Search Results (14,938)

Urban areas across Europe are undergoing rapid morphological transformations driven by densification, redevelopment, and infrastructure expansion. Monitoring these urban changes requires operational, harmonized, and reproducible approaches grounded in Earth Observation. This study presents a Copernicus use case demonstrating how the High-Resolution Layer Imperviousness Change (2015–2018) and Urban Atlas datasets can be integrated with the Guidos Toolbox (GTB) to quantify structural urban change across six metropolitan areas (Milan, Sofia, Riga, Warsaw, Viseu, Santander). Morphological Spatial Pattern Analysis (MSPA) and entropy-based indicators were applied to characterize land take, fragmentation, compaction, and internal reorganization of impervious surfaces. The combined framework captured both configurational morphology and spatial disorder, revealing divergent development patterns: pronounced heterogeneity and fragmentation in Sofia, stabilization or compact growth in Milan, Warsaw, and Santander, controlled densification in Riga, and localized intensification without outward expansion in Viseu. All analyses rely on openly accessible Copernicus data and open-source tools, ensuring full reproducibility and transferability. Outputs were disseminated through a FAIR-compliant geoportal developed within a Copernicus FPCUP project, supporting transparency and reuse. The findings underscore the value of Copernicus services for operational urban monitoring and provide a scalable methodology to support European land-use policies, including the Zero Net Land Take 2050 target and the EU Soil Strategy. Full article

Safe and sustainable water sources are a serious global concern because of growing population, urbanization, industrialization, and climate change. The conventional water surveillance systems that rely on periodic sampling and laboratory analysis fail to provide time-sensitive and high-resolution data utilized for proactive water management. Artificial Intelligence of Things (AIoT) offers a viable solution, as they can provide tools of constant active monitoring and predictive analytics. The integration of IoT sensor networks with machine learning (ML) methods enables real-time data-driven water resource monitoring and intelligent decision-making, enhances water quality assessment, supports early detection of anomalies, improves predictive capabilities for floods and droughts, and facilitates efficient irrigation and reservoir management, ultimately leading to sustainable and resilient water management systems. The paper presents an extensive overview of AIoT solutions for water quality monitoring and water resource management, including IoT sensor networks for real-time data acquisition, machine learning methods for prediction, classification, anomaly detection, and edge computing platforms for data processing and decision support. This study also highlights existing possibilities, obstacles, and research gaps identified through a review of the recent literature. Key challenges reported across multiple studies include limited data availability, sensor calibration bias, integration of heterogeneous data, and insufficient model interpretability. Advanced paradigms such as digital twin systems, TinyML, federated learning, and explainable AI (XAI) are examined as enabling technologies to enhance system efficiency, flexibility, and transparency. Future research directions are outlined to develop scalable, interpretable, and real-time water management solutions. Full article

Urban areas are increasingly exposed to water-related challenges, including flood risk and water scarcity, amplified by climate change, population growth, and extensive soil sealing. Addressing these pressures requires integrated stormwater management (SWM) strategies that balance hydraulic, environmental, and social objectives. This study introduces a novel, replicable Key Performance Indicator (KPI)-based assessment framework for 36 green–blue and grey sustainable stormwater management systems (SWMSs), designed to enable cross-typology, multiscale comparison. Six KPIs, encompassing flood regulation, water consumption, water quality, air quality, environmental amenity, and biodiversity potential, are derived through a critical synthesis and harmonisation of the literature and complemented with new parameters and sub-parameters to address existing methodological gaps. The framework structures evaluations into six analytical tables and one summary table, ensuring transparent, systematic, and comparative assessment of heterogeneous solutions. Application to a pilot project in Rome demonstrates how integrating KPI evaluation with parametric hydraulic modelling provides actionable insights for solution selection. It also facilitates identification of potential synergies between performance dimensions, enhancing its value as a decision-support tool in preliminary design. Overall, the study demonstrates the research value of multi-scalar, performance-based approaches for urban water planning, highlights the transferability of resilient stormwater strategies in climate-sensitive contexts, and identifies promising avenues for future research, including multi-sectoral integration, trade-off analysis, and cross-platform application. Full article

