Search Results (295)

Sustainable urban transportation is fundamentally linked to public health outcomes, specifically the mitigation of fatal traffic risks under environmental stress. While stressors like adverse weather affect entire cities, traditional road safety models often assume uniform risk, thereby masking the spatial inequalities inherent in the urban fabric. This study addresses this gap by investigating the geographically heterogeneous impact of environmental stressors—including rainfall, surface moisture, and lighting conditions—on the conditional probability of fatal crash outcomes in Melbourne, Australia. Analyzing 43,075 severe crashes through a multi-stage geospatial framework (Getis-Ord Gi* and Geographically Weighted Logistic Regression), this research diagnoses how varying urban development patterns mediate the lethality of these stressors. The findings unmask a critical “threshold-crossing” pattern for wet surfaces, where risk transitions from protective to hazardous based on local infrastructure form and street geometry. Significant spatial inequalities are identified: high-density inner-urban cores and adjacent coastal corridors exhibit a heightened sensitivity to visibility failures and moisture, whereas newer industrial peripheries show stronger protective “risk compensation” effects. These results reveal a systemic mismatch between historical urban form and contemporary climate-driven public health risks. By identifying localized “lethality thresholds”, this study provides a robust evidence base for integrated planning and equitable resource allocation. It enables urban planners to move beyond generalized safety warnings toward targeted structural interventions, ensuring that sustainable transportation networks prioritize safety equity for all citizens regardless of their location within the urban environment. Full article

As metropolitan areas (MAs) become increasingly complex, reconciling land development with ecological protection has become a major challenge in spatial governance. Although ecological security patterns (ESPs) are widely used to assess ecological networks, they are often treated as diagnostic outputs after simulation rather than directly incorporated into land use/land cover (LULC) simulation processes. In addition, conventional ecosystem health assessments commonly assign uniform values to broad LULC classes, thereby overlooking variations among patches within the same class. This study proposes a spatially explicit framework that integrates forest-centered ESPs into LULC simulation as scenario-specific conversion constraints. It also applies a modified Pressure–Vitality–Organization (P–V–O) model that incorporates explicit socioeconomic pressures instead of relying on uniform, class-based resilience values and assesses ecosystem health separately for each LULC type. The framework was applied to the Tokyo, Chubu, and Kinki MAs in Japan. From 2000 to 2020, forest-corridor configurations evolved differently among the three MAs. Declines in forest connectivity were more pronounced in Tokyo and Chubu, whereas Kinki remained comparatively stable. Patch-scale ecosystem health showed marked spatial heterogeneity within cultivated land, grassland, and shrubland, and its temporal trends varied among MAs and LULC types. Simulations for 2050 under the Urban Priority, Business-as-Usual, and Ecological Priority scenarios showed that increasing levels of ecological protection imposed progressively broader constraints on land conversion, resulting in region-specific patterns of urban expansion, cultivated land change, and forest retention. The proposed framework shows how ESPs and patch-level ecosystem health information can be operationalized as spatial planning constraints, providing a practical basis for comparing development and conservation priorities and supporting differentiated LULC planning across MAs. Full article

This study examines the effects of silvicultural management on the functional connectivity of fragmented Abies pinsapo forests in southern Spain. Using biomass stock as a resistance proxy, connectivity was assessed through accumulated cost-distance and least-cost path analyses under three scenarios: low intervention, traditional silviculture, and intensive thinning aimed at reducing climate vulnerability. The intensive thinning scenario produced the greatest connectivity gains, reducing mean accumulated costs by approximately 18% and standard deviation by 15%, with local reductions reaching up to 60% between specific population pairs. Median costs also declined, indicating widespread improvements rather than isolated effects. Spatial analyses revealed that previously high-resistance zones, particularly in central and northern sectors, shifted toward more permeable conditions. Least-cost paths were shortened and alternative, more efficient corridors emerged, especially in areas subjected to silvicultural treatments. Connectivity benefits extended to peripheral populations, decreasing their relative isolation and contributing to a more balanced network structure. Targeted biomass reduction may reshape landscape resistance patterns and strengthened ecological linkages, highlighting adaptive silviculture as a potentially valuable strategy for improving landscape connectivity and supporting conservation planning. Full article

