Journal of Urban Management最新文献_第9页

Spatial structure and mechanism of cross-city patient mobility network in the Yangtze River economic belt of China 长江经济带跨城市患者流动网络空间结构与机制

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-12-11 DOI: 10.1016/j.jum.2024.11.013

Bowen Xiang , Mengyao Hong , Fang Guo , Wei Wei

Cross-city patient mobility reflects the geographic mismatch in medical resources, posing significant challenges for healthcare accessibility and equitable resource allocation. However, existing research methods inadequately capture the complex relationships between healthcare supply and demand as well as the proximity mechanisms influencing patient mobility. In this study, we used 500,120 patient online evaluations to build the 2023 Cross-city Patient Mobility Network (CPMN) for the Yangtze River Economic Belt (YREB), and analyzed its spatial structure and influencing factors using healthcare relative size index, dominant association analysis, and explainable machine learning modeling. The results show that: (1) There is a double logarithmic linear relationship between healthcare supply size and intensity (coefficient 0.627), and a weak negative correlation between demand size and intensity; (2) While the spatial organization of healthcare aligns with administrative boundaries and hierarchies, exceptions are observed in parts of Shanghai and Chongqing's healthcare catchment areas; (3) Social proximity, geographical proximity and institutional proximity are significant in patient mobility. This research contributes new data and methods to health geography and offers theoretical and empirical insights critical for optimizing healthcare resource allocation in the YREB, ultimately addressing the challenges of equitable healthcare access.

跨城市患者流动反映了医疗资源的地理不匹配，对医疗服务的可及性和资源的公平分配提出了重大挑战。然而，现有的研究方法未能充分捕捉到医疗保健供需之间的复杂关系以及影响患者流动性的邻近机制。本研究利用500,120名患者的在线评价，构建了长江经济带2023年跨城市患者流动网络（CPMN），并利用医疗卫生相对规模指数、优势关联分析和可解释机器学习模型分析了其空间结构和影响因素。结果表明：(1)卫生服务供给规模与卫生服务强度呈双对数线性关系（系数为0.627），卫生服务需求规模与卫生服务强度呈弱负相关；(2)医疗卫生服务的空间组织与行政区划的边界和层级基本一致，但在上海和重庆的部分医疗卫生服务集水区存在差异；(3)社会接近性、地理接近性和机构接近性对患者流动有显著影响。该研究为健康地理学提供了新的数据和方法，并为优化YREB的医疗资源分配提供了至关重要的理论和实证见解，最终解决了公平医疗获取的挑战。

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引用次数: 0

Comprehensive geospatial analysis of urban expansion dynamic in Lahore, Pakistan (1998–2023) 巴基斯坦拉合尔城市扩展动态的综合地理空间分析（1998-2023）

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-12-06 DOI: 10.1016/j.jum.2024.11.012

Sona Karim , Yaning Chen , Patient Mindje Kayumba , Ishfaq Ahmad , Hassan Iqbal

Lahore, a UNESCO city in Pakistan, is projected to rise from the sixth to the third fastest-growing city worldwide by 2030. This rapid urbanization challenges its commitment to cultural and ecological preservation, positioning it as an international case study in urbanization research. Thus, the Lahore Development Authority emphasizes the need for ongoing monitoring of urban dynamics to support effective planning and achieve sustainability targets, including Sustainable Development Goal 11. To contribute, we used high-resolution Landsat imagery to analyze the spatial diverging patterns of urban extent from 1998 to 2023 in Lahore. Additionally, we employed a Cellular Automata (CA) Markov Chain model to project urban growth over the next 25 years. As of 2023, we estimated that approximately 53.6% (92,660.9 ha) of Lahore is urbanized, while 46.4% remains unaffected by urban activities. Projections for 2048 suggest that the urban footprint may expand to 75.8% (131,031.5 ha), leaving only 24.2% of the area free from urbanization. Our analysis also revealed divergent urban expansion patterns significantly impacting local ecosystems. It showed a 31% reduction in inland water bodies, a 39.8% loss of vegetation, and a 60.1% decrease in sparse areas, all attributable to urban development. As natural landscapes are replaced by built environments, Lahore is likely facing increasing challenges that could jeopardize the city's green growth and urban ecological balance. Therefore, we urge land use managers, urban planners, and stakeholders in Pakistan to promote initiatives that enhance urban resilience, particularly through smart city planning and creating green and blue spaces. By focusing on Lahore, this study also provides valuable insights that can serve as a benchmark for other rapidly urbanizing cities facing similar challenges.

