Search Results (1,618)

The escalating global contradiction between water supply and demand has imposed novel imperatives on regional water security within the paradigm of resilient city development. To elucidate the supply–demand dynamics of water provisioning services under heterogeneous institutional contexts, this study selected the Guangdong–Hong Kong–Macao (GHKM) region as the empirical study area. Employing the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, we coupled meteorological, land-use/land-cover (LULC), and pedological data to quantify the provisioning of water yield services in 2024. Concurrently, sector-specific water demands—encompassing agricultural, industrial, domestic, and ecological categories—were accounted for using statistical yearbooks. Subsequently, a Supply–Demand Index (SDI) was formulated to delineate the spatial matching patterns. The findings reveal pronounced spatial heterogeneity in water service provisioning; high-value zones are predominantly aggregated along the western and southern coastal belts, whereas low-value zones are dispersed across the northern mountainous terrains. Based on the SDI classification, the study area comprises 12 supply-surplus, 6 supply–demand-equilibrium, and 5 supply-deficit administrative units. Notably, the northern Guangdong mountainous region assumes a critical ecological role in water conservation, whereas the core megalopolises of the Pearl River Delta exhibit an acute dependency on extrinsic water subsidies, with Macao demonstrating a distinct ecological deficit in water provisioning. Furthermore, this study uncovers the overestimation artifact of water yield estimations over urban impervious surfaces, thereby providing a robust empirical foundation for the cross-regional synergistic governance and adaptive management of water resources. Full article

Although recreational experience segmentation is widely used in coastal tourism research, existing motivational frameworks have been developed primarily in island and protected-area destinations, leaving urban, open-access, developing-country contexts theoretically underexplored. This study addresses that gap by identifying the dimensions of recreational experience and market segments for the city of Salinas, Ecuador—an accessible, family-oriented, urban coastal destination—to advance sustainable tourism management. Using a quantitative, cross-sectional design, data were collected through a structured questionnaire administered to 385 tourists; 374 cases with complete scale responses were retained for analysis. An exploratory factor analysis (EFA) identified seven motivational dimensions: environment and sustainable recreational resources, learning and knowledge, affective well-being and creative harmony, interest and enjoyment in the experience, aquatic natural resources and wildlife, cognitive stimulation and emotional connection, and hedonic well-being. A K-means cluster analysis, validated through the elbow method (inflection at k = 3) and silhouette coefficient (0.25), revealed three distinct tourist segments: intensive recreational tourists (n = 183; 48.9%), moderate recreational tourists (n = 136; 36.4%), and passive recreational tourists (n = 55; 14.7%). Chi-square tests confirmed significant associations between clusters and sociodemographic variables including gender, marital status, and number of visits. This study offers four theoretical contributions: it reports a more detailed motivational factor structure than previously documented three- and four-factor models for coastal destinations; it proposes recreational amotivation—grounded in self-determination theory—as a candidate visitor profile that merits further theoretical and empirical validation; it advances a destination-type-sensitive motivational framework; and it provides boundary condition evidence clarifying the contextual scope of recreational experience theory. These findings offer actionable segmentation tools for destination managers seeking to differentiate and sustain coastal tourism markets. Full article

Urban Heat Island (UHI) effects are increasingly affecting Mediterranean coastal cities, where climate change, urbanization, and seasonal tourism intensify thermal stress and environmental vulnerability. In this context, climate-oriented planning and green infrastructure are recognized as key strategies for urban adaptation. This study investigates the spatiotemporal evolution of Land Surface Temperature (LST) and vegetation cover in the coastal municipality of Lignano Sabbiadoro (northeastern Italy) through the analysis of Landsat imagery acquired between 1984 and 2023. Summer LST and Normalized Difference Vegetation Index (NDVI) maps were derived from June–August observations and used to assess long-term thermal dynamics, vegetation patterns, and Urban Heat Island development. Meteorological data indicate a significant increase in mean annual air temperature, with a warming trend of approximately 0.57 °C per decade between 1984 and 2023. Correspondingly, Landsat-derived LST maps reveal a marked intensification of summer surface temperatures, with mean summer LST increasing from 32.16 °C in 1984–1993 to a peak of 35.91 °C in 2004–2013, followed by a slight decrease to 35.77 °C during 2014–2023. During the same period, the proportion of municipal surfaces characterized by temperatures above 35 °C increased from 10.7% to more than 60%, while cooler areas (<30 °C) declined from 17.7% to 2.3%. The comparison between LST and NDVI patterns revealed a persistent inverse relationship between vegetation cover and surface temperature, with coastal pinewoods, green spaces, and water bodies consistently exhibiting lower thermal values than densely urbanized sectors. A key methodological contribution of the study is the operational integration of satellite-derived thermal remote sensing into the Green Plan of Lignano Sabbiadoro. LST mapping was used to identify priority areas for climate adaptation measures, including ecological corridors, wooded landscape connections, urban green corridors, and depaving interventions. The results demonstrate how multi-temporal thermal analysis can support evidence-based planning by linking climate assessment with the spatial prioritization and design of green infrastructure strategies. The proposed workflow provides a transferable framework for integrating remote sensing into climate-informed planning processes in Mediterranean coastal cities and other urban contexts increasingly exposed to heat-related risks. Full article