This study examines how the city’s evolving spatial structure shapes its thermal environment. Using Google Earth Engine (GEE) and the Local Climate Zone (LCZ) scheme, we tracked structural changes across Chengdu and its central districts (Jinjiang and Wuhou) in 2017, 2021, and 2025. We then combined the Weather Research and Forecasting (WRF) model with the NSGA-II algorithm. This allowed us to explore links between LCZ patterns and the Universal Thermal Climate Index (UTCI) in the urban center. Results confirm a strong but non-linear relationship between built form and the local climate. Optimized scenarios, respecting practical planning constraints, show that rebalancing LCZ proportions can reduce peak temperatures in the core area by 1.72–2.75 °C. Future plans for Chengdu should therefore limit high-risk compact types (LCZ 1, 3, 8), expand mid-rise and open arrangements (LCZ 4, 5), and preserve or restore natural surfaces (LCZ A–C) to achieve a more thermally equitable urban landscape. Full article

This article compares selected fire safety regulatory systems in Japan, China, the United States, and the EU/UK, interpreted through the lens of responsive architecture and the implementation of digital technologies—building information modelling (BIM), digital twins (DTs), artificial intelligence (AI), and the Internet of Things (IoT). The study adopts a qualitative approach based on a structured review of legal acts, technical standards, public-sector reports, and the scientific and professional literature, organised using a common analytical framework. First, the analysis identifies shared foundations across regimes: the primacy of life safety, mandatory detection and alarm functions, fire compartmentation, requirements for protected means of exit, and the increasing importance of documenting the operational status of protection measures. Then, it contrasts key differences, including the permissibility of performance-based design (PBD), the degree to which digital documentation is formally recognised, organisational enforcement models, and cybersecurity approaches for integrated fire alarm/voice alarm/building management/IoT ecosystems. Japan and selected Chinese cities combine stringent requirements with openness to dynamic solutions and urban-scale data platforms. The USA relies on a decentralised code-based ecosystem with a strong role for professional and industry bodies, while the EU/UK continues to strengthen harmonised standards and digital building registers, reinforced by lessons after the Grenfell Tower fire. Against this background, Poland is discussed as broadly aligned in goals and baseline technical requirements yet lagging behind in implementing PBD pathways, digital registers, formal BIM/DT integration, and minimum cybersecurity requirements. The proposed directions for change aim to create a more predictable regulatory and technical framework for the development of responsive architecture and dynamic fire safety systems in Poland. The study contributes to the sustainability literature by framing regulatory readiness for digital fire safety as a lifecycle resilience strategy, directly relevant to safe, resource-efficient, and inclusive built environments. Full article

Built heritage is increasingly affected by climate-driven processes, yet its capacity to inform broader understandings of urban environmental change remains insufficiently explored. Here, we synthesize the recent literature (2020–2024) on the application of the Historic Urban Landscape (HUL) approach to the integrated management of cultural heritage under climate risk, reframing the historic built environment as a multi-scale diagnostic medium for climate–urban interactions. We analyze the steps and tools employed to support decision-making across territorial planning, risk assessment, and heritage governance in the papers selected from Web of Science, Science Direct, and Scopus databases. Results show that the approach is a flexible analytical framework that allows the integration of heterogeneous data, multi-criteria evaluations, and diverse stakeholder perspectives across spatial and temporal scales. Information modeling tools are shown to play a central role in structuring territorial knowledge, identifying patterns of vulnerability, and supporting comparative analyses across urban contexts. Nonetheless, significant challenges persist, including limited quantification of climate-induced degradation mechanisms, uncertainties in linking vulnerability assessments to predictive models, structural constraints on participatory implementation, and a tendency to apply the approach as a checklist due to inadequate understanding of its holistic dimensions. Overall, the HUL approach emerges as a scalable and transferable framework for embedding cultural heritage within climate research, advancing the conceptual integration of built heritage into resilience science and sustainability-oriented urban systems. Full article

