本次给大家整理的是《Computers, Environment and Urban Systems》杂志2024年10月第113期的论文的题目和摘要，一共包括13篇SCI论文！
论文1
Can consumer big data reveal often-overlooked urban poverty? Evidence from Guangzhou, China
消费者大数据能否揭示经常被忽视的城市贫困？来自中国广州的证据
【摘要】
In the evolving landscape of poverty research, especially in China, the focus has shifted from eliminating absolute poverty to relieving relative poverty. Although much of the existing studies have begun to use built environment big data, such as remote sensing and street view imagery, to measure poverty, peoples' consumption, an essential indicator of poverty receives less attention. This study delves into the relationship and spatial disparity between poverty measured by consumer big data and multidimensional poverty measured based on the census data. We investigated 1731 communities in Guangzhou as case study regions and combined their residents' mobile phone metadata and spatial cost of living data as the input consumer big data. Then, we constructed Index of Multiple Deprivation (IMD) levels based on the census data and built random forest classification model based on our consumer big data to predict IMD level at community level. The result shows that the predicted poverty of 81.11% communities were generally consistent with the IMD level, indicating that the consumer big data poverty mapping provided a viable poverty measurement from consumer behavior perspective. The SHapley Additive exPlanations' values result shows that Pinduoduo (a low-cost online shopping mobile application) contributes the most to predicted poverty from consumer behavior. For spatial disparities, poverty mapping based on consumer big data is more sensitive to the poverty in suburban developing neighborhoods and affordable housing communities compared with the IMD. The urban poverty mapping based on consumer big data offers a timely portray of communities' socio-economic challenges and consumption-related poverty, and provides support and evidence for accurate urban poverty alleviation strategies.
【摘要翻译】
在中国的贫困研究领域中，随着重点从消除绝对贫困转向缓解相对贫困，研究方向也在不断演变。尽管已有许多研究开始使用建筑环境大数据（如遥感和街景图像）来衡量贫困，但人们的消费——这一贫困的重要指标——却很少受到关注。本研究深入探讨了通过消费者大数据衡量的贫困与基于人口普查数据的多维贫困之间的关系及其空间差异。我们以广州的1731个社区为研究对象，结合其居民的手机元数据和空间生活成本数据作为消费者大数据的输入。随后，我们基于人口普查数据构建了多重剥夺指数（IMD）等级，并基于消费者大数据构建了随机森林分类模型，以预测社区层面的IMD等级。研究结果表明，81.11%的社区的预测贫困与IMD等级总体一致，表明从消费者行为角度进行的消费者大数据贫困映射提供了一种可行的贫困测量方法。SHapley Additive exPlanations（SHAP）值的结果显示，拼多多（一个低成本的线上购物应用）在预测贫困中对消费者行为的贡献最大。在空间差异方面，基于消费者大数据的贫困映射对郊区发展中的社区和经济适用房社区的贫困更为敏感，优于IMD。基于消费者大数据的城市贫困映射及时描绘了社区的社会经济挑战和与消费相关的贫困，为精准的城市贫困缓解策略提供了支持和证据。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102158
【作者信息】
Qingyu Wu, 中山大学地理与规划学院，广州510275，中国；广东省城市化与地理模拟重点实验室，中山大学，广州510275，中国
Yuquan Zhou, 南加州大学索尔普莱斯公共政策学院城市规划与空间分析系，美国加利福尼亚州洛杉矶90089-0626
Yuan Yuan, 中山大学地理与规划学院，广州510275，中国；广东省城市化与地理模拟重点实验室，中山大学，广州510275，中国
Xi Chen, 中山大学地理与规划学院，广州510275，中国；广东省城市化与地理模拟重点实验室，中山大学，广州510275，中国
Huiwen Liu，中山大学地理与规划学院，广州510275，中国；广东省城市化与地理模拟重点实验室，中山大学，广州510275，中国
论文2
Predicting human mobility flows in response to extreme urban floods: A hybrid deep learning model considering spatial heterogeneity
预测极端城市洪水响应中的人类移动流量：考虑空间异质性的混合深度学习模型
【摘要】
Resilient post-disaster recovery is crucial for the long-term sustainable development of modern cities, and in this regard, predicting the unusual flows of human mobility when disasters hit, could offer insights into how emergency responses could be managed to cope with such unexpected shocks more efficiently. For years, many studies have been dedicated to developing various models to predict human movement; however, abnormal human flows caused by large-scale urban disasters, such as urban floods, remain difficult to capture accurately using existing models. In this paper, we propose a spatiotemporal hybrid deep learning model based on a graph convolutional network and long short-term memory with a spatial heterogeneity component. Using 1.32 billion movement records from smartphone users, we applied the model to predict total hourly flows of human mobility in the “7.20” extreme urban flood in Zhengzhou, China. We found that the proposed model can significantly improve the prediction accuracy (i.e., R2from 0.887 to 0.951) for during-disaster flows while maintaining high accuracy for before- and after-disaster flows. We also show that our model outperforms selected mainstream machine learning models in every disaster stage in a set of sensitivity tests, which verifies not only its better performance for predicting both usual and unusual flows but also its robustness. The results underscore the effective role of spatial heterogeneity in predicting human mobility flow in a disaster context. This study offers a novel tool for better depicting human mobility under the impact of urban floods and provides useful insights for decision-makers managing how people move in large-scale disaster emergencies.
