Sustainable Cities and Society最新文献_第6页

Data fusion for enhancing urban air quality modeling using large-scale citizen science data 利用大规模公民科学数据进行数据融合以加强城市空气质量建模

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-11 DOI: 10.1016/j.scs.2024.105896

Rapid urbanization has led to many environmental issues, including poor air quality. With urbanization set to continue, there is an urgent need to mitigate air pollution and minimize its adverse health impacts. This study aims to advance urban air quality modelling by integrating a dispersion model output with large-scale citizen science data, collected over a 4-week period by 642 participants in Cork City, Ireland. The dispersion model enabled the identification of major sources of NO₂ air pollution while also addressing gaps in regulatory monitoring efforts. Integrating the diffusion tube data with the dispersion model output, we developed a data fusion model that captured localized fluctuations in air quality, with increases of up to 22μg/m³ observed at major road intersections. The data fusion model provided a more accurate representation of NO₂ concentrations, with estimates within 1.3μg/m³ of the regulatory monitoring measurement at an urban traffic location, an improvement of 11.7μg/m³ from the baseline dispersion model. This enhanced accuracy enabled a more precise assessment of the population exposure to air pollution. The data fusion model showed a higher population exposure to NO₂ compared to the dispersion model, providing valuable insights that can inform environmental health policies aimed at safeguarding public health.

快速城市化导致了许多环境问题，包括空气质量差。随着城市化进程的继续，迫切需要缓解空气污染并将其对健康的不利影响降至最低。这项研究旨在通过将分散模型输出与大规模公民科学数据相结合，推进城市空气质量建模工作，这些数据是由爱尔兰科克市的 642 名参与者在 4 周内收集的。弥散模型能够确定二氧化氮空气污染的主要来源，同时还能弥补监管监测工作的不足。通过将扩散管数据与弥散模型输出结果进行整合，我们开发出了一种数据融合模型，该模型能够捕捉空气质量的局部波动，在主要道路交叉口观测到的空气质量升幅最高可达 22 微克/立方米。数据融合模型更准确地反映了二氧化氮的浓度，在一个城市交通地点的估计值与监管监测测量值相差在 1.3 微克/立方米以内，比基线扩散模型提高了 11.7 微克/立方米。精确度的提高使我们能够更精确地评估人口暴露于空气污染的情况。与分散模型相比，数据融合模型显示人口暴露于二氧化氮的程度较高，为旨在保障公众健康的环境卫生政策提供了宝贵的信息。

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引用次数: 0

Expanding the associations between built environment characteristics and residential mobility in high-density neighborhood unit 拓展高密度邻里单元中建筑环境特征与居住流动性之间的联系

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-11 DOI: 10.1016/j.scs.2024.105885

Global trend of urbanization has led to frequent residential mobility and urban shrinkage issues. Planners and policy makers advocate for enhancing built environment quality of neighbourhood units to address these issues. Although the impact factors and degree of the influence of the built environment on residential mobility have been studied, the nonlinear effects at the neighbourhood level, and the relative importance when considered alongside other factors, remain unclear. In this study, the central area of Nanjing using mobile phone signalling data, the 5Ds framework, machine learning algorithms, and interpretable model Shapley Additive exPlanations (SHAP) are examined. The finding shows that (1) economy and neighbourhood ties are still key drivers of relocation. (2) Optimizing highly accessible road network for short-distance travel and developing low-density urban mode has become significant methods to attract relocators, interacting with other factors to influence residential mobility. (3) High-quality neighbourhood design, diverse amenities, and proximity to natural landscapes increase willingness to relocate, (4) while religion, socio-demographics, and large-scale transportation accessibility have minimal impact. The study offers four urban development recommendations to help municipal planners and policy makers create liveable cities and cohesive communities, providing essential insights for early or renewal stage urban planning stages.

