Computers Environment and Urban Systems最新文献_第9页

Corrigendum to “How do contributions of organizations impact data inequality in OpenStreetMap?” [Computers, Environment and Urban Systems, Volume 109 (2024), 102077] “组织的贡献如何影响OpenStreetMap中的数据不平等？”[计算机，环境和城市系统，第109卷（2024），102077]

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-04 DOI: 10.1016/j.compenvurbsys.2025.102272

Anran Yang , Hongchao Fan , Qingren Jia , Mengyu Ma , Zhinong Zhong , Jun Li , Ning Jing

引用次数: 0

From theory to deep learning: Understanding the impact of geographic context factors on traffic violations 从理论到深度学习：了解地理环境因素对交通违规行为的影响

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-27 DOI: 10.1016/j.compenvurbsys.2025.102268

Hao Yang , X. Angela Yao , Farnoosh Roozkhosh , Ruowei Liu , Gengchen Mai

Traffic violations pose significant threats to road safety, often leading to accidents, injuries, fatalities, and property damage. While driving behavior results from a dynamic interaction among drivers, vehicles, and the environment, most studies have primarily focused on human factors, neglecting the critical influence of social and environmental elements of the geographical context. To address this gap, we first develop a theoretical framework that explores how vehicles, drivers, and environmental factors interact, with particular emphasis on the environmental impact on driving behavior and road safety. Building on this framework, we introduce TraVio, a multitask deep learning model that combines Graph Convolutional Networks (GCNs) with Multilayer Perceptrons (MLPs) to detect and classify traffic violations. Through a case study in Montgomery County, Maryland, we demonstrate that TraVio outperforms traditional machine learning baselines in both binary and multi-label classification tasks. The results underscore the critical role of geographic context and time factors in shaping traffic violations. This study not only provides a robust modeling technique for predicting traffic violations but also offers a theoretical foundation that can be extended to other driving-related themes, contributing to safer road environments through informed urban planning and policymaking.

交通违法行为对道路安全构成重大威胁，往往导致事故、伤害、死亡和财产损失。虽然驾驶行为是驾驶员、车辆和环境三者动态交互作用的结果，但大多数研究主要集中在人为因素上，而忽视了地理环境中社会和环境因素的关键影响。为了解决这一差距，我们首先建立了一个理论框架，探讨车辆、驾驶员和环境因素如何相互作用，特别强调环境对驾驶行为和道路安全的影响。在此框架的基础上，我们引入了TraVio，这是一个多任务深度学习模型，它将图卷积网络（GCNs）与多层感知器（mlp）相结合，以检测和分类交通违规。通过马里兰州蒙哥马利县的一个案例研究，我们证明了TraVio在二元和多标签分类任务中都优于传统的机器学习基线。研究结果强调了地理环境和时间因素在形成交通违规行为中的关键作用。本研究不仅为预测交通违规提供了强大的建模技术，而且还提供了理论基础，可以扩展到其他与驾驶相关的主题，通过明智的城市规划和政策制定，为更安全的道路环境做出贡献。

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引用次数: 0

A planning support framework to enable smart mobility: Integrating multi-objective spatial optimization and GIS to enhance commuting efficiency 实现智能出行的规划支持框架：整合多目标空间优化和GIS，提高通勤效率

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-27 DOI: 10.1016/j.compenvurbsys.2025.102269

Reza Mortaheb , Piotr Jankowski , Alan Murray

Planning support approaches can play a transformative role in shaping sustainable, resilient, and equitable urban landscapes that promote efficient mobility patterns. This paper develops a prescriptive framework that integrates Geographic Information Systems with a variant of the transportation problem to evaluate planning initiatives and inform land use policies and growth management strategies aimed at enhancing commuting efficiency at both local and regional levels. A multi-step approach is structured including 1) a multi-objective spatial optimization model that simulates the impacts of alterations to urban locational structure on work trip durations, capturing normative commuting patterns across three major workforce groups under varying urban growth scenarios; and 2) a modified gravity model that estimates regional commuting efficiency at the economic-sector level based on optimized inputs. Results indicate that this framework enables a critical evaluation of urban spatial configurations and corresponding commuting efficiency indicators under both conventional and alternative planning systems. The proposed framework also supports tactical and strategic land use and transportation planning, allowing planners and policymakers to analyze potential urban forms across different development scenarios, dissect commuting efficiency outcomes by industry, and identify sectors with critical spatial mismatches between job locations and housing. The ability to guide more balanced urban development and foster more efficient commuting patterns is demonstrated for Central Florida.

