Search Results (461)

As a complex heritage site embodying maritime defense civilization, the Ming Dynasty Coastal Defense Garrisons face a profound contradiction between protection and development. Current research has failed to effectively explain the spatial mechanism of the transformation of coastal defense garrisons from military fortresses to modern towns. This study selects three coastal defense garrisons in southern Zhejiang—Jinxiang Garrison, Puzhuang Fort, and Hai’an Fort—and, based on long-term spatial data from 1969 to 2025, uses GIS, spatial syntax, and fractal index methods to construct a morphological analysis framework from four dimensions: architecture, land parcels, streets and alleys, and boundaries, revealing their evolutionary patterns and functional transformation mechanisms. The results show that (1) morphological evolution follows an asynchronous and coordinated rhythm of “buildings filling in first, road network updating lagging behind, and boundaries continuously constraining.” (2) Differences in urbanization pressure, industrial implantation intensity, and cultural heritage management drive the three garrisons to differentiate into three transformation paths: gradual preservation, radical reconstruction, and balanced regularization. The intensity of street and alley renovation is the core indicator for judging whether the historical fabric is preserved. (3) The boundaries of the garrison exhibit a “macroscopically regular but microscopically fragmented” characteristic, with a simple outer boundary and a complex inner boundary. Even after the city walls disintegrated, the moat still served as a morphological inertial line, maintaining the stability of the macroscopic outline. This research can provide quantitative evidence and empirical reference for the differentiated protection of coastal defensive heritage. Full article

Urban vitality is a key indicator for characterizing the quality of urban space and the operational status of urban functions. However, existing studies still have limitations in multidimensional vitality measurement at the block scale, the representation of hierarchical differences in cultural facilities, and the coupling coordination diagnosis of multidimensional vitality. This study takes 2504 blocks in the central urban area of Nanjing as the basic analytical units and integrates multi-source geospatial data, including VIIRS nighttime light data, Baidu Huiyan population heat data, POIs, road networks, and water systems, to construct a three-dimensional urban vitality evaluation system encompassing economic, social, and cultural vitality. A Composite Nighttime Light Index (CNLI) is constructed by geometrically fusing VIIRS nighttime light data with the kernel density of industry- and consumption-related POIs to reduce the impact of the spatial generalization of nighttime lights on block-scale economic vitality measurement. Meanwhile, population heat data and cultural POIs are used to characterize social vitality and cultural resource supply, respectively, and PCA, a coupling coordination model, and spatial autocorrelation analysis are combined to identify the spatial structure of multidimensional vitality and the dominant factors of disorder. External reference variables are also introduced to conduct convergent validity verification. The results indicate that the comprehensive vitality of Nanjing’s central urban area exhibits a distinct “core agglomeration–multi-node diffusion” structure. High-vitality zones are primarily concentrated in Xinjiekou, Confucius Temple, Hunan Road–Zhongyang Road, Longjiang, and the Nanjing Olympic Sports Center, with localized vitality patches forming at peripheral commercial and transportation nodes. Both comprehensive vitality and coupling coordination degree exhibit significant positive spatial autocorrelation, with Moran’s I values of 0.8089 and 0.8372, respectively. The disorder types show distinct quantitative differences and spatial differentiation. Among these, blocks with lagging cultural vitality are the most numerous; peripheral new towns and newly developed residential areas are more prone to cultural vitality lag; areas surrounding scenic spots, universities, and large ecological spaces tend to exhibit economic vitality lag; and less developed peripheral blocks primarily exhibit comprehensive disorder. Based on accessible multi-source geospatial data, this study constructs a block-scale framework for measuring multidimensional urban vitality and diagnosing coordination status. This framework can provide a reference for vitality identification, functional shortcoming diagnosis, and refined spatial governance in Nanjing’s central urban area, and offer a case reference for historic and cultural cities with similar spatial structures. Full article

The production of refined ferrochrome is accompanied by the formation of self-disintegrating slags caused by the β→γ-Ca₂SiO₄ polymorphic transformation during cooling, resulting in environmental and technological problems. This study aimed to develop and validate a technology for long-term stabilization of refined ferrochrome slags using remelted and desulfurized borate ore (RDBO) from the Inder deposit as an alternative to colemanite. Thermodynamic modeling, X-ray diffraction (XRD), scanning electron microscopy (SEM), and pilot-industrial trials were conducted to evaluate phase transformations, microstructure formation, and slag stability. The results showed that the addition of boron oxide promoted the formation of stable borate phases, primarily CaB₄O₇, and reduced the content of unstable Ca₂SiO₄ phases. Autoclave testing under saturated steam conditions (400 kPa, ~180 °C, 24 h) demonstrated complete preservation of structural integrity in all RDBO-stabilized samples, with an average mass loss of 0.19 ± 0.01%, whereas colemanite-stabilized slags exhibited cracking and partial disintegration. The stabilization effect was achieved at a B₂O₃ content of 0.17–0.47 wt.% without boron contamination of ferrochrome. The proposed technology ensures long-term slag stability and enables the utilization of stabilized slag as a technogenic material for road construction. Full article