全球城市化趋势导致了频繁的居住流动和城市缩水问题。规划者和政策制定者主张通过提高街区单元的建筑环境质量来解决这些问题。尽管人们已经研究了建筑环境对居住流动性的影响因素和影响程度，但街区层面的非线性效应以及与其他因素一起考虑时的相对重要性仍不明确。本研究利用手机信号数据、5Ds 框架、机器学习算法和可解释模型 Shapley Additive exPlanations（SHAP）对南京市中心区域进行了研究。研究结果表明：（1）经济和邻里关系仍是搬迁的主要驱动因素。(2）优化短距离出行的高可达性道路网络和发展低密度城市模式已成为吸引搬迁者的重要方法，并与其他因素相互作用，影响居住流动性。(3）高质量的街区设计、多样化的便利设施和邻近自然景观会提高搬迁意愿，（4）而宗教、社会人口和大型交通的便利性影响甚微。该研究提出了四项城市发展建议，帮助市政规划者和政策制定者创建宜居城市和具有凝聚力的社区，为早期或更新阶段的城市规划提供了重要见解。

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引用次数: 0

Designing breezeways to enhance wind environments in high-density cities: A comprehensive analysis of ten morphological parameters 设计通风廊道，改善高密度城市的风环境：十个形态参数的综合分析

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-11 DOI: 10.1016/j.scs.2024.105898

To advance urban breezeway designs, this paper presents a pioneering and comprehensive study of breezeway morphological parameters. Ten parameters, identified through extensive literature review, include coverage ratio, porosity, line density, sinuosity, rotation angle, width, length, average height, height variation, and aspect ratio. Regression analysis, utilizing over 200 data points collected from wind tunnel experiments in Hong Kong, established correlations between these parameters and pedestrian-level wind velocity ratio (VR_point). Results reveal that among the 2D parameters, width, length, line density, and coverage ratio exhibit the strongest correlations with VR_point, while aspect ratio and porosity emerge as significant factors among the 3D parameters. Notably, simple 2D parameters, coverage ratio and width, can effectively substitute for their 3D counterparts, porosity and aspect ratio, in high-density urban environments. Furthermore, the results highlight the relative contributions of different parameters to urban ventilation. From a street-level perspective, VR_point is primarily influenced by configurations of street segments (width, 80 %) and street intersections (rotation angle, 20 %). From a neighborhood-level perspective, permeability (coverage ratio, 35 %), fragmentation (line density, 30 %), and roughness (average height, 35 %) are critical factors. Illustrative examples are provided to help translate these findings into spatial analysis tools and design guidelines, aiding planners and decision-makers in improving urban living environments.

为了推进城市通风廊道的设计，本文对通风廊道的形态参数进行了开创性的综合研究。通过查阅大量文献，确定了十个参数，包括覆盖率、孔隙率、线密度、蜿蜒度、旋转角、宽度、长度、平均高度、高度变化和长宽比。利用从香港风洞实验中收集的 200 多个数据点进行回归分析，确定了这些参数与行人水平风速比 (VRpoint) 之间的相关性。结果显示，在二维参数中，宽度、长度、线密度和覆盖率与 VRpoint 的相关性最强，而纵横比和孔隙率则是三维参数中的重要因素。值得注意的是，在高密度城市环境中，简单的二维参数（覆盖率和宽度）可以有效替代三维参数（孔隙率和长宽比）。此外，研究结果还强调了不同参数对城市通风的相对贡献。从街道一级的角度来看，VRpoint 主要受街道段（宽度，80%）和街道交叉口（旋转角度，20%）配置的影响。从街区层面来看，渗透性（覆盖率，35%）、破碎度（线密度，30%）和粗糙度（平均高度，35%）是关键因素。本报告提供了一些示例，有助于将这些发现转化为空间分析工具和设计指南，帮助规划者和决策者改善城市生活环境。

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引用次数: 0

Robust day-ahead scheduling of cooperative energy communities considering multiple aggregators 考虑多个聚合器的合作能源社区稳健的日前调度

