Computers Environment and Urban Systems最新文献_第8页

Advancing population-targeted urban sensing: A comparative study on mobile and static sensing paradigms 推进以人口为目标的城市感知：移动与静态感知范式的比较研究

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-04-08 DOI: 10.1016/j.compenvurbsys.2025.102288

Yuan-Qiao Hou , Xiao-Jian Chen , Zhou Huang , Xia Peng , Yu Liu

To evaluate human exposure to environmental factors, sufficient population-targeted sensing power of sensor carriers is crucial. However, the traditional static sensing approach is constrained by its limited coverage. Recently, equipping moving vehicles with sensors has emerged as a new approach. However, a quantitative comparison between mobile and traditional static sensing is still lacking. Using empirical taxi trajectory and population data in Beijing and Xiamen, we found that while a small number of taxi-based mobile sensors can cover a larger portion of the population, well-located static sensors eventually surpass mobile sensors in coverage as their number increases. In addition, a higher required frequency reduces the coverage of mobile sensors, whereas a higher cost ratio between static and mobile sensors reduces the coverage of static sites. Taxis provide extensive spatial coverage but with some uncertainty, especially in peripheral areas, whereas static sensors ensure localized and stable coverage. Based on the advantage of taxis and static sites, we propose an effective greedy-add-guided strengthen elitist genetic algorithm to determine the optimal combination of static and mobile sensors. The key idea is to position static sensors in areas with relatively low taxi visit probabilities but high population density. The results indicate that this optimal combination achieves higher population coverage compared to using taxis alone. It addresses the uncertainty in taxi coverage and significantly reduces the number of sensors required. These results support the feasibility of using taxis as a sensing paradigm and further highlight the potential of combining these two sensing paradigms in population-targeted sensing applications.

为了评估人类对环境因子的暴露，传感器载体具有足够的人群感知能力至关重要。然而，传统的静态传感方法受限于其有限的覆盖范围。最近，为移动车辆配备传感器已成为一种新方法。然而，移动传感与传统静态传感之间的定量比较仍然缺乏。利用北京和厦门的出租车轨迹和人口数据，我们发现，虽然少量基于出租车的移动传感器可以覆盖大部分人口，但位置良好的静态传感器最终会随着数量的增加而覆盖范围超过移动传感器。此外，更高的频率要求降低了移动传感器的覆盖范围，而更高的静态和移动传感器之间的成本比降低了静态站点的覆盖范围。出租车提供了广泛的空间覆盖，但也有一些不确定性，尤其是在周边地区，而静态传感器则确保了局部和稳定的覆盖。基于出租车和静态站点的优势，我们提出了一种有效的贪婪添加导向强化精英遗传算法来确定静态和移动传感器的最优组合。关键思想是将静态传感器定位在出租车访问概率相对较低但人口密度较高的地区。结果表明，与单独使用出租车相比，这种优化组合实现了更高的人口覆盖率。它解决了出租车覆盖范围的不确定性，并显著减少了所需传感器的数量。这些结果支持了出租车作为一种感知范式的可行性，并进一步强调了将这两种感知范式结合起来用于人群目标感知应用的潜力。

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引用次数: 0

A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation 建筑高度建模的分段方法：描绘高层和低层建筑以增强高度估计

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-04-08 DOI: 10.1016/j.compenvurbsys.2025.102287

Clinton Stipek, Daniel Adams, Philipe Dias, Taylor Hauser, Viswadeep Lebakula, Alexander Sorokine, Justin Epting, Jessica Moehl, Robert Stewart

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within

3 m

error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building

> 12 m

. Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.

