Search Results (1,323)

Designing deep foundations in densely urbanized areas presents significant challenges due to complex soil conditions, high groundwater levels, and the proximity of sensitive infrastructure. This study addresses these challenges through the development and numerical analysis of a combined pile–raft foundation (CPRF) system for a 75 m tall hotel tower in Frankfurt am Main, Germany. The construction site is characterized by heterogeneous soil layers and is located adjacent to a historic quay wall and bridge abutments, necessitating strict deformation control and robust structural performance. A comprehensive three-dimensional finite element model was developed using P_LAXIS 3D to simulate staged construction and soil–structure interaction (SSI). The CPRF system comprises a 2 m thick triangular raft and 34 large-diameter bored piles (1.5 m in diameter, 40–45 m in length), designed to achieve a load-sharing ratio of 0.89. The raft contributes significantly to the overall bearing capacity, reducing bending moments and settlement. The predicted settlement of the high-rise structure remains within 45 mm, while displacement of adjacent heritage structures does not exceed critical thresholds (≤30 mm), ensuring compliance with serviceability criteria. The study provides validated stiffness parameters for superstructure design and demonstrates the effectiveness of CPRF systems in mitigating geotechnical risks in historically sensitive urban environments. By integrating advanced numerical modeling with staged construction simulation and heritage preservation criteria, the research contributes to the evolving practice of performance-based foundation design. The findings support the broader applicability of CPRFs in infrastructure-dense settings and offer a methodological framework for future projects involving complex SSI and cultural heritage constraints. Full article

Accurate delineation of urban built-up areas is critical for urban monitoring and planning. We evaluated the performance and consistency of three widely used methods—thresholding, multi-temporal image fusion, and support vector machine (SVM)—across three major nighttime light (NTL) datasets (DMSP/OLS, SNPP/VIIRS, and Luojia-1). We developed a unified methodological framework and applied it to Wuhan, China, encompassing data preprocessing, feature construction, classification, and cross-dataset validation. The results show that SNPP/VIIRS combined with thresholding or SVM achieved highest accuracy (kappa coefficient = 0.70 and 0.61, respectively) and spatial consistency (intersection over union, IoU = 0.76), attributable to its high radiometric sensitivity and temporal stability. DMSP/OLS exhibited robust performance with SVM (kappa = 0.73), likely benefiting from its long historical coverage, while Luojia-1 was constrained by limited temporal availability, hindering its suitability for temporal fusion methods. This study highlights the critical influence of sensor characteristics and method–dataset compatibility on extraction outcomes. While traditional methods provide interpretability and computational efficiency, the findings suggest a need for integrating deep learning models and hybrid strategies in future work. These advancements could further improve accuracy, robustness, and transferability across diverse urban contexts. Full article

Flood impacts are intensifying due to the increasing frequency and severity of factors such as severe weather events, climate change, and unplanned urbanization. This study focuses on Briar Creek in Charlotte, North Carolina, an area historically affected by flooding. Three machine learning algorithms —bagging (random forest), extreme gradient boosting (XGBoost), and logistic regression—were used to develop a flood susceptibility model that incorporates topographical, hydrological, and meteorological variables. Key predictors included slope, aspect, curvature, flow velocity, flow concentration, discharge, and 8 years of rainfall data. A flood inventory of 750 data points was compiled from historic flood records. The dataset was divided into training (70%) and testing (30%) subsets, and model performance was evaluated using accuracy metrics, confusion matrices, and classification reports. The results indicate that logistic regression outperformed both XGBoost and bagging in terms of predictive accuracy. According to the logistic regression model, the study area was classified into five flood risk zones: 5.55% as very high risk, 8.66% as high risk, 12.04% as moderate risk, 21.56% as low risk, and 52.20% as very low risk. The resulting flood susceptibility map constitutes a valuable tool for emergency preparedness and infrastructure planning in high-risk zones. Full article