The concrete industry intends to include HPC for structural applications in Southern Europe and, therefore, Greece is a region characterized by stricter and problem-oriented sizing and reinforcement limitations due to its strong seismicity. For this purpose, the effect of using of high performance concrete (HPC) on the dimensioning of conventional reinforced concrete (RC) and prestressed concrete (PC) structures is investigated by designing two ten-story office buildings and typical PC pedestrian, railway, and road bridges, while conforming to all the relevant provisions of the Eurocodes. The designs involve practical construction forms obeying geometric limitations, while satisfying all serviceability and ultimate limit states for conventional and accidental earthquake loads. Conventional strength-class concrete, namely C30 for buildings and C35 for PC bridges, and HPC concrete classes C60 to C120 are considered. Based on the parametric designs, it is concluded that using HPC leads to a reduction in concrete volume of between 30% and 50% compared to conventional concrete use. This reduction, however, depends strongly on the design-controlling criteria, building occupancy, and bridge type and span, which may lead to smaller material savings, particularly where serviceability criteria govern. The analysis is extended in order to also investigate the increase in the design service life of these structural forms under marine chloride exposure conditions, using C90 and conventional concretes. It is shown that, in addition to the material reductions above, the use of HPC also results in a significant increase in the design service life of the structures considered. Full article

Frequent extreme climate events pose severe threats to human health. Existing studies mainly focused on summer thermal environments, while few compared summer and winter extreme climate risks from the perspective of urban functional zones (UFZs). This study classified more precise UFZs using the machine-learning method and constructed heat and cold exposure indicators. GeoDetector was adopted to analyze driving factors and interactions of both types of exposure across UFZs. The results showed that UFZ classification achieved an overall accuracy of 81.8% and a Kappa coefficient of 0.75. High heat exposure concentrated in core public, residential, and commercial zones, while high cold exposure occurred in peripheral industrial and greenspace zones. Dual high exposure zones lay between the 3rd and 5th Ring Roads. Industrial zones positively contributed to both exposures, while commercial, public, and residential zones showed positive heat but negative cold exposure contributions, and greenspace zones presented opposite effects. Vulnerable population ratios had a strong explanatory power. Heat exposure interactions were dominated by vulnerable populations, building morphology, and landscape patterns, while cold exposure was also affected by the degree of facility agglomeration and human activities with varied mechanisms across UFZs. This study advanced single-season thermal research to multi-season exposure and zoned governance for climate-adaptive renewal. Full article

Persistent urban–rural inequality remains a major challenge for sustainable regional development, especially in countries where rural communities still face limited access to markets, employment, and public services. This study examines whether rural road network density promotes inclusive regional growth in China. Using county-level panel data from 2013 to 2024, we construct an inclusive regional growth index that combines economic output, nighttime-light-measured economic activity, rural income, and the urban–rural income gap. rural road network density is measured by the length of county, township, and village roads per 100 square kilometers. Two-way fixed-effects models, mechanism tests, robustness checks, instrumental-variable estimation, and heterogeneity analysis are employed. The results show that rural road network density significantly improves inclusive regional growth. Dimensional analysis indicates that higher rural road network density increases real GDP per capita, strengthens nighttime-light-measured economic activity, raises rural income, and reduces the urban–rural income gap. Mechanism analysis shows that these effects operate through labor mobility, market access, and non-agricultural industrial development. The results remain robust to alternative road measures, lagged specifications, outlier treatment, sample restrictions, and instrumental-variable estimation. Heterogeneity analysis further shows that the effects are larger in central-western counties, low-accessibility counties, and less-developed counties. These findings suggest that rural road network density is not only a transport infrastructure indicator but also a key spatial condition for promoting sustainable and inclusive regional development. Full article