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-10 DOI: 10.1016/j.scs.2024.105878

Future cities must play a vital role in reducing energy consumption and decarbonizing the electricity sector, thus evolving from passive structures towards more efficient smart cities. This transition can be facilitated by energy communities. This emerging paradigm consists of collectivizing a set of residential installations equipped with onsite renewable generators and storage assets (i.e., prosumers), which can eventually share resources to pursue collective welfare. This paper focuses on cooperative communities, where prosumers share resources without seeking selfish monetary counterparts. Despite their apparent advantages, energy management and scheduling of energy communities suppose a challenge for conventional tools due to the high level of uncertainty (especially due to intermittent renewable generation and random demand), and privacy concerns among prosumers. This paper addresses these issues. Specifically, a novel management structure based on multiple aggregators is proposed. This paradigm preserves users' confidential features while allowing them to extract the full potential of their assets. To efficiently manage the variety of assets available under uncertainty, an adaptive robust day-ahead scheduling model is developed, which casts as a solvable and portable Mixed Integer Linear Programming framework, which eases its implementation in real-world cases. The new proposal concerns uncertain generation and demand using a polyhedral representation of the uncertainty set. A case study is conducted to validate the developed model, showing promising results. Moreover, different results are obtained and analysed. Finally, it is worth remarking on how the level of robustness impacts the collective bill, incrementing it by 75 % when risk-averse conditions are assumed. In addition, the role of storage assets under pessimistic conditions is remarked, pointing out that these assets rule the scheduling plan of the community instead of renewable generators.

未来的城市必须在减少能源消耗和电力部门去碳化方面发挥重要作用，从而从被动结构向更高效的智能城市发展。能源社区可以促进这一转变。这一新兴模式包括将一系列配备现场可再生能源发电机和储能资产的住宅设施（即专业消费者）集体化，最终实现资源共享，以追求集体福利。本文的重点是合作社区，在这些社区中，消费者共享资源，而不追求自私的金钱回报。能源社区的能源管理和调度尽管具有明显的优势，但由于高度的不确定性（特别是由于间歇性可再生能源发电和随机需求）以及对消费者隐私的担忧，对传统工具来说是一个挑战。本文就是要解决这些问题。具体而言，本文提出了一种基于多个聚合器的新型管理结构。这种模式既能保护用户的保密特征，又能让他们充分挖掘其资产的潜力。为了有效管理不确定性条件下的各种可用资产，本文开发了一个自适应稳健日前调度模型，该模型是一个可求解、可移植的混合整数线性规划框架，便于在现实世界中实施。新建议采用不确定性集合的多面体表示法来处理不确定的发电量和需求量。为验证所开发的模型，我们进行了一项案例研究，结果表明该模型大有可为。此外，还获得并分析了不同的结果。最后，值得注意的是稳健性水平如何影响集体账单，在假设规避风险的条件下，集体账单会增加 75%。此外，还指出了储能资产在悲观条件下的作用，指出这些资产而不是可再生能源发电机决定着社区的调度计划。

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引用次数: 0

Enhancing road traffic flow in sustainable cities through transformer models: Advancements and challenges 通过变压器模型提高可持续城市的道路交通流量：进步与挑战

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-10 DOI: 10.1016/j.scs.2024.105882

Efficient traffic flow is crucial for sustainable cities, as it directly impacts energy consumption, pollution levels, and overall quality of life. The integration of superficial intelligence, particularly transformer models, plays a significant role in enhancing the predictive capabilities for traffic management, thereby supporting sustainable urban development. In this survey, we explored the application of transformer models to predict and optimize traffic flow in sustainable cities. These models leverage advanced machine learning to capture intricate spatiotemporal patterns,thereby providing valuable insights for urban planners and traffic management centers. By systematically reviewing the literature, we emphasize the importance of transformer models in urban planning and sustainable resource use. Our study demonstrates how transformer models can learn complex spatiotemporal patterns from traffic data by incorporating both real-time and historical data to enhance prediction accuracy. This improved predictive capability aids the development of smart cities by reducing traffic congestion, facilitating smoother movement for city dwellers and tourists, and ultimately contributing to the sustainability goals of urban areas. This comprehensive review highlights the transformative potential of predictive modeling using transformer models, underscoring their critical role in optimizing urban infrastructure and promoting sustainable city development.