Climate change has intensified the occurrence of wildfires, increasing their frequency and intensity worldwide, and threatening sustainable development through ecological and socioeconomic impacts. Understanding the driving factors behind wildland–urban interface (WUI) fire events and predicting future wildfire hazards in WUI areas are essential for effective wildfire management and sustainable land-use planning. In this study, we developed a WUI fire hazard prediction model for China using machine learning techniques. Diagnostic attribution analysis was employed to identify key drivers of WUI fire hazards. The results revealed that the random forest-based WUI fire hazard model outperformed other models, demonstrating strong generalization capability. SHapley Additive exPlanations analysis revealed that meteorological factors are the primary drivers of WUI fire hazards. These factors include temperature, precipitation, and relative humidity. We further examined the evolution of WUI fire hazards under historical and future climate change scenarios. During the historical baseline period (1985–2014), regions classified as moderate and high hazards were concentrated in southern China. These regions include East China, South Central China, and Southwest China. Climate change exacerbates future WUI fire hazards in China. Projections under the high emission scenario (SSP5–8.5) indicate a rapid increase in WUI fire hazard indices in northern China by the end of the 21st century. Concurrently, the gravity center of high hazard areas is predicted to shift northward, accompanied by a substantial expansion in their area coverage. These findings highlight an urgent need to reorient fire management resources toward northern China under high-emission scenarios. Our findings establish a predictive framework for WUI fire hazards and emphasize the urgency of implementing climate-adaptive management strategies aligned with future hazard patterns. These strategies are critical for enhancing sustainability by reducing fire-related ecological and socioeconomic losses in WUI areas. Full article

The Adriatic–Ionian region is seismically very active and poses a major challenge for risk mitigation. Each country has developed laws, standards, and techniques to reduce seismic vulnerability. The ADRISEISMIC project created a database of existing regulatory and incentive frameworks, based on a comprehensive study conducted in six countries. The study covered seismic norms, building regulations, urban planning regulations, incentive frameworks, and post-earthquake planning. A comparative matrix was developed in which key parameters, such as year of issuance, references to EU regulations, level of enforcement, mandatory status, target groups, reference period in relation to earthquake occurrence, and consideration of cultural heritage, were analyzed. The database aims to support a harmonized strategy to reduce seismic vulnerability by promoting measures based on common reference standards. This increases safety, improves the built environment, and minimizes risks to people and nature. Particular attention will be paid to historic urban areas that are both vulnerable and rich in cultural heritage. The collected regulatory and incentive framework will serve as a basis for future research to support the identification of good practices and the formulation of customized roadmaps to apply them to reduce seismic vulnerability. Full article

The purpose of this study is to analyze the temporal and spatial characteristics of urban expansion and its influencing factors in Shaanxi Province, China, as well as simulate future land use and predict the situation and development stage of urban expansion. An understanding of these factors is conducive to the coordinated development of the population, resources, and the economy; the optimization of the urban spatial layout; and the high-quality development of Shaanxi Province. Research methods: With IDRISI Selva17 and the expansion intensity index, the CA–Markov model was adopted to simulate and predict the land use type based on the land use data of Shaanxi Province from 2000 to 2020. The urban built-up areas in Shaanxi Province have been continuously expanding in the past 30 years, especially since 2010, when expansion slightly accelerated, and the expansion intensity changed, first rising and then falling. The Kappa index is as high as 0.70, which further confirms the accuracy of the land use spatial evolution prediction by the CA–Markov model. By combining the urban expansion index with the simulation model, this paper provides an in-depth analysis of the internal relationship between the historical evolution of and future trends in construction land expansion because of the high-quality coordinated development of Shaanxi Province and extends the research perspective with creative ideas. Full article