【摘要翻译】
灾后韧性恢复对于现代城市的长期可持续发展至关重要。在此背景下，预测灾害发生时异常的人类流动可以为如何更高效地应对突发冲击的应急响应提供有益见解。多年来，许多研究致力于开发各种预测人类移动的模型，但现有模型在准确捕捉由大规模城市灾害（如城市洪水）引发的异常人流方面仍存在困难。本文提出了一种基于图卷积网络和长短期记忆的时空混合深度学习模型，并结合了空间异质性组件。利用来自智能手机用户的13.2亿条移动记录，我们应用该模型预测了中国郑州“7·20”极端城市洪水中的每小时人类流动总量。研究发现，所提出的模型可以显著提高灾中流动的预测精度（即R²从0.887提高到0.951），同时在灾前和灾后流动的预测中也保持了较高的准确性。通过一系列敏感性测试，我们还证明了该模型在每个灾害阶段都优于选定的主流机器学习模型，不仅在预测常规和非常规流动方面表现更好，还验证了其鲁棒性。结果强调了空间异质性在预测灾害背景下人类流动中的有效作用。本研究提供了一种新的工具，更好地描绘城市洪水影响下的人类流动，为决策者管理大规模灾害应急中的人流提供了有价值的见解。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102160
【作者信息】
Junqing Tang, 北京大学深圳研究生院城市规划与设计学院，中国深圳518055，
Jing Wang, 北京大学深圳研究生院城市规划与设计学院，中国深圳518055
Jiaying Li, 北京大学深圳研究生院城市规划与设计学院，中国深圳518055
Pengjun Zhao, 北京大学深圳研究生院城市规划与设计学院，中国深圳518055；北京大学城市与环境学院，中国北京100871
Wei Lyu, 北京大学深圳研究生院城市规划与设计学院，中国深圳518055
Wei Zhai, 德克萨斯大学圣安东尼奥分校Klesse工程与综合设计学院建筑与规划学院，美国德克萨斯州圣安东尼奥78207
Li Yuan, 北京大学深圳研究生院电子与计算机工程学院，中国深圳518055
Li Wan, 剑桥大学土地经济系，英国剑桥CB3 9EP
Chenyu Yang，北京大学深圳研究生院城市规划与设计学院，中国深圳518055
论文3
Does real time experience matter? Comparison of retrospective and in-situ spatial data in participatory mapping
实时体验重要吗？参与式制图中回顾性数据与现场空间数据的比较
【摘要】
Public Participation GIS is a widely used method in research, planning, and many other domains. Approaches to participatory data collection have traditionally taken place retrospectively, whereby a digital mapping platform is used for participants to elucidate their spatial through to and feelings. More recently, enabled by the proliferation of smartphones, data collection has also taken place in-situ, whereby participants report their spatial thoughts and feelings at their current location and time. There has yet to be any investigation into the implications of choice between retrospective and in-situ data collection, nor has there been any investigation into how comparable or compatible datasets collected using these methods might be expected to be. This paper addresses this shortcoming by providing a comparative analysis of retrospective and in-situ data collected in Olomouc, Czech Republic. Through a combination of theoretical, quantitative and qualitative approaches, the differences between the two methods are formalised along with their respective benefits and limitations. We find substantial differences between the results of the two methods, which have implications for methodological decision making. These implications are then examined in detail, providing critical guidance in the design of Public Participation GIS surveys for researchers and practitioners.
【摘要翻译】
公共参与地理信息系统（Public Participation GIS，PPGIS）是研究、规划等众多领域广泛应用的一种方法。传统的参与式数据收集方式通常是回溯性的，使用数字制图平台让参与者表达其对空间的想法和感受。最近，随着智能手机的普及，数据收集也开始在现场进行，参与者在当前位置和时间即时报告其空间想法和感受。然而，关于回溯性和现场数据收集方式的选择及其影响，尚未进行深入探讨，也没有研究探讨这两种方法收集的数据集在可比性或兼容性方面的预期表现。本文通过对捷克共和国奥洛穆茨市的回溯性和现场收集的数据进行比较分析，弥补了这一不足。通过理论、定量和定性方法的结合，本文系统化了两种方法之间的差异及其各自的优点和局限性。研究发现，两种方法的结果存在显著差异，这对方法选择有重要影响。本文详细探讨了这些影响，为研究人员和实践者设计PPGIS调查提供了关键指导。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102159
【作者信息】
Lucia Brisudová, 捷克共和国奥洛穆茨帕拉茨基大学地理系
Jonathan J. Huck, 英国曼彻斯特大学地理系
Reka Solymosi，英国曼彻斯特大学犯罪学系
论文4
LCZ-based city-wide solar radiation potential analysis by coupling physical modeling, machine learning, and 3D buildings
基于LCZ的城市范围太阳辐射潜力分析：结合物理建模、机器学习和3D建筑物
【摘要】
Addressing climate change and urban energy problems is a great challenge. Building Integrated Photovoltaics (BIPV) plays a pivotal role in energy conservation and carbon emission reduction. However, traditional approaches to assessing solar radiation on buildings with physical models are computing-intensive and time-consuming. This study presents a hybrid approach by integrating physical model-based solar radiation calculation and machine learning (ML) for city-wide building solar radiation potential (SRP) analysis. By considering urban morphology, land cover, and meteorological characteristics, local climate zones (LCZs) are classified. The SRP of representative LCZs is precisely evaluated using computing-intensive physical models integrated with 3D building models. A ML model is then developed to effectively predict the SRP of building roofs and facades throughout the city. An experiment was conducted in Shenzhen, China to validate the presented approach. The results demonstrate that Shenzhen has a total annual building solar radiation of 3.28*1011 kwh. Luohu District exhibits the highest SRP density. The LCZ-based analysis highlights that compact low-rise LCZs offer greater SRP for roofs, while compact high-rise LCZs do so for facades. Moreover, BIPV could cut CO2 emission by up to 41.85 million tons annually. Notably, solar PV installation only on rooftops in Shenzhen could meet 87.81% of the city's electricity department's carbon reduction goal. This study provides an alternative for city-wide SRP estimation by combining physical modeling and ML and offers valuable insights for data-driven and model-driven urban planning and management in low-carbon cities.
