Search Results (600)

The complex topography and harsh natural environment of the Loess Plateau in Longzhong have been suffering from an undefined living circle structure, which has hindered rural planning and development. A rural community living circle is a spatial unit centered on meeting the needs of villagers, within which various service facilities are rationally allocated within a specific spatial scope. To refine its spatial patterns, the concept of living circles was introduced to address travel challenges. The extent of these living circles is affected by the accessibility of public service facilities and barriers to travel. Using land use data, DEM, population density, and road networks, this study employed the MCR model, gravity model, and ArcGIS spatial analysis to examine the patterns of rural community living circles. The focus was on analyzing the living circle structure of rural communities on the Loess Plateau in Longzhong, considering both natural and artificial environmental constraints. The results show: (1) Rural community living circles present multi-scale spatial features. The basic living circle covers a 15 min slow-travel area. The central living circle corresponds to village-level needs, accessible within 35 min by both slow and motorized travel. The town living circle covers a 10 km radius, reachable within 60 min by a mix of transport modes. The county living circle, dominated by motorized travel, represents the top tier of public service configuration. (2) Quantitatively, the delineation identified 2753 basic, 444 central, 19 township, and 1 county-level living circles in the Anding District of Dingxi City. The Northern, Eastern, and Southwest Zones suffer from fragmented mountainous landscapes, limiting mobility and accessibility. The Central Zone, however, benefits from a combination of mountainous terrain and river valley plains, offering superior service accessibility. (3) The analysis results based on the MCR model and gravity model aligned more closely with reality, reflecting the scale patterns of rural community living circles. The results of this study can provide theoretical guidance for rural planning, construction, and management in the hilly and gully areas of the Loess Plateau. Full article

With rapid urbanization, issues such as blind planning, disorder, and inefficiency in urban construction and land use have become increasingly prominent. To address these challenges, this study proposes a comprehensive suitability evaluation framework for urban construction land, using Zhengzhou City as a case study. The evaluation system incorporates five dimensions: topography, transportation, location, current land use status, and soil clay content. A hybrid weighting method, combining the Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM), was employed to determine indicator weights. The research indicates that the suitability of the construction land can be classified into four categories: highly suitable, moderately suitable, critically suitable, and unsuitable. Among them, the highly suitable area accounted for 6.907% (502.71 km²), the moderately suitable area accounted for 81.668% (5943.54 km²), the critically suitable area accounted for 11.422% (830.98 km²), and the unsuitable area only accounted for 0.003% (0.18 km²). The results show that most areas in Zhengzhou City are highly suitable or moderately suitable for construction land, while Gongyi and Dengfeng, due to their complex terrain and long distances from the city center, are mostly in the critically suitable or unsuitable construction land. This evaluation result is in good agreement with the actual situation and can offer valuable insights for sustainable urban development. Full article

This article presents a modular and replicable framework to assess spatial accessibility to essential public services in the Lazio Region (Italy). Current policies, framed within the EU Urban Agenda and the UN Sustainable Development Goals, emphasize improving accessibility rather than mobility, integrating land-use and transport planning, and supporting sustainable modes. The study adopts urban centres, densely populated sub-municipal units, as the main spatial unit to capture intra-municipal variability. Accessibility is measured as distance and travel time to the nearest education and healthcare facilities, for both private car and public transport, considering traffic conditions. Distances and times are computed using routing APIs and aggregated into service-specific indicators at urban-centre and municipal levels. Due to GTFS availability, the public transport analysis is restricted to the Province of Rome. Indicators are published as Linked Open Data following DCAT-AP, exposed via a SPARQL endpoint, and visualized through an interactive web map viewer. Results highlight pronounced disparities: car accessibility is relatively uniform, while public transport shows critical gaps in peripheral and mountainous areas. The framework enables transparent benchmarking and supports evidence-based, place-sensitive planning across different European contexts. Full article

