Search Results (103)

E-commerce growth has reshaped consumer behavior and retail services, driving parcel demand and challenging last-mile logistics. Existing research predominantly relies on survey data and global regression models that overlook intra-urban spatial heterogeneity in shopping behaviors. This study bridges this gap by analyzing e-commerce demand’s spatial distribution from a retail service perspective, identifying key drivers, and evaluating implications for omnichannel strategies and logistics. Utilizing waybill big data, spatial analysis, and multiscale geographically weighted regression, we reveal: (1) High-density e-commerce demand areas are predominantly located in central districts, whereas peripheral regions exhibit statistically lower volumes. The spatial distribution pattern of e-commerce demand aligns with the urban development spatial structure. (2) Factors such as population density and education levels significantly influence e-commerce demand. (3) Convenience stores play a dual role as retail service providers and parcel collection points, reinforcing their importance in shaping consumer accessibility and service efficiency, particularly in underserved urban areas. (4) Supermarkets exert a substitution effect on online shopping by offering immediate product availability, highlighting their role in shaping consumer purchasing preferences and retail service strategies. These findings contribute to retail and consumer services research by demonstrating how spatial e-commerce demand patterns reflect consumer shopping preferences, the role of omnichannel retail strategies, and the competitive dynamics between e-commerce and physical retail formats. Full article

This study explores the spatial and social implications of urban food systems in Quito, Ecuador, focusing on how food access inequalities reflect and reinforce broader urban disparities. The research addresses a critical problem in contemporary urbanization: the disconnection between food provisioning and spatial equity in rapidly growing cities. The objective is to assess and map disparities in food accessibility using a mixed-methods approach that includes field observation, participatory mapping, value chain analysis, and statistical modeling. Five traditional and emerging food markets were studied in diverse districts across the city. A synthetic accessibility function F(x) was constructed to model food access levels, integrating variables such as income, infrastructure, transport availability, and travel time. These variables were subjected to Principal Component Analysis (PCA) and hierarchical clustering to generate three typologies of territorial vulnerability. The results reveal that peripheral areas exhibit lower F(x) values and weaker integration with the formal food system, leading to higher consumer costs and limited fresh food options. In contrast, central districts benefit from multimodal infrastructure and greater diversity of supply. This study concludes that food systems should be treated as critical urban infrastructure. Integrating food equity into land use and mobility planning is essential to promote inclusive, sustainable, and resilient urban development. Full article

With the rapid advancement of urbanization, the increasing demand and insufficient supply of public service facilities for children have become urgent problems requiring resolution. This study employs the Shannon diversity index, the location entropy, spatial autocorrelation, and the Geographically Weighted Regression (GWR) to analyze the spatial distribution characteristics and influencing factors of children’s public service facilities in the central urban area of Shenyang. The findings of the study are as follows: (1) There are significant differences in the spatial distribution of children’s public service facilities. Higher quantity distribution and diversity index are observed in the core area and Hunnan District compared to the peripheral areas. The Gini coefficient of various facilities is below the fair threshold of 0.4, but 90.32% of the study units have location entropy values below 1, indicating a supply–demand imbalance. (2) The spatial distribution of various facilities exhibits significant clustering characteristics, with distinct differences between high-value and low-value cluster patterns. (3) The spatial distribution of facilities is shaped by four factors: population, transportation, economy, and environmental quality. Residential area density and commercial service facility density emerge as the primary positive drivers, whereas road density and average housing price act as the main negative inhibitors. (4) The mechanisms of influencing factors exhibit spatial heterogeneity. Positive driving factors exert significant effects on new urban areas and peripheral zones, while negative factors demonstrate pronounced inhibitory effects on old urban areas. Non-linear threshold effects are observed in factors such as subway station density and public transport station density. Full article