This study addresses maritime traffic risks in the Labuan Bajo–Komodo marine tourism corridor, a spatially constrained archipelagic environment characterized by mixed vessel traffic, intensive tourism activity, and high ecological sensitivity. An integrated decision-support framework was developed by combining the Analytic Network Process (ANP) with stakeholder-supported grid-based spatial risk analysis. Expert pairwise comparisons from eight respondents were used to evaluate eight interdependent criteria: Natural Conditions, Navigational Channel, Vessel Factors, Maritime Traffic Conditions, Port Control, Authority/Stakeholders, Tourism, and Environmental Impact. The ANP calculation was conducted using geometric mean group aggregation, consistency ratio assessment, and targeted follow-up clarification for matrices requiring refinement. The final ANP results show that Port Control received the highest priority weight (0.172), followed by Natural Conditions (0.148), Maritime Traffic Conditions (0.144), Environmental Impact (0.135), Vessel Factors (0.121), Navigational Channel (0.120), Authority/Stakeholders (0.104), and Tourism (0.0566). At the global subcriteria level, communication effectiveness, channel complexity, environmental compliance, local traffic density, and seasonal traffic variation emerged as the dominant contributors to risk. A stakeholder-supported partial spatial risk index (SRI) was then calculated for 21 grid cells using spatially mappable ANP criteria. The highest-risk cells were grids 3, 5, 6, 8, 9, 10, and 14, while sensitivity analysis confirmed that grids 3, 5, 6, 9, 10, and 14 remained high risk across all tested spatial-weight scenarios. The findings indicate that maritime traffic risk in Komodo National Park is not driven by environmental exposure alone, but by the interaction of traffic control capacity, natural hazards, traffic concentration, environmental sensitivity, and institutional coordination. The proposed framework supports spatially informed traffic management, environmental compliance, and emergency preparedness planning in marine protected tourism corridors. Full article

Railway transportation networks increasingly share constrained corridors with transmission lines, buried pipelines, and other linear infrastructure. Electromagnetic interference in these corridors is important for safe railway planning and operation, particularly when nearby high-voltage lines cross oil and gas pipelines. This paper investigates transmission-line-induced pipeline potential under crossing conditions in the Zhangbei region. The CDEGS moment-method framework is applied with locally refined segmentation in the crossing regions, and an electromagnetic coupling model for multiple-crossing transmission line-oil and gas pipeline systems is established. The qualitative effects of crossing angle and parallel length on pipeline potential were obtained under both normal operating conditions and single-phase ground fault transient conditions. The results show that induced voltage decreases nonlinearly as the crossing angle increases and rises markedly with crossing length. The contribution of ground potential rise during transient processes to pipeline potential is significantly greater than that during steady-state processes. Installing zinc ribbons as a drainage measure can reduce the pipeline-to-ground voltage. However, supplementary mitigation measures may still be required under severe interference conditions. These findings are relevant to railway transportation because railway corridors often coexist with transmission lines and buried pipelines, making coordinated electromagnetic compatibility assessment essential for infrastructure safety and operational reliability. The proposed framework supports corridor planning, risk assessment, and protective design for railway-related infrastructure in complex shared corridors. Full article

With the rapid growth of urban motorization, personalized travel modes, including taxis and private cars, have expanded considerably. However, conventional public transportation systems, constrained by fixed routes and limited service flexibility, often struggle to satisfy residents’ increasingly diversified and high-quality commuting needs. To address this issue, this study proposes an integrated planning framework for customized bus services using taxi trajectory data. First, passenger origin–destination (OD) information is extracted by detecting changes in the taxi passenger-status field. The extracted OD records are then used to identify potential commuting demand by jointly considering peak-hour travel characteristics and regional OD stability. Second, the identified potential commuting demand is used to generate candidate boarding and alighting stops through an improved DBSCAN-based clustering method, namely IDK-SG. For route planning among the candidate stops, a bi-objective optimization model is developed to simultaneously account for passenger travel-time costs and bus operating costs, and the model is solved using a genetic algorithm. Finally, timetable optimization is formulated as a Markov decision process and solved using a Deep Q-Network (DQN) algorithm. Case studies using taxi GPS trajectory data from Chongqing demonstrate that the proposed framework can effectively identify stable commuting demand, optimize stop layouts and route schemes, and improve vehicle occupancy and service quality. These findings provide practical decision-making support for the operation and dynamic scheduling of customized bus services in urban peak-hour commuting corridors. Full article