了解建筑高度对能源效率、人口分布、城市形态、应急响应等方面的整体研究至关重要。目前，现有的大规模建筑高度建模方法受到两个普遍问题的阻碍。首先，没有一致的方法来量化宏观尺度上的高层建筑，这使得研究人员无法准确地比较不同地域和领域的结果。其次，高层建筑只占建筑环境的一小部分，这意味着数据不平衡的挑战会对当前的方法产生负面影响。这是一个具有实际意义的问题，因为高层建筑的信息对于研究城市热岛、人口动态和污染扩散非常重要。在这里，我们引入了一种新的方法来绘制建筑高度，该方法首先在建筑环境中识别出两种不同的分布，一种由低层建筑组成，另一种由高层建筑组成。然后，我们开发了一个集成方案，其中为低层建筑和高层建筑的每个子集训练离散的专家模型，以从形态特征推断建筑高度。对于绘制日本485万幢建筑高度的实验，我们显示，与目前最先进的高层建筑建模相比，在3米误差范围内的精度提高了34%，基于KNN实验，我们将其定义为任何12米的建筑。我们的研究结果表明，这样的集成框架优于当前最先进的方法，这在推断高层建筑的高度方面尤其相关，这是现有的绘制建筑环境方法的一个突出问题。

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引用次数: 0

Measuring evacuation rates from mobility data during the McDougall Creek wildfire in British Columbia, Canada 从加拿大不列颠哥伦比亚省麦克杜格尔河野火期间的移动数据测量疏散率

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-04-03 DOI: 10.1016/j.compenvurbsys.2025.102286

Hui Jeong Ha, Jed A. Long

In recent years, the intensity and occurrence of wildfires have risen globally, driven by climate change triggering extreme dry weather conditions. This study focuses on the 2023 McDougall Creek wildfire in British Columbia, highlighting the vulnerability of urban communities to severe wildfires. Using aggregated and de-identified network mobility data from a Canadian telecommunications provider, we quantified neighborhood-level evacuation rates and examined inter-regional travel patterns during the wildfire event. We applied a spatial difference-in-difference (DID) model to understand how neighborhood characteristics influenced evacuation rates. Our findings suggest that formal evacuation orders were positively associated with evacuation rates. We also found that the distance to the wildfire perimeter was a strong and significant predictor of evacuation rates, while socio-demographic variables previously identified as strong predictors of evacuation rates were not significant in this particular context. The analysis of travel patterns before and during the wildfire event reveals distinct directional patterns and variations in inter-regional travel across spatial scales. This research contributes to the understanding of wildfire evacuation dynamics and the application of human mobility data into disaster management, enhancing our knowledge of the human response to natural disasters.

近年来，在气候变化引发极端干燥天气条件的推动下，全球野火的强度和发生率都有所上升。这项研究的重点是2023年不列颠哥伦比亚省的麦克杜格尔河野火，突出了城市社区对严重野火的脆弱性。使用来自加拿大电信提供商的聚合和去识别网络移动数据，我们量化了社区一级的疏散率，并检查了野火事件期间的区域间旅行模式。我们应用空间差分模型来了解社区特征如何影响疏散率。我们的研究结果表明，正式的疏散命令与疏散率呈正相关。我们还发现，到野火周边的距离是疏散率的一个强大而重要的预测因子，而以前被确定为疏散率的强预测因子的社会人口变量在这种特殊情况下并不显著。对森林火灾发生前和发生期间的旅行模式进行分析，揭示了区域间旅行在空间尺度上的明显方向性模式和变化。本研究有助于了解野火疏散动态，并将人员流动数据应用于灾害管理，提高我们对人类应对自然灾害的认识。

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引用次数: 0

Route planning of mobile sensing fleets for repeatable environmental monitoring tasks 可重复环境监测任务的移动传感车队路线规划

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-28 DOI: 10.1016/j.compenvurbsys.2025.102285

Wen Ji , Ke Han , Qian Ge

Vehicle-based mobile sensing is a new paradigm for urban data collection. Certain urban sensing scenarios require sensing vehicles for highly targeted monitoring, such as air pollutant and accident site investigation. A hallmark of these scenarios is that the points of interest (POIs) need to be repeatedly visited by a set of agents, whose routes should provide sufficient sensing coverage with coordinated overlap at certain important POIs. For these applications, this paper presents the open team orienteering problem with repeatable visits (OTOP-RV) and specifically tailors an adaptive large neighborhood search (ALNS) algorithm to address it. Test results on randomly generated datasets show that the ALNS significantly outperforms the greedy algorithm (by 7.2 % to 32.4 %), and a heuristic based on sequential orienteering problem (by about 6 %). Finally, a real-world air pollution sensing case study demonstrates the unique applicability of the OTOP-RV and the effectiveness of the proposed algorithms in enhancing sensing capabilities.