Water-quality degradation from nutrient pollution remains a major challenge for resource managers. Developing effective strategies requires tools to characterize nutrient sources and transport. This study used the RSPARROW framework to develop and assess new, smaller-scale models for Total Nitrogen (TN) and Total Phosphorus (TP) transport across Mississippi (MS). These state-level models were built using 15 years (2005–2020) of observation data and considered variables including multiple nutrient sources, land characteristics, and attenuation processes. The MS models demonstrated comparable accuracy to larger regional SPARROW models, validating the use of smaller-scale models for local management. Results showed agricultural sources are the major contributors to TN, dominated by fertilizer in northern MS and livestock manure in the south. Urban land cover also significantly influenced TN and was the second most significant source of TP, following geologic material (background P). Fertilizer and manure were also important TP sources. This study provides valuable, spatially explicit data on nutrient distribution in MS streams, supporting the state’s nutrient reduction planning. It concludes by highlighting the need for future model improvements via updated source data and mean annual flow estimates. Full article

Controlling pre-analytical conditions for medical biology tests, particularly during transport, is crucial for complying with the ISO 15189 standard and ensuring high-quality medical services. The use of drones, also known as unmanned aerial vehicles, to transport clinical samples is growing in scale, but requires prior validation to verify that there is no negative impact on the test results provided to doctors. This study aimed to establish a secure, high-quality solution for transporting biological samples by drone in a coastal region of France. The 80 km routes passed over several densely populated urban areas, with take-off and landing points within hospital grounds. The analytical and clinical impact of this mode of transport was compared according to two protocols: an interventional clinical trial on 30 volunteers compared to the reference transport by car, and an observational study on samples from 126 hospitalized patients compared to no transport. The system enabled samples to be transported without damage by maintaining freezing, refrigerated, and room temperatures throughout the flight, without any significant gain in travel time. Analytical variations were observed for sodium, folate, GGT, and platelet levels, with no clinical impact on the interpretation of the results. There is a risk of time-dependent alterations of blood glucose measurements in heparin tubes, which can be corrected by using fluoride tubes. This demonstrated the feasibility and security of transporting biological samples over long distances in line with the ISO 15189 standard. Controlling transport times remains crucial to assessing the quality of analyses. It is imperative to devise contingency plans for backup solutions to ensure the continuity of transportation in the event of inclement weather. Full article

Transit-Oriented Development (TOD), formalized by Calthorpe and Poticha in 1993, emerged to counter urban sprawl, reduce car dependency, and revitalize historical community centers. Rooted in “new urbanism”, TOD emphasizes integrated regional land-use planning and high-capacity public transportation. In the Middle East, TOD implementation remains understudied, particularly regarding heritage integration and social equity in arid climates. Doha’s rapid social and economic transformation presents both opportunities and risks: growth offers urban revitalization yet threatens to displace communities and dilute cultural identity. Shifts in urban planning have aimed to address sustainability, connectivity, and heritage preservation. This study examines Msheireb Downtown Doha (MDD) to assess how TOD can restore historic districts while managing gentrification, enhancing accessibility and promoting inclusiveness. A mixed-methods approach was applied, including 12 semi-structured interviews with stakeholders (Qatar Rail, Msheireb Properties, Ministry of Municipality and Environment), purposive surveys of 80 urban users, site observations, and spatial mapping. Using the Node-Place-People (NPP) model, the study evaluates TOD effectiveness across transportation connectivity (node), built environment quality (place), and equity metrics (people). The findings show that MDD successfully implements fundamental TOD principles through its design, which enhances connectivity, walkability, social inclusiveness, and heritage preservation. However, multiple obstacles remain: the “peripheral island effect” limits benefits to the core, pedestrian–vehicular balance is unresolved, and commercial gentrification is on the rise. This research provides evidence-based knowledge for GCC cities pursuing sustainable urban regeneration by demonstrating both the advantages of TOD and the necessity for critical, context-sensitive implementation that focuses on social equity together with physical transformation. Full article