巴基斯坦的联合国教科文组织城市拉合尔预计到2030年将从全球增长最快的第六位上升到第三位。这种快速的城市化挑战了其对文化和生态保护的承诺，将其定位为城市化研究的国际案例研究。因此，拉合尔发展局强调需要持续监测城市动态，以支持有效规划和实现可持续发展目标，包括可持续发展目标11。利用高分辨率Landsat影像分析了1998 - 2023年拉合尔城市范围的空间分异格局。此外，我们采用元胞自动机（CA）马尔可夫链模型来预测未来25年的城市增长。截至2023年，我们估计拉合尔约53.6%（92660.9公顷）的土地已城市化，46.4%仍未受到城市活动的影响。对2048年的预测表明，城市足迹可能会扩大到75.8%（131,031.5公顷），只剩下24.2%的地区没有城市化。我们的分析还揭示了不同的城市扩张模式对当地生态系统的显著影响。内陆水体减少31%，植被减少39.8%，稀疏地区减少60.1%，均归因于城市发展。随着自然景观被建筑环境所取代，拉合尔可能面临越来越多的挑战，这些挑战可能危及城市的绿色增长和城市生态平衡。因此，我们敦促巴基斯坦的土地利用管理者、城市规划者和利益攸关方推动增强城市韧性的举措，特别是通过智慧城市规划和创造绿色和蓝色空间。通过关注拉合尔，本研究还提供了有价值的见解，可以作为其他面临类似挑战的快速城市化城市的基准。

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引用次数: 0

Evolution logic of urban spatial growth governance and its enlightenment in China: From a perspective of spatial governance 中国城市空间增长治理的演化逻辑及其启示——基于空间治理的视角

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-12-06 DOI: 10.1016/j.jum.2024.11.014

Ju He , Yongzhong Tan

As the governance modernization and new-type urbanization deepens, China's urbanization process is gradually entering the "second half". Understanding the policy practices and transformation logic of China's urban spatial growth in a systematic perspective is significant in clarifying the enhancement path of future urban spatial growth governance. This study, based on the perspective of spatial governance, focuses on the basic elements of urban spatial growth governance such as goals, actors, methods, and objects. It comprehensively examines the evolution of China's urban spatial growth governance since the reform and opening-up, and analyzes the underlying logic of the transformation. The study finds that the governance of urban spatial growth in China has gone through four main stages, with the multidimensional shifts in governance goals, subject relations, governance methods, and spatial objects behind each stage constituting the basic storyline of governance evolution, influenced by a combination of macro environment, system reforms, spatial issues, and technological changes. In the future, clarifying the governance concepts of urban spatial growth in the new stage, shaping interactive and collaborative subject relations, improving institutional systems and innovative technological tools, and designing differentiated governance strategies based on the characteristics of spatial objects will become important directions for enhancing China's urban spatial governance capacity and even spatial governance modernization.