Green Stormwater Infrastructure (GSI), as a nature-based solution, has gained widespread recognition for its role in mitigating urban flood risks and enhancing resilience. Equitable spatial distribution of GSI remains a pressing challenge, critical to harmonizing urban hydrological systems and maintaining ecological balance. However, the complexity of matching GSI supply with urban demand has limited comprehensive spatial assessments. This study introduces a quantitative framework to identify priority zones for GSI deployment and to evaluate supply–demand dynamics in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) using a coupled coordination simulation model. Clustering and proximity matrix analysis were applied to map spatial relationships across districts and to reveal underlying mismatches. Findings demonstrate significant spatial heterogeneity: over 90% of districts show imbalanced supply–demand coupling. Four spatial clusters were identified based on levels of GSI disparity. Economically advanced urban areas such as Guangzhou and Shenzhen showed high demand, while peripheral regions like Zhaoqing and Huizhou were characterized by oversupply and misaligned allocation. These results provide a systematic understanding of GSI distribution patterns, highlight priority intervention areas, and offer practical guidance for large-scale, equitable GSI planning. Full article

Air pollution is a growing environmental and public health concern, particularly in urban areas where vehicular emissions, industrial activities, and public events contribute to deteriorating air quality. This study examines air pollution concentrations in two districts of Cusco, Peru, using an interdisciplinary approach that integrates environmental monitoring and social risk perception analysis. Air quality measurements revealed elevated levels of PM2.5 and NO₂, with 40–60% of data falling within “Moderate” or “Unhealthy for sensitive groups” categories according to international standards. Notably, major cultural events such as Inti Raymi were associated with a threefold increase in pollutant concentrations, highlighting their impact on urban air quality. Simultaneously, surveys and interviews assessed public perception, revealing a varied understanding of pollution risks and a general concern for health impacts, especially in more polluted and densely populated areas. However, trust in scientists remains limited, which poses challenges for the implementation of evidence-based environmental strategies. This study highlights significant environmental inequality within the city, with central districts facing greater pollution burdens than peripheral zones. These findings underscore the need for holistic air quality management strategies that combine scientific assessments with community engagement. Strengthening trust between scientists and local populations is essential to develop inclusive and effective interventions that align with both technical and social priorities, particularly in rapidly urbanizing contexts such as Cusco. Full article

Cultural ecosystem services (CES) in urban parks, as a vital component of urban ecosystem services (ES), are increasingly recognized as an important tool for advancing urban sustainability and implementing nature-based solutions (NbS). The supply–demand relationship of CES in urban parks is strongly shaped by sociocultural and spatial geographic factors, playing a crucial role in optimizing urban landscape structures and enhancing residents’ well-being. However, current research generally lacks adaptive evaluation frameworks and quantitative methods, particularly for cities with significant spatial and cultural diversity. To address this gap, this study examines the central district of Lhasa as a case study to develop a CES supply–demand evaluation framework suitable for plateau river valley cities. The study adopts the spatial integration analysis method to establish an indicator system centered on “recreational potential–recreational opportunities” and “social needs–material needs,” mapping the spatial distribution and matching characteristics of supply and demand at the community scale. The results reveal that: (1) in terms of supply–demand balance, 25.67% of communities experience undersupply, predominantly in the old city cluster, while 16.22% experience oversupply, mainly in key development zones, indicating a notable supply–demand imbalance; (2) in terms of supply–demand coupling coordination, 55.11% and 38.14% of communities are in declining and transitional stages, respectively. These communities are primarily distributed in near-mountainous and peripheral urban areas. Based on these findings, four urban landscape optimization strategies are proposed: culturally driven urban park development, demand-oriented park planning, expanding countryside parks along mountain ridges, and revitalizing existing parks. These results provide theoretical support and decision-making guidance for optimizing urban park green space systems in plateau river valley cities. Full article

Tumor diseases are characterized by high interindividual and intratumoral heterogeneity (ITH). The development and progression of neoplasms outline complex networks of extracellular and cellular signals that have yet to be fully elucidated. This narrative review provides a comprehensive overview of the literature related to the cellular and molecular mechanisms underlying the heterogeneity of the tumor mass. Furthermore, it examines the possible role of the tumor microenvironment in the development and support of the neoplasm, in order to highlight its potential in the construction of a diagnostic–therapeutic approach to precision medicine. Many authors underline the importance of the tumor microenvironment (TME) as it actively takes part in the growth of the neoplastic mass and in the formation of metastases and in the acquisition of resistance to anticancer drugs. In specific body districts, the ideal conditions occur for the TME establishment, particularly the inflammatory state, the recruitment of cell types, the release of specific cytokines and growth factors, hypoxic conditions. These components actively intervene by enabling tumor progression and construction of physical barriers shaped by the extracellular matrix that contribute to forming peripheral tolerance by intervention of myeloid precursors and the polarization of M2 macrophages. In recent years, ITH and the TME have assumed an important position in cancer research and pharmacology as they enable understanding the dense network of communication existing between the neoplasm and the surrounding environment, and to monitor and deepen the effects of drugs with a view to develop increasingly precise and effective therapies. In the last decade, knowledge of TME has been exploited to produce targeted molecular agents (inhibitory small molecules, monoclonal antibodies, gene therapy). Nonetheless, the bibliography shows the need to study ITH through new prognostic and predictive biomarkers (e.g., ctDNA and CTCs) and to increase its basic biology knowledge. Precision medicine is a new opportunity in the treatment of oncological diseases that is transforming the development of new drug approaches and their clinical use. Biology and biotechnologies are providing the bases for this revolution. Full article