Understanding how transport conditions and the built environment shape urban CO₂ emissions is critical for low-carbon urban development. This study analyses CO₂ emission intensity across fifty major Chinese cities using integrated ODIAC emissions, VIIRS night-time lights, traffic performance indicators, built-environment morphology, population/POI structure, and socioeconomic controls. We develop a GeoAI workflow that couples XGBoost modelling with SHAP interpretation, congestion-based city grouping, and 1 km grid-level GNNWR to map intra-urban spatial non-stationarity. The global model identifies night-time light intensity as the strongest predictor, followed by population density and building density. SHAP results reveal pronounced nonlinearities, with high sensitivity at low–medium levels and diminishing marginal effects as activity and density increase. Although transport indicators are less influential in the aggregate model, their roles differ across congestion regimes: in low-congestion cities, emissions align more consistently with overall activity intensity, whereas in high-congestion cities they respond more strongly to population distribution, motorisation, and built-form intensity, with less stable relationships. Grid-level GNNWR further shows that key mechanisms are spatially uneven within cities, with local effects concentrating in specific cores and corridors or fragmenting across multiple subareas. These findings demonstrate that emission drivers are context-dependent across and within cities. Accordingly, uncongested cities may gain more from activity-related energy-efficiency measures, while highly congested cities may require congestion-sensitive land-use planning, spatial-structure optimisation, and motorisation control. Integrating explainable GeoAI with regime differentiation and spatial heterogeneity mapping provides actionable evidence for targeted low-carbon planning. Full article

The worldwide transition to renewable energy systems is motivated by diminishing fossil fuel availability and the intensifying consequences of climate change. This study presents a Mixed-Integer Linear Programming (MILP) model for designing and optimising the bio-fuel and electricity supply chain in Colombia, using sugarcane as the main feedstock and integrating microalgae cultivation in vinasse. Six alternative biorefinery configurations and four microalgae conversion pathways were evaluated to inform strategic planning. The optimisation results indicate that microalgae achieve higher energy yields per unit of land than sugarcane. Ethanol production from sugarcane could meet all of Colombia’s gasoline demand, while diesel and sustainable aviation fuel derived from microalgae could supply around 9% and 16%, respectively, of the country’s consumption. Further-more, pelletised bagasse emerges as a viable alternative to replace part of the coal used in thermoelectric plants. From an economic perspective, all scenarios achieve a positive net present value, confirming their profitability. Sensitivity analysis highlights the critical factors influencing the deployment of distilleries as ethanol price, algae productivity, and sugarcane cost. Furthermore, transportation costs play a decisive role in the geographic location of microalgae-based facilities and the distribution of their products. Full article

The development of street-based outdoor physical activities plays a vital role in improving public health issues and advancing the goals of the “Healthy China” initiative, and the built environment is widely considered a key factor in promoting such activities and urban sustainability. Existing studies have paid limited attention to the nonlinear relationships between the built environment and outdoor physical activity and have mostly focused on a single type of activity (such as walking or cycling), with few comparative analyses across different activity types. With the purpose of addressing these limitations and providing cross-sectional empirical evidence for sustainable street design and active-transport policy, this study examines streets within the Second Ring Road of Changsha and uses large-scale street-level outdoor activity trajectory data to investigate associations between built environment indicators and outdoor activity flows. A Random Forest model, followed by the application of SHapley Additive exPlanations (SHAP), is used to characterize the nonlinear associations and interactions among variables, capturing patterns relevant to sustainable mobility, public health and urban form. The results indicate the following: (1) The built environment indicators are associated with walking, jogging, and cycling in distinctly different patterns—walking shows stronger associations with population density and access to bus stops; jogging demonstrates stronger associations with the accessibility of large open spaces; and cycling is more associated with land use mix and road intersection density. (2) Nonlinear associations and threshold-like patterns commonly exist between built environment variables and activity flows, with indicators such as bus stop density and walking continuity exhibiting pronounced effects within specific intervals. (3) Interaction effects among variables contribute importantly to model predictions, especially for jogging where their influence can even exceed the main effects of individual factors. These results underscore the potential value of implementing tailored street design strategies for different activity types and provide empirical evidence relevant to health-oriented urban planning. Full article