规划支持方法可以在塑造可持续、有弹性和公平的城市景观方面发挥变革性作用，促进高效的交通模式。本文开发了一个规范性框架，将地理信息系统与交通问题的一个变体相结合，以评估规划举措，并为土地使用政策和增长管理战略提供信息，旨在提高地方和区域层面的通勤效率。本文构建了一个多步骤的方法，包括：1)一个多目标空间优化模型，模拟城市区位结构变化对工作旅行时间的影响，捕捉不同城市增长情景下三个主要劳动力群体的规范通勤模式；2)基于优化投入的修正重力模型在经济部门层面估算区域通勤效率。结果表明，该框架能够对传统和替代规划系统下的城市空间配置和相应的通勤效率指标进行批判性评估。拟议的框架还支持战术和战略土地使用和交通规划，使规划者和决策者能够分析不同发展情景下潜在的城市形态，按行业剖析通勤效率结果，并确定工作地点和住房之间存在严重空间不匹配的部门。引导更平衡的城市发展和培养更高效的通勤模式的能力在佛罗里达中部得到了证明。

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引用次数: 0

Interpreting core forms of urban morphology linked to urban functions with explainable graph neural network 用可解释的图神经网络解释与城市功能相关的城市形态核心形式

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-24 DOI: 10.1016/j.compenvurbsys.2025.102267

Dongsheng Chen , Yu Feng , Xun Li , Mingya Qu , Peng Luo , Liqiu Meng

Understanding the high-order relationship between urban form and function is essential for modeling the underlying mechanisms of sustainable urban systems. Nevertheless, it is challenging to establish an accurate data representation for complex urban forms that are readily explicable in human terms. This study proposed the concept of core urban morphology representation and developed an explainable deep learning framework for explicably symbolizing complex urban forms into the novel representation, which we call CoMo. By interpretating the well-trained deep learning model with a stable weighted F1-score of 89.14 %, CoMo presents a promising approach for revealing links between urban function and urban form in terms of core urban morphology representation. Using Boston as a study area, we analyzed the core urban forms at the individual-building, block, and neighborhood level that are important to corresponding urban functions. The residential core forms follow a gradual morphological pattern along the urban spine, which is consistent with a center-urban-suburban transition. Furthermore, we prove that urban morphology directly affects land use efficiency, which has a significantly strong correlation with the location (R² = 0.721, p < 0.001). Overall, CoMo can explicably symbolize urban forms, provide evidence for the classic urban location theory, and offer mechanistic insights for digital twins.

了解城市形态和功能之间的高阶关系对于建立可持续城市系统的潜在机制至关重要。然而，为复杂的城市形式建立一个准确的数据表示是具有挑战性的，这些形式很容易用人类的术语来解释。本研究提出了核心城市形态表征的概念，并开发了一个可解释的深度学习框架，用于将复杂的城市形态解释为新的表征，我们称之为CoMo。CoMo通过解释训练良好的深度学习模型，其加权f1得分稳定在89.14%，为揭示城市功能和城市形态之间的联系提供了一种很有前途的方法，可以从核心城市形态表征的角度来揭示城市功能和城市形态之间的联系。我们以波士顿为研究区域，分析了个体建筑、街区和社区层面的核心城市形态，这些核心城市形态对相应的城市功能至关重要。住宅核心形式遵循城市脊梁的渐变形态模式，与中心-城市-郊区过渡相一致。此外，我们还证明了城市形态直接影响土地利用效率，其与区位具有显著的强相关性(R2 = 0.721, p <；0.001)。总体而言，CoMo可以解释地象征城市形态，为经典的城市区位理论提供证据，并为数字孪生提供机制见解。

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引用次数: 0

Future scenarios for urban agriculture and food security in sub-Saharan Africa: Modelling the urban land-food system in an agent-based approach 撒哈拉以南非洲城市农业和粮食安全的未来情景：以主体为基础的方法模拟城市土地-粮食系统

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.compenvurbsys.2025.102258

Lisa-Marie Hemerijckx , Koen De Vos , Joseph Oseko Kaunda , Anton Van Rompaey

Food systems in sub-Saharan African cities are increasingly pressured by rapid urban sprawl and socio-economic changes. While land conversion from cropland to built-up area is limiting the opportunity for urban agriculture, food demand is rising because of population growth and changing diets. Meanwhile, socio-economic segregation – often associated with urbanization - can hinder access to food. For the case study of Kampala (Uganda), we spatiotemporally model the land-food system using an agent-based approach. Based on 747 household surveys, we recalibrated the Agent-based model of Social Segregation and Urban Expansion (ASSURE) by Vermeiren et al. (2016) and included food system dynamics to assess future trajectories (2020–2040) of Kampala's dependency on urban agriculture. While food that is both produced and consumed within the city is often considered the most resilient food source in times of crisis, we show that it is particularly this source that is threatened. Overall, about 10 % of the urban and peri-urban agricultural land in Kampala is projected to disappear by 2040. This may lead to decreased levels of food security and dietary diversity, particularly for households that strongly rely on urban agriculture. Information on the links between urban growth and local food provision is essential for planners who aim to develop strategies for more secure, just and sustainable African urban food systems.