Greenhouse gases, such as carbon dioxide (CO₂), released from excessive fossil fuel consumption, are major contributors to global warming. Understanding the spatial distribution of CO₂ emissions on a refined scale is crucial for promoting green economic development. Xi’an, a key central city in China, serves as the case study for this research. Using nighttime light data from Black Marble, combined with energy statistics and socio-economic information, this study employed spatial analysis to simulate CO₂ emissions on the district and county levels in Xi’an for the years 2012 and 2022. The results indicated that nighttime light data were significantly correlated with CO₂ emissions (linear function; coefficients of determination: 0.7838 and 0.7941 for 2012 and 2022, respectively). The spatial distribution analysis revealed a clear pattern in CO₂ emissions, with higher emissions concentrated in central urban areas and lower emissions in peripheral regions. Additionally, a comparative analysis of carbon emissions and carbon emission intensity across districts and counties between 2012 and 2022 showed that CO₂ emissions in central urban areas had continued to grow and expand, while emission intensity had declined. These findings suggest that the socio-economic development, policy interventions, and industrial structure in Xi’an influence the spatial distribution of CO₂ emissions. Full article

Rapid urbanization has transformed cityscapes worldwide, yet vertical urban growth (VUG) receives less attention than horizontal expansion. This study mapped and analyzed VUG patterns in Wuhan, China, from 2012 to 2020 based on a Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) dataset derived from a long time series of 375 COSMO-SkyMed SAR images. The methodology involved full-stack processing (analyzing all 375 images for a stable reference), sub-stack processing (independently processing sequential image subsets to track temporal changes), and post-processing to extract persistent scatterer (PS) candidates, estimate building heights, and analyze temporal changes. Validation was conducted through drone surveys and ground measurements in the Hanyang district. Results revealed substantial vertical expansion in central districts, with Hanyang experiencing a 66-fold increase in areas with buildings exceeding 90 m in height, while Hongshan district saw a 34-fold increase. Peripheral districts instead displayed more modest growth. Time series analysis and 3D visualization captured VUG temporal dynamics, identifying specific rapidly transforming urban sectors within Hanyang. Although the study is focused on one city with accuracy assessed on a spatially confined sample of more than 500 buildings, the findings suggest that PSInSAR height estimates from high-resolution SAR imagery can complement global settlement datasets (e.g., Global Human Settlement Layer, GHSL) in order to achieve better accuracy for individual building heights. Validation generally confirmed the accuracy of PSInSAR-derived height estimates, though challenges remain with noise and the distribution of PS. The location of PS along the building instead of the building rooftops can affect height estimation precision. Full article

Investigating the coupling coordination between urban scale and vitality is critical for enhancing holistic urban development quality and advancing sustainability. Taking the Changsha-Zhuzhou-Xiangtan (ChangZhuTtan) metropolitan area as a case study, this research integrates multi-source raster and vector data to: (1) analyze spatial patterns of urban scale and virtual–substantive vitality; (2) delineate a “scale-vitality” hierarchical zonal structure; (3) quantify coupling relationships across subzones; and (4) propose synergistic spatial optimization strategies. Key findings reveal that, distinct core-periphery structure characterizes urban scale and vitality, with Changsha’s central districts dominating population, land use, and economic metrics, while Zhuzhou and Xiangtan exhibit moderate concentrations. Significant positive correlations exist between urban scale and dual vitality types, with scale-driven vitality enhancement being most pronounced in core agglomeration zones. Furthermore, in the metropolitan core, where both urban scale and vitality values are high, they exhibit a high-value coupling state. As they expanded outward, both metrics gradually decreased, resulting in a low-value coupling state. However, zonal comparisons (core agglomeration circle–peripheral expansion circle) reveal that the proportion of spatially coupled units progressively increases. By elucidating scale-vitality coupling in the ChangZhuTtan metropolitan area, this study provides actionable insights for spatial planning and sustainable urban transition. The methodology framework is replicable for similar metropolitan regions globally. Full article