Heavy metal contamination of agricultural soils represents a critical environmental and agronomic challenge, particularly in regions exposed to intensive land use and transport-related emissions. This study presents a detailed assessment of soil contamination in the Dargov cadastral area (Eastern Slovakia), where elevated concentrations of Cu, Zn, Pb, Ni, As, Cd, and Cr were detected through multi-depth sampling near the I/19 first-class road. Analytical results confirmed exceedances of Slovak regulatory thresholds (Decree No. 59/2013), with persistent contamination observed even in the deepest sampling interval (20–40 cm), indicating vertical migration and long-term accumulation. Concentrations of Pb (85–210 mg·kg⁻¹), Cd (2.1–5.4 mg·kg⁻¹), Zn (120–340 mg·kg⁻¹), and Ni (45–95 mg·kg⁻¹) exceeded Slovak regulatory thresholds. The highest values were consistently detected in the 0–10 cm layer and within 3 m of the I/19 road, with a gradual decline at greater depths and distances. Nevertheless, Cd and Ni remained above permissible limits even in the deepest sampling interval (20–40 cm), confirming vertical migration and long-term persistence of contamination. The spatial distribution of contaminants suggests a dominant influence of road traffic, with implications for crop safety, soil fertility, and rural land management. Based on the findings, the study proposes context-sensitive remediation strategies, including phytoremediation and chemical immobilization, and emphasizes the need for integrated monitoring systems and land-use planning to mitigate risks. The case study contributes to the broader discourse on sustainable soil management in Central European agricultural landscapes affected by diffuse pollution. Full article

This study analyzes the establishment of Local Agri-Food Systems (LAFSs) in the triple-border region between the states of Minas Gerais, Rio de Janeiro, and São Paulo, by identifying and mapping potential areas of primary peasant agri-food production. An integrated analysis of data sources was treated, processed, and integrated into a common spatial support. Land use and land cover data were used from demographic and agricultural censuses, from the Rural Environmental Registry, agrarian reform settlement projects and conservation units. Our study revealed that 23.73% of the regional area has potential for peasant production, identifying four regions that stand out in terms of this potential. The area presented livestock and animal husbandry as the main agri-food chain, with potential for processing within the territory itself, in addition to extractive activities in the Atlantic Forest biome. The results indicate that there are possibilities for the establishment of LAFSs as a local development strategy associated with social inclusion and environmental responsibility, although there is a need to expand and strengthen the transportation and marketing channels for products from these short chains. The cartographies produced aim to contribute as auxiliary instruments to land use planning and management, seeking to strengthen LAFSs at different scales of governance. Full article

In the context of rapid population aging in China, ensuring pedestrian safety for older adults has become a critical concern, particularly in mountainous cities where the built environment’s role remains understudied. This study examines how built environment factors influence road traffic crashes involving older pedestrians in such terrains, aiming to propose targeted safety optimization strategies. Using ten-year road traffic crash data from Yuzhong District, Chongqing, the research employed both Standard Poisson Regression and Bayesian Poisson Regression models for analysis. Key findings indicate that crash frequency significantly increased with higher densities of footbridges and recreational facilities, as well as with a greater proportion of parks and green space, whereas it decreased with a higher land use mix, greater densities of educational facilities, and higher public transport stop density. The proportion of storage land and the density of medical facilities showed no significant effects. These results provide concrete, evidence-based guidance for urban planning and transportation management in mountainous cities to optimize pedestrian infrastructure and enhance walking safety for the elderly. Full article