撒哈拉以南非洲城市的粮食系统正日益受到城市快速扩张和社会经济变化的压力。虽然从农田到建成区的土地转换限制了城市农业的机会，但由于人口增长和饮食变化，粮食需求正在上升。与此同时，社会经济隔离——通常与城市化有关——可能阻碍获得粮食。对于坎帕拉（乌干达）的案例研究，我们使用基于代理的方法对土地-粮食系统进行时空建模。基于747个家庭调查，我们重新校准了Vermeiren等人（2016）的基于主体的社会隔离和城市扩张模型（ASSURE），并纳入了粮食系统动力学来评估坎帕拉对城市农业依赖的未来轨迹（2020-2040）。虽然在危机时期，城市生产和消费的食物通常被认为是最具弹性的食物来源，但我们表明，受到威胁的尤其是这一来源。总体而言，预计到2040年，坎帕拉约10%的城市和城郊农业用地将消失。这可能导致粮食安全和饮食多样性水平下降，对高度依赖都市农业的家庭来说尤其如此。关于城市增长与当地粮食供应之间联系的信息对于旨在制定更安全、公正和可持续的非洲城市粮食系统战略的规划者至关重要。

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引用次数: 0

Plot-scale population estimation modeling based on residential plot form clustering and locational attractiveness analysis 基于小区形态聚类和区位吸引力分析的小区尺度人口估计模型

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.compenvurbsys.2025.102257

Youmei Peng, Quan Liu

In many regions, urbanization has advanced to a stage that requires urban renewal, making precise population data essential for effective regional renewal and sustainable development. Therefore, this paper aims to disaggregate Jiedao-level (an administrative unit under the district) census population data to the Plot level. From an urban morphology perspective, the Gaussian Mixture Model (GMM) clustering algorithm was applied to classify the form of residential plots, assigning a type parameter for each type: the per capita housing area, to describe population density differences among the types. We then used Pearson correlation analysis to assess the relationship between POI density and population density at various bandwidths, identifying the optimal bandwidth for different POI types and calculating the overall POI density for each plot to evaluate its locational attractiveness. A regression model was established using per capita housing area, POI density, and total building area to derive population weight layers for estimating population at the plot level. The results of accuracy assessment show that using the morphological type parameter can effectively improve the estimation accuracy at plot scale, especially in areas with diverse land-use patterns and lower population density. However, our optimized locational attractiveness calculation method shows only a slight improvement to the method using a fixed bandwidth. This study develops a more accurate population estimation method of plot-level based on morphological classification， and highlights the population distribution characteristics of different types of residential plots, aiding urban decision-makers in developing targeted strategies for housing optimization and community resource allocation.

在许多地区，城市化已经发展到需要城市更新的阶段，精确的人口数据对于有效的区域更新和可持续发展至关重要。因此，本文旨在将街道级（区下的行政单位）人口普查数据分解到地块级。从城市形态学角度出发，采用高斯混合模型（GMM）聚类算法对居住地块的形态进行分类，并为每一种类型分配一个类型参数：人均住房面积，以描述不同类型之间的人口密度差异。然后，我们使用Pearson相关分析来评估不同带宽下POI密度与人口密度之间的关系，确定不同POI类型的最佳带宽，并计算每个地块的总体POI密度，以评估其位置吸引力。利用人均住房面积、POI密度和总建筑面积建立回归模型，推导人口权重层，估算地块人口。精度评价结果表明，利用形态类型参数可以有效提高样地尺度上的估算精度，特别是在土地利用模式多样、人口密度较低的地区。然而，我们优化的位置吸引力计算方法仅比使用固定带宽的方法略有改进。本研究发展了基于形态分类的更精确的小区级人口估计方法，并突出了不同类型住宅小区的人口分布特征，有助于城市决策者制定有针对性的住房优化和社区资源配置策略。

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引用次数: 0

Model-based estimation of the isolated impacts of urban expansion on projected streamflow values under varied climate scenarios 不同气候情景下城市扩张对预估流量的孤立影响的基于模型的估算

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-16 DOI: 10.1016/j.compenvurbsys.2025.102259