The revitalization of post-industrial areas has emerged as a critical strategy for sustainable urban development, achieving a balance between economic, social, and environmental priorities. This study assesses the transformative capacity of revitalization strategies by conducting a comprehensive case analysis of “Radex Park Marywilska” in Warsaw, Poland. The analysis quantifies the benefits of revitalization in comparison to demolition and new construction methodologies. An examination of the revitalization initiative demonstrates that it yielded a total of PLN 41.15 million in benefits, with PLN 28.13 million attributed to direct cost savings and another PLN 13.02 million resulting from environmental improvements. In practical terms, this equates to a return of PLN 1.93 for every PLN 1 invested—a notably efficient outcome. The project transformed four industrial buildings, significantly increasing usable space in some (e.g., Building L1 by 345% and K1 by 21.6%) while slightly reducing it in others (B1 by 4.7% and I1 by 10.5%). From an environmental impact perspective, the success was staggering: 48,217 tons of carbon dioxide emissions were prevented, and 72,315 tons of building waste were diverted from landfills. To these figures, the study further adds a return in economic activity, the generation of new jobs, and improvement in local infrastructure. The retrofitting of historical buildings to contemporary standards has encountered numerous challenges; nonetheless, the implementation of circular economy principles has succeeded in negating such challenges. Generally, the results show economic, environmental, and social benefits of revitalization projects compared to new, greenfield projects. The case study provides valuable lessons to policymakers and urban planners, rendering adaptive reuse a fundamental approach in achieving sustainable urban development. Full article

Heavy rainfall events, characterized by extreme downpours that exceed 100 mm per day, pose an intensifying hazard to the densely settled valleys of the western Himalaya; however, their coupling with expanding urban land cover remains under-quantified. This study mapped the spatiotemporal exposure of built-up areas to heavy-day rainfall (HDR) across Jammu, Kashmir, and Ladakh and the adjoining areas by integrating daily Climate Hazards Group InfraRed Precipitation with Stations product (CHIRPS) precipitation (0.05°) with Global Human Settlement Layer (GHSL) built-up fractions within the Google Earth Engine (GEE). Given the limited sub-hourly observations, a daily threshold of ≥100 mm was adopted as a proxy for HDR, with sensitivity evaluated at alternative thresholds. The results showed that HDR is strongly clustered along the Kashmir Valley and the Pir Panjal flank, as demonstrated by the mean annual count of threshold-exceeding pixels increasing from 12 yr⁻¹ (2000–2010) to 18 yr⁻¹ (2011–2020), with two pixel-scale hotspots recurring southwest of Srinagar and near Baramulla regions. The cumulative high-intensity areas covered 31,555.26 km², whereas 37,897.04 km² of adjacent terrain registered no HDR events. Within this hazard belt, the exposed built-up area increased from 45 km² in 2000 to 72 km² in 2020, totaling 828 km². The years with the most expansive rainfall footprints, 344 km² (2010), 520 km² (2012), and 650 km² (2014), coincided with heavy Western Disturbances (WDs) and locally vigorous convection, producing the largest exposure increments. We also performed a forecast using a univariate long short-term memory (LSTM), outperforming Autoregressive Integrated Moving Average (ARIMA) and linear baselines on a 2017–2020 holdout (Root Mean Square Error, RMSE 0.82 km²; measure of errors, MAE 0.65 km²; R² 0.89), projecting the annual built-up area intersecting HDR to increase from ~320 km² (2021) to ~420 km² (2030); 95% prediction intervals widened from ±6 to ±11 km² and remained above the historical median (~70 km²). In the absence of a long-term increase in total annual precipitation, the projected rise most likely reflects continued urban encroachment into recurrent high-intensity zones. The resulting spatial masks and exposure trajectories provide operational evidence to guide zoning, drainage design, and early warning protocols in the region. Full article