高效的交通流对于可持续发展的城市至关重要，因为它直接影响到能源消耗、污染水平和整体生活质量。表面智能的集成，尤其是变压器模型，在增强交通管理预测能力方面发挥着重要作用，从而支持城市的可持续发展。在本次调查中，我们探讨了如何应用变压器模型来预测和优化可持续城市的交通流量。这些模型利用先进的机器学习捕捉错综复杂的时空模式，从而为城市规划者和交通管理中心提供有价值的见解。通过系统回顾文献，我们强调了变压器模型在城市规划和资源可持续利用中的重要性。我们的研究展示了变压器模型如何通过结合实时数据和历史数据，从交通数据中学习复杂的时空模式，从而提高预测准确性。这种预测能力的提高有助于智慧城市的发展，可以减少交通拥堵，为城市居民和游客提供更顺畅的交通，并最终为实现城市地区的可持续发展目标做出贡献。这篇综合评论强调了使用变压器模型进行预测建模的变革潜力，突出了其在优化城市基础设施和促进城市可持续发展方面的关键作用。

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引用次数: 0

An integrated hydrological-hydrogeological model for analysing spatio-temporal probability of groundwater infiltration in urban infrastructure 用于分析城市基础设施地下水渗透时空概率的水文-水文地质综合模型

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-10 DOI: 10.1016/j.scs.2024.105891

While groundwater serves as a valuable resource, its infiltration poses significant challenges to urban infrastructure. This study develops and demonstrates a computationally efficient spatio-temporal analysis of groundwater infiltration (GWI) in urban facilities, specifically sewer networks (SNs), within the Lower River Otter Water Body, United Kingdom. To achieve this, the Fuzzy-Analytic Hierarchy Process (F-AHP) within a Geographic Information System (GIS) framework was employed, considering geology, geomorphology, hydrology, hydrogeology, climate, and topography. The proposed model encompasses 16 thematic maps, categorised into 6 groups: (1) groundwater (groundwater depth (GWD)); (2) altitude (elevation, slope, and topographic wetness index); (3) precipitation (monthly precipitation); (4) ground cover (rock permeability, alluvial permeability, soil type, land cover, and made ground); (5) earth movement (fault proximity, fault length density, and mass movement); and (6) runoff (river, flood potential, and drainage density). Expert judgment, F-analysis, and AHP were applied to the layers for classification, normalisation, and weight assignment, respectively. Verified by data from outfalls, GWI probability maps were generated considering the shallowest GWD and highest precipitation for temporal analysis. Overall, higher GWI probability scores were found in regions with shallower GWD, lower elevations, especially near river, and higher permeabilities. Assigning a probability score between 0 and 1 for each 1-metre area in each season, the vulnerability maps can guide water agencies in implementing protective strategies for infrastructure. The findings contribute to enhancing groundwater sustainability in urban areas, particularly in the face of potential climate change.

