Search Results (6,292)

Assessment of cultural ecosystem services (CESs) is a key component in advancing the sustainable development of urban ecosystems. Mapping the spatial distribution of CESs provides spatially explicit insights for urban landscape planning. However, most assessments lack regional adaptability, particularly in cities with pronounced environmental and cultural heterogeneity. To address this gap, this study focused on the central urban area of Lhasa, using communities as units to develop a tailored CES assessment framework. The framework integrated the MaxEnt model with multi-source indicators to analyze the spatial distribution of five CES categories and their relationships with environmental variables. Spatial statistics and classification at community level informed the CES spatial optimization strategies. Results indicated that high-value CES areas were predominantly concentrated in the old city cluster, typified by Barkhor and Jibenggang subdistricts, following an east–west spatial pattern along the Lhasa River. Distance to tourist spot contributed 78.3% to cultural heritage, 86.1% to spirit and religion, and 42.2% to ecotourism and aesthetic services, making it the most influential environmental variable. At the community level, CESs exhibited a distinct spatial gradient, with higher values in the central area and lower values in the eastern and western peripheries. For the ecotourism and aesthetic category, 61.47% of the community area was classified as low service, whereas only 1.48% and 7.33% were identified as excellent and high. Moreover, communities within subdistricts such as Barkhor and Zhaxi demonstrated excellent service across four CES categories, with notably lower performance in the health category. This study presents a quantitative and adaptable framework and planning guidance to support the sustainable development of CESs in cities with similar characteristics. Full article

With the development of the maritime Internet of Things (MIoT), a large number of sensors are deployed, generating massive amounts of data. However, due to the limited data processing capabilities of the sensors and the constrained service capacity of maritime communication networks, the local and cloud data processing of MIoT are restricted. Thus, there is a pressing demand for efficient edge-based data processing solutions. In this paper, we investigate unmanned aerial vehicle (UAV)-assisted maritime edge computing networks. Under energy constraints of both UAV and MIoT devices, we propose a Deep Deterministic Policy Gradient (DDPG)-based maritime computation offloading and resource allocation algorithm to efficiently process MIoT tasks current form of UAV. The algorithm jointly optimizes task offloading ratios, UAV trajectory planning, and edge computing resource allocation to minimize total system task latency while satisfying energy consumption constraints. Simulation results validate its effectiveness and robustness in highly dynamic maritime environments. Full article

With the advancement of China’s industrialization, demand for express freight transportation has been rising. However, high-speed rail freight faces challenges, such as relatively low transport efficiency and lower revenues, compared with air and road modes. To address these issues, this paper focuses on freight train operations. First, it analyzes key influencing factors, including operating costs and benefits. Next, it conducts a comprehensive assessment of train consist capacity, freight node capacity, transport demand, and the number of freight services, and formulates an operational planning model that maximizes rail revenue, minimizes intermediate stops, and satisfies freight demand. Finally, an Improved Golden Jackal Optimization–based Genetic Algorithm (IGJOGA) is proposed to solve the model. Simulation results indicate that IGJOGA achieves higher solution efficiency than a traditional genetic algorithm for the freight train operation planning problem, and the results can provide a practical reference for freight train set operation schemes. Full article

Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6 multi-model ensemble precipitation projections for Shanghai, integrating Delta statistical downscaling with observational data to enhance spatial accuracy and reduce uncertainty. After downscaling, RMSE values of daily precipitation for individual models range from 10.158 to 12.512, with correlation coefficients between −0.009 and 0.0047. The BMA exhibits an RMSE of 8.105 and a correlation coefficient of 0.056, demonstrating better accuracy compared to individual models. The BMA-weighted projections, coupled with Soil Conservation Service Curve Number (SCS-CN) hydrological model and drainage capacity constraints, reveal spatiotemporal flood risk patterns under Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios. Key findings indicate that while SSP245 shows stable extreme precipitation intensity, SSP585 drives substantial increases—particularly for 50-year and 100-year return periods, with late 21st century maximums rising by 24.9% and 32.6%, respectively, compared to mid-century. Spatially, flood risk concentrates in peripheral districts due to higher precipitation exposure and average drainage capacity, contrasting with the lower-risk central urban core. This study establishes a watershed-based risk assessment framework linking climate projections directly to urban drainage planning, proposing differentiated strategies: green infrastructure for runoff reduction in high-risk areas, drainage system integration for vulnerable suburbs, and ecological restoration for coastal zones. This integrated methodology provides a replicable approach for climate-resilient urban flood management, demonstrating that effective adaptation requires scenario-specific spatial targeting. Full article