Fine-scale accounting of land use carbon budgets and identification of their driving factors provides an essential scientific basis for constructing green and low-carbon territorial spatial systems. This is of great significance for optimizing territorial spatial structure and promoting low-carbon development in urban agglomerations. Taking the Central Guizhou Urban Agglomeration as the study area, this study employed a composite carbon coefficient method to construct a 30 m × 30 m grid-based carbon budget index and quantitatively assessed carbon budget changes induced by land use transitions from 2000 to 2024. POI data and a quantile regression model were further integrated to analyze the dominant spatial characteristics associated with carbon budgets, and a carbon budget monitoring and early-warning index was developed to delineate risk zones. The results show that: (1) From 2000 to 2024, the total area of land use change reached 0.95 × 10⁴ km² in the Central Guizhou Urban Agglomeration, accounting for 17.68% of the total land area, and leading to a net increase of 2.3821 million tons of carbon emissions. This increase was primarily associated with the conversion of cultivated land to construction land, with an accelerated growth rate observed in the later period. (2) The spatial patterns of carbon budgets and carbon emission risk levels exhibit a distinct “core–periphery” structure, with high carbon emission levels concentrated in built-up urban areas and lower levels observed in peripheral ecological land. (3) The expansion of construction land is the dominant contributor to the increase in net carbon emissions; industrial, transportation, and residential spaces exert significant positive driving effects, whereas commercial and service spaces show a negative association. (4) Carbon budget risk zoning based on dominant spatial characteristics identifies Guiyang and Anshun as extremely high-risk areas. The results further suggest that reducing carbon-increment spaces and increasing carbon-reduction spaces may play an important role in territorial carbon budget optimization. The integrated “accounting–driving–monitoring” analytical framework established in this study provides a scientific basis for territorial spatial optimization and carbon emission reduction in mountainous urban agglomerations. Full article

Ecosystem services (ESs) support human well-being, but their integrated assessment in urban green spaces remains challenging, particularly at the project scale, where finer spatial resolution (tens of meters) is required. Historical parks are complex socio-ecological systems with non-linear ES interactions. This study develops a design-oriented framework to assess how restoration interventions influence regulation, maintenance, and cultural ES potential provision. Indicators derived from field surveys and established models were selected according to CICES V5.2 and adapted to ecological and cultural features of historical parks. Survey units were defined for each ES section to enable a spatially explicit comparison between current and design scenarios. A normalized scoring system was applied to evaluate category-level changes and overall interaction patterns. The framework was tested on the restoration project of Monza Park (northern Italy). Results show a marked increase in cultural and regulation services (+28% and +17%, respectively), while maintenance services exhibited a slight decrease (−3%). These trends are reflected in the Cumulative Indicator Score (CIS), indicating an overall positive balance of ES provision in the design scenario. The Design Effectiveness Score (DES) showed consistently non-negative values (DES ≥ 0), reaching maximum effectiveness in transitions to woody vegetation (DES ≈ 1). The Synergy–Trade-off Score (STS) confirmed a general increase in ES supply across all categories, with a clear prevalence of synergies over trade-offs. The proposed framework supports the data-driven, spatially explicit evaluation of design alternatives and can guide decision-making in historical park restoration. Full article

Ongoing urbanization continuously reshapes water quality, habitat structure, and biological communities in river ecosystems; however, its impacts on host-associated microbial communities remain poorly documented. The fish gut microbiota, a critical interface between the aquatic environment and host physiology, is widely recognized as an integrative indicator of both environmental change and host ecological traits. This study established a continuous urbanization gradient along Shanghai’s Suzhou River, spanning from suburban areas through the outer and inner ring roads to the city center. Five common wild fish species (Coilia nasus, Hemiculter bleekeri, Culter alburnus, Acheilognathus macropterus, and Pseudorasbora parva) were collected, and their gut microbiota were characterized via high-throughput 16S rRNA gene sequencing. Significant variation in OTU richness, alpha diversity, and community structure was observed across urbanization gradients and among fish species. Principal coordinate analysis revealed that samples from suburban areas were structurally distinct from those collected in other zones, whereas inner-ring and urban-core areas exhibited substantial compositional overlap. Taxonomic analysis revealed that Firmicutes and Pseudomonadota dominated all samples; however, their relative abundances and genus-level composition varied considerably among fish species and across the urbanization gradient. PICRUSt-based functional prediction indicated that metabolic pathways predominated, particularly those involved in global and overview maps, carbohydrate metabolism, amino acid metabolism, energy metabolism, and metabolism of cofactors and vitamins. Collectively, these findings demonstrate that fish gut microbial communities exhibit spatial structuring along the urbanization gradient, with species-specific responses linked to ecological traits. This study provides valuable data on host-associated microbial communities in urban rivers and offers a reference for incorporating microbial indicators into urban water ecological assessments. Full article