As a pivotal industrial hub in southwestern China, Kunming City has accumulated abundant industrial heritage resources. Investigating the spatial distribution characteristics and influencing factors of industrial heritage across different districts in Kunming is critical for understanding its historical evolution and current status, and for providing scientific guidance for conservation and sustainable development. From a sustainability perspective, this study selected 80 industrial heritage sites in Kunming as research subjects. Utilizing ArcGIS spatial analysis techniques combined with kernel density estimation, standard deviational ellipse, and Geographical Detector analysis, we systematically visualized the spatial distribution patterns and driving factors. Key findings include that (1) industrial heritage exhibits significant spatial heterogeneity, concentrating primarily in the city center and surrounding areas, forming high-density clusters in Wuhua District, Panlong District, and Haikou Subdistrict, while showing marked disparities among regions; (2) distinct spatial distribution patterns emerge across heritage types—manufacturing heritage clusters in central urban zones, whereas mining heritage disperses in peripheral mountainous areas; and (3) historical preservation policies are identified as the dominant factor shaping the current distribution, whereas terrain and natural environmental impacts remain secondary. These findings offer actionable insights for optimizing the conservation and adaptive reuse of Kunming’s industrial heritage. Full article

Community regeneration plays a pivotal role in creating human-centered spaces by transforming spatial configurations, enhancing multifunctional uses, and optimizing designs that promote sustainability and vibrancy. However, the influence of such regeneration on spatial vitality—particularly its spatial heterogeneity and nonlinear effects—remains insufficiently explored. This study presents a comprehensive framework that combines the Difference-in-Differences (DID) method with multiple socio-spatial correlated factors, including place agglomeration, individual agglomeration, and social perception, offering a systematic assessment of urban vitality and evaluating the impact of regeneration interventions. By leveraging street-level imagery to capture environmental changes pre- and post-regeneration, this research applies Gradient Boosting Decision Tree Regression (GBDT) to uncover nonlinear built environment dynamics affecting urban vitality. Empirical analysis from six districts in Suzhou reveals the following: (1) A pronounced increase in urban vitality is seen in core areas, while peripheral districts exhibit more moderate improvements, highlighting spatially uneven regeneration outcomes. (2) In historically significant areas such as Wuzhong, limited vitality gains underscore the complex interplay among historical preservation, spatial configurations, and urban development trajectories. (3) Furthermore, environmental transformations, including variations in sky visibility, nonprivate vehicles, architectural elements, and the introduction of glass-wall structures, exhibit nonlinear impacts with distinct threshold effects. This study advances the discourse on sustainable urban regeneration by proposing context-sensitive, data-driven assessment tools that reconcile heritage conservation with contemporary urban regeneration goals. It underscores the need for integrated, adaptive regeneration strategies that align with local conditions, historical contexts, and urban development trajectories, informing policies that promote green, inclusive, and digitally transformed cities. Full article

This study investigates how urban decline and intensifying flood hazards interact to threaten Japan’s urban environments, focusing on three main dimensions. First, a fine-scale analysis of spatial shrinkage was conducted using transition potential maps generated with a maximum entropy classifier. This approach enabled the identification of neighborhoods at high risk of future abandonment, revealing that peripheral districts, such as Hirakue-cho and Shimoirino-cho, are especially susceptible due to their distance from central amenities. Second, this study analyzed the 2019 Naka River flood induced by Typhoon Hagibis, evaluating water detection performance through both a U-Net-based deep learning model applied to Sentinel-1 SAR imagery in ArcGIS Pro and the DioVISTA Flood Simulator. While the SAR-based approach excelled in achieving high accuracy with a score of 0.81, the simulation-based method demonstrated higher sensitivity, emphasizing its effectiveness in flagging potential flood zones. Third, forward-looking scenarios under Representative Concentration Pathways (RCP) 2.6 and RCP 8.5 climate trajectories were modeled to capture the potential scope of future flood impacts. The primary signal is that flooding impacts 3.2 km² of buildings and leaves 11 of 82 evacuation sites vulnerable in the worst-case scenario. Japan’s proven disaster expertise can still jolt adaptation toward greater flexibility. Adaptive frameworks utilizing real-time and predictive insights powered by remote sensing, GIS, and machine intelligence form the core of proactive decision-making. By prioritizing the repositioning of decaying suburbs as disaster prevention hubs, steadily advancing hard and soft measures to deployment, supported by the reliability of DioVISTA as a flood simulator, and fueling participatory, citizen-led ties within a community, resilience shifts from a reactive shield to a living ecosystem, aiming for zero victims. Full article