Background: Although the expansion of medical resources has largely alleviated challenges of “more diseases but fewer medicines”, the growing urbanization and rapid aging in China have led to increasing demands of healthcare services in metropolitan cities. The uneven distribution of medical facilities makes services unequal for residents in the city. To achieve fair and rapid access to medical services, healthcare accessibility and equity have become key concerns. The introduction of tele-health, i.e., online visits or digital health, can help balance the distribution of medical resources to improve accessibility and equity, particularly for elderly patients with chronic diseases. Methods: To quantitatively assess the spatial accessibility of healthcare facilities, an improved two-step floating catchment area method with tele-health (i2SFCA-TH) is proposed to study the demand–supply ratio by considering traveling time, chronic diseases, and online visits based on services provided by community and tertiary hospitals. An optimization model using mixed-integer programming to maximize average accessibility under resource constraints could help improve overall accessibility and reduce differences in access among all residential divisions to achieve better equity in the region. Results: By applying the method in a metropolitan city in China, it is observed that the overall spatial accessibility of residential divisions in the city is 0.72, but the gap between the highest and the lowest reaches 2.36; i.e., significant differences exhibit due to uneven allocation of medical resources. By introducing tele-health, the gaps of access among different divisions can be decreased, with the largest gap reduced to 1.49, and the accessibility in divisions with poor medical resource allocation can be increased. Finally, the mean healthcare accessibility and equity in the study region can be improved to 0.75. In addition, it is shown that proper management of medical resources and patients’ willingness to accept online visits could help improve accessibility and equity, which can provide insights for hospital management and urban planning. Conclusions: An integrated framework to quantitatively assess and optimally improve healthcare accessibility and equity of medical resource allocation through tele-health is presented in this paper. An i2SFCA-TH method and an optimization model are used in the framework, which provides hospital management and urban planners a quantitative tool to improve accessibility and equity in metropolitan cities in China and other countries. Full article

Accurate prediction and management of the service life of buildings and structural components are crucial for ensuring durability and economic efficiency. This paper investigates both discrete- and continuous-time Markov chains as probabilistic models for representing deterioration processes of building structures. Transition probabilities, fundamental matrices, and absorption times are computed to quantify expected lifespans and degradation pathways. Numerical simulations illustrate how state probabilities evolve, inevitably converging toward structural failure in the absence of maintenance interventions. Additionally, this study explicitly addresses uncertainties inherent in lifecycle predictions through the application of fuzzy set theory. A fuzzy Markov chain model is formulated to represent imprecise deterioration states and transition probabilities, which validate the predictable yet uncertain progression of structural deterioration through graphical analyses and fuzzy simulations. The proposed methodology, including fuzzy modeling, provides building managers and engineers with a robust analytical framework to optimize maintenance scheduling, refurbishment planning, and resource allocation for sustainable lifecycle management under uncertainty. Full article

Coastal erosion and shoreline change represent major challenges for the sustainable management of coastal environments, with implications for infrastructure, ecosystems, biodiversity, and the socio-economic well-being of coastal communities. This study investigates the shoreline evolution of 79 Mediterranean microtidal beaches located along the southern coast of Sardinia Island (Italy), using the Digital Shoreline Analysis System (DSAS). Shorelines were manually digitised from high-resolution aerial orthophotos made available through the WMS service of the Autonomous Region of Sardinia, covering the period 1954–2022. Shoreline changes were assessed through five statistical indicators: Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), Weighted Linear Regression (WLR), and Linear Regression Rate (LRR). The results highlight marked spatial and temporal variability in shoreline retreat and accretion, revealing patterns that link shoreline dynamics to the degree of anthropisation or naturalness of each beach. In fact, coastal areas characterised by local anthropogenic factors showed higher rates of shoreline retreat and/or accretion, while natural beaches showed greater stability and resilience in the long term. The outcomes of this analysis provide valuable insights into local coastal dynamics and represent a critical knowledge base for developing targeted adaptation strategies, supporting spatial planning, and reducing coastal risks under future climate change scenarios. Full article

Rapid population aging in developing countries has intensified demand for accessible nursing home services, yet spatial disparities in service distribution remain insufficiently examined in secondary cities. This study investigates spatial distribution and multi-dimensional accessibility of nursing homes in Kunming, China, using comprehensive spatial analytical methods to inform sustainable urban development. We analyzed 205 nursing homes with 47,600 beds, evaluating spatial distribution patterns, economic accessibility, and spatial accessibility across different transportation modes. Our analysis reveals a pronounced monocentric pattern with nursing resources concentrated within central urban districts, creating a “primary core-multiple satellite” structure and spatial mismatch between service supply and older adult population needs. A distinct institutional dichotomy exists between publicly and privately operated facilities, establishing a dual-track system with different accessibility implications for social equity. Economic accessibility analysis demonstrates significant barriers in central urban and tourism-oriented districts dominated by higher-priced private facilities, where minimum prices frequently exceed average monthly pension. Spatial accessibility remains inadequate across all transportation modes, with only 24.3% of communities achieving normal or higher accessibility via private car, 21.5% via public bus, and merely 13.9% via walking. These limitations primarily stem from insufficient service capacity (34 beds per 1000 older adults) relative to demographic needs rather than transportation constraints. We recommend three sustainable interventions: implementing demand-based planning mechanisms, establishing progressive pricing policies, and developing older adult-friendly transportation networks. This framework supports sustainable urbanization by promoting spatial equity and efficient resource allocation, providing valuable insights for secondary cities pursuing sustainable development goals. Full article