A. Botero-Acosta , M.L. Chu , C.L. Wu , G.F. McIsaac , J.H. Knouft

The use of computationally intensive hydrologic models under future climate scenarios has become a common practice to project water resource concerns in the coming decades. Under this approach, hydrologic models are parameterized and run under various climate forcings. Although urban areas are expected to expand during the time frame of these simulations, potentially impacting watershed hydrology, the uncertainty of forecasted streamflow is usually estimated based on the ensemble of climate scenarios, with minimal (if any) attention given to the uncertainty introduced by land transformations. The objective of this study is to quantify the Isolated Impacts on Projected Streamflow (IIPS) caused by urban expansion as climate changes in a watershed in the midwestern United States. IIPS time series were estimated as the difference between projected streamflows under future climate scenarios with and without urban expansion and weighted by the historical (1980–2010) monthly average. Two gradual and two abrupt urbanization scenarios, having equivalent developed areas by the end of the 21st century, were implemented. Results indicate that gradual urbanization could result in both increased (up to 26 %) and decreased (up to 16 %) projected streamflows, suggesting the increase in variability of extremes, with potential impacts on human and natural systems. Yearly minimum and maximum IIPS for all scenarios were found to be more likely to occur in summer and fall months, respectively. Impacts of the abrupt urban expansion were mainly observed in the cumulative IIPS and the ensemble variability of extreme IIPS. These results provide insights into the uncertainty of future streamflow estimates attributable to urban expansion.

在未来气候情景下使用计算密集型水文模型已成为预测未来几十年水资源问题的一种普遍做法。在这种方法下，水文模型被参数化并在各种气候强迫下运行。虽然预计城市地区在这些模拟的时间范围内会扩大，可能会影响流域水文，但预测流量的不确定性通常是根据气候情景的集合来估计的，很少（如果有的话）注意到土地改造带来的不确定性。本研究的目的是量化美国中西部流域气候变化引起的城市扩张对预计流量（IIPS）的孤立影响。IIPS时间序列估计为未来气候情景下有和没有城市扩张的预测流量之差，并加权历史（1980-2010）月平均值。到21世纪末，中国城市化将出现两种渐进式和两种突发性的情景，并形成相当的发达地区。结果表明，逐渐城市化可能导致预估流量增加（最多26%）和减少（最多16%），这表明极端事件的变异性增加，对人类和自然系统有潜在影响。所有情景的年最小和最大IIPS分别更有可能发生在夏季和秋季。城市突发性扩张的影响主要体现在累积IIPS和极端IIPS的集合变率上。这些结果提供了对归因于城市扩张的未来流量估计的不确定性的见解。

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引用次数: 0

Shortest covering paths and other covering walks: Refinements and prospects for subtour prevention 最短覆盖路径与其他覆盖路径：改进与展望

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-13 DOI: 10.1016/j.compenvurbsys.2024.102247

T.C. Matisziw

The shortest covering path problem (SCPP) is a network optimization model in which a least-cost route connecting an origin and destination that can be accessed by all demand nodes in a network is sought. Thus, it is applicable to transportation planning tasks such as designing routes for public transit and distribution systems. However, deriving optimal solutions to the SCPP can be challenging as an iterative solution approach is often required. Also, problems can arise in accounting for coverage of network nodes and in the handling of certain types of cycles. To this end, a family of model variants for the SCPP is proposed to remedy these problems and to assist with the identification of covering paths and other walks. Additionally, the case in which the origin node is also the destination node is incorporated into the SCPP framework. A flow-constrained SCPP that does not require an iterative solution process is then proposed to identify optimal walks of different types. The flow-constrained SCPP and its iterative counterpart are solved for all origin-destination pairs in a network and their relative computational characteristics are assessed. The results demonstrate that optimal solutions to the flow-constrained SCPP can be obtained more quickly than those obtained using the iterative approach. The results also provide further evidence of the relevance of cycles, particularly those involving U-turns, in solutions to network routing problems. Together, the proposed refinements, extensions, and documented computational experience will extend the applicability and the utility of the SCPP and its counterpart path covering models.

