimal cooling effect. This study finally proposes optimization strategies to maximize the cooling island effect of urban rivers, offering insights for the development of climate-adaptive urban riparian zones. Full article

Rapid urbanization in Karachi, Pakistan, has resulted in increased impervious surfaces, leading to significant challenges, such as frequent flooding, urban heat islands, and loss of vegetation. These issues pose challenges to urban resilience, livability, and sustainability, which further demand solutions that incorporate urban greening and effective water management. This research uses remote sensing technologies and Geographic Information Systems (GISs), to analyze current surface treatments and their relationship to Karachi’s blue-green infrastructure. By following this approach, we evaluate flood risk and identify key flood-conditioning factors, including elevation, slope, rainfall distribution, drainage density, and land use/land cover changes. By utilizing the Analytical Hierarchy Process (AHP), we develop a flood risk assessment framework and a comprehensive flood risk map. Additionally, this research proposes an innovative Sponge City (SC) framework that integrates nature-based solutions (NBS) into urban planning, especially advocating for the establishment of green infrastructure, such as green roofs, rain gardens, and vegetated parks, to enhance water retention and drainage capacity. The findings highlight the urgent need for targeted policies and stakeholder engagement strategies to implement sustainable urban greening practices that address flooding and enhance the livability of Karachi. This work not only advances the theoretical understanding of Sponge Cities but also provides practical insights for policymakers, urban planners, and local communities facing similar sustainability challenges. Full article

Floods represent one of the most significant global risks, threatening human lives, infrastructure, and economic development. Although various strategies for flood water management have been developed, their effectiveness and applicability vary depending on geopolitical, economic, and climatic factors. This systematic review aims to analyze and critically assess existing mechanisms and programs focused on industry engagement in flood risk reduction and flood water management. Through a comprehensive literature review, key strategies have been identified, including nature-based solutions such as blue-green infrastructure, technological innovations in flood prediction, and regulatory frameworks designed to strengthen cooperation between the public and private sectors. Special attention is given to the limitations of previous research, including methodological shortcomings, the lack of empirical evidence on the long-term effects of strategies, and challenges in implementing existing policies. The findings highlight the need for an integrated approach that combines technical, regulatory, and socio-economic solutions for more effective flood risk reduction. This study contributes to academic and practical discussions by providing a comprehensive analysis of current strategies and offering guidelines for future research. Full article

The aim of this study is to present a methodology for diagnosing cities in terms of hydrological and meteorological threats, with the goal of improving water management and helping cities adapt to changing conditions. Urbanisation is expected to progress unevenly across countries and cities, influenced by factors such as climatic conditions, economic disparities, and governance structures. Consequently, urban landscapes should strive for a balanced approach that integrates safety and risk management, commercial spaces, emotional well-being, and the promotion of biodiversity. Cities play a pivotal role in addressing climate change, as they account for a significant share of global energy consumption and greenhouse gas emissions. In Poland, numerous national and international projects are being implemented to help cities mitigate the impacts of climate change. Among these, the City with Climate project aimed to enhance residents’ quality of life while facilitating a pro-climate transition for cities. A holistic and multifaceted approach was adopted, incorporating the analysis of historical flood events based on archival documents and rescue service reports, detailed GIS data such as soil sealing, non-drained basins, NDVI, NDBI, and a multi-criteria analysis targeting hydrological and water management factors to develop effective solutions for urban retention challenges. The main findings indicate that: (1) combining insightful analyses using well-established methods provides a robust foundation for informed decision-making by city authorities; (2) overlaying information layers, such as local flooding interventions, non-drained areas, drainage networks, and soil sealing, helps identify areas requiring large-scale, technical, or nature-based solutions; and (3) regardless of city size, there is a concerning trend of increasing impervious surfaces replacing green areas, alongside urban sprawl altering land use in flood-prone regions, including mountainous, forested, and floodplain areas that should be protected. These findings illustrate that employing a structured project methodology alongside a comprehensive approach can significantly contribute to urban landscape planning, addressing the challenges of climate change while enhancing urban biodiversity through blue and green infrastructure. Full article