随着治理现代化和新型城镇化的深入，中国城镇化进程正逐步进入“下半场”。从系统的角度理解中国城市空间增长的政策实践和转型逻辑，对于厘清未来城市空间增长治理的提升路径具有重要意义。本文基于空间治理的视角，探讨了城市空间增长治理的目标、行为主体、方法和对象等基本要素。全面考察了改革开放以来中国城市空间增长治理的演变，并分析了转型的内在逻辑。研究发现，中国城市空间增长治理经历了四个主要阶段，每个阶段背后的治理目标、主体关系、治理方式和空间客体的多维转变构成了治理演变的基本脉络，受到宏观环境、体制改革、空间问题和技术变革的综合影响。未来，厘清新阶段城市空间增长的治理理念，塑造互动协作的主体关系，完善制度体系和创新技术工具，设计基于空间客体特征的差别化治理策略，将成为提升中国城市空间治理能力乃至空间治理现代化的重要方向。

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引用次数: 0

Assessment of urban expansion susceptibility in major urban units of Bangladesh leveraging machine learning and geostatistical approach 利用机器学习和地质统计学方法评估孟加拉国主要城市单元的城市扩张敏感性

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-12-06 DOI: 10.1016/j.jum.2024.11.011

Mafrid Haydar, Sakib Hosan, Al Hossain Rafi

This study examines the governing factors and susceptibility zones for urban expansion in Bangladesh's major urban areas, including Dhaka, Barisal, Chittagong, Comilla, Narayanganj, Gazipur, Khulna, Sylhet, Rajshahi, Rangpur, and Mymensingh. The main goals of this research are to determine the impact of governing factors and to identify susceptibility zones for urban expansion in major urban units using a data-driven approach. By using governing factors (DEM, Slope, LST, NDVI, Population, distance to (industry, growth center, settlement, facilities, waterbody, road), and machine learning (Random Forest) and geostatistical approach (Binary Logistic Regression), the research identifies the most important factors influencing urban expansion, including NDVI, LST, waterbodies, roads, and settlements. The RF model's ROC-AOC values showed the highest accuracy (1.00) in Comilla and Mymensingh, moderate accuracy (0.99) in Barisal, Chittagong, Narayanganj, Gazipur, Khulna, and Rajshahi, and lower accuracy in Dhaka (0.98), Sylhet (0.89), and Rangpur (0.85). For the Binary Logistic Regression model, Comilla, Narayanganj, Gazipur, and Mymensingh had the best fit (Nagelkerke R² = 1.00), while Sylhet had the lowest significance (0.482). Furthermore, Khulna, a major urban unit, is the highest urban expansion susceptibility zone which is 35.72%. Rajshahi and Barisal are the moderate and low urban expansion susceptibility where 83.17% and 0.88% respectively. This unplanned and rapid urban expansion zone has also confronted policymakers and planners with an insurmountable challenge and stressed local governments' ability to manage and use their scarce land-based resources with geospatial data. Thus, this study's machine learning and geostatistical findings will help explain land cover change and urban expansion in Bangladesh's eleven metropolitan areas. This study will improve urban development understanding in Bangladesh. Findings will help planners, stakeholders, and policymakers understand urban expansion patterns, enabling better environmental planning.

本研究考察了孟加拉国主要城市地区城市扩张的控制因素和易感区，包括达卡、巴里萨尔、吉大港、科米拉、纳拉扬甘杰、加济布尔、库尔纳、锡尔赫特、拉杰沙希、兰格布尔和迈门辛格。本研究的主要目标是利用数据驱动的方法确定控制因素的影响，并确定主要城市单位的城市扩张易感区。利用DEM、坡度、LST、NDVI、人口、距离（工业、增长中心、聚落、设施、水体、道路）、机器学习（随机森林）和地统计学方法（二元Logistic回归）等控制因子，识别出影响城市扩张的最重要因素，包括NDVI、LST、水体、道路和聚落。RF模型的ROC-AOC值在Comilla和Mymensingh地区精度最高（1.00），在Barisal、吉大港、Narayanganj、Gazipur、Khulna和Rajshahi地区精度中等（0.99），在Dhaka（0.98）、Sylhet（0.89）和Rangpur（0.85）地区精度较低。在二元Logistic回归模型中，Comilla、Narayanganj、Gazipur和Mymensingh的拟合最佳（Nagelkerke R2 = 1.00）， Sylhet的显著性最低（0.482）。其中，主要城市单元库尔纳的城市扩张敏感性最高，为35.72%。Rajshahi和Barisal为中等和低城市扩张敏感性，分别为83.17%和0.88%。这个未经规划的快速城市扩张区也给政策制定者和规划者带来了难以克服的挑战，并强调了地方政府管理和利用地理空间数据的稀缺土地资源的能力。因此，本研究的机器学习和地质统计学发现将有助于解释孟加拉国11个大都市区的土地覆盖变化和城市扩张。本研究将提高对孟加拉国城市发展的认识。研究结果将有助于规划者、利益相关者和决策者了解城市扩张模式，从而实现更好的环境规划。