【摘要翻译】
应对气候变化和城市能源问题是一个巨大的挑战。建筑集成光伏（Building Integrated Photovoltaics, BIPV）在节能和减少碳排放中起着关键作用。然而，传统的通过物理模型评估建筑物太阳辐射的方法计算量大且耗时。本研究提出了一种混合方法，将基于物理模型的太阳辐射计算与机器学习（ML）相结合，用于全市范围内建筑太阳辐射潜力（SRP）分析。通过考虑城市形态、土地覆盖和气象特征，研究对局部气候区（LCZ）进行了分类。采用集成3D建筑模型的计算密集型物理模型对代表性LCZ的SRP进行了精确评估。随后开发了一个ML模型，以有效预测全市建筑屋顶和立面的SRP。本文在中国深圳进行了实验验证。结果表明，深圳市的年建筑太阳辐射总量为3.28*10¹¹千瓦时。罗湖区表现出最高的SRP密度。基于LCZ的分析显示，紧凑型低层LCZ的屋顶SRP较高，而紧凑型高层LCZ则立面SRP较高。此外，BIPV每年可减少最多4185万吨的二氧化碳排放量。值得注意的是，仅在深圳的屋顶安装太阳能光伏系统就可以实现城市电力部门87.81%的碳减排目标。该研究通过结合物理建模和ML为全市范围内的SRP估算提供了另一种选择，并为低碳城市中的数据驱动和模型驱动的城市规划和管理提供了有价值的见解。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102176
【作者信息】
Xiana Chen, 广东省城市信息学重点实验室, 深圳大学, 深圳 518060, 中国；深圳空间信息智能感知与服务重点实验室, 深圳大学建筑与城市规划学院城市信息学系, 深圳 518060, 中国
Wei Tu, 广东省城市信息学重点实验室, 深圳大学, 深圳 518060, 中国；深圳空间信息智能感知与服务重点实验室, 深圳大学建筑与城市规划学院城市信息学系, 深圳 518060, 中国；粤港澳大湾区智能城市联合实验室, 深圳大学, 深圳 518060, 中国；大湾区地理环境监测重点实验室 (自然资源部), 深圳 518060, 中国
Junxian Yu, 广东省城市信息学重点实验室, 深圳大学, 深圳 518060, 中国；深圳空间信息智能感知与服务重点实验室, 深圳大学建筑与城市规划学院城市信息学系, 深圳 518060, 中国
Rui Cao, 城市治理与设计组, 香港科技大学(广州), 广州, 中国
Shengao Yi, 城市与区域规划系, 宾夕法尼亚大学, 费城, PA 19104, 美国
Qingquan Li，广东省城市信息学重点实验室, 深圳大学, 深圳 518060, 中国；深圳空间信息智能感知与服务重点实验室, 深圳大学建筑与城市规划学院城市信息学系, 深圳 518060, 中国；大湾区地理环境监测重点实验室 (自然资源部), 深圳 518060, 中国；广东省人工智能与数字经济实验室 (深圳), 深圳 518107, 中国
论文5
Large-scale integration of remotely sensed and GIS road networks: A full image-vector conflation approach based on optimization and deep learning
大规模集成遥感和GIS道路网络：基于优化和深度学习的全图像-矢量融合方法
【摘要】
Road networks play an important role in the sustainable development of human society. Conventionally, there are two sources of road data acquisition: road extraction from Remote Sensing (RS) imagery and GIS based map production. Each method has its limitations. The RS road extraction methods are primarily raster-based and the extracted roads are not directly usable in GIS due to their fragmented and noisy nature, while vector-based methods cannot utilize rich raster information. Further more, the vector and raster data can have discrepancies for various reasons. Efficient road data production requires an image-vector conflation process that can match and combine raster and vector-based road data automatically.In this study, we propose a full image-vector conflation framework that directly integrates image and vector road data by appropriately transforming extracted roads from imagery and establishing a match relation between these roads and a credible target GIS road dataset. Based on analyzing these match relations, we propose new metrics for measuring the degree of agreement between the raster and vector road data. The proposed framework combines state-of-the-art deep learning methods for image segmentation and optimization-based models for object matching. We prepared a large-scale high-resolution road dataset covering two counties in Kansas, US. Using trained models from one of the two counties, we were able to extract road segments in the other county and match them to the TIGER/Line roads.Our experiments show that conventional performance metrics for road extraction (e.g. IoU) are insufficient for measuring the degree of agreement between image and vector roads as they are pixel-based and are too sensitive to spatial displacement. Instead, the newly defined vector-based agreement metrics are needed for image-vector conflation purposes. Experiments show that, by the vector-based metrics, nearly 90% of GIS road lengths in the study area were extracted and over 90% of extracted roads matched the target GIS roads. The new framework streamlines raster-vector conflation of roads and can potentially expedite relevant geospatial analyses regarding change detection, disaster monitoring and GIS data production, among others.