The challenge for healthcare policy makers, managers and practitioners is finding ways to effectively collaborate with patients and community to plan, deliver and evaluate services. The study examined how managers engage the community with the strategic redesign of health services. The study focused on four large scale redevelopment projects, valued at A$2.8B, occurring within a health district in New South Wales, Australia. The study employed a multiple qualitative methods design comprising semi-structured interviews and focus groups. Participants were professionals (n = 24) involved in the strategic planning of health facility redevelopment. Thematic analysis was used to identify, analyse and report findings. Three issues emerged as significant factors influencing engagement, including the following: establishing a new mindset to service planning and delivery; future proofing service delivery; and management of stakeholder expectations. The unique contribution of the research is the identification of three interwoven strategies with 30 actions proposed to assess, understand and respond to external factors: 1. Foster an environment that allows for flexible and adaptable thinking and discussion; 2. Develop systems, structures and processes that facilitate engagement; 3. Encourage systems thinking for effective continuous service provision and redevelopment. Large scale redevelopment projects provide a platform for the strategic redesign of health services. When doing so, engaging the community with strategic planning, implementation and evaluation of healthcare services can lead to improved care outcomes. Full article

Background/Objectives: This study aims to provide a comprehensive understanding of the current mental health workforce and the factors influencing its distribution within adult community mental health services in Western Australia’s North Metropolitan Health Service. Methods: Mental health workforce supply across North Metropolitan Statistical Area Level 2 (SA2-Australian Statistical Geography Standard) was estimated using the Geographically-adjusted Index of Relative Supply (GIRS) and categorised as low (0–3) or moderate-to-high (4–8) for analysis and testing associations with multiple covariates. Population, clinic, and individual-level data were analysed using principal component analysis and logistic regression to identify the factors associated with workforce distribution. Results: Of the 68 SA2s analysed, 25 SA2s (representing 45 suburbs) were identified as having a low workforce supply, defined by a GIRS score of ≤3. These areas were compared to those with a moderate-to-high supply (GIRS > 3) to assess the differences in service performance. A principal component analysis identified three key components within the data: service usage, health service providers, and service efficiency. A logistic regression analysis revealed that areas with a low workforce supply were significantly more likely to experience reduced service usage (OR = 3.3, p = 0.037, CI [0.09–0.92]), indicating fewer patient interactions and lower engagement with mental health services. In addition, these areas demonstrated a lower service efficiency as evidenced by longer wait times (OR = 3.7, p = 0.002, CI [1.62–8.50]), suggesting that workforce shortages directly impact timely access to health care. Conclusions: The findings revealed disparities in workforce supply across different urban locations, with low-supply areas facing tangible challenges in service accessibility and operational efficiency. These findings highlight the need for targeted mental health workforce planning. Developing and implementing best practice guidelines is essential for effectively managing service demands and reducing waitlists. Full article

Background: Urban rail transit ensures efficient mobility in densely populated metropolitan areas. This study focuses on the Cairo Metro Network and addresses the Rolling Stock Rotation Planning Problem (RSRPP), aiming to improve operational efficiency and service quality. Methods: A Mixed-Integer Linear Programming (MILP) model is developed to integrate rolling stock rotation, deadhead routing, and maintenance scheduling. Two single-objective formulations are introduced to separately minimize denied passengers and the number of Electric Multiple Units (EMUs) used. To address scalability for larger instances, a Simulated Annealing (SA) metaheuristic is designed using a list-based solution representation and customized neighborhood operators that preserve feasibility. Results: Computational experiments based on real-world data validate the practical relevance of the model. The MILP achieves optimal solutions for small and medium-sized instances but becomes computationally infeasible for larger ones. In contrast, the SA algorithm consistently produces high-quality solutions with significantly reduced solve times. Conclusions: To the best of the authors’ knowledge, this is the first study to apply SA to the urban rail RSRPP while jointly integrating deadhead routing and maintenance scheduling. The proposed approach proves to be robust and scalable for large metro systems such as Cairo’s. Full article