With the accelerated advancement of smart city construction, the development of urban underground space in coastal areas faces significant safety challenges due to randomly distributed granite boulders. Conventional geophysical methods often struggle to identify these heterogeneous bodies efficiently. This study proposes a comprehensive detection approach fusing the Cone-based Transient Electromagnetic Method (CTEM) and Microtremor Array Surveying. Taking the eastern coast of Jiaozhou Bay, Qingdao, as the research area, we integrated borehole data to validate the geophysical interpretation. The results demonstrate that the joint inversion accurately delineates four stratigraphic interfaces with depths consistent with borehole logs: the artificial fill (bottom at ~8–12 m), Quaternary sediments (~28–33 m), strongly weathered granite (~59–74 m), and moderately weathered granite. Specifically, boulders within the Quaternary and strongly weathered layers are distinctly identified by dual high-value anomalies: high apparent resistivity (>220 Ωm, approximately 1.5–2 times that of the surrounding rock) and high shear-wave velocity (>660 m/s). Furthermore, the method effectively differentiates boulders from water-rich fractured zones, which exhibit contrasting low resistivity (<50 Ωm) and low shear-wave velocity (<420 m/s). These quantitative findings confirm that the fused CTEM and microtremor technique provides precise spatial localization and reliable identification of boulders in complex coastal geological environments. Full article

Urban ground collapse (UGC) threatens dense coastal cities because failures can occur abruptly beneath roads and buried lifelines. We developed a dynamic and interpretable machine-learning framework for UGC susceptibility assessment in Shenzhen, China. We integrated 1687 events from 2017 to 2024 with 20 predictors covering terrain, rainfall, drainage infrastructure and urban disturbance. Event-date rainfall was assigned to collapse samples, and background controls received year-constrained pseudo-event dates after spatial exclusion. Three tree-ensemble models were evaluated under random 75/25 testing, leave-one-district-out spatial validation and temporal hold-out testing. The selected LightGBM 1:5 model achieved ROC-AUC = 0.934, AP = 0.790 and BA = 0.860 in random testing, with more conservative ROC-AUC values of 0.905 and 0.884 under spatial and temporal validation. High-rainfall mapping expanded high and very high susceptibility zones from 4.60% to 15.26% and increased event capture from 19.32% to 58.92%. Grouped SHAP indicated comparable pipeline and rainfall contributions (26.01% and 25.13%). The leading predictors were pipe burial depth, road density and 30-day rainfall. PDP and spatial SHAP diagnostics highlighted high model responses where deep pipes coincided with high antecedent rainfall or dense roads in mature urban cores. This framework supports the rainfall-conditioned, mechanism-informed susceptibility diagnosis for early warning and mitigation. Full article

The deterioration of SBS-modified asphalt under coupled temperature–ultraviolet (UV)–coastal humidity conditions is significantly accelerated in coastal regions because of seawater evaporation, leading to severe durability degradation of pavement materials. However, the performance evaluation laws and underlying regeneration mechanisms under such coupled environmental aging conditions remain insufficiently understood. Therefore, taking Shanghai as a representative coastal city, a temperature–UV–coastal humidity coupled aging system was established to simulate the saline and humid environment of coastal regions. Industrial animal oil and waste engine oil were selected as regeneration materials, and a multi-scale experimental approach was adopted to evaluate the performance recovery of aged asphalt. The results indicate that both regeneration materials effectively restore ductility and improve rheological behavior, while reducing viscosity but cause a measurable decrease in softening point, indicating a reduction in high-temperature stability. Industrial animal oil shows superior improvement in ductility, whereas waste engine oil exhibits stronger effects on viscosity reduction and microstructural regulation. A content of approximately 6% was recommended as a practical content to balance performance recovery and high-temperature stability under the tested coupled-aging condition. Microstructural analysis confirms that the regeneration mechanism is dominated by light component replenishment and colloidal structure reconstruction rather than chemical modification of SBS chains. Full article