虽然地下水是一种宝贵的资源，但它的渗透也给城市基础设施带来了巨大挑战。本研究开发并演示了一种高效计算的时空分析方法，用于分析英国奥特河下游水体中城市设施（特别是下水道网络 (SN)）的地下水渗透（GWI）情况。为此，在地理信息系统 (GIS) 框架内采用了模糊分析层次过程 (F-AHP)，考虑了地质、地貌、水文、水文地质、气候和地形。拟议模型包括 16 幅专题地图，分为 6 组：(1) 地下水（地下水深度 (GWD)）；(2) 海拔（海拔高度、坡度和地形湿润指数）；(3) 降水（月降水量）；(4) 地面覆盖（岩石渗透性、冲积层渗透性、土壤类型、土地覆盖和人造地面）；(5) 地球运动（断层邻近度、断层长度密度和质量运动）；以及 (6) 径流（河流、洪水潜力和排水密度）。专家判断、F 分析和 AHP 分别应用于图层的分类、归一化和权重分配。经排污口数据验证，考虑到最浅的 GWD 和最高的降水量，生成了 GWI 概率图，用于时间分析。总体而言，全球降水潜能值较浅、海拔较低（尤其是靠近河流）和渗透率较高的地区，其全球降水潜能值概率得分较高。在每个季节，每个 1 米区域的概率分数介于 0 和 1 之间，脆弱性地图可指导水利机构实施基础设施保护战略。这些发现有助于提高城市地区地下水的可持续性，尤其是在面临潜在气候变化的情况下。

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引用次数: 0

A multi-stakeholder engagement framework for material-building-city synergy through circular transformation 多方利益相关者参与框架：通过循环转型实现材料建设与城市协同作用

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-10 DOI: 10.1016/j.scs.2024.105892

Scholars, industrial stakeholders, and governmental institutions are developing the circular economy paradigm. However, the emergence of multiple perspectives has challenged its implementation. As the industry that is the biggest contributor to the negative impacts on the environment, the construction industry stakeholders are paving the way for more sustainable as well as circular and regenerative construction by considering all actors in the system. Yet, the construction industry has a complex supply chain that requires clear strategies and stakeholder engagement across materials, buildings, and cities for efficient flows in the supply chain. Nonetheless, there is a need for improvement in the engagement of construction stakeholders for circular transformation. Therefore, this study aims to develop a multi-stakeholder engagement framework through circular transformation to guide the decision-makers for circular city governance. It has identified critical success factors by considering the construction stakeholders. The framework includes strategies at the micro (material), meso (building), and macro (city) scales to strengthen the material-building-city synergy. It's a significant step toward advancing circular city governance by bridging the gap between theoretical understanding and practical implementation and establishing a robust engagement for material-building-city synergy. The study employs a systematic literature review to extract strategies and natural language processing to analyze the strategies by topic modeling and defines critical success factors for multi-stakeholder engagement at multiscale. The outcome introduces the REVERT framework, bridging resource, envisagement, validation, entity, regulation, and technology, to facilitate a seamless transition by material-building-city synergy advancing circular city governance.

学者、行业利益相关者和政府机构正在发展循环经济范式。然而，多种观点的出现对其实施提出了挑战。作为对环境造成最大负面影响的行业，建筑行业的利益相关者正在通过考虑系统中的所有参与者，为更具可持续性以及循环和再生性的建筑铺平道路。然而，建筑行业的供应链十分复杂，需要明确的战略和利益相关者的参与，以实现材料、建筑和城市在供应链中的高效流动。尽管如此，仍需要改进建筑利益相关者的参与，以实现循环转型。因此，本研究旨在通过循环转型制定一个多方利益相关者参与框架，为循环型城市治理的决策者提供指导。它通过考虑建筑利益相关者，确定了关键的成功因素。该框架包括微观（材料）、中观（建筑）和宏观（城市）尺度的战略，以加强材料-建筑-城市的协同作用。通过弥合理论理解与实际执行之间的差距，建立材料-建筑-城市协同作用的有力参与，这是推进循环型城市治理的重要一步。本研究通过系统的文献综述提取策略，并采用自然语言处理技术通过主题建模对策略进行分析，定义了多利益相关者多尺度参与的关键成功因素。研究成果引入了 REVERT 框架，将资源、设想、验证、实体、监管和技术连接起来，通过材料建设-城市协同推进循环城市治理，促进无缝过渡。

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引用次数: 0

Integrating Street-View Imagery and Points of Interest for Refining Population Spatialization: A Case Study in Wuhan City 整合街景图像和兴趣点以完善人口空间化：武汉市案例研究