基于车辆的移动传感是城市数据采集的新范式。某些城市传感场景需要传感车辆进行高度针对性的监测，如空气污染物和事故现场调查。这些场景的一个特点是，兴趣点（poi）需要由一组代理反复访问，其路由应提供足够的感知覆盖，并在某些重要的poi上协调重叠。针对这些应用，本文提出了具有可重复访问的开放式团队定向问题（OTOP-RV），并专门定制了一种自适应大邻域搜索（ALNS）算法来解决该问题。在随机生成的数据集上的测试结果表明，ALNS显著优于贪婪算法（7.2%比32.4%）和基于顺序定向问题的启发式算法（约6%）。最后，一个现实世界的空气污染传感案例研究证明了OTOP-RV的独特适用性以及所提出算法在增强传感能力方面的有效性。

引用次数: 0

Physical urban change and its socio-environmental impact: Insights from street view imagery 城市物理变化及其社会环境影响：来自街景图像的见解

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-27 DOI: 10.1016/j.compenvurbsys.2025.102284

Yingjie Liu , Zeyu Wang , Siyi Ren , Runying Chen , Yixiang Shen , Filip Biljecki

Urban transformation not only reshapes physical spaces but also impacts public perception, influencing how people experience their environments. This study utilizes Street View Imagery (SVI) as an emerging, human-level data source to assess urban changes, providing perspective beyond traditional datasets. Existing studies often focus on either urban physical changes or human perception changes, without bridging the two. This research integrates both aspects by combining a change detection model, trained on a self-labeled dataset, and a human perception model based on the crowdsourced Place Pulse 2.0 dataset with input from 81,630 online volunteers, to analyze urban transformation in New York City and Memphis from 2007 to 2023. Our findings reveal differences between the two cities: New York City exhibited small, isolated changes often driven by community needs, while Memphis transitioned from concentrated to more dispersed development patterns. This study provides insights into how physical changes influence public perception within these two cities. It demonstrates how thoughtful, well-planned urban transformation can improve neighborhood's perception such as safety and livability, while also pointing out potential challenges like gentrification or social fragmentation. These findings provide policymakers with valuable insights into human perception, aiding in the creation of more inclusive, vibrant, and resilient urban transformation. This helps ensure that urban transformation efforts are based on community desires and align with long-term sustainability goals.

城市转型不仅重塑了物理空间，也影响了公众的感知，影响了人们对环境的体验。本研究利用街景图像（SVI）作为一种新兴的、人性化的数据源来评估城市变化，提供了超越传统数据集的视角。现有的研究往往只关注城市物理变化或人类感知变化，而没有将两者联系起来。本研究结合自标记数据集训练的变化检测模型和基于81630名在线志愿者输入的众包Place Pulse 2.0数据集的人类感知模型，对2007年至2023年纽约市和孟菲斯的城市转型进行了分析。我们的研究结果揭示了两个城市之间的差异：纽约市表现出通常由社区需求驱动的小而孤立的变化，而孟菲斯则从集中的发展模式过渡到更分散的发展模式。这项研究提供了关于这两个城市的身体变化如何影响公众感知的见解。它展示了经过深思熟虑、精心规划的城市转型如何能够改善社区的安全感和宜居性，同时也指出了士绅化或社会分裂等潜在挑战。这些发现为政策制定者提供了有关人类感知的宝贵见解，有助于实现更具包容性、活力和弹性的城市转型。这有助于确保城市转型工作以社区愿望为基础，并与长期可持续发展目标保持一致。

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引用次数: 0

ZenSVI: An open-source software for the integrated acquisition, processing and analysis of street view imagery towards scalable urban science ZenSVI：一款开源软件，用于集成街景图像的采集、处理和分析，以实现可扩展的城市科学

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-20 DOI: 10.1016/j.compenvurbsys.2025.102283