【摘要翻译】
道路网络在人类社会的可持续发展中发挥着重要作用。传统上，道路数据的获取主要有两个来源：通过遥感（RS）影像提取道路和基于GIS的地图生产。每种方法都有其局限性。RS道路提取方法主要是基于光栅的，提取的道路由于其碎片化和噪声特性，不能直接在GIS中使用，而基于矢量的方法则无法利用丰富的光栅信息。此外，矢量和光栅数据可能由于各种原因存在差异。高效的道路数据生产需要一个影像-矢量融合过程，能够自动匹配和组合基于光栅和矢量的道路数据。在本研究中，我们提出了一个完整的影像-矢量融合框架，该框架通过适当地转换提取的影像道路，并建立这些道路与可信的目标GIS道路数据集之间的匹配关系，直接整合影像和矢量道路数据。基于对这些匹配关系的分析，我们提出了用于衡量光栅和矢量道路数据一致性的新指标。该框架结合了最先进的深度学习方法进行影像分割，以及基于优化的模型进行对象匹配。我们准备了一个覆盖美国堪萨斯州两个县的大规模高分辨率道路数据集。利用从两个县中的一个训练的模型，我们能够提取另一个县的道路段，并将其与TIGER/Line道路进行匹配。我们的实验表明，传统的道路提取性能指标（例如IoU）不足以衡量影像和矢量道路之间的一致性，因为它们是基于像素的，并且对空间位移过于敏感。相反，影像-矢量融合需要新的矢量一致性指标。实验表明，使用这些基于矢量的指标，研究区域中近90%的GIS道路长度被提取，且提取的道路中超过90%与目标GIS道路匹配。新的框架简化了道路的光栅-矢量融合，并可能加速与变化检测、灾害监测和GIS数据生产等相关的地理空间分析。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102174
【作者信息】
Zhen Lei, 自动化学院，武汉理工大学，武汉 430070，中国
Ting L. Lei，地理与大气科学系，堪萨斯大学，堪萨斯 66045，美国
论文6
The great equalizer? Mixed effects of social infrastructure on diverse encounters in cities
城市中的“伟大平等者”？社会基础设施对多样化交往的混合影响
【摘要】
Casual encounters with diverse groups of people in urban spaces have been shown to foster social capital and trust, leading to higher quality of life, civic participation, and community resilience to hazards. To promote such diverse encounters and cultivate social ties, policymakers develop social infrastructure sites, such as community centers, parks, and plazas. However, their effects on the diversity of encounters, compared to baseline sites (e.g., grocery stores), have not been fully understood. In this study, we use a large-scale, privacy-enhanced mobility dataset of >120 K anonymized mobile phone users in the Boston area to evaluate the effects of social infrastructure sites on the observed frequencies of inter-income and inter-race encounters. Contrary to our intuition that all social infrastructure sites promote diverse encounters, we find the effects to be mixed and more nuanced. Overall, parks and social businesses promote more inter-income encounters, while community spaces promote more same-income encounters, but each produces opposite effects for inter-race encounters. Parks and community spaces located in low-income neighborhoods were shown to result in higher inter-income and inter-race encounters compared to ordinary sites, respectively, however, their associations were insignificant in high-income areas. These empirical results suggest that the type of social infrastructure and neighborhood traits may alter levels of diverse encounters.
【摘要翻译】
在城市空间中，与不同群体的人进行偶遇被证明能够促进社会资本和信任，从而提高生活质量、推动公民参与以及增强社区抵御灾害的韧性。为了促进这样的多元化遭遇并培养社会联系，政策制定者开发了社会基础设施场所，如社区中心、公园和广场。然而，与基准场所（例如，杂货店）相比，它们对遭遇多样性的影响尚未完全理解。本研究利用波士顿地区超过12万名匿名手机用户的大规模隐私增强移动数据集，评估社会基础设施场所对收入和种族交往频率的影响。与我们直觉上认为所有社会基础设施场所都会促进多样化遭遇的想法相反，我们发现这些影响是混合且更为细致的。总体而言，公园和社会商业促进了更多的跨收入遭遇，而社区空间则促进了更多的同收入遭遇，但在跨种族遭遇方面，它们各自产生了相反的效果。位于低收入社区的公园和社区空间在普通场所中被证明导致了更多的跨收入和跨种族遭遇，然而，在高收入地区，它们的关联并不显著。这些实证结果表明，社会基础设施的类型和社区特征可能会改变多样化遭遇的水平。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102173
【作者信息】
Timothy Fraser, 康奈尔大学系统工程项目，美国纽约州伊萨卡市14850，
Takahiro Yabe, 麻省理工学院数据、系统与社会研究所，美国马萨诸塞州剑桥市02139；纽约大学坦登工程学院技术管理与创新系和城市科学与进展中心，美国纽约布鲁克林11201，
Daniel P. Aldrich, 东北大学公共政策与城市事务学院，美国马萨诸塞州波士顿02115
Esteban Moro，东北大学网络科学研究所，物理系，美国马萨诸塞州波士顿02115；麻省理工学院媒体实验室，美国马萨诸塞州剑桥02139
论文7
Integrating species distribution and piecewise linear regression model to identify functional connectivity thresholds to delimit urban ecological corridors
结合物种分布和分段线性回归模型以识别功能连接性阈值以划定城市生态廊道
【摘要】
Urban ecological corridors are essential for sustainable urban development, but determining their width remains challenging. This paper addresses this issue by focusing on the unique habitat requirements of urban undercanopy bird species. We employ Species Distribution Model to simulate their potential living spaces in Shanghai and quantify their functional connectivity in urban mobility. We then use segmented linear regression models to identify turning points in functional connectivity within different buffer zones, which represent the physical width of the corridor. Our findings show that urban undercanopy birds are less sensitive to human activity and building distribution compared to surface temperature, land cover types, and vegetation canopy height. We also find that conventional linear weighting methods tend to overestimate the impact of environmental factors on undercanopy birds, leading to subtle deviations in corridor path recognition. Finally, we demonstrate that employing segmented linear regression helps to quantify the turning points of functional connectivity for each urban ecological corridor, allowing us to determine their physical width range. This study is the first attempt to quantitatively assess the functional connectivity of urban ecological corridors from the perspective of undercanopy birds and demarcate their extent.