Urban surface water networks are closely associated with the urban land surface thermal environment, but the spatial non-stationarity of their relationships with land surface temperature (LST) remains insufficiently understood. This study examined relationships between water network indicators and LST in Fuzhou. Following scale-sensitivity analysis to select the analytical grid scale, this study used global correlation and regression analyses to identify key indicators and applied multiscale geographically weighted regression (MGWR) to examine spatial non-stationarity in their relationships with LST. Based on the selected 150 m grid scale, the results showed the following: (1) Water coverage ratio (WCR), water body shape index (SI), and water network density (D) were retained as key explanatory variables, with WCR showing the strongest negative association with LST. (2) The relationships between water network indicators and LST showed spatial non-stationarity. WCR showed the most stable negative local association with LST, especially in built-up areas with higher background heat loads, whereas the local associations of SI and D were more context-dependent. These findings suggest that thermal-environment-oriented planning for urban surface water networks should prioritize water coverage while considering water network structure, water body morphology, the surrounding built environment and land cover conditions. These associations can inform spatially differentiated planning of urban surface water networks in comparable subtropical coastal cities. Full article

Urban flood resilience depends not only on the scale of infrastructure investment, but also on whether such investment can be translated into observable flood-mitigation outcomes. Focusing on the transformation from infrastructure response to flood outcomes, this study uses panel data for 21 prefecture-level cities in Guangdong Province from 2016 to 2022. Annual maximum monthly precipitation is used to represent rainfall pressure, stormwater pipe density to represent infrastructure scale, and the number of reported flood events to represent the outcome variable. A two-way fixed-effects Poisson pseudo-maximum likelihood (PPML) model is employed. The results show that, in the full sample, rainfall pressure is positively, but not significantly, associated with reported flood occurrence, while stormwater pipe density does not exhibit a stable negative moderating effect. The main conclusion remains broadly unchanged when alternative outcome and precipitation indicators are used, when pipe density is lagged by one period, and when a conservative sample is adopted. Extended analysis provides only limited weak negative evidence for Pearl River Delta cities, and this evidence is not robust across alternative specifications. The findings indicate that pipe length per unit of built-up area primarily reflects the scale of infrastructure provision and cannot be directly equated with the operational performance of the drainage system. By separating response inputs from outcome performance, this study reveals the conditional nature of the transformation from infrastructure scale to operational performance in urban flood resilience research and provides empirical support for a shift from infrastructure expansion toward performance-oriented and integrated governance in high-density coastal cities. Full article

Rapid urbanization has generated substantial economic growth but has also intensified pressure on the environment. China’s New-Type Urbanization Policy (NTU) was designed to promote people-centered, smart governance, and green development. However, whether the NTU policy has improved the coordination between urbanization and environmental quality remains insufficiently examined. Using panel data in China from 2010 to 2021, this study constructs an urbanization–environment coupling coordination degree index based on satellite-derived China’s High-resolution Eco-Environmental Quality dataset and applies a continuous difference-in-differences model to evaluate the impact of NTU policy intensity. The results show that greater NTU policy intensity is associated with significant improvements in urbanization–environment coordination after controlling for pre-existing socioeconomic, ecological, and geographical differences across cities. This finding is consistent with a corrective effect: rather than simply expanding urban scale, NTU appears to help offset the misalignment between urban development and environmental quality. Conditional analyses further suggest that the estimated policy effect is more readily observed where industrial structures are more advanced and local attention to ecological governance is stronger, indicating that these conditions shape the extent to which NTU can be translated into coordination gains. Heterogeneity analyses show that the estimates are statistically more robust in eastern, coastal, and non-resource-based cities, while the comparison across green-coverage groups remains inconclusive because the low-coverage group has a larger but less precisely estimated coefficient. Overall, the findings suggest that NTU has corrective potential, but that its effect is conditional rather than uniform across cities and depends on local governance, industrial, and ecological circumstances. Full article