Koichi Ito , Yihan Zhu , Mahmoud Abdelrahman , Xiucheng Liang , Zicheng Fan , Yujun Hou , Tianhong Zhao , Rui Ma , Kunihiko Fujiwara , Jiani Ouyang , Matias Quintana , Filip Biljecki

Street view imagery (SVI) has been instrumental in many studies in the past decade to understand and characterize street features and the built environment. Researchers across a variety of domains, such as transportation, health, architecture, human perception, and infrastructure have employed different methods to analyze SVI. However, these applications and image-processing procedures have not been standardized, and solutions have been implemented in isolation, often making it difficult for others to reproduce existing work and carry out new research. Using SVI for research requires multiple technical steps: accessing APIs for scalable data collection, preprocessing images to standardize formats, implementing computer vision models for feature extraction, and conducting spatial analysis. These technical requirements create barriers for researchers in urban studies, particularly those without extensive programming experience. We developed ZenSVI, a free and open-source Python package that integrates and implements the entire process of SVI analysis, supporting a wide range of use cases. Its end-to-end pipeline includes downloading SVI from multiple platforms (e.g., Mapillary and KartaView) efficiently, analyzing metadata of SVI, applying computer vision models to extract target features, transforming SVI into different projections (e.g., fish-eye and perspective) and different formats (e.g., depth map and point cloud), visualizing analyses with maps and plots, and exporting outputs to other software tools. We demonstrated its use in Singapore through a case study of data quality assessment and clustering analysis in a streamlined manner. Our software improves the transparency, reproducibility, and scalability of research relying on SVI and supports researchers in conducting urban analyses efficiently. Its modular design facilitates extensions of the package for new use cases. This package is openly available at https://github.com/koito19960406/ZenSVI, and it is supported by documentation including tutorials (https://zensvi.readthedocs.io/en/latest/examples/index.html).

在过去的十年中，街景图像（SVI）在许多研究中发挥了重要作用，以了解和表征街道特征和建筑环境。不同领域（如交通、健康、建筑、人类感知和基础设施）的研究人员采用了不同的方法来分析SVI。然而，这些应用和图像处理程序尚未标准化，并且解决方案是孤立实施的，这往往使其他人难以复制现有工作并开展新的研究。使用SVI进行研究需要多个技术步骤：访问api以进行可扩展的数据收集，预处理图像以标准化格式，实现计算机视觉模型以进行特征提取，并进行空间分析。这些技术要求给城市研究人员，特别是那些没有广泛规划经验的研究人员造成了障碍。我们开发了ZenSVI，这是一个免费的开源Python包，它集成并实现了SVI分析的整个过程，支持广泛的用例。其端到端流程包括从多个平台（如Mapillary和KartaView）高效下载SVI，分析SVI元数据，应用计算机视觉模型提取目标特征，将SVI转换为不同的投影（如鱼眼和视角）和不同的格式（如深度图和点云），用地图和绘图将分析可视化，并将输出输出到其他软件工具。我们通过一个精简方式的数据质量评估和聚类分析的案例研究展示了它在新加坡的使用。我们的软件提高了依赖于SVI的研究的透明度、可重复性和可扩展性，并支持研究人员有效地进行城市分析。它的模块化设计便于为新的用例扩展包。该软件包可在https://github.com/koito19960406/ZenSVI上公开获得，并由包括教程在内的文档（https://zensvi.readthedocs.io/en/latest/examples/index.html）提供支持。

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引用次数: 0

Mapping urban villages in China: Progress and challenges 中国城中村制图：进展与挑战

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-15 DOI: 10.1016/j.compenvurbsys.2025.102282