Road transport is an important source of carbon emissions worldwide, yet the factors driving these emissions may differ under varying geographical conditions. Plateau regions are characterized by high altitude and strong spatial constraints, but their transport carbon emission mechanism remains insufficiently understood. Taking Qinghai Province on the Qinghai–Tibetan Plateau as a case, this study estimates road transport CO₂ emissions from 2003 to 2022 using annual statistical data. It constructs a multidimensional indicator system covering economic development, industrial structure, energy use, and road transport activity, and applies correlation analysis, PCA, and LASSO regression to diagnose variable relationships and identify key drivers. The results show that GDPI, VATSP, CVO, and TPT have stable positive effects on road transport CO₂ emissions, indicating that economic expansion, transport services, vehicle ownership, and passenger mobility are the dominant drivers. Industrial and energy-related variables have more indirect and stage-dependent effects: NMI and NFMO are negatively associated with emissions, whereas NMEC has a weak positive effect. These findings suggest that, under the dispersed spatial development and long-distance transport dependence of plateau regions, emissions are more directly shaped by economic and transport activity than by short-term changes in energy structure. Low-carbon transport policy in Qinghai should therefore combine transport-demand management, more efficient transport organization, public-transport improvement, and gradual transport electrification. The results provide evidence for emission-reduction strategies in high-altitude and ecologically fragile regions. Full article

The construction industry is a major contributor to global greenhouse gas (GHG) emissions. Different strategies have been implemented to reduce the environmental impact of construction sites and create better city environments for construction workers and citizens. Electrification of construction machinery is one such measure and is rapidly evolving. However, existing literature has largely concentrated on either electrification of road vehicles or emission reduction via the electrification of a building’s operational energy use. This paper presents a systematic literature review on available publications focusing on the electrification of construction sites, identifying and analyzing the key drivers and barriers influencing this. In addition, it provides recommendations for better and effective electrification of construction sites. A total of 55 publications were analyzed to extract insights and organize findings into eight key themes: requirements, technology and market, economic, process and operations, infrastructure, knowledge and experience, environmental, and attitude. The findings indicate strong interconnections between the barriers and drivers to electrification of construction sites. Clear policy frameworks, strategic public procurement, knowledge sharing initiatives, and robust data systems emerged as critical enablers for scaling emission-free construction sites. The lessons learnt are largely drawn from Norwegian experiences but are highly transferable to other cities and regions and offer practical insights into policy design, procurement strategies, and collaborative models for actors interested in reducing GHG emissions and transition into electrification of construction sites. Full article

Against the backdrop of the deep advancement of the carbon peak and carbon neutrality goals and the superposition of the transportation power strategy, leveraging the spatial restructuring of highway networks to optimize the low-carbon layout of county-level industries has become a crucial lever for balancing economic quality improvement with carbon intensity control. This study selects panel data from 129 counties in Yunnan Province spanning 2015–2024, constructing a comprehensive highway network development index from four dimensions: highway density, road network connectivity, weighted hierarchical structure, and county accessibility. Using a two-way fixed effects benchmark model, a stepwise mediation effect testing framework, and a regional heterogeneity identification strategy, the paper systematically examines the marginal effects, transmission pathways, and spatially differentiated characteristics of highway network development on county-level industrial carbon emission intensity. Key findings are as follows: Enhanced highway network development significantly suppresses the increase in county-level industrial carbon emission intensity, and a well-developed road network can provide long-term empowerment for the low-carbon transformation of county-level industries. Mechanism analysis confirms that highway network development reduces emissions through two core pathways: first, a direct emission reduction effect achieved by optimizing the county-wide freight organization system, reducing inefficient transport energy consumption, and improving overall transport efficiency; second, an indirect low-carbon enabling effect realized by breaking down administrative barriers in county markets, lowering cross-regional business transaction costs, deepening industrial division of labor and collaboration, and forcing resource allocation improvements. Heterogeneity analysis reveals that the low-carbon dividends of highway network development exhibit significant gradient differentiation: the emission reduction enabling effect is strongest in counties within the Central Yunnan urban agglomeration, followed by cultural tourism counties in western Yunnan and border counties in southern Yunnan, with the weakest marginal enabling effect observed in traditional agricultural counties in northeastern Yunnan. Full article

Autonomous vehicle open-road testing is a crucial component in the development of intelligent and connected vehicle (ICV) industries. The classification of road complexity plays a key role in ensuring the safety and efficiency of such tests. This study, based on the practices of the High-Level Autonomous Driving Demonstration Zone in Beijing, proposes a scientific and systematic framework for classifying road complexity. The framework integrates static road features, dynamic traffic flow indicators, and safety event metrics, employing the Analytic Hierarchy Process (AHP) to quantify road complexity and categorize roads into five distinct levels. The findings provide significant guidance for the phased opening of test roads, optimization of autonomous driving algorithms, construction of accident scenario databases, and deployment of infrastructure. This paper further explores the practical applications and future development directions of road complexity classification, aiming to offer theoretical and practical support for the testing and demonstration of intelligent and connected vehicles. Full article