Coupled grey and green infrastructure (CGGI) offers a promising pathway toward sustainable stormwater management in historic urban environments. This study compares CGGI and conventional grey infrastructure (GREI)-only strategies across four degrees of layout centralization (0%, 33.3%, 66.7%, and 100%) in the Quanzhou West Street Historic Reserve, China. Using a multi-objective optimization framework integrating SWMM simulations, life-cycle cost (LCC) modeling, and resilience metrics, we found that the decentralized CGGI layouts reduced the total LCC by up to 29.6% and required 60.7% less green infrastructure (GI) area than centralized schemes. Under nine extreme rainfall scenarios, the GREI-only systems showed slightly higher technical resilience (Tech-R: max 99.6%) than CGGI (Tech-R: max 99.1%). However, the CGGI systems outperformed GREI in operational resilience (Oper-R), reducing overflow volume by up to 22.6% under 50% network failure. These findings demonstrate that decentralized CGGI provides a more resilient and cost-effective drainage solution, well-suited for heritage districts with spatial and cultural constraints. Full article

Numerous studies have demonstrated that in residential areas of Western cities, both luxury and legacy effects significantly shape tree species diversity dynamics. However, the specific mechanisms driving these diversity patterns in China, where urbanization has progressed at an unprecedented pace, remain poorly understood. In this study we selected 20 residential settlements and 7 key socio-economic properties to investigate the change trend of tree diversity (2006–2021) and its socio-economic driving factors in Beijing. Our results demonstrate significant increases in total, native, and exotic tree species richness between 2006 and 2021 (p < 0.05), with average increases of 36%, 26%, and 55%, respectively. Total and exotic tree Shannon-Wiener indices, as well as exotic tree Simpson’s index, were also significantly higher in 2021 (p < 0.05). Housing prices was the dominant driver shaping total and exotic tree diversity, showing significant positive correlations with both metrics. In contrast, native tree diversity exhibited a strong positive association with neighborhood age. Our findings highlight two dominant mechanisms: legacy effect, where older neighborhoods preserve native diversity through historical planting practices, and luxury effect, where affluent communities drive exotic species proliferation through ornamental landscaping initiatives. These findings elucidate the dual dynamics of legacy conservation and luxury-driven cultivation in urban forest development, revealing how historical contingencies and contemporary socioeconomic forces jointly shape tree diversity patterns in urban ecosystems. Full article

In 1961, Los Angeles experienced the disastrous Bel Air fire, which swept through an affluent neighborhood situated in a hilly, WUI (wildland–urban interface) location. In January 2025, the city was devastated again by a nearly-simultaneous series of wildfires, the most severe of which took place close to the 1961 fire location. Disastrous WUI fires are, unfortunately, an anticipatable occurrence in many U.S. cities. A number of issues identified earlier remained the same. Some were largely solved, while other new ones have emerged. The paper examines the Palisades Fire of January, 2025 in this context. In the intervening decades, the population of the city grew substantially. But firefighting resources did not keep pace. Very likely, the single-most-important factor in causing the 2025 disasters is that the Los Angeles Fire Department operational vehicle count shrank to 1/5 of what it was in 1961 (per capita). This is likely why critical delays were experienced in the initial attack on the Palisades Fire, leading to a runaway conflagration. Two other crucial issues were the management of vegetation and the adequacy of water supplies. On both these issues, the Palisades Fire revealed serious problems. A problem which arose after 1961 involves the unintended consequences of environmental legislation. Communities will continue to be devastated by wildfires unless adequate vegetation management is accomplished. Yet, environmental regulations are focused on maintaining the status quo, often making vegetation management difficult or ineffective. House survival during a wildfire is strongly affected by whether good vegetation management practices and good building practices (“ignition-resistant” construction features) have been implemented. The latter have not been mandatory for housing built prior to 2008, and the vast majority of houses in the area predated such building code requirements. California has also suffered from a highly counterproductive stance on insurance regulation. This has resulted in some residents not having property insurance, due to the inhospitable operating conditions for insurance firms in the state. Because of the historical precedent, the details in this paper focus on the Palisades Fire; however, many of the lessons learned apply to managing fires in all WUI areas. Policy recommendations are offered, which could help to reduce the potential for future conflagrations. Full article