Rui Cao , Wei Tu , Dongsheng Chen , Wenyu Zhang

The shift toward high-quality urbanization has brought increased attention to the issue of “urban villages”, which has become a prominent social problem in China. However, there is a lack of available geospatial data on urban villages, making it crucial to prioritize urban village mapping. In order to assess the current progress in urban village mapping and identify challenges and future directions, we have conducted a comprehensive review, which to the best of our knowledge is the first of its kind in this field. Our review begins by providing a clear context for urban villages and elaborating the method for literature review, then summarizes the study areas, data sources, and approaches used for urban village mapping in China. We also address the challenges and future directions for further research. Through thorough investigation, we find that current studies only cover very limited study areas and periods and lack sufficient investigation into the scalability, transferability, and interpretability of identification approaches due to the challenges in concept fuzziness and variances, spatial heterogeneity and variances of urban villages, and data availability. Future research can complement and further the current research in the following potential directions in order to achieve large-area mapping across the whole nation: 1) establish a unified standard of urban villages in China to accommodate significant variances and fuzzy concepts, 2) address the challenges of data availability via flexible use of available multisource data and explore potential use of data-driven image super-resolution approaches, 3) create public benchmarks to ensure fair comparison and focus on the scalability, transferability, and interpretability of urban village recognition approaches, 4) initiate a crowdsourcing program to enable effective and efficient data collection and validation as well as application. This review not only supports urban village-related research in China, but also contributes valuable knowledge from a Chinese perspective to global informal settlements mapping research and the achievement of the United Nations' Sustainable Development Goals (SDGs).

向高质量城市化的转变引起了人们对“城中村”问题的越来越多的关注，这已经成为中国一个突出的社会问题。然而，由于缺乏可用的城中村地理空间数据，因此将城中村测绘列为优先事项至关重要。为了评估城中村测绘的当前进展，确定挑战和未来方向，我们进行了一次全面的审查，据我们所知，这是该领域的第一次。本文首先为城中村提供了一个清晰的背景，并阐述了文献综述的方法，然后总结了中国城中村制图的研究领域、数据来源和方法。我们还讨论了进一步研究的挑战和未来方向。通过深入调查，我们发现由于概念的模糊性和差异性、城中村的空间异质性和差异性以及数据的可获得性等方面的挑战，现有研究仅涵盖了非常有限的研究领域和时期，缺乏对识别方法的可扩展性、可转移性和可解释性的充分研究。未来的研究可以在以下几个潜在的方向上对目前的研究进行补充和深化，以实现全国范围内的大面积制图：1)在中国建立统一的城中村标准，以适应显著差异和模糊概念；2)通过灵活使用现有的多源数据来解决数据可用性的挑战，并探索数据驱动的图像超分辨率方法的潜在用途；3)创建公共基准，以确保公平比较，并关注城中村识别方法的可扩展性、可转移性和可解释性。4)启动众包计划，以实现有效和高效的数据收集、验证和应用。这一综述不仅为中国城中村相关研究提供了支持，也为全球非正式住区制图研究和联合国可持续发展目标的实现提供了中国视角下的宝贵知识。

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引用次数: 0

Quantify relationships between bike network connectivity and bike safety: A comparative analysis of connectivity metrics conducted in two California cities 量化自行车网络连接和自行车安全之间的关系：在加州两个城市进行的连接指标的比较分析

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-11 DOI: 10.1016/j.compenvurbsys.2025.102271

Jiahua Chen , Peter Kedron , Trisalyn Nelson , Dan Willett , Achituv Cohen , Colin Ferster

To motivate people to use bikes for transportation, cities are shifting their focus from constructing isolated bike lanes to building interconnected bike networks. The effectiveness of these networks is measured by their level of connectivity, specifically how easily individuals of all ages and abilities can reach their destinations by bike. While most researchers and policymakers hypothesize that well-connected bike networks will reduce crash risk by offering bicyclists extended protection from traffic, most studies find positive or null associations between network connectivity and bike crashes. This discrepancy may arise either from actual processes, such as increased ridership in high-traffic areas, or from variability in how connectivity is measured. Our study aims to understand relationships between bike safety and various connectivity metrics at the neighborhood level by deconstructing and comparing different metrics. We critique previous constructs of density-based metrics rely solely on bike infrastructure and introduce new density-based and routing-based metrics derived from low-stress networks. Using a negative binomial regression model, we examine the association between bike crashes and connectivity metrics across 125 block groups in Santa Barbara and Goleta, California. We find that increased density-based connectivity in both bike infrastructure and low-stress networks correlates with fewer crashes. In contrast, routing-based connectivity measures, which reflect bike access to key destinations, are positively associated with crashes. We conclude that different connectivity metrics can alter the direction of connectivity-safety associations. Our proposed metrics, which incorporate low-stress networks and routing algorithms, provide a more nuanced understanding of how connectivity is related to bicycling safety.