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引用次数: 0

Applying pareto frontier theory and ball tree algorithms to optimize growth boundaries for sustainable mountain cities 应用pareto边界理论和球树算法优化可持续发展山地城市的增长边界

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-12-05 DOI: 10.1016/j.jum.2024.11.015

Lindan Zhang , Guangjie Wang , Li Peng , Wenfu Peng , Ji Zhang

The terrain complexity of mountain cities often limits the rational layout and agglomeration distribution of newly added urban land. To this end, this paper proposes an innovative urban growth boundary optimization model —— Pareto Frontier theory and Ball-Tree algorithm optimized model (SP-BT). By treating newly added urban land as agents, the model dynamically optimizes the land patch locations based on the two goals of urban landscape compactness degree and suitability for urban construction. The SP-BT model is unique in that its optimal search and update process always unfolds along the Pareto front, achieving a balance between urban land agglomeration and suitability. In addition, compared with Suitability Optimum Evaluation Model (SOE), Artificial Neural Network in Cellular Automata (ANN-CA), and Ant Colony Optimization Model (ACO), the model has simplified parameter setting, fast evolution speed, flexible output results, and excellent defragmentation effect, especially suitable for mountain cities under complex terrain conditions. In the empirical study taking Bazhong city, China as an example: (1) SP-BT model significantly increased the mean size of urban landscape patch from 8.86 to 22.74–95.88, and the decrease of urban total suitability was controlled at 3.14%. (2) The SP-BT model excels in handling urban planning in mountainous cities, particularly in reducing landscape fragmentation, making it suitable for practical urban planning in mountainous environments. In general, the model proposed in this paper provides an efficient and flexible solution to the problem of new land use optimization under the complex terrain conditions of mountainous cities, which has important practical application value and can provide planners with more scientific and practical decision support tools.

山地城市地形的复杂性往往限制了城市新增用地的合理布局和集聚分布。为此，本文提出了一种创新的城市增长边界优化模型——帕累托边界理论和球树算法优化模型（SP-BT）。该模型以新增城市用地为agent，以城市景观紧凑度和城市建设适宜性两个目标为基础，对斑块位置进行动态优化。SP-BT模型的独特之处在于其最优搜索和更新过程始终沿着帕累托前沿展开，实现了城市土地集聚与适宜性之间的平衡。此外，与适宜性最优评价模型（SOE）、元胞自动性人工神经网络（ANN-CA）和蚁群优化模型（ACO）相比，该模型具有参数设置简化、演化速度快、输出结果灵活、碎片整理效果好等优点，特别适用于地形条件复杂的山地城市。在以巴中市为例的实证研究中：(1)SP-BT模型显著提高了城市景观斑块的平均大小，从8.86增加到22.74-95.88，城市总适宜性下降幅度控制在3.14%。(2) SP-BT模型在处理山地城市规划方面表现突出，特别是在减少景观破碎化方面，适用于山地环境下的实际城市规划。总体而言，本文提出的模型为山地城市复杂地形条件下新建土地利用优化问题提供了高效、灵活的解决方案，具有重要的实际应用价值，可以为规划者提供更加科学实用的决策支持工具。