最短覆盖路径问题（SCPP）是一种网络优化模型，其目的是寻找连接起点和终点且网络中所有需求节点都能访问的代价最小的路径。因此，它适用于公共交通和分配系统的路线设计等交通规划任务。然而，获得SCPP的最优解决方案可能具有挑战性，因为通常需要迭代解决方法。此外，在计算网络节点的覆盖范围和处理某些类型的周期时可能会出现问题。为此，提出了SCPP的一系列模型变体来解决这些问题，并协助识别覆盖路径和其他路径。此外，源节点同时也是目标节点的情况被合并到SCPP框架中。然后，提出了一种不需要迭代求解过程的流约束SCPP来识别不同类型的最优行走。对网络中所有出发地对进行了流约束SCPP及其迭代求解，并评估了它们的相对计算特性。结果表明，与迭代法相比，该方法能更快地得到流约束SCPP的最优解。研究结果还进一步证明了周期的相关性，特别是那些涉及u型转弯的周期，在网络路由问题的解决方案中。总之，提出的改进、扩展和记录的计算经验将扩展SCPP及其对应路径覆盖模型的适用性和实用性。

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引用次数: 0

Simulating household energy behavior diffusion using spatial microsimulation and econometric models 利用空间微观模拟和计量模型模拟家庭能源行为扩散

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-08 DOI: 10.1016/j.compenvurbsys.2025.102256

Jianhua Zhang , Loes Bouman , Dimitris Ballas , Xiaolong Liu

Analyzing household energy behaviors from a spatial perspective is crucial for both policymakers and network operators. However, conducting spatial analysis at a fine scale presents significant challenges, primarily due to data scarcity. This article demonstrates the potential of integrating spatial microsimulation and spatial econometric models to address this issue. Specifically, we construct a static spatial microsimulation model to create a synthetic population for the entire Netherlands, simulating neighborhood-level spatial distributions of household energy behaviors. The results indicate significant neighborhood-level spatial heterogeneity in the adoption of energy behaviors. Subsequently, this simulated output is used as input for spatial econometric models to analyze the neighborhood-level spatial determinants of household energy behavior adoption. We identify the roles of both spatial endogenous effects and neighborhood-specific characteristics in contributing to the observed spatial variations in household energy behaviors.

从空间角度分析家庭能源行为对政策制定者和网络运营商都至关重要。然而，在精细尺度上进行空间分析面临着重大挑战，主要是由于数据稀缺。本文展示了整合空间微观模拟和空间计量经济学模型来解决这一问题的潜力。具体而言，我们构建了一个静态空间微观模拟模型，为整个荷兰创建一个合成人口，模拟家庭能源行为的邻里空间分布。结果表明，能源行为的采用存在显著的邻里空间异质性。随后，该模拟输出被用作空间计量模型的输入，以分析家庭能源行为采用的邻里水平的空间决定因素。我们确定了空间内生效应和社区特征在促进观察到的家庭能源行为的空间变化中的作用。

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引用次数: 0

Predicting Desire Paths: Agent-Based Simulation for Neighbourhood Route Planning 期望路径预测：基于智能体的邻里路线规划仿真

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-02-05 DOI: 10.1016/j.compenvurbsys.2025.102251

Józef Bossowski , Tomasz Szandała , Jacek Mazurkiewicz

This study addresses how informal “desire paths” emerge when urban infrastructure does not align with pedestrian preferences, focusing on small, local neighbourhoods to bridge a recognised research gap in urban planning. It introduces an agent-based modelling (ABM) framework that builds on path optimisation, affordance theory, and two novel models: a weighted preferences model that accounts for varied pedestrian priorities beyond route length and an obstacle avoidance model that achieves 60 % accuracy, indicating it can successfully replicate aspects of natural navigation, but still showing potential for further refinements. Conducted in three-dimensional simulations using Unity3D and the Agent-Based Modelling for Unity (ABMU) toolkit, this approach yields complex path networks that illuminate pedestrian decision-making processes and highlight the impact of diverse priorities, including local optimisation of route length, on network efficiency. By clarifying these ABM-driven insights, we underscore the significance of integrating multiple pedestrian preferences into urban planning to foster more sustainable development in local neighbourhoods.

本研究探讨了当城市基础设施与行人偏好不一致时，非正式的“愿望路径”是如何出现的，重点关注小型当地社区，以弥合城市规划中公认的研究差距。它引入了一个基于智能体的建模（ABM）框架，该框架建立在路径优化、功能理论和两个新模型的基础上：一个加权偏好模型，该模型考虑了路径长度以外行人优先级的变化，另一个避障模型达到了60%的准确率，表明它可以成功复制自然导航的各个方面，但仍显示出进一步改进的潜力。使用Unity3D和基于agent的建模工具（ABMU）进行三维模拟，这种方法产生了复杂的路径网络，阐明了行人的决策过程，并强调了不同优先级的影响，包括局部优化路线长度，对网络效率的影响。通过阐明这些以abm为导向的见解，我们强调了将多种行人偏好纳入城市规划的重要性，以促进当地社区的可持续发展。

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引用次数: 0