为了鼓励人们使用自行车作为交通工具，城市正在将重点从建设孤立的自行车道转向建设互联的自行车网络。这些网络的有效性是通过它们的连通性来衡量的，特别是不同年龄和能力的人骑自行车到达目的地的容易程度。虽然大多数研究人员和政策制定者假设，连接良好的自行车网络可以为骑自行车的人提供更多的交通保护，从而降低车祸风险，但大多数研究发现，网络连接与自行车事故之间存在正相关或零相关。这种差异可能来自实际流程，例如高流量区域的客流量增加，或者来自如何测量连接性的可变性。我们的研究旨在通过解构和比较不同的指标，了解自行车安全与社区层面的各种连接性指标之间的关系。我们批判了先前仅依赖自行车基础设施的基于密度的度量结构，并引入了来自低压力网络的基于密度和基于路由的新度量。使用负二项回归模型，我们研究了加利福尼亚州圣巴巴拉和戈莱塔125个街区组的自行车事故与连通性指标之间的关系。我们发现，在自行车基础设施和低压力网络中，基于密度的连接性的增加与更少的交通事故有关。相比之下，基于路线的连通性措施（反映自行车到达主要目的地的情况）与交通事故呈正相关。我们得出结论，不同的连接指标可以改变连接-安全关联的方向。我们提出的指标，结合了低压力网络和路由算法，提供了更细致入微的理解连接如何与自行车安全相关。

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引用次数: 0

GeoAvatar: A big mobile phone positioning data-driven method for individualized pseudo personal mobility data generation GeoAvatar：一种用于个性化伪个人移动数据生成的大手机定位数据驱动方法

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-10 DOI: 10.1016/j.compenvurbsys.2025.102252

Peiran Li , Haoran Zhang , Wenjing Li , Dou Huang , Zhiling Guo , Jinyu Chen , Junxiang Zhang , Xuan Song , Pengjun Zhao , Jinyue Yan , Shibasaki Ryosuke , Noboru Koshizuka

The importance of personal mobility data is widely recognized in various fields. However, the utilization of real personal mobility data raises privacy concerns. Therefore, it is crucial to generate pseudo personal mobility data that accurately reflects real-world mobility patterns while safeguarding user privacy. Nevertheless, existing methods for generating pseudo mobility data, mostly focusing on trip or trajectory generation, have limitations in capturing sufficient individual heterogeneity. To address these gaps, taking pseudo-person(avatar) as ground-zero, a novel individual-based human mobility generator named GeoAvatar has been proposed – which considering individual heterogeneity in spatial and temporal decision-making, incorporates demographic characteristics. Our method utilizes a deep generative model to generate heterogeneous individual life patterns, a variation inference model for inferring individual demographic characteristics, and a Bayesian-based approach for generating spatial choices considering individual demographic characteristics. Through our method, we have achieved generating realistic pseudo personal human mobility data - we evaluated the proposed method based on physical features – obeying common law of human mobility, activity features – showing diverse and realistic activities, and spatial-temporal characteristics – presenting high-accuracy in terms of temporal grid population and od-count, demonstrating its good performance, with both a big mobile phone GPS trajectory dataset from Tokyo Metropolis and a big mobile phone CDR dataset from Shanghai. Furthermore, this method maintains extensibility for broader applications, making it a promising framework for generating pseudo personal human mobility data.