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引用次数: 0

Assessing the efficacy of artificial intelligence based city-scale blue green infrastructure mapping using Google Earth Engine in the Bangkok metropolitan region 利用谷歌Earth Engine评估基于人工智能的曼谷大都市区蓝绿色基础设施测绘效果

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-12-04 DOI: 10.1016/j.jum.2024.11.009

Md. Mehedi Hasan , Malay Pramanik , Iftekharul Alam , Atul Kumar , Ram Avtar , Mohamed Zhran

Urbanization disrupts natural water, energy, and nutrient cycles, but integrating green and blue infrastructures (BGI) can mitigate these effects by facilitating processes like evapotranspiration, soil water infiltration, and root nutrient absorption. In Bangkok Metropolitan Region (BMR), escalating urbanization poses challenges to these natural cycles. Mapping Land Use and Land Cover (LULC) and identifying green infrastructure locations are crucial for effective urban planning, sustainable development, and environmental conservation amidst rapid urban growth. Continuous monitoring of dynamic urban areas is time-consuming, labor-intensive, and costly. Previous research primarily focused on land use and land cover classification followed by BGI identification. An automated classification system focusing solely on BGI can greatly enhance efficiency, accuracy, and cost-effectiveness in land classification for urban planning and decision-making. However, automating this system remains a significant challenge for the remote sensing community. Therefore, the research is first to develop a cloud based artificial intelligence tools such as Smile Random Forest and Smile CART integration with Google Earth Engine (GEE) to identify BGI for BMR. For this analysis, we have used open-sources and mostly used satellite images (e.g., Landsat and Sentinel) and consider to analyze seasonal changes for waterbodies, natural vegetations and human intervened vegetations with developing cloud-based artificial intelligence (AI). Surprisingly, Landsat-9 data demonstrated superior accuracy compared to Sentinel-2, indicating that the advanced technology of Landsat 9 may be more effective for BGI classification using AI. The study revealed a most distinct transition from deep green to green infrastructures during the transition from summer to monsoon season, whereas significant changes in blue infrastructure occurred between the monsoon and winter seasons. Seasonal variations in BGI are complex and influenced by factors such as the types of BGI implemented and the nuances of local climatic conditions. These advancements could provide precise insights for urban managers and policymakers, offering valuable tools to identify and understand BGI dynamics across various urban scales.

城市化破坏了自然的水、能量和养分循环，但整合绿色和蓝色基础设施（BGI）可以通过促进蒸散、土壤水分渗透和根系养分吸收等过程来缓解这些影响。在曼谷都市圈（BMR），不断升级的城市化对这些自然循环提出了挑战。在城市快速发展的背景下，绘制土地利用和土地覆盖（LULC）地图以及确定绿色基础设施位置对于有效的城市规划、可持续发展和环境保护至关重要。对充满活力的城市地区进行持续监测既耗时又费力，而且成本高昂。以往的研究主要集中在土地利用和土地覆盖分类，其次是华大基因识别。一个完全以华大基因为中心的自动分类系统可以大大提高城市规划和决策的土地分类的效率、准确性和成本效益。然而，该系统的自动化仍然是遥感界面临的重大挑战。因此，本研究首先开发基于云的人工智能工具，如Smile Random Forest和Smile CART与谷歌Earth Engine （GEE）的集成，以识别BMR的BGI。在这项分析中，我们使用了开源的卫星图像（例如Landsat和Sentinel），并考虑通过开发基于云的人工智能（AI）来分析水体、自然植被和人为干预植被的季节变化。令人惊讶的是，与Sentinel-2相比，Landsat-9的数据显示出更高的精度，这表明Landsat 9的先进技术可能更有效地利用人工智能进行华大基因分类。研究表明，在夏季到季风季节的过渡期间，基础设施从深绿色到绿色的转变最为明显，而在季风和冬季之间，基础设施的蓝色发生了显著变化。BGI的季节变化是复杂的，并受到诸如实施的BGI类型和当地气候条件的细微差别等因素的影响。这些进步可以为城市管理者和政策制定者提供精确的见解，为识别和理解不同城市规模的华大基因动态提供有价值的工具。