Bus networks are a crucial support for urban commuting. By studying the evolutionary characteristics of bus networks, we can uncover their development patterns, coverage efficiency, and changes in regional balance, providing a scientific basis for sustainable urban development and the optimization of transportation resources. This study systematically analyzes the spatiotemporal evolution characteristics of the bus network in Beijing from 2006 to 2024 using specific spatial analysis tools to analyze spatiotemporal evolution characteristics. By analyzing spatial coverage rates of transit stations using road network and administrative division data, the study reveals the convenience of bus networks in different regions. By combining the research methodology of the Sustainable Development Goals (SDGs) report, a 500-m service radius for bus stops was assessed. A complex network model was used to extract the nodes and edges of the bus network, and the betweenness centrality (BC) characteristics were analyzed. The findings indicate that Beijing’s bus network has gradually expanded from the central urban areas to peripheral regions, with notable expansion in Tongzhou and Yanqing, resulting in an improved balance in the distribution of stations and routes and the emergence of Tongzhou as a new bus hub. The diffusion characteristics of the bus network are significantly influenced by administrative boundaries and the layout of the ring roads. Bus routes and stops are highly concentrated in the central urban areas and within the Second Ring Road, while as the number of ring roads increases, various network indices gradually decrease. The distribution of bus stops shows notable clustering and an uneven directional development. Beijing’s bus stop distribution exhibits significant clustering characteristics, and the areas with a high Population Conveniently Served by Buses (PCSB) are predominantly concentrated in the central urban areas, with a large gap compared to the outer suburban districts. These conclusions expand on the exploration of isolated and static characteristics of the bus network structure, revealing the dynamic mechanisms and evolution patterns of Beijing’s bus network. They provide guidance and recommendations for improving the bus network and offer more comprehensive support for urban planning and resource allocation. Full article

Land subsidence, a slow-onset geohazard, poses a severe threat to cities worldwide. However, the lack of quantification in terms of intensity, probability, and hazard zoning complicates the assessment and understanding of the land subsidence risk. In this study, we employ a weighted Bayesian model to explicitly present the spatial distribution of land subsidence probability and map hazard zoning in Shanghai. Two scenarios based on distinct aquifers are analyzed. Our findings reveal the following: (1) The cumulative land subsidence probability density functions in Shanghai follow a skewed distribution, primarily ranging between 0 and 50 mm, with a peak probability at 25 mm for the period 2017–2021. The proportions of cumulative subsidence above 100 mm and between 50 and 100 mm are significantly lower for 2017–2021 compared to those for 2012–2016, indicating a continuous slowdown in land subsidence in Shanghai. (2) Using the cumulative subsidence from 2017–2021 as a measure of posterior probability, the probability distribution of land subsidence under the first scenario ranges from 0.02 to 0.97. The very high probability areas are mainly located in the eastern peripheral regions of Shanghai and the peripheral areas of Chongming District. Under the second scenario, the probability ranges from 0.04 to 0.98, with high probability areas concentrated in the eastern coastal area of Pudong District and regions with intensive construction activity. (3) The Fit statistics for Scenario I and Scenario II are 67% and 70%, respectively, indicating a better fit for Scenario II. (4) High-, medium-, low-, and very low-hazard zones in Shanghai account for 14.2%, 48.7%, 23.6%, and 13.5% of the city, respectively. This work develops a method based on the weighted Bayesian model for assessing and zoning land subsidence hazards, providing a basis for land subsidence risk assessment in Shanghai. Full article