【摘要翻译】
城市生态廊道对可持续城市发展至关重要，但确定其宽度仍然具有挑战性。本文通过关注城市下层鸟类物种的独特栖息地需求来解决这一问题。我们采用物种分布模型（Species Distribution Model）模拟它们在上海的潜在栖息空间，并量化其在城市流动性中的功能连接性。然后，我们使用分段线性回归模型识别不同缓冲区内功能连接性的转折点，这些转折点代表了廊道的物理宽度。我们的研究结果表明，城市下层鸟类对人类活动和建筑分布的敏感性低于对地表温度、土地覆盖类型和植被冠层高度的敏感性。我们还发现，传统的线性加权方法往往高估环境因素对下层鸟类的影响，导致廊道路径识别的细微偏差。最后，我们证明使用分段线性回归有助于量化每个城市生态廊道的功能连接性转折点，从而确定其物理宽度范围。这项研究首次从下层鸟类的角度定量评估城市生态廊道的功能连接性并划定其范围。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102177
【作者信息】
Haoran Yu, 南京林业大学, 景观建筑学院, 南京 210037, 中国
Hanwen Xiao, 天津大学, 土木工程学院, 天津 300072, 中国
Xinchen Gu，天津大学, 土木工程学院, 天津 300072, 中国；中国水利水电科学研究院, 北京 100044, 中国
论文8
Urban streets profiling with coupled spatio-temporal characteristics and topological information from the biking perspective
从骑行视角结合时空特征和拓扑信息的城市街道剖析
【摘要】
Urban street profiling is the spatio-temporal pattern discovery of street-level urban areas, which plays a vital role in understanding urban structures and dynamics. Due to the natural topology and various geographic characteristics on the streets, it is necessary to combine multi-dimensional spatio-temporal information to understand different profiles of streets. This research aims to develop a street profiling framework according to the coupled characteristics of streets. At the start, a bidirected dual graph and a spatial weighted graph embedding method were used to solve the street representation. Then, the street profiles can be extracted by clustering embedding vectors of streets and feature importance analysis. As the case study, we employed the bike trajectories and street view images in Xiamen, China to depict the geographic attributes of streets. The results can reveal nine spatio-temporal street profiles from the biking perspective, including three spatial distribution patterns and two spatial semantic patterns. Urban streets in the study area show a significant hierarchical pattern because of locations and the spatial lags of the biking behaviors. Meanwhile, the spatio-temporal characteristics of biking behaviors are the main factors of street profiles, though the street environment attributes participate in over half the number of profile types. We further evaluated the profiling ability of the proposed framework and the importance of urban street profiles using coupled characteristics. Overall, this study explored the profiling method for coupling static and dynamic characteristics of urban streets. The profiling results also help understand street usage and experiences by bikers, which have a practical value on the human-oriented classification of streets and further urban development from a geographic view.
【摘要翻译】
城市街道剖面分析是街道层面城市区域的时空模式发现，这在理解城市结构和动态方面起着至关重要的作用。由于街道的自然地形和各种地理特征，有必要结合多维时空信息来理解街道的不同剖面。本研究旨在根据街道的耦合特征开发一个街道剖面框架。首先，采用双向双图和空间加权图嵌入方法来解决街道表示问题。然后，通过对街道的嵌入向量进行聚类和特征重要性分析，提取街道剖面。作为案例研究，我们使用了中国厦门的自行车轨迹和街景图像来描绘街道的地理属性。结果显示，从骑行的角度可以揭示九种时空街道剖面，包括三种空间分布模式和两种空间语义模式。研究区域的城市街道表现出显著的层次模式，这是由于位置和骑行行为的空间滞后造成的。同时，骑行行为的时空特征是街道剖面的主要因素，尽管街道环境属性在超过一半的剖面类型中也有所参与。我们进一步评估了所提出框架的剖面能力及其在耦合特征下的城市街道剖面的重要性。总体而言，本研究探索了静态和动态特征耦合的城市街道的剖面方法。剖面结果还有助于理解骑行者对街道的使用和体验，这在从地理角度进行人性化街道分类和进一步城市发展方面具有实际价值。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102180
【作者信息】
Disheng Yi, 资源环境与旅游学院，北京市海淀区西三环北路105号，首都师范大学，邮政编码100048，中国；北京市水资源安全实验室，首都师范大学，北京市邮政编码100048，中国；教育部3D信息采集与应用重点实验室，首都师范大学，北京市邮政编码100048，中国；首都师范大学城市环境过程与数字仿真北京市重点实验室孵化基地，北京市邮政编码100048，中国。
Jing Zhang，资源环境与旅游学院，北京市海淀区西三环北路105号，首都师范大学，邮政编码100048，中国；北京市水资源安全实验室，首都师范大学，北京市邮政编码100048，中国；教育部3D信息采集与应用重点实验室，首都师范大学，北京市邮政编码100048，中国；首都师范大学城市环境过程与数字仿真北京市重点实验室孵化基地，北京市邮政编码100048，中国
论文9
An ontology-based approach for harmonizing metrics in bike network evaluations
基于本体的自行车网络评估指标统一方法
【摘要】
The urgency to decarbonize the transportation sector has accelerated the adoption of micro-mobility solutions, with cycling network development witnessing remarkable growth. Robust and quantitative evaluation frameworks are needed to evaluate the quality of such developments. While a plethora of bike network evaluation approaches exist, their diversity creates issues of interpretability and comparability due to varying metrics and domain-specific terms. We present three contributions to address these challenges. First, we construct a formal ontology, VeloNEMO, that captures key attributes of evaluation metrics for harmonizing bike network evaluation metrics. Second, we generate a machine-readable knowledge base containing these metrics, enabling meta-analyses and resolving some of the existing terminological discrepancies. Third, we propose recommendations for transparent and comparable metric descriptions across various evaluation approaches, illustrated by exploratory metric selection scenarios for a forthcoming bike network evaluation tool. In summary, our research addresses the need for a structured and shared vocabulary for bike network evaluations. This ontology-based approach aims to improve the coherence of evaluation methods as the field of bike network planning continues to evolve, ultimately supporting decision-making for sustainable transportation planning.