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引用次数: 0

Tracing the dual-circulation value chain: Measurement on the embedding characteristics and evidence from China 追踪双循环价值链：嵌入特征的测度与中国证据

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-11-30 DOI: 10.1016/j.jum.2024.11.008

Yi Ren , Jinniu Zhang , Yuan Tian

The rational allocation of value chain space can effectively promote regional development. In China, various regions have optimized their National Value Chain (NVC) by participating in the Global Value Chain (GVC), forming a structure of Dual-Circulation Value Chain (DCVC) dominated by NVC. This study aims to integrate multiple analytical models to construct an analytical method for studying the DCVC, thereby addressing the existing gaps in the literature in this field. When considering each province in China as the research subject, the following conclusions can be drawn: ①Point analysis results indicate that provinces such as Beijing and Jiangsu excel in connecting domestic and international markets, while resource-rich regions like Tibet and Xinjiang exhibit lower coupling between the NVC and the GVC. Coastal cities such as Shanghai and Guangdong are primarily situated in the mid-to-downstream segments, closely linked to the GVC; in contrast, resource-rich areas like Xinjiang and Shanxi predominantly occupy upstream positions. The effects of value creation and value transfer contribute to the relatively low value rate of return in provinces such as Beijing and Jiangsu. ②Area analysis further reveals that the coupling degree of the dual circulation value chain presents an east-to-west gradient, with domestic circulation as the dominant component, gradually forming a structure centered on the domestic cycle. The division of labour in the value chain is linear: inland areas focus on upstream resource production, central regions emphasize primary processing, and coastal areas are concentrated in downstream manufacturing and trade. Overall, the value chain return decreases from west to east, indicating that despite higher production levels in coastal regions, actual profits remain relatively low.

合理配置价值链空间，可以有效促进区域发展。在中国，各地区通过参与全球价值链（GVC）来优化本国价值链（NVC），形成了以NVC为主导的双循环价值链（DCVC）结构。本研究旨在整合多种分析模型，构建一种研究DCVC的分析方法，从而弥补该领域现有文献的空白。以中国各省为研究对象，可以得出以下结论：①点分析结果表明，北京、江苏等省区的国内市场与国际市场的连接能力较强，而西藏、新疆等资源富集区的全国价值链与全球价值链的耦合能力较弱。上海、广东等沿海城市主要位于中下游，与全球价值链联系紧密；相比之下，新疆、山西等资源丰富的地区则主要占据上游位置。北京、江苏等省份的价值回报率相对较低，主要是受价值创造和价值转移的影响。②区域分析进一步发现，双流通价值链的耦合度呈现出东向西的梯度，以国内流通为主导成分，逐步形成以国内循环为中心的结构。价值链上的分工是线性的：内陆地区以上游资源生产为主，中部地区以初级加工为主，沿海地区以下游制造业和贸易为主。整体来看，价值链回报自西向东递减，说明沿海地区虽然生产水平较高，但实际利润相对较低。

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引用次数: 0

Social conflicts and their resolution paths in the commercialized renewal of old urban communities in China under the perspective of public value 公共价值视角下中国城市旧社区商业化更新中的社会矛盾及其解决路径

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-11-29 DOI: 10.1016/j.jum.2024.11.007