Climate change is increasingly reshaping species habitat suitability worldwide. Primula L., the largest genus in Primulaceae, comprises 404 species in China (including 296 endemic species) and is characterized by high endemism and numerous rare and endangered taxa. However, global warming has intensified habitat fragmentation and loss, while its distribution patterns and key environmental drivers remain insufficiently understood. We compiled 7647 occurrence records of 404 wild Primula species in China and integrated 60 environmental variables (climatic, topographic, and soil factors). Using the MaxEnt model combined with ArcGIS spatial analysis, we assessed current and future habitat suitability, identified dominant environmental drivers, and quantified conservation gaps under multiple climate scenarios. Species richness is highly concentrated in Sichuan (186 species), Yunnan (177 species), and Xizang (165 species), with the Hengduan Mountains and eastern Himalayas representing the core distribution area and showing clear peripheral differentiation. The optimized MaxEnt model performed well (AUC = 0.858), identifying temperature seasonality (bio4, 39.8%) and elevation (27.1%) as the main limiting factors. The total suitable habitat area is 268.52 × 10⁴ km², with high-suitability areas mainly distributed in the Hengduan Mountains, southeastern Qinghai–Xizang Plateau, and the Central Mountain Range of Taiwan. Under three shared socioeconomic pathway (SSP) scenarios (SSP126, SSP245, and SSP585), suitable habitat shows a persistent decline, most pronounced under SSP585 in the 2090s (−20.73%), accompanied by a 25.86% reduction in low-suitability areas. Localized expansion of high-suitability habitats suggests that the Hengduan Mountains and southeastern Qinghai–Xizang Plateau may act as potential climatic refugia. Habitat loss consistently exceeds habitat gain, while the distribution centroid shifts westward and northwestward, with migration distances increasing under higher-emission scenarios. Conservation gap analysis indicates that 90.01% of high-suitability habitats lie outside the current protected area network, revealing a strong mismatch between biodiversity hotspots and conservation coverage. These findings highlight the urgent need to expand protected areas and establish micro-reserves in key gap regions (southwestern Sichuan, northwestern Yunnan, southeastern Xizang, and southern Gansu), and to integrate climate-driven migration corridors into conservation planning to support long-term alpine plant persistence under climate change. Full article

Rapid urbanisation has reshaped Shanghai’s ecological land base and intensified fragmentation of its green infrastructure (GI). This study evaluates the spatiotemporal evolution of Shanghai’s GI network from 2000 to 2020 using a resilience-informed patch-corridor-connectivity assessment. In this study, resilience is not just an explanatory label but a measurable structural criterion. Morphological Spatial Pattern Analysis (MSPA) was used to identify core patches; patch importance was evaluated using delta Probability of Connectivity (dPC); a Minimum Cumulative Resistance (MCR) model was used to derive potential corridors; and a gravity model was used to classify corridor importance. The results show that important ecological corridors increased from 22 in 2000 to 33 in 2010 and 68 in 2020, while the total area of the MSPA core class declined and north–south connectivity remained uneven. The key finding is not the growth of corridor number itself, but the mismatch between corridor densification and contraction of major source patches. This mismatch indicates a structural vulnerability that would be overlooked by a conventional network-optimisation reading. Therefore, based on the results of indicator-based resilience assessment, this study proposes a planning scheme that combines core-area conservation, corridor continuity, redundancy improvement, and cross-regional connectivity enhancement. Full article

The rapid development of high-density cities has triggered severe ecological challenges, including habitat fragmentation, urban heat island (UHI) effects, and conflicting demands for public recreation. Traditional ecological networks (ENs) often focus only on “source” landscapes while neglecting degraded “sink” areas. This bias limits the ability of planners to resolve complex spatial conflicts. Therefore, the primary aim of this study is to develop a robust spatial planning framework that mitigates urban ecological conflicts and enhances regional resilience. To achieve this, we constructed a composite ecological network (CEN) for the high-density city of Guangzhou that harmonizes bird habitat conservation, thermal regulation, and cultural recreation. We combined the MaxEnt model, morphological spatial pattern analysis (MSPA), and circuit theory to identify functional “sources” and “sinks” across these three dimensions. Next, using complex network theory, we optimized the CEN and evaluated its structural robustness using low degree addition (LDA) and low betweenness addition (LBA) strategies. The results indicate the following: (1) The CEN effectively captured the complex mosaic landscape of the city. (2) Single-objective networks displayed distinct spatial differences—the recreational network formed a dispersed web of 242 corridors, while habitat and climate networks remained highly clustered. (3) The integrated CEN generated 1137 multi-layered corridors, creating a vital green skeleton to support species dispersal, mitigate UHI effects, and improve cultural access. (4) Optimization simulations verified that the LBA strategy provided the highest stability against targeted attacks by balancing network connectivity with local aggregation. Ultimately, this framework offers a highly adaptable planning tool for dense cities, providing precise spatial guidance to overcome ecological bottlenecks and harmonize urban growth with ecosystem resilience. Full article