【摘要翻译】
为了应对交通运输部门脱碳的紧迫性，微型出行解决方案的采用加速了自行车网络的发展。需要健全和定量的评估框架来评估这些发展的质量。虽然存在大量的自行车网络评估方法，但它们的多样性由于不同的指标和特定领域术语，造成了解释性和可比性的问题。我们提出了三项贡献来应对这些挑战。首先，我们构建了一个正式本体，VeloNEMO，捕捉评估指标的关键属性，以协调自行车网络评估指标。其次，我们生成了一个包含这些指标的机器可读知识库，使得元分析成为可能，并解决了一些现有的术语不一致问题。第三，我们提出了跨各种评估方法的透明和可比的指标描述建议，通过即将推出的自行车网络评估工具的探索性指标选择场景进行了说明。总之，我们的研究解决了自行车网络评估所需的结构化和共享词汇的问题。这种基于本体的方法旨在改善评估方法的一致性，随着自行车网络规划领域的不断发展，最终支持可持续交通规划的决策。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102178
【作者信息】
Ayda Grisiute，瑞士苏黎世联邦理工学院制图与地理信息研究所，8093 苏黎世，瑞士
Nina Wiedemann，瑞士苏黎世联邦理工学院制图与地理信息研究所，8093 苏黎世，瑞士
Pieter Herthogs，，新加坡-ETH中心，未来城市实验室全球项目，CREATE校园，138602 新加坡
Martin Rauba，瑞士苏黎世联邦理工学院制图与地理信息研究所，8093 苏黎世，瑞士
论文10
A physics-guided automated machine learning approach for obtaining surface radiometric temperatures on sunny days based on UAV-derived images基于无人机影像的晴天地表辐射温度获取的物理引导自动化机器学习方法
【摘要】
Urban surface radiometric temperatures, approximate to the surface kinetic temperatures, are predominantly retrieved using satellites or unmanned aerial vehicles (UAVs) and exhibit pronounced spatiotemporal variations. Despite numerous methods ranging from empirical to physical models for obtaining urban microscale surface radiometric temperatures via UAVs, challenges remain given the limited physical significance and substantial professional barriers to method application. Against this background, this study introduces a novel and straightforward approach for acquiring spatially distributed radiometric temperatures on sunny days without understanding the complex radiative transfer process as well as acquiring low-altitude atmospheric parameters. An automated machine learning was employed to train a model capable of efficiently estimating radiometric temperatures. Training and testing datasets were created based on the urban radiative transfer equation, incorporating three independent variables: UAV-measured surface brightness temperature, broadband emissivity, and sky view factor, which collectively represent the diverse thermal environments across different surface characteristics and urban layouts during sunny transitional and summer seasons. The model's accuracy was subsequently confirmed through direct comparisons with radiometric temperatures retrieved from UAV-collected multimodal images and kinetic temperatures synchronously collected on the ground across four periods. The results indicate that AutoGluon achieved high accuracy (MAE: 0.04 K; RMSE: 0.06 K; R2: 0.99). Additional ground measurement validations further demonstrated the model's reliability, with absolute biases on sunlit surfaces maintained within 1.25 K. Given its capability for real-time, high-spatial-resolution mapping of radiometric temperatures (April test: 8.70 cm, July test: 6.89 cm) in urban microscales with considerable heterogeneity, such a method is envisioned to be an effective tool for the dynamic monitoring and management of thermal environments at the microscale level in urban settings.
【摘要翻译】
城市表面辐射温度近似于表面动能温度，主要通过卫星或无人机（UAV）获取，并表现出明显的时空变化。尽管已有多种方法（从经验模型到物理模型）用于通过无人机获得城市微观表面辐射温度，但由于物理意义有限和方法应用的专业壁垒，仍面临许多挑战。在此背景下，本研究提出了一种新颖而简单的方法，用于在晴天获取空间分布的辐射温度，无需理解复杂的辐射传输过程，并可获取低空大气参数。采用自动化机器学习训练模型，以有效估算辐射温度。训练和测试数据集基于城市辐射传输方程创建，包含三个独立变量：无人机测得的表面亮度温度、宽波段发射率和天空视野因子，这些变量共同代表不同表面特征和城市布局在晴天过渡季节和夏季的多样热环境。随后，通过与无人机收集的多模态图像中提取的辐射温度以及在四个时间段内同步收集的地面动能温度进行直接比较，确认了模型的准确性。结果表明，AutoGluon实现了高准确度（MAE：0.04 K；RMSE：0.06 K；R²：0.99）。额外的地面测量验证进一步证明了模型的可靠性，阳光照射下的绝对偏差保持在1.25 K以内。考虑到其在城市微观尺度上对辐射温度（四月测试：8.70 cm，七月测试：6.89 cm）的实时高空间分辨率映射能力，该方法被设想为有效工具，用于动态监测和管理城市环境中的热环境。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102175
【作者信息】
Xue Zhong, 广东工业大学建筑系，亚热带建筑与城市科学国家重点实验室，广州510640，中国
Lihua Zhao, 广东工业大学建筑系，亚热带建筑与城市科学国家重点实验室，广州510640，中国
Peng Ren, 广东工业大学建筑系，亚热带建筑与城市科学国家重点实验室，广州510640，中国
Xiang Zhang, 慕尼黑工业大学生命科学学院，战略景观规划与管理，Emil-Ramann-Str. 6，Freising 85354，德国
Jie Wang，西华师范大学地理科学学院，南充637009，中国
论文11
Disparities in public transport accessibility in London from 2011 to 2021
2011年至2021年伦敦公共交通可达性差异
【摘要】