Dexin Wang, Shijun Li

Constructing a sustainable community renewal model and effectively resolving social conflicts are key issues in urban governance and social stability in contemporary China. This study focuses on the social conflicts arising from the commercialization-driven renewal of the Workers' Village community in Chengdu. Using a combination of case study methods, structured interviews, and participant observation, we explore the public value conflicts and their resolution pathways in the process of community renewal. The study reveals that the formation of public values is a dynamic process characterized by the interplay of multiple value systems, with various public value conflicts emerging in the commercialization of communities. To resolve these social conflicts, it is essential to fully consider the diverse interests of different groups and contexts, as well as the varying public values at stake. By promoting democratization and institutionalization, the different public values that arise from these conflicts can be transformed into a widely recognized value consensus. Grounded in public value theory, this study proposes a social conflict resolution model that transcends traditional approaches. It not only examines the key stakeholders involved in social conflicts during community renewal and the manifestations of value conflicts among them, but also emphasizes the importance of integrating and transforming divergent public values through active dialogue and negotiation. This process, involving multiple stakeholders, follows a trajectory from the aggregation of public values to negotiation and ultimately to value reshaping. The proposed model provides a new governance framework and methodological support for addressing social conflicts in community renewal, offering innovative insights into the integration and reconciliation of public values.

构建可持续的社区更新模式，有效化解社会矛盾，是当代中国城市治理与社会稳定的关键问题。本研究聚焦于成都工村社区在商业化驱动下的更新所引发的社会矛盾。本文采用案例研究、结构化访谈和参与式观察相结合的方法，探讨了社区更新过程中的公共价值冲突及其解决途径。研究表明，公共价值的形成是一个多种价值体系相互作用的动态过程，社区商业化过程中出现了各种公共价值冲突。要解决这些社会矛盾，必须充分考虑不同群体和背景的不同利益，以及所涉及的不同公共价值观。通过推动民主化和制度化，可以将这些冲突中产生的不同公共价值转化为广泛认可的价值共识。本研究以公共价值理论为基础，提出一种超越传统方法的社会冲突解决模型。它不仅考察了社区更新过程中涉及社会冲突的关键利益相关者及其之间价值冲突的表现，而且强调了通过积极对话和谈判整合和转化不同公共价值观的重要性。这一过程涉及多个利益相关者，遵循从公共价值聚集到谈判，最终到价值重塑的轨迹。该模型为解决社区更新中的社会冲突提供了新的治理框架和方法支持，为公共价值观的整合与和解提供了创新的见解。

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引用次数: 0

Generated nighttime street view image to inform perceived safety divergence between day and night in high density cities: A case study in Hong Kong 生成夜间街景图像，告知高密度城市的安全感知差异：以香港为例

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-11-28 DOI: 10.1016/j.jum.2024.11.006

Xiaotong Ye , Yuankai Wang , Jiajing Dai , Waishan Qiu

Safety perception is widely considered a fundamental aspect of urban life, which significantly influences citizens' well-being and quality of life as well as having crucial impact on the nighttime economy. However, there is a scarcity of understanding of nighttime safety despite the fast-growing body of urban scene auditing research based on daytime street view imagery (SVI). To fill the gap, this study collected ∼1000 pairwise day-and-night SVIs to train a day-to-night (D2N) SVI generator to effectively predict nighttime SVI based on daytime counterpart using generative adversarial network (GAN). The accuracy of fake nighttime image was evaluated with commonly-used GAN metrics (e.g., structural similarity index, inception score) and human validation. Then, an online visual survey with 46 participants was conducted to collect their perceived safety on street scenes during daytime and nighttime (D&N), and the results become training labels for machine learning models to predict D&N safety perceptions. Our results revealed significant discrepancies in D&N safety perception. First, through correlation analysis, we found that the sky and building features matter to the prediction accuracy of generated nighttime SVIs. Second, the micro-level streetscape features (e.g., pavements, roads, and buildings) play influential roles in perceived safety. Third, higher safety perceptions are consistently found in areas with higher building density regardless of whether they are daytime or night. In contrast, untended trees and grass reduce perceived safety at night. This study provides a valuable reference for improving the accuracy of generating nighttime images from daytime SVIs. It also reveals how streetscapes affect D&N safety perceptions in high-density cities like Hong Kong, providing empirical evidence for urban design policies to facilitate nighttime attractiveness and prosperity.