Lake eutrophication exhibits pronounced spatial heterogeneity at the watershed scale, yet a systematic and quantitative understanding of how landscape characteristics drive these variations remains limited. In this study, a long-term and internally consistent trophic state dataset for the Liangzi Lake Basin was constructed by integrating Landsat imagery from 1990 to 2022 with a semi-analytical water color inversion method. A multi-scale landscape feature system incorporating both land use composition and landscape pattern metrics was developed at the sub-basin level to elucidate the mechanisms by which landscape characteristics influence eutrophication dynamics. The XGBoost model was employed to characterize the nonlinear relationships between landscape attributes and trophic conditions, while the SHAP interpretability approach was applied to quantify the relative contribution of individual landscape components and their interaction pathways. The analytical framework demonstrates that landscape pattern attributes—such as fragmentation, diversity, and connectivity—play essential roles in shaping the spatial variability of eutrophication by modulating hydrological processes, nutrient transport, and ecological buffering capacity. By integrating remote sensing observations with interpretable machine learning, the study reveals the complexity and scale dependence of landscape–water interactions, providing a methodological foundation for advancing the understanding of eutrophication drivers. The findings offer theoretical guidance and practical references for optimizing watershed landscape planning, controlling non-point source pollution, and supporting ecological restoration efforts in lake basins. Full article

In the context of accelerating global urbanization and sustainable development challenges, impervious surfaces, as a key component of urban land cover, are significantly associated with regional economic development. This study takes Harbin, a typical cold region city, as a research object and constructs a three-level analytical framework of “land surface classification-economic simulation-mechanism analysis.” By innovatively integrating multi-source remote sensing, demographic, and economic data, the research addresses gaps in understanding urban sustainability in cold environments. An enhanced XGBoost algorithm was employed to achieve high-precision classification of ten land surface materials, resulting in a high overall accuracy. Furthermore, a gridded GDP spatialization model developed using high-resolution population data demonstrated superior performance compared to traditional methods. Machine learning-assisted analysis revealed that asphalt and metal surfaces are the most significant impervious materials driving economic output, reflecting the respective influences of transportation infrastructure and industrial agglomeration. Spatial pattern analysis indicates that Harbin’s impervious surfaces exhibit a lower fractal dimension and a distinct grid-like morphology compared to the typical subtropical city of Guangzhou, underscoring urban form adaptations to cold climatic constraints. The strong spatial coupling between gradients of GDP intensity and the attenuation of impervious surface density is quantitatively confirmed. This study provides a quantitative basis and a transferable technical framework for optimizing land use intensity and infrastructure planning in cold cities, thereby offering a scientific foundation for sustainable, intensive land utilization in climate-vulnerable urban systems. Full article

The quality of groundwater is essential to sustain human and environmental activities now and in the future. However, the current intensification of anthropogenic activities has increased the magnitude of contaminant sources. When those contaminants reach a saturated zone (groundwater), their levels of presence may make their use for various purposes unfeasible. Therefore, research into the vulnerability degree is essential for estimations of potential for contamination and possible risks. This manuscript presents the results obtained by applying a parametric procedure for mapping groundwater vulnerability based on a set of attributes related to contaminant sources, transport, and natural attenuation of contaminants. In addition to vulnerability zoning, the set of attributes supports the adoption of measures and recommendations related to territorial and environmental planning guidelines and orientations about land uses. The open source Geographical Information System—QGIS open source version 3.22.4 was used for spatially integrating different attribute maps and obtaining partial indices for contaminant introduction, transport, and attenuation; hence, the specific vulnerability index. The results promoted the division of the region into six classes of specific vulnerability, namely, extremely high, accounting for around 23% vulnerability, very high (20%), moderate (24%), very low (23%), and high and low together accounting for 10%. Such categories were associated with measures and recommendations aimed at territorial and environmental planning and protection and control of environmental functions. Approximately 50% of the study area requires restrictive measures regarding buildings, sustainable drainage systems, waste disposal, chemical storage, and petrol stations, and other measures are necessary for the protection of wells and natural springs. The method employed can produce results that enable areas to be categorized and ranked in terms of specific vulnerability; however, it requires a large quantity of data and spatial details according to the scale adopted. The specific vulnerability map produced will help planners make more appropriate territorial and environmental planning decisions and risk management, avoiding groundwater contamination. Full article