The rapid growth of cities and expansion of impervious surfaces have intensified surface runoff problems and urban flooding risk. This scenario, exacerbated by the effects of climate change, demands sustainable and integrated solutions. Thus, this study evaluates the pre-feasibility of implementing sustainable urban drainage systems (SUDS) in the Monteverde neighborhood in Montería, Colombia; an area that is critically affected by floods during rainfall events. Using the storm water management model (SWMM) and hydrological simulations based on design hyetographs for different return periods, the performance of a conventional drainage system was compared with five scenarios using SUDS. To determine the modeling scenarios, a decision-making method through the analytic hierarchy process, AHP, was used to select the most appropriate SUDS. The results showed that implementing storage tanks reduces peak flows at outlets 1 and 2 up to 50%, while bioretention zones and rain gardens in isolation showed reduced effectiveness (<6%). Combining strategies slightly improves overall efficiency, although the impact keeps being dominated by tanks. This study demonstrates that the incorporation of SUDS in vulnerable urban areas lessens water risks, strengthens urban resilience, promotes rainwater harvesting, and eases the transition to a more sustainable infrastructure. In addition, it proposes a methodology that can be replicated in other similar Latin American cities. Full article

Urban accessibility is commonly evaluated using static spatial indicators, which assume stable travel conditions throughout the day. Road congestion, network saturation, and service variability change the function and experience of the built environment (BE). This study tests the Temporal City Framework (TCF) by examining how time of day (TOD) reshapes urban accessibility and travel behaviour with varying levels of congestion. Using 30,288 trip records from the 2022 US National Household Travel Survey (NHTS), duration is operationalised as a sixth dimension of the BE. A time-normalised impedance metric, measured in minutes per mile (MPM), is used that captures realised congestion independently of distance. Temporal impedance (TI) varies strongly with TOD, with substantially higher MPM during peak and midday periods than at night. Compared with nighttime conditions, midday travel requires approximately 19% more time per mile. This indicates a measurable contraction in functional accessibility under identical BE conditions. The TI model outperforms duration-only models, with impedance remaining dominant when both measures are included. These results support interpreting duration as a structural dimension of urban accessibility. TI significantly increases the relative likelihood of active and public transport compared to private cars, even after accounting for absolute trip duration. Hired transport modes (taxi and ride-hailing services) are most prevalent at night, reflecting a greater reliance on on-demand services outside regular daytime schedules. This study tests duration as a structural dimension of the BE by operationalising time-normalised TI. Associations are interpreted as trip-level behavioural constraints rather than causal effects. Planning frameworks based on static travel times systematically misrepresent exposure, equity, and travel mode feasibility. Time-stratified accessibility metrics should therefore be integrated into transport and land-use evaluation and associated policies. Full article

Effective incident management is a cornerstone of transportation system performance, influencing roadway clearance times (RCTs) and the risk of secondary crashes. This study investigated how towing regulations involving large commercial vehicle crashes and jurisdictional variations affect the management of large-vehicle crashes, focusing on the relationship between regulatory frameworks, incident duration, and secondary crash occurrence with the state of Tennessee as a case study. The objective was to determine whether differences in towing policies, operational mandates, and rural/urban contexts lead to measurable changes in clearance efficiency. A multi-year dataset of more than 770,000 traffic incidents and 4400 towing-involved large-vehicle crashes from 2017 to 2022 was analyzed. Statistical methods, including two-sample testing and hazard-based survival modeling, were applied to evaluate the impact of towing regulations and operational protocols on roadway clearance and secondary crash patterns. The results consistently showed that strong performance-based towing regulations, such as mandated maximum response times and standardized training and equipment requirements, were associated with significantly lower average RCTs. Jurisdictions with enforced rapid-response mandates achieved average clearance durations of approximately 120–130 min, even under high incident volumes, compared to over 150 min in areas without performance benchmarks or with more complex procedural requirements. A pronounced rural–urban divide was observed, with incidents outside urbanized areas averaging 30–40% longer clearance times, largely due to limited towing resources, longer dispatch distances, and less stringent regulatory enforcement. Secondary crash analysis identified that more than 90% of secondary collisions were linked to crashes requiring towing, with the majority occurring within 20 min and 0.5 miles of the primary incident, underscoring the direct connection between delayed clearance and safety risk. These results carry direct implications for transportation policy and incident management practice by providing empirical evidence that standardized, performance-based towing regulations can meaningfully reduce RCTs and secondary crash risk, particularly when paired with investments in rural towing infrastructure Full article