Coastal cities protected by artificial structures are vulnerable to wave overtopping during typhoons, where flooding can occur even when the still water level stays below the structure crest. This study develops EurOtop-based wave overtopping modules within the cross-scale SCHISM-WWM modelling framework and applies the coupled model to Marine City, Busan, South Korea. At each time step, the module extracts the local water level and wave conditions at a coastal-structure pair-node, computes the overtopping or overflow discharge from the EurOtop formulae while accounting for wave direction, roughness reduction, and crest-width transfer losses, and injects it as a landward source term for inland flood propagation. The framework is evaluated against two typhoon events. For Typhoon Hinnamnor in 2022, comparison with the CCTV-based overtopping record reproduces the timing and intensity of overtopping. For Typhoon Chaba in 2016, validation against field-surveyed inundation marks shows that the modelled maximum inundation depth matches the observed spatial pattern and the survey-point observations to within a mean absolute difference of about 12 cm. These results demonstrate the framework’s applicability to overtopping-induced compound flooding in urbanised coastal cities and, since it is fully coupled within the SCHISM-WWM codebase, its capacity to incorporate further drivers such as pluvial and fluvial flooding. Full article

The use of Satellite-Derived Bathymetry (SDB) constitutes an efficient, cost-effective, time-saving, and scalable approach for generating high-resolution shallow-water bathymetry. In this context, SDB can be proven to be a valuable method for supporting bathymetric surveys of submerged archaeological sites. This paper focuses on the ancient city of Asopos, located on the coast of the modern village of Plytra in Laconia, SE Peloponnese, Greece. The site occupies an extensive coastal area characterised by numerous ancient remains and geomorphological features distributed along the shoreline and within the nearshore zone. To achieve the objective of producing a very-high-resolution SDB map, one empirical and four machine learning approaches were evaluated: (a) the quadratic Stumpf band-ratio model; (b) Categorical Boosting; (c) Random Forest; (d) Extreme Gradient Boosting, with all models trained using the same three optimal spectral band ratios; and (e) the CatBoost model trained using principal components derived from a Principal Component Analysis of the multispectral dataset. These approaches were developed using multispectral WorldView-2 imagery and 208 in situ depth measurements as ground truth, collected across a different range of depths and distances from the coastline. Pan-sharpened imagery was used for visual interpretation. Model accuracy was assessed using an additional validation dataset of 57 depth measurements. This combined approach demonstrates that VHR SDB mapping of the nearshore zone is highly effective when employing three band ratios involving the blue, green, and yellow bands, achieving a root mean squared error of less than 1 m, and can therefore serve as a reliable method for shallow-water geoarchaeological investigations. Full article

Rapid urbanisation and climate change intensify heat, drought, wind exposure, and salinity risks in arid coastal cities, while simultaneously increasing dependence on trees for microclimate regulation and public-space quality. However, integrated evidence linking taxonomic concentration, spatial structure, tree dimensions, and current vitality remains scarce for Central Asian cities on the Caspian coast. This study characterised 13,951 trees across 10 green spaces in Aktau, Kazakhstan, belonging to 10 species, 10 genera, and 7 families, using a comprehensive inventory and an integrated taxonomic, spatial, and vitality framework. Stand density ranged from 27.1 to 510.3 trees ha⁻¹. Ailanthus altissima and Platycladus orientalis accounted for 42.74% and 23.13% of all trees, respectively, and together formed 65.87% of the inventory. Two species, two genera, and one family exceeded the indicative 10/20/30 diversification thresholds. The Shannon index ranged from 1.19 to 2.00, Pielou evenness from 0.52 to 0.87, and the share of the dominant species from 24.2% to 63.2%. Of all trees, 12,205 (87.48%) were classified as in good condition, but three sites accounted for 83.0% of all satisfactory or unsatisfactory trees. Maclura pomifera and Gleditsia triacanthos had the highest proportions of trees in good condition (96.3% and 94.2%), whereas Catalpa speciosa had the lowest (66.0%). The inventory, therefore, reveals a favourable current condition, but limited taxonomic redundancy and localised management hotspots. The findings provide a baseline for climate-resilient urban landscape planning based on gradual diversification, site-specific irrigation and soil management, control of invasive recruitment, and repeated monitoring of condition, growth, and mortality. Full article