安全感知被广泛认为是城市生活的一个基本方面，它显著影响着市民的幸福感和生活质量，并对夜间经济产生至关重要的影响。然而，尽管基于日间街景图像（SVI）的城市场景审计研究迅速发展，但对夜间安全的了解却很少。为了填补这一空白，本研究收集了约1000个成对的昼夜SVI来训练一个日-夜（D2N） SVI生成器，使用生成对抗网络（GAN）有效地预测基于白天对应的夜间SVI。利用常用的GAN指标（如结构相似性指数、初始分数）和人工验证来评估假夜间图像的准确性。然后，对46名参与者进行了一项在线视觉调查，以收集他们在白天和夜间对街道场景的感知安全性（D&；N），结果成为机器学习模型的训练标签，以预测D&；N安全感知。我们的研究结果揭示了D&；N安全感知的显著差异。首先，通过相关分析，我们发现天空和建筑物特征对生成的夜间svi的预测精度有影响。其次，微观层面的街道景观特征（如人行道、道路和建筑物）在感知安全中发挥着重要作用。第三，无论是白天还是晚上，建筑密度高的地区都有较高的安全意识。相比之下，无人看管的树木和草地会降低夜间的安全感。该研究为提高白天svi生成夜间图像的精度提供了有价值的参考。它还揭示了街道景观如何影响香港等高密度城市的安全观念，为城市设计政策提供了经验证据，以促进夜间吸引力和繁荣。

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引用次数: 0

Categorising neighbourhoods using OpenStreetMap POIs: Affinity propagation clustering of 7,213 subdistricts in Thailand 使用OpenStreetMap poi对街区进行分类：泰国7,213个街道的亲和传播聚类

IF 3.9 2区社会学 Q1 URBAN STUDIES

Journal of Urban Management

Pub Date : 2024-11-26 DOI: 10.1016/j.jum.2024.11.005

Viriya Taecharungroj , Nikos Ntounis

The effective categorisation of neighbourhoods is a critical component of urban planning and development, providing a systematic framework for identifying and addressing the distinct characteristics and needs of different areas. This study utilises data from the open-source platform OpenStreetMap (OSM) to propose a novel approach to neighbourhood categorisation, with a focus on amenities as key elements. Data were collected on 4,121,900 points of interest (POIs) across 7213 subdistricts in Thailand, and the categorisation was conducted using the Affinity Propagation (AP) clustering technique. Through this approach, ten distinct neighbourhood clusters in Thailand were identified, demonstrating the efficacy of integrating OSM data with AP clustering. The findings underscore the necessity for more evidence-based planning policies aimed at enhancing amenities, vibrancy, and overall quality of life in neighbourhoods by promoting innovation and the development of creative districts. Furthermore, the study advocates for the consideration of ecological urbanism as an alternative pathway for neighbourhood development, a concept that has yet to be thoroughly explored in Thailand.

有效的社区分类是城市规划和发展的重要组成部分，为识别和处理不同地区的独特特征和需求提供了一个系统的框架。本研究利用开源平台OpenStreetMap （OSM）的数据，提出了一种新的社区分类方法，重点关注设施作为关键要素。收集了泰国7213个街道的4,121,900个兴趣点（poi）的数据，并使用亲和传播（AP）聚类技术进行了分类。通过这种方法，确定了泰国10个不同的邻里聚类，证明了将OSM数据与AP聚类相结合的有效性。研究结果强调了制定更多以证据为基础的规划政策的必要性，这些政策旨在通过促进创新和创意区发展来提高社区的便利设施、活力和整体生活质量。此外，该研究提倡将生态城市主义作为社区发展的另一种途径，这一概念在泰国尚未得到彻底的探索。

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引用次数: 0