Over the past decade the industry has developed technical, contractual and managerial tools for road construction without recognizing their capacity as solutions to land access restrictions. This systematic review analyzes the strategies for executing road projects under such restrictions. Following the PRISMA 2020 protocol, 51 indexed articles (2015–2026) retrieved from Scopus and Web of Science were examined and classified into land access restrictions, execution strategies (four families: technical–constructive, project management, social–institutional and contractual–legal) and impact on performance. Strategies are documented in 64.7% of the studies, but only 25.5% analyze them as an object, which explains why they have not been recognized as available solutions. The four families are not alternatives: they operate at different moments of the cycle, and their effectiveness depends on the type of restriction, the moment of activation and the institutional capacity, a determining variable that the corpus does not measure. Treating the restriction as a planning variable, rather than a contingency, distinguishes the projects with positive impact. Full article

This paper integrates the Elastic Net-TVP-VAR-BK framework and constructs a high-dimensional multilayer frequency-domain network, including short-, medium-, and long-term layers, to investigate extreme risk spillovers among 56 industries in the Chinese stock market. We examine the topology of the multilayer network at the system, cross-sector, and industry levels, as well as from both static and dynamic perspectives. Using daily data on 56 industry indices from 1 March 2007 to 30 September 2024, our empirical results show that: (1) All multilayer network topologies, including edge structures, node characteristics, and spillover strengths, exhibit significant frequency heterogeneity, and the dynamic topology of the three-layer network shows fluctuations and directional differences during critical periods. (2) In most periods, the short-term layer exhibits stronger average spillover intensity and denser inter-industry linkages, suggesting that short-horizon risk transmission plays a more prominent role in rapid contagion. However, the medium- and long-term layers remain important for identifying persistent and structural risk transmission. (3) At the industry level, capital markets and textiles, apparel, and luxury goods within the short-term layer, food products, household products, and road and rail in the medium-term layer as well as construction and engineering, industrial conglomerates, trading companies and distributors, metals and mining, and distributors in the long-term layer, all demonstrate high cross-industry systemic importance and total systemic importance, thereby establishing themselves as key nodes within their respective frequency domains. The findings provide theoretical support for policymakers in formulating strategies to address market risks and offer important references for investors in asset allocation and risk management decisions. Full article

Real-time kinematic (RTK) positioning in open-pit mining environments is critically compromised by non-line-of-sight (NLOS) signals and anisotropic multipath effects induced by pit walls, haul roads, and industrial infrastructure. Conventional elevation-dependent stochastic models fail to discriminate between geometrically favorable low-elevation satellites and those subject to directional obstruction, resulting in degraded ambiguity resolution and decimeter-level positioning errors that undermine safety-critical deformation monitoring. This paper presents an adaptive RTK positioning framework utilizing azimuth-integer-based elevation masking to explicitly model site-specific obstruction geometry. The proposed method discretizes the horizontal plane into 360 integer-degree sectors, extracts minimum elevation angles per sector from 24 h line-of-sight (LOS) data, and constructs a smoothed 360°mask profile via moving-window filtering. A virtual elevation-angle transformation is introduced to normalize satellite geometry relative to the local mask, enabling adaptive down-weighting of diffraction-susceptible observations within the stochastic model without requiring multi-day satellite repeat arcs or hardware modifications. The approach was validated using 54 h of BDS data collected at eight monitoring stations within the Wangjialing open-pit mine, China. Implementation of the mask model engendered a selective 8.1% reduction in satellite participation (15.66 to 14.39 satellites) while significantly enhancing observation quality. The ambiguity validation ratio improved by 19.5% (from 9.43 to 11.27 in the experimental project), and the fix success rate increased from 92.4% to 97.2% (exceeding the 95% reliability threshold at all stations). The RMS errors in the east, north, and up directions improved by 34.8% to 65.2%, 28.7% to 77.0%, and 44.8% to 70.8%, respectively, with the most dramatic gains observed at stations subject to severe azimuthal obstruction (e.g., ZDH6 vertical RMS: from 50.7 mm to 14.8 mm). By explicitly modeling anisotropic obstruction geometry through discrete angular sampling, the proposed method achieves sub-centimeter positioning accuracy and robust ambiguity resolution in challenging mining environments without additional hardware or empirical threshold tuning, offering a cost-effective solution for large-scale, real-time deformation monitoring systems. Full article