Addressing urban inequalities has become a pressing concern on both the global sustainable development agenda and for local policy. Improving public transport services is seen as an important area where local governments can exert influence and potentially help reduce inequalities. Existing measures of accessibility used to inform decision-making for public transport infrastructure in London show spatial disparities, yet there is a gap in understanding how these disparities vary across demographic groups and how they evolve over time—whether they are improving or worsening. In this study, we investigate the distribution of public transport accessibility based on ethnicity and income deprivation in London over the past decade. We used data from the Census 2011 and 2021 for area-level ethnicity characteristics, English Indices of Deprivation for income deprivation in 2011 and 2019, and public transport accessibility metrics from Transport for London for 2010 and 2023, all at the small area level using lower super output areas (LSOAs) in Greater London. We found that, on average, public transport accessibility in London has increased over the past decade, with 78% of LSOAs experiencing improvements. Public transport accessibility in London showed an unequal distribution in cross-sectional analyses. Lower income neighbourhoods had poorer accessibility to public transportation in 2011 and 2023 after controlling for car-ownership and population density. These disparities were particularly pronounced for underground accessibility. Temporal analyses revealed that existing inequalities with respect to income deprivation and ethnicity are generally not improving. While wealthier groups benefited most from London Underground service improvements; lower income groups benefited more from bus service improvements. We also found that car ownership levels declined in areas with substantial increases to public transport accessibility and major housing developments, but not in those with moderate improvements.
【摘要翻译】
解决城市不平等问题已成为全球可持续发展议程和地方政策的紧迫关注点。改善公共交通服务被视为地方政府可以发挥影响力并可能帮助减少不平等的重要领域。现有用于指导伦敦公共交通基础设施决策的可达性测量显示出空间差异，但在理解这些差异如何在不同人口群体之间变化以及如何随时间演变——无论是改善还是恶化——方面仍然存在差距。在本研究中，我们调查了过去十年中伦敦公共交通可达性在种族和收入贫困方面的分布。我们使用了2011年和2021年人口普查的数据来获取区域级的种族特征，2011年和2019年的英国贫困指数数据来衡量收入贫困，以及来自伦敦交通局的2010年和2023年的公共交通可达性指标，所有数据均在大伦敦地区的小区域（低超级输出区，LSOAs）级别进行分析。我们发现，平均而言，伦敦的公共交通可达性在过去十年中有所增加，78%的LSOAs经历了改善。在横向分析中，伦敦的公共交通可达性表现出不均衡的分布。经过控制汽车拥有量和人口密度后，低收入社区在2011年和2023年均表现出较差的公共交通可达性。这些差异在地铁可达性方面尤其明显。时间序列分析显示，与收入贫困和种族相关的现有不平等通常没有改善。尽管更富裕的群体从伦敦地铁服务的改善中受益最多，但低收入群体在公共汽车服务改善方面受益更多。我们还发现，在公共交通可达性大幅提高和主要住房开发的地区，汽车拥有水平下降，但在改善幅度适中的地区则没有这种现象。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102169
【作者信息】
Yuxin Nie, 高级空间分析中心 (CASA), 伦敦大学学院, 伦敦 W1T 4TJ, 英国
Shivani Bhatnagar,伦敦交通局 (TfL), 伦敦 E20 1JN, 英国
Duncan Smith, 高级空间分析中心 (CASA), 伦敦大学学院, 伦敦 W1T 4TJ, 英国
Esra Suel，高级空间分析中心 (CASA), 伦敦大学学院, 伦敦 W1T 4TJ, 英国
论文12
‘Green or short: choose one’ - A comparison of walking accessibility and greenery in 43 European cities
“绿色或近：择其一”——对43个欧洲城市步行可达性与绿化的比较
【摘要】
Promoting environmentally and socially sustainable urban mobility is crucial for cities, with urban greening emerging as a key strategy. Contact with nature during travel not only enhances well-being but also promotes sustainable behaviour. However, the availability of travel greenery varies, and only recently have new datasets and computational approaches made it possible to compare the conditions in the distribution of travel greenery within and between cities quantitatively. In this study of 43 large European cities, we undertook a comparative analysis of travel greenery availability by using high-resolution spatial data and daily school trips as a marker of a daily travel need. By recognising walking accessibility as the most sustainable and equally available mode of transportation, we first estimated the proportion of the population residing within walking distance to upper secondary schools. Second, we associated the detailed school routes with monthly green cover data and compared the spatial variation in travel greenery availability between European cities, taking seasonal variation into account. Lastly, we analysed spatial inequalities of travel greenery availability within the study cities using the Gini index, the Kolm-Pollak equally-distributed equivalent (EDE) index and Moran's I. Our findings reveal a consistent negative association between accessibility and green cover implying a trade-off between access and greenery. We found large variations between European cities in the walking accessibility of schools, ranging from 44% to 98% of the population being within 1600 m of their school. Moreover, our results show substantial within-city disparities in travel greenery availability in large European cities. We demonstrated methodologically the importance of considering seasonal variations when measuring greenery availability. Our study offers empirical evidence of urban greenery availability from a mobility-focused perspective. It provides a novel understanding with which to support researchers and planners in affording the benefits of nature to more people as they travel.