个人移动数据的重要性在各个领域得到了广泛的认识。然而，使用真实的个人移动数据引起了隐私问题。因此，在保护用户隐私的同时，生成准确反映现实世界移动模式的伪个人移动数据至关重要。然而，现有的生成伪迁移数据的方法主要集中在行程或轨迹生成上，在捕获足够的个体异质性方面存在局限性。为了解决这些差距，以伪人（化身）为基础，提出了一种新的基于个体的人类移动生成器GeoAvatar，该生成器考虑了个体在空间和时间决策中的异质性，并结合了人口统计学特征。该方法利用深度生成模型生成异质个体生活模式，利用变异推理模型推断个体人口特征，利用基于贝叶斯的方法生成考虑个体人口特征的空间选择。通过我们的方法，我们实现了真实的伪个人人类活动数据的生成，我们基于物理特征-符合人类活动的共同规律，活动特征-显示多样化和真实的活动，以及时空特征-在时间网格人口和计数方面具有较高的准确性，证明了该方法的良好性能。使用来自东京大都会的大型手机GPS轨迹数据集和来自上海的大型手机CDR数据集。此外，该方法为更广泛的应用程序保持了可扩展性，使其成为生成伪个人人体移动数据的有前途的框架。

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引用次数: 0

Modelling active travel accessibility at the micro-scale using multi-source built environment data 基于多源建筑环境数据的微尺度主动交通可达性建模

IF 7.1 1区地球科学 Q1 ENVIRONMENTAL STUDIES

Computers Environment and Urban Systems

Pub Date : 2025-03-07 DOI: 10.1016/j.compenvurbsys.2025.102270

Corin Staves , Irena Itova , Belen Zapata-Diomedi , Audrey de Nazelle , Jenna Panter , Lucy Gunn , Alan Both , Yuchen Li , Ismail Saadi , James Woodcock , S.M. Labib

Accessibility models explore how land use and transport systems interact to facilitate access to activities and daily needs. Existing applications generally model accessibility based on distance or travel time. For pedestrians and cyclists, the street-level environment (e.g., green visibility, streetside amenities, dedicated infrastructure) significantly influences people's willingness and ability to travel. Incorporating these features into accessibility models can help them to be more representative of active travellers' experienced environment.

This study presents a methodology for incorporating the street-level environment into active mode accessibility. First, micro-scale built environment data from multiple sources are harmonised into a high-resolution digital representation of the land use and transport system. Second, a compute-optimised framework is developed for modelling accessibility at the micro-scale (i.e., each dwelling separately) incorporating the street-level environment. The methods build upon the open geodatabase OpenStreetMap and open-source MATSim project, facilitating expandability and transferability to other contexts. We apply this methodology to develop policy-relevant accessibility indicators for Greater Manchester.

In the results, we observe that the street-level environment can cause accessibility indicators to vary at the micro-scale, especially in less connected neighbourhoods where the choice of routes is limited. We also observed that for cyclists, the accessibility advantage over walking reduces substantially when traffic stress is considered. Our findings support further adoption of micro-scale built environment data and high-resolution analysis methods for active travel accessibility modelling in research and practice.

可达性模型探讨土地利用和交通系统如何相互作用，以促进活动和日常需求。现有的应用程序通常基于距离或旅行时间对可访问性进行建模。对于行人和骑自行车的人来说，街道环境（例如，绿色能见度、路边设施、专用基础设施）显著影响人们出行的意愿和能力。将这些功能整合到可访问性模型中，可以帮助它们更能代表活跃旅行者的体验环境。本研究提出了一种将街道环境纳入主动模式可达性的方法。首先，来自多个来源的微尺度建筑环境数据被协调成土地利用和交通系统的高分辨率数字表示。其次，开发了一个计算机优化框架，用于模拟微观尺度（即每个住宅单独）的可达性，并结合街道环境。这些方法建立在开放地理数据库OpenStreetMap和开源MATSim项目的基础上，促进了可扩展性和可移植性。我们运用这种方法为大曼彻斯特制定与政策相关的无障碍指标。在研究结果中，我们观察到街道层面的环境会导致可达性指标在微观尺度上发生变化，特别是在连通性较差的社区，那里的路线选择有限。我们还观察到，当考虑交通压力时，骑自行车的人比步行的可达性优势大大降低。我们的研究结果支持在研究和实践中进一步采用微尺度建筑环境数据和高分辨率分析方法进行主动出行可达性建模。

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