The construction of green mines is a core strategy for promoting ecological civilization in China’s mining sector, yet its long-term ecological effects require quantitative assessment. Using a cement-grade limestone mine operated by Linyi Zhonglian Cement Co., Ltd. in Shandong Province as an illustrative case, we employed Landsat 8 OLI/TIRS imagery acquired in 2015, 2020, and 2025 to develop a five-indicator framework for assessing ecological environment quality. The selected indicators comprised greenness (NDVI), wetness, dryness (NDBSI), land surface temperature (LST), and dust concentration (MECDI). These five indicators were subsequently integrated via principal component analysis to generate the Mine Ecological Quality Index (Mine-EQI). Using this index, we applied the Theil–Sen median slope estimator alongside zonal statistics to examine ecological change trajectories across the full study area and three functional zones—the industrial square, haul roads, and active mining area—over the 2015–2025 period. The ecological outcomes attributable to the green mine policy were then quantified. The results show that (1) the mean Mine-EQI of the study area decreased from 0.3713 in 2015 to 0.3460 in 2025, exhibiting a slight overall decline. However, the rate of decline decreased from −6.1% during 2015–2020 to −0.7% during 2020–2025, yielding a Temporal Change Intensity index (TCI) of +88.5%, indicating that the ecological degradation trend has been effectively curbed. (2) Significant spatial heterogeneity was observed. The industrial square showed substantial improvement (Theil–Sen slope = +0.0726), while the haul roads (slope = −0.0705) and mining area (slope = −0.0408) continued to exhibit degradation trends. The improved areas (9.7% of the study area) were spatially coincident with green mine engineering projects. (3) The dust indicator (MECDI) decreased by 24.7% during 2020–2025, and the vegetation index (NDVI) increased by 19.5% over the decade, representing the dominant contributors to ecological improvement. This study reveals that China’s green mine policy has yielded remarkable ecological improvements in relatively stable functional zones such as industrial squares. In contrast, ecological restoration within persistently disturbed areas, including haul roads and mining pits, demands long-term sustained investment and governance. By integrating remote sensing techniques with policy analysis, this research establishes a replicable framework for evaluating progress toward sustainable mining practices. The findings directly support the monitoring of SDG 12 (Responsible Consumption and Production) and SDG 15 (Life on Land), providing a quantitative pathway to balance mineral resource extraction with ecological protection—a core sustainability challenge for resource-dependent regions. Full article

Existing research on the landscape patterns of urban parks and green spaces demonstrates a disproportionate focus across tiers within China’s urban hierarchy. Numerous studies have concentrated on economically developed first-tier cities, such as Beijing, Shanghai, and Guangzhou. In contrast, medium-to-large non-first-tier cities, especially provincial capitals and emerging cities within the first- and second tiers, have been relatively understudied, although they have received increasing attention in recent years. This bias extends regionally, with studies predominantly examining cities in the more developed central and eastern regions, while less-developed areas and lower-tier cities receive significantly less attention. This study tracks changes in park quantity, spatial concentration, patch structure and driver associations at three planning-related time points. Shenyang provides a distinct cold-region and old industrial city case, shaped by long winters, industrial renewal and outward urban growth. Furthermore, to inform park and green-space planning in Northeast China’s cold-climate cities, exemplified here by Shenyang, a major metropolis with a monsoon-influenced humid continental climate (Köppen Dwa), long cold winters, and relatively short warm summers, we document a shift in park distribution from the urban core to peripheral areas. Based on park vector layers reconstructed from planning documents, remote sensing interpretation and field verification, this study combined spatial analysis, landscape metric calculation and driver-association modeling. ArcGIS Pro was used to identify changes in distribution centers, directional extension and local clustering; FRAGSTATS 4.2 was used to calculate park landscape metrics; and SIMCA-P 14.1 was used to examine the statistical associations between selected landscape indicators and potential driving variables. The results show that the number and total area of parks in central Shenyang increased substantially from 2000 to 2024. Spatially, park distribution became less concentrated in the traditional inner city, while new clusters gradually appeared in peripheral districts and newly developed urban areas. The old urban core remained important, but its dominance weakened as park provision expanded outward. The landscape metric results further indicate that park expansion was accompanied by more irregular patch forms, stronger fragmentation and declining structural continuity. The driver association analysis suggests that climate conditions, population change, industrial restructuring, real estate investment, road construction and urban greening policies were related to different aspects of park landscape change. These associations should be interpreted as statistical relationships rather than direct causal effects. Overall, this study clarifies the spatial restructuring of park green spaces in a cold-region old industrial city and provides planning evidence for improving park connectivity, coordinating green space expansion with urban construction and supporting sustainable park system development in Northeast China. Full article