In the context of subtropical cities, the slow-moving environment of HOD (Hospital-Oriented Development) faces the dual challenges of spatial fragmentation and an extreme hot and humid climate, which also restricts the outdoor space’s thermal environment performance. Taking the Macau Light Rapid Transit (LRT) Union Hospital Station as an example, this study constructs a “topology-climate” dual quantitative assessment framework that integrates space syntax and parametric universal thermal climate index (UTCI) simulation. In response to the current problems of mixed pedestrian and vehicular traffic and high-intensity heat radiation, a comprehensive intervention strategy combining three-dimensional stitching and spatial optimization is proposed. The results show that: (1) The implantation of three-dimensional corridors improved the spatial integration of the core area of the site by 67.0%, significantly optimizing network connectivity. (2) During the extreme high-temperature period of daytime (9:00–18:00) in summer and autumn, the intervention strategy precisely opened up a continuous low-heat-stress linear shade zone through the synergistic mechanism of building projection shadows, physical shading of connecting corridors, (landscape shading effect, original evaporation removed). (3) The study confirms that landscape-coupled shading layout is the most effective method, reducing potential pedestrian heat exposure across the entire area, while the three-dimensional connecting corridors precisely control the thermal environment of core walkways. Together, these two elements construct a “topology-climate” optimization framework, achieving a synergistic improvement in spatial accessibility and simulated thermal comfort performance under standard meteorological input and quantitatively verifying the optimization effectiveness of the tiered intervention scheme. This study provides a data-driven decision-making basis for optimizing potential walking thermal conditions for vulnerable groups and reshaping the space’s potential to improve microclimate via shading design of medical hub areas and also provides a scientific paradigm for TOD microclimate planning focused on shading-based thermal environment optimization. Full article

Public transport reliability largely determines the performance of smart urban mobility systems, as it directly affects passenger satisfaction and network efficiency. However, the strategic planning of public transport infrastructure is often carried out without dynamic, data-driven insights into operational performance, instead relying solely on static historical records of network operations. This study develops a data-driven framework based on the XGBoost machine learning algorithm to support the prioritization of infrastructure interventions by predicting delay severity and identifying reliability hotspots along an urban bus route. Delay severity is categorized into three classes (minor, moderate, and severe), using a model that incorporates spatial, temporal, operational, and meteorological variables. The XGBoost framework achieves a high predictive performance, with classification accuracies of 91.5% and 89.7% for the outbound and inbound bus route directions, respectively. Feature importance analysis indicates that seasonal and meteorological variables are critical factors influencing delay severity, highlighting the role of broader external environmental conditions on corridor performance. Furthermore, spatial analysis identifies specific bus stops with high delay probabilities, indicating hotspots where infrastructure upgrades should be prioritized at the stop and corridor levels. This study proposes a decision-support tool that enables targeted infrastructure investments at locations where they are most needed, contributing to more efficient and resilient public transport systems in smart cities. Full article

Urban heat mitigation in megacities depends not only on cooling sources, but also on the connectivity through which cooling effects are transmitted across heterogeneous landscapes. However, existing studies have mainly focused on the static patterns of urban cold islands (UCIs), while the connectivity and disturbance response of urban cooling systems remain poorly understood. Taking Landsat-based summer thermal observations in Beijing, this study developed an integrated framework to assess the structure and resilience of the urban cold island network (CIN) by combining thermal source identification, resistance-surface construction, connectivity modeling, and disturbance simulations. Land surface temperature (LST) was extracted from Landsat 8 OLI/TIRS Collection 2 Level-2 surface temperature products acquired in July–August 2022, and cold island core sources (CICS) were subsequently identified by integrating thermal conditions with land-use characteristics. GeoDetector was used to quantify the explanatory power and interaction effects of natural, land-use, and socio-economic factors on LST spatial heterogeneity, serving as an attribution tool for interpreting thermal-environment drivers. These factors were then integrated into a resistance surface for circuit-theory-based connectivity analysis. Under the summer heat-stress scenario, 202 CICS covering 6416.95 km² were identified, mainly concentrated in peripheral mountainous areas. A total of 401 corridors were identified, including 70 primary corridors forming the structural backbone of the CIN. This spatial distribution reveals a mountain–plain cooling structure in Beijing, in which mountainous CICS constitute the regional cooling-supply base, while potential cooling transmission toward the urban core mainly depends on a limited number of backbone corridors. LULC was the dominant driver of LST, and its interactions with PD, NTL, and vegetation-related factors substantially enhanced explanatory power. Compared with random disturbance, targeted node removal led to an earlier and sharper decline in network resilience, with substantial deterioration already evident after approximately 20–30% of critical nodes were removed. These summer-based findings provide spatially explicit evidence for prioritizing cooling corridors, critical nodes, and restoration areas in connectivity-oriented urban heat mitigation and climate-responsive planning, thereby supporting hierarchical maintenance and restoration strategies based on their relative importance within the cooling network. Full article