The landscapes of China’s multi-ethnic areas are rich in natural and cultural value, but they are threatened by homogenization and urbanization. This study aims to establish a method for identifying and classifying the landscape characters in China’s multi-ethnic areas to support the protection and sustainable development of the landscape in these areas. Taking the Miao Frontier Corridor as an example, the study optimized a parameterization method of landscape character assessment (LCA), integrated relevant cultural and natural elements, and used the K-means clustering algorithm to determine the landscape character types and regions of the Miao Frontier Corridor. The results show that (1) the natural conditions, ethnic exchanges, and historical institutions of the Miao Frontier Corridor have had a significant impact on its overall landscape; and (2) using ethnic group culture as a cultural element in LCA helps to reveal the unique cultural value of areas with different landscape characters. This study expands the LCA framework and applies it to multi-ethnic areas in China, thereby establishing a database that can serve as the basis for cross-regional landscape protection, management, and development planning in these areas. The research methods can be widely used in other multi-ethnic areas in China. Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. Full article

The NW–SE-trending Firenze-Pistoia Basin (FPB) is an intermontane tectonic depression in the Northern Apennines (Italy) bounded to the northeast by a SW-dipping normal fault system. Although it has moderate historical seismicity (maximum estimated Mw 5.5 in 1895), the FPB lacks detailed characterization of its recent tectonic structures, unlike those of nearby basins that have produced Mw > 6 events. This study focuses on the southeastern sector of the basin, including the urban area of Florence, using tectonic geomorphology derived from remote sensing, in particular LiDAR data, field verification, and high-resolution geophysical surveys such as electrical resistivity tomography and seismic reflection profiles. The integration of these techniques enabled interpretation of the subdued and anthropogenically masked tectonic structures, allowing the identification of Holocene activity and significant, although limited, surface vertical offset for three NE–SW-striking normal faults, the Peretola, Scandicci, and Maiano faults. The Scandicci and Maiano faults appear to segment the southeasternmost strand of the master fault of the FPB, the Fiesole Fault, which now shows activity only along isolated segments and cannot be considered a continuous active fault. From empirical relationships, the Scandicci Fault, the most relevant among the three active faults, ~9 km long within the basin and with an approximate Late Quaternary slip rate of ~0.2 mm/year, might source Mw > 5.5 earthquakes. These findings highlight the need to reassess the local seismic hazard for more informed urban planning and for better preservation of the cultural and architectural heritage of Florence and the other artistic towns located in the FPB. Full article

Amid ongoing societal development, tourists’ travel behavior patterns have been undergoing substantial transformations, and understanding their evolution has emerged as a key area of scholarly interest. Taking Beijing as a case study, this research aims to uncover the spatiotemporal evolution patterns of tourist flows and their underlying driving mechanisms. Based on digital footprint relational data, a dual-perspective analytical framework—“tourist perception–tourist flow network”—is constructed. By integrating the center-of-gravity model, social network analysis, and regression models, the study systematically examines the dynamic spatial structure of tourist flows in Beijing from 2012 to 2024. The findings reveal that in the post-pandemic period, Beijing tourists place greater emphasis on the cultural connotation and experiential aspects of destinations. The gravitational center of tourist flows remains relatively stable, with core historical and cultural blocks retaining strong appeal, though a slight shift has occurred due to policy influences and emerging attractions. The evolution of the spatial network structure reveals that tourism flows have become more dispersed, while the influence of core scenic spots continues to intensify. Government policy orientation, tourism information retrieval, and the agglomeration of tourism resources significantly promote the structure of tourist flows, whereas the general level of tourism resources exerts no notable influence. These findings offer theoretical insights and practical guidance for the sustainable development and regional coordination of tourism in Beijing, and provide a valuable reference for the spatial restructuring of urban tourism in the post-COVID-19 era. Full article