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-09 DOI: 10.1016/j.scs.2024.105883

Fine-scale population spatialization is the frontier of geosciences, it is essential for sustainable urban planning and effective resource allocation. Various approaches have been proposed to enhance population estimation accuracy using multi-source geospatial data. However, the approaches based on remote sensing data usually suffer from the problem of spatial homogeneity, while the social-sensing-based approach such as point of interest (POI) data cannot distinguish the population distribution around POIs with the same category but different scales. Thus, this study proposes a novel method that incorporates street view imagery (SVI) with POI, to enrich the semantic landscape of street-level objects and provide a visual representation of spatial heterogeneity within an urban environment. Specifically, we extract POI and SVI features at grid-, street-, and community-level, respectively, and then select modelling features based on cross-scale consistency analysis with population. After that, grid-level SVI features are adjusted by community-level SVI features to alleviate its sparsity and transiency. Finally, we train random forest (RF) at the street-level and estimate grid-level population weight for population allocation. Experiments in Wuhan City at a grid size of 100 × 100m show that our method yields higher accuracy compared to WorldPop, GPW datasets, Ye's method, and heterogeneous population attraction of POI modelling (HPA-POI), demonstrating its effectiveness in fine-scale population spatialization.

精细的人口空间化是地球科学的前沿领域，对于可持续的城市规划和有效的资源分配至关重要。为了利用多源地理空间数据提高人口估算精度，人们提出了多种方法。然而，基于遥感数据的方法通常存在空间同质性问题，而基于社会传感的方法，如兴趣点（POI）数据，则无法区分同一类别但不同尺度的兴趣点周围的人口分布。因此，本研究提出了一种将街景图像（SVI）与兴趣点相结合的新方法，以丰富街景对象的语义景观，并提供城市环境中空间异质性的可视化表示。具体来说，我们分别从网格级、街道级和社区级提取 POI 和 SVI 特征，然后根据与人口的跨尺度一致性分析选择建模特征。然后，通过社区级 SVI 特征对网格级 SVI 特征进行调整，以减轻其稀疏性和瞬时性。最后，我们在街道级进行随机森林（RF）训练，并估算网格级人口权重，以进行人口分配。在武汉市进行的网格大小为 100 × 100m 的实验表明，与 WorldPop、GPW 数据集、叶氏方法和 POI 异质性人口吸引模型（HPA-POI）相比，我们的方法获得了更高的精度，证明了其在精细尺度人口空间化方面的有效性。

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引用次数: 0

Exploring the complex relationship between metro and shared bikes in the built environment: competition, connection, and complementation 探索建筑环境中地铁与共享单车之间的复杂关系：竞争、联系与互补

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-09 DOI: 10.1016/j.scs.2024.105870

Merging the flexibility of bike-sharing systems with the high capacity of metro transit significantly enhances both connectivity and efficiency in urban transportation, promoting eco-friendly travel options and supporting sustainable urban development. Current studies primarily examine how these two transportation modes work together to enhance urban travel efficiency and convenience. However, there is still a lack of discussion on the spatial heterogeneity of the competitive and complementary relationships between two modes across different built environments. This study selects Shenzhen as a case study and employs a data-driven approach to explore the relationships between bike-sharing and the metro system in practical application, including competition, connection, and complementation. The OPGD model is deployed to assess how the built environment influences these dynamics. The results reveal that bike-sharing typically complements the metro system, with longer ride durations occurring mainly in the urban core areas. Conversely, competitive interactions between these two modes are less frequent and associated with shorter rides, typically occurring in locales with a high density of metro stations. Educational, service, and residential factors are the main influences on people's choice of the "bike-sharing + metro" travel mode. The built environment exerts a greater impact on competitive relationships and less on complementary ones.