【摘要翻译】
推动环保和社会可持续的城市交通对城市至关重要，而城市绿化逐渐成为一项关键策略。在旅行过程中与自然接触不仅能提升幸福感，还能促进可持续行为。然而，旅行中的绿化可用性存在差异，直到最近，新的数据集和计算方法才使得定量比较城市内部和城市之间的旅行绿化分布状况成为可能。在对43个大型欧洲城市的研究中，我们利用高分辨率空间数据和日常上学旅行作为日常出行需求的标志，进行了旅行绿化可用性的比较分析。我们首先将步行可达性视为最可持续且可平等获取的交通方式，估算了居住在步行距离内的上中学人口比例。其次，我们将详细的上学路线与每月的绿化覆盖数据关联起来，比较了欧洲城市之间旅行绿化可用性的空间变化，并考虑了季节性变化。最后，我们使用基尼指数、Kolm-Pollak均等分配等值（EDE）指数和莫兰指数分析了研究城市内旅行绿化可用性的空间不平等。我们的研究结果揭示了可达性与绿化覆盖之间存在一致的负相关关系，这暗示了可达性与绿化之间的权衡。我们发现，欧洲城市之间学校的步行可达性差异显著，从44%到98%的人口可在1600米内到达学校。此外，结果还显示，大型欧洲城市内旅行绿化可用性存在显著差异。我们在方法论上证明了在测量绿化可用性时考虑季节性变化的重要性。我们的研究从以出行为中心的角度提供了城市绿化可用性的实证证据，为研究人员和规划者提供了一种新的理解，旨在使更多人能够在旅行时享受到自然的益处。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102168
【作者信息】
Elias Willberg, 数字地理实验室, 地球科学与地理系, 赫尔辛基大学, 赫尔辛基, 芬兰；赫尔辛基可持续发展科学研究所, 城市与区域研究所, 赫尔辛基大学, 赫尔辛基, 芬兰
Christoph Fink, 数字地理实验室, 地球科学与地理系, 赫尔辛基大学, 赫尔辛基, 芬兰；赫尔辛基可持续发展科学研究所, 城市与区域研究所, 赫尔辛基大学, 赫尔辛基, 芬兰
Robert Klein, 数字地理实验室, 地球科学与地理系, 赫尔辛基大学, 赫尔辛基, 芬兰
Roope Heinonen, 数字地理实验室, 地球科学与地理系, 赫尔辛基大学, 赫尔辛基, 芬兰
Tuuli Toivonen，数字地理实验室, 地球科学与地理系, 赫尔辛基大学, 赫尔辛基, 芬兰；赫尔辛基可持续发展科学研究所, 城市与区域研究所, 赫尔辛基大学, 赫尔辛基, 芬兰
论文13
Developing two-dimensional indicators of transport demand and supply to promote sustainable transportation equity
开发交通需求与供给的二维指标以促进可持续交通公平
【摘要】
Inadequate supply of transport infrastructure is often seen as a barrier to a sustainable future for cities globally. Such barriers often perpetuate significant inequalities in who can and who cannot benefit from sustainable transport opportunities, and as a result there is momentum for transformative urban planning to promote sustainable transportation equity. This study introduces a new set of two-dimensional indicators, merging elements of supply and demand, to identify barriers and imbalances in sustainable transport equity. The accessibility indicators, which are generated for bus, rail, and cycle infrastructure, consider the proximity of administrative areas to good quality transport infrastructure, as well as mode-specific demand, to clearly identify areas where the supply of infrastructure is inadequate to support local populations. We present a policy case study for Liverpool City Region, which demonstrates how these indicators can be used in an analytical framework to support transformative urban planning in long-term. In particular, the indicators reveal policy priority areas where demand for sustainable transport is greater than supply, as well as neighbourhoods where multiple transport inequalities are intersecting spatially, highlighting the need for specific types of infrastructure investment to promote sustainable transport equity (e.g. more frequent services, additional cycle paths). Our framework lays the foundations for improved decision-making in urban systems, through development of mode-specific sustainable transport indicators at small area levels, which harmonise elements of supply and demand for the first time.
【摘要翻译】
交通基础设施供应不足通常被视为全球城市可持续未来的障碍。这些障碍常常加剧了谁能受益于可持续交通机会和谁不能受益之间的显著不平等，因此推动变革性城市规划以促进可持续交通公平的势头不断增强。本研究引入了一套新的二维指标，融合了供需元素，以识别可持续交通公平中的障碍和不平衡。这些可及性指标是针对公交、铁路和自行车基础设施生成的，考虑了行政区域与优质交通基础设施的接近程度以及特定模式的需求，以明确识别基础设施供应不足以支持当地人口的区域。我们为利物浦城市地区提供了一个政策案例研究，展示了这些指标如何在分析框架中使用，以支持长期的变革性城市规划。特别是，这些指标揭示了可持续交通需求大于供应的政策优先区域，以及多个交通不平等交叉的邻里，强调了进行特定类型基础设施投资以促进可持续交通公平的必要性（例如，更频繁的服务、更多的自行车道）。我们的框架为改善城市系统中的决策奠定了基础，通过在小区域层面开发特定模式的可持续交通指标，首次协调了供需元素。
【doi】
https://doi.org/10.1016/j.compenvurbsys.2024.102179
【作者信息】
Patrick Ballantyne, 利物浦大学地理与规划系，罗克斯比大楼，利物浦，L69 7ZT，英国
Gabriele Filomena, 利物浦大学地理与规划系，罗克斯比大楼，利物浦，L69 7ZT，英国
Francisco Rowe, 利物浦大学地理与规划系，罗克斯比大楼，利物浦，L69 7ZT，英国
Alex Singleton，利物浦大学地理与规划系，罗克斯比大楼，利物浦，L69 7ZT，英国