High-density commercial areas in northern monsoon coastal cities face dual microclimate challenges: hot summers and harsh winters. This study aims to optimize year-round outdoor thermal comfort (Physiological Equivalent Temperature, PET) by exploring morphological optimization strategies in Qingdao. Combining field observations with ENVI-met simulations, we evaluated the impact of building density, street aspect ratio (H/W), and orientation. The results reveal a fundamental “seasonal mechanism conflict.” In summer, a 45% density point-tower configuration with a deep canyon profile (H/W ≈ 2.5) maximizes shade and sea-breeze ventilation. Conversely, in winter, a 35% density enclosed topology with an open profile (H/W ≈ 1.6) optimally blocks cold northwesterly monsoons and increases solar gain. To resolve these conflicting seasonal requirements, we propose a dynamic morphological equilibrium. We recommend adjusting the H/W ratio dynamically between 1.6 and 2.5 and adopting a southeast block orientation of 15–30° to synergistically guide summer breezes while blocking winter winds. Ultimately, this study shifts the design paradigm from static parameters to dynamic seasonal trade-offs, offering actionable morphological guidelines for climate-resilient built environments. Full article

Rapid urbanization presents a fundamental challenge to global sustainable development, as urban expansion increasingly conflicts with resource constraints, ecological carrying capacity, and carbon emission mandates. Serving as a highly spatially heterogeneous laboratory, China offers a critical context for embedding green development into urban efficiency assessments. This study reconceptualizes new urbanization efficiency (NUE) through a multidimensional framework encompassing resource inputs, coordinated development processes, and sustainable outcomes. Using a panel of 281 prefecture-level cities, we evaluated NUE via a remote-sensing-constrained Super-SBM model, utilizing LISA time paths and an interpretable spatial machine learning framework (GWR-XGBoost-SHAP) to unpack its spatiotemporal dynamics. Key findings indicate: (1) China’s NUE exhibited a fluctuating upward trajectory, transitioning from an east-high/west-low to a south-high/north-low spatial pattern. (2) Spatiotemporal analysis revealed strong spatial inertia and profound path dependency in North China, characterizing it as a persistent low-value basin, whereas southeastern coastal cities demonstrated dynamic, path-breaking trajectories. (3) While green development intensity, industrial upgrading, and technological innovation emerged as primary drivers, they operate through complex nonlinear mechanisms. Specifically, green development and innovation exhibit threshold-triggered synergies, population agglomeration acts as a nonlinear amplifier, and external openness presents context-dependent negative interactions. These findings refine NUE measurement methodologies and provide a transferable analytical framework to inform differentiated, place-based urbanization policies for regions navigating the friction between urban growth and ecological limits. Full article

The paper addresses the intersection between modern built heritage preservation and Climate-Aided Design (CADe) processes in fragile coastal Mediterranean contexts. The study focuses on the city of Beirut in Lebanon, part of the Eastern Mediterranean and Middle East (EMME) region and considered a climate change hotspot facing extreme challenges. Rapid urbanization and socio-political instability, especially during the twentieth century, have undermined the city’s ability to mitigate and adapt to future climate change scenarios. Moreover, Beirut’s modern built heritage faces a constant threat of demolition due to the absence of protective legislation, compounded by aggressive real-estate development ambitions. The hypothesis is that the integration of climatic data and regenerative design with modern cultural heritage classification frameworks can aid the preservation process, drive a more adaptive and inclusive approach to urban regeneration, and inform legislative integration of climate adaptation in conservation frameworks. To test this hypothesis, a multi-scalar case-study-based methodology is adopted using a combination of digital tools to assess and analyze the current and future impacts of climate change on two main case studies. First, the St. George Hotel & Bay, one of the first reinforced concrete recreational buildings in the city, was built during the French Mandate (1920–1946) and is vulnerable to sea-level rise, flooding, and demolition. Second, the Beirut City Center “The Egg”, a Brutalist structure built during Beirut’s modernist “golden era”, which is prone to structural deterioration and demolition. The main objective is to highlight 20th-century built heritage as part of Beirut’s spatial narrative worthy of conservation and rehabilitation by analyzing their capability to adapt to, mitigate, or benefit from future environmental risk. Ultimately, the study explores their potential to catalyze climate-resilient urban regeneration practices in the city. Results show that the integration of current and future forecast environmental analyses informed early preservation and intervention decision-making stages to position 20th-century modern built heritage as an asset to climate action in addition to being a socio-cultural and economic asset. Full article