共享单车系统的灵活性与地铁交通的大容量相结合，大大提高了城市交通的连通性和效率，促进了生态友好型出行方式的选择，支持了城市的可持续发展。目前的研究主要探讨这两种交通方式如何共同提升城市交通的效率和便利性。然而，对于两种交通方式在不同建筑环境中的竞争和互补关系的空间异质性仍缺乏讨论。本研究选取深圳作为案例，采用数据驱动的方法，探讨共享单车与地铁系统在实际应用中的竞争、衔接、互补等关系。采用 OPGD 模型来评估建筑环境如何影响这些动态关系。结果显示，共享单车通常是地铁系统的补充，较长的骑行时间主要发生在城市核心区。相反，这两种交通方式之间的竞争性互动并不频繁，且与较短的骑行时间相关，通常发生在地铁站密集的地方。教育、服务和居住因素是人们选择 "共享单车+地铁 "出行方式的主要影响因素。建筑环境对竞争关系的影响较大，而对互补关系的影响较小。

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引用次数: 0

Spatio-temporal modeling of asthma-prone areas: Exploring the influence of urban climate factors with explainable artificial intelligence (XAI) 哮喘易发区的时空建模：利用可解释人工智能（XAI）探索城市气候因素的影响

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-09 DOI: 10.1016/j.scs.2024.105889

Urbanization's impact on climate is increasingly recognized as a significant public health challenge, particularly for respiratory conditions like asthma. Despite progress in understanding asthma, a critical gap remains regarding the interaction between urban environmental factors and asthma-prone areas. This study addresses this gap by applying innovative spatio-temporal modeling techniques with explainable artificial intelligence (XAI). Using data from 872 asthma patients in Tehran, Iran, and 19 factors affecting asthma exacerbations, including climate and air pollution, spatio-temporal modeling was conducted using XGBoost (eXtreme Gradient Boosting) algorithm optimization by the Bat algorithm (BA). Evaluation of asthma-prone area maps using receiver operating characteristic (ROC) curves revealed accuracies of 97.3 % in spring, 97.5 % in summer, 97.8 % in autumn, and 98.4 % in winter. Interpretability analysis of the XGBoost model utilizing the SHAP (Shapley Additive exPlanations) method highlighted rainfall in spring and autumn and temperature in summer and winter as having the most significant impacts on asthma. Particulate matter (PM_2.5) in spring, carbon monoxide (CO) in summer, ozone (O₃) in autumn, and PM₁₀ in winter exhibited the most substantial effects among air pollution factors. This research enhances understanding of asthma dynamics in urban environments, informing targeted interventions for urban planning strategies to mitigate adverse health consequences of urbanization.

人们日益认识到，城市化对气候的影响是一项重大的公共卫生挑战，尤其是对哮喘等呼吸系统疾病而言。尽管在了解哮喘方面取得了进展，但在城市环境因素与哮喘易发地区之间的相互作用方面仍存在重大差距。本研究通过应用创新的时空建模技术和可解释人工智能（XAI）来弥补这一不足。利用伊朗德黑兰 872 名哮喘患者的数据和 19 个影响哮喘恶化的因素（包括气候和空气污染），采用蝙蝠算法（BA）优化的 XGBoost（eXtreme Gradient Boosting）算法进行了时空建模。使用接收器操作特征曲线（ROC）对哮喘易发区地图进行评估后发现，春季的准确率为 97.3%，夏季为 97.5%，秋季为 97.8%，冬季为 98.4%。利用 SHAP（Shapley Additive exPlanations）方法对 XGBoost 模型进行的可解释性分析表明，春季和秋季的降雨量以及夏季和冬季的气温对哮喘的影响最大。在空气污染因素中，春季的颗粒物（PM2.5）、夏季的一氧化碳（CO）、秋季的臭氧（O3）和冬季的可吸入颗粒物（PM10）对哮喘的影响最大。这项研究加深了人们对城市环境中哮喘动态的了解，为城市规划战略提供了有针对性的干预措施，以减轻城市化对健康造成的不利影响。

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引用次数: 0