This paper assesses the role of green hydrogen and green ammonia in the low-carbon reconstruction of Ukraine’s energy sector. The country, severely affected by war, has more than 70% of its energy infrastructure damaged or destroyed, which calls for novel solutions for not only reconstructing but also rethinking Ukraine’s energy sector shaped by the Soviet-era planning. In this context, decentralized and renewable energy solutions appear to be one of the best options to achieve this goal. This study combines four novel and mutually reinforcing methods: a Scopus-based literature review of highly cited green hydrogen publications, natural language processing (NLP) and bibliometric network analysis of Ukraine-related hydrogen research, a SWOT assessment, and a geospatial hydrogen production cost model (GEOH2). The novelty of this research lies in this integrated Ukraine-specific framework, which links research trends, wartime reconstruction constraints, hub-level policy choices, and financing risk-sensitive cost modeling. Therefore, the quantitative part of GEOH2 estimates the levelized cost of green hydrogen, while ammonia is treated as a downstream screening-level conversion and export pathway rather than as a full plant-level ammonia model. Our results show that Ukrainian green hydrogen research is concentrated on renewable-energy strategy, wind and solar electrolysis, water and desalination constraints, gas grid blending, underground storage, ammonia derivatives, and decentralized energy systems. The GEOH2 results indicate that southern Ukraine has strong physical potential for competitive green hydrogen production under de-risked financing, while war risk financing can make even resource-rich areas economically unattractive. Odesa and Dnipro emerge as important export-oriented and industrial hubs, whereas Zakarpattia remains strategically relevant as a safer western corridor linked to European markets. Our findings demonstrate that Ukraine’s hydrogen and ammonia development needs to follow a phased pathway: domestic renewable build-out and grid repair, pilot electrolysis projects and screening-level ammonia conversion pathways, targeted de-risking and insurance mechanisms, and only then broader export corridor development. This pathway can support decarbonization, energy security, industrial modernization, and Ukraine’s long-term integration into European clean energy value chains. Full article

Rapid urbanization and increasing landscape fragmentation pose significant threats to ecological connectivity, creating a need for integrative decision support approaches in sustainable spatial planning. This study presents a systematic review of ecological network optimization studies published between 2005 and 2025, following the PRISMA protocol. A total of 78 peer-reviewed studies were analyzed to identify methodological trends, recurring limitations, and research gaps in the assessment of structural and functional connectivity. Based on the gaps identified through the systematic review, this study proposes a conceptual Sustainable Spatial Decision Support System (S-SDSS) framework that integrates Morphological Spatial Pattern Analysis (MSPA), Multi-Criteria Evaluation (MCE/AHP), Minimum Cumulative Resistance (MCR), Least-Cost Path (LCP), and Gravity Modeling (GM) within a unified analytical structure. The review findings reveal a clear shift from single-method applications toward integrated multi-model approaches that better represent ecological processes and improve corridor prioritization. The proposed framework synthesizes the complementary strengths of these established methods to support evidence-based ecological network planning. The framework operates as a hybrid structure that combines a sequential analytical workflow with a unified typological classification system, generating Hybrid Ecological Typologies (T1–T5) as planning-oriented outputs that cannot be produced by any individual method alone. The proposed S-SDSS offers a transferable and policy-relevant conceptual basis for ecological network optimization, supporting green infrastructure planning, biodiversity conservation, and long-term landscape resilience across multiple spatial scales. Full article

Traffic impedance modeling is fundamental for analyzing the supply–demand characteristics of the comprehensive transportation system (CTS). However, existing studies mainly focus on highway traffic impedance, while the impedance of other transport modes, such as railways, waterways, and airways, has received much less attention. Moreover, most existing models are developed for traffic operation analysis rather than planning, which limits their comparability and practical applicability in CTS analysis. To address this gap, this study develops a unified multimodal traffic impedance modeling framework for CTS and proposes simple and comparable impedance models for highways, railways, waterways, and airways based on their respective travel characteristics. The proposed models are calibrated using real-world field data with $R^2$ values above 0.8. To further verify their effectiveness in large-scale network analysis, the models are applied to the New International Land–Sea Trade Corridor project to evaluate network flow distribution and infrastructure impacts after planned transport projects are introduced. The results show that the proposed models can reproduce network flow trends well and provide quantitative support for evaluating network performance improvement after infrastructure construction. The proposed framework can assist decision-makers in multimodal infrastructure planning and in improving the efficiency and sustainability of CTS. Full article