Cities play a central role in territorial development, acting as engines of economic growth, innovation, and social well-being. However, contemporary urban challenges, such as socio-spatial segregation, environmental degradation, and mobility constraints, necessitate innovative planning approaches. The “15-minute city” model, conceptualised by Moreno, seeks to reorganise urban spaces to enhance proximity, sustainability, and quality of life by ensuring that essential services are accessible within a short walk or bike ride. This study examines the applicability of this model in Portugal, analysing its presence in national scientific research and its integration into recent Sustainable Urban Mobility Action Plans. Additionally, a spatial analysis using pedestrian-based isochrone mapping assesses accessibility to education and health services, identifying areas with potential for implementation. The results indicate a selective adoption of the model’s operational dimensions, with an emphasis on fare integration and soft mobility infrastructure. However, there is a noticeable deficiency in regulatory instruments designed to promote multifunctionality and social–spatial inclusion. The spatial pattern in northern Portugal reveals disparities in pedestrian accessibility. This study highlights the stronger need for context-sensitive urban strategies, emphasising that while the 15-minute city offers a promising framework, its success depends on local adaptations and governance models. Full article

To address the impact of distributed energy resource volatility on distribution network fault restoration, this paper proposes a strategy that incorporates net load forecasting. A Bayesian-optimized long short-term memory neural network is used to accurately predict the net load within fault-affected areas, achieving an R² of 0.9569 and an RMSE of 12.15 kW. Based on the forecasting results, a fast restoration optimization model is established, with objectives to maximize critical load recovery, minimize switching operations, and reduce network losses. The model is solved using a genetic algorithm enhanced with quantum particle swarm optimization (GA-QPSO), a hybrid metaheuristic known for its superior global exploration and local refinement capabilities. GA-QPSO has been successfully applied in various power system optimization problems, including service restoration, network reconfiguration, and distributed generation planning, owing to its effectiveness in navigating large, complex solution spaces. Simulation results on the IEEE 33-bus system show that the proposed method reduces network losses by 33.2%, extends the power supply duration from 60 to 120 min, and improves load recovery from 72.7% to 75.8%, demonstrating enhanced accuracy and efficiency of the restoration process. Full article

Urban spatial justice is a critical issue in the context of rapid urbanization. Improving public well-being depends on the efficient use of park green space (PGS) resources. This study evaluates the spatial distribution equity and social equity of PGS in Jinan City, Shandong Province, China, with the aim of optimizing their spatial layout, mitigating poor accessibility due to uneven spatial distribution, and improving the quality of life for all inhabitants. Firstly, based on Sustainable Development Goal 11 (SDG11), we constructed an urban sustainable development index system to quantify residents’ demand levels. The supply level was measured through three dimensions: quantity, quality, and accessibility of PGS utilizing multi-source geospatial data. A coupling coordination degree model (CCDM) was employed to analyze the supply-demand equilibrium. Secondly, Lorenz curves and Gini coefficients were utilized to evaluate the equity of PGS resource distribution to disadvantaged populations. Finally, a k-means clustering algorithm found the best sites for additional parks in low-accessibility regions. The results show that southern areas—that is; those south of the Yellow River—showed greater supply-demand equilibrium than northern ones. With a Gini index for PGS services aimed at vulnerable populations of 0.35, the citywide social level distribution appeared to be relatively balanced. This paper suggests an evaluation technique to support fair resource allocation, establishing a dual-perspective evaluation framework (spatial and social equality) and giving a scientific basis for PGS planning in Jinan. Full article

Urban green spaces are important nature-based solutions to mitigate climate change. While the distribution of green spaces within cities is well documented, few studies assess whether inequities in green space quantity (i.e., percent cover) are mirrored by inequities in green space quality (i.e., vegetation health or sensitivity to stressors). Green space quality is important to measure alongside green space quantity because vegetation that is healthier and less sensitive to stressors such as climatic fluctuations sustain critical ecosystem services through stressful environmental conditions, especially as the climate changes. We use a 40-year remote sensing dataset to examine the spatial patterns and underlying drivers of vegetation sensitivity to short-term (monthly) climate fluctuations in Chicago. Our results show that although vegetation cover was not equitably distributed between racially and ethnically segregated census tracts, socio-demographic composition was not a key driver of spatial variation in short-term vegetation sensitivity to climate. Instead, we found that vegetation growth form was a strong predictor of differences in vegetation sensitivity among communities. At the census tract level, higher herbaceous/shrub cover was associated with increased sensitivity to climate, while higher tree cover was associated with decreased sensitivity. These results suggest that urban green spaces comprising trees will be less sensitive (i.e., more resistant) to short-term climate fluctuations than those comprising predominately herbaceous or shrub cover. Our findings highlight that urban green space quality can vary spatially within cities; however, more work is needed to understand how the drivers of vegetation sensitivity vary among cities, especially those experiencing different climatic regimes. This work is key to planning and planting high-quality, climate change-resilient and equitable urban green spaces. Full article