Global climate change continues to intensify, leading to an increase in extreme meteorological disasters characterized by high intensity, frequency, and extensive impact. Chinese cities are facing increasingly severe flood disaster risks. As the fundamental unit of the urban system, scientifically quantifying a community’s post-disaster recovery capacity provides a crucial basis for formulating disaster prevention and mitigation strategies. Existing research has largely focused on either quantitative resilience assessment of communities or the functional recovery of specific systems within communities, falling short of meeting the quantitative needs for assessing community functional recovery after flood disasters. Given this, this paper aims to construct a community functional recovery model based on different land use types to precisely quantify the recovery trajectory of community functions. First, the MIKE 21 two-dimensional hydrodynamic model is employed to simulate 100-year and 200-year flood scenarios, obtaining dynamic inundation data at the community scale. Subsequently, a semi-Markov process is adopted to model the recovery of individual buildings, with the aggregated building functions within the community summarized to derive building recovery curves. A road network topology model is constructed using the Space L method, and network global efficiency is applied to quantify community road functionality. Green space functional loss is quantified based on the percentage of inundated areas. Finally, calculation is performed based on the proposed dual-layer computational framework consisting of a connectivity layer and a functional layer, and the overall community functional recovery curve after the disaster is generated, thereby achieving precise quantification of the recovery process. The research findings indicate that increased disaster intensity significantly amplifies functional losses and recovery delays. Concurrently, distinct land use types exert markedly different impacts on community recovery. This study quantitatively reveals the phased dominant roles of various land use types throughout the community recovery process, providing a scientific basis for formulating phased, prioritized resilience enhancement strategies. Full article

Tourism has become a structural driver of land-system transformation, influencing urban restructuring, rural land consumption, coastal development, and housing dynamics. Although tourism sustainability has received growing scholarly attention, less systematic evidence exists on how land governance and spatial planning frameworks mediate tourism-related land-use change. This study presents a systematic review of peer-reviewed journal articles published between 2000 and 2025 examining the relationship between spatial planning, land-use regulation, and tourism development. Following PRISMA guidelines, a structured search strategy and multi-stage screening process were applied using predefined inclusion and quality criteria, resulting in a final dataset of 58 studies. The findings indicate that tourism-driven land transformation is shaped by interconnected governance layers, including statutory planning instruments, institutional coordination mechanisms, and land administration infrastructures. However, these dimensions are rarely analyzed within an integrated framework. By synthesizing tourism planning and land administration scholarship through a land governance perspective, this review clarifies how regulatory tools and administrative systems interact in shaping spatial outcomes across scales. The study offers a structured basis for future comparative research and for more coherent policy responses to tourism-related land governance challenge. Full article

Climate change and rapid urbanization are intensifying urban pluvial flooding and threatening sustainable urban development. This study proposes a three-stage, four-dimensional framework (TSFD-UPFR) to assess urban pluvial flood resilience across resistance, response, and recovery phases that integrate natural, infrastructural, social, and economic dimensions. Using a representative urban catchment affected by a typical extreme rainfall event, we couple hydrological–hydrodynamic simulations with multi-source remote sensing and socio-economic indicators at a 100 m grid resolution to enable spatially explicit assessment. The results indicate moderate overall resilience with pronounced spatial heterogeneity. Resistance is primarily constrained by drainage capacity and impervious surfaces, response is shaped by road connectivity and public service accessibility, and recovery is determined by essential facility restoration and economic support. Low-resilience clusters are concentrated in dense built-up areas and transport hubs, revealing structural weaknesses in adaptive capacity. By linking flood processes with socio-economic recovery dynamics, the framework captures cross-stage interactions within urban systems. The findings support climate-adaptive planning, targeted infrastructure investment, and resilience-oriented governance, contributing to sustainable and equitable urban transformation in megacities facing intensifying extreme rainfall. Full article