本次给大家整理的是《Environment and Planning B: Urban Analytics and City Science》杂志2024年2月第51卷第2期的论文的题目和摘要，一共包括17篇SCI论文！
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The innovative role of cities in solving global problems with local solutions
城市在利用地方解决方案解决全球问题方面的创新作用
The impacts of climate change are being felt around the world, whether through increased flooding and more intense and frequent storms, wildfires that encroach on inhabited areas or more pronounced heat waves that are intensifying urban heat island effects in cities. With almost 70% of the world’s population projected to become city dwellers by 2050 (UN-Habitat, 2022), we will be living in a much warmer and highly urbanized environment in the near future. Yet despite increasing evidence of the need to act quickly, real action at a collective international level remains slow. Although progress was made at the recent United Nations Climate Change Conference to the Parties (COP28) in Dubai, such as the Global Stocktake, climate financing, the Loss and Damage Fund, and recognition of climate risks to food security and agriculture, COP28 also highlighted the disconnect between the significant transformations that are urgently required and the contradictory and competing actions and interests of national and international actors (Aryal et al., 2023).世界各地都感受到了气候变化的影响，无论是通过加剧的洪水、更猛烈和更频繁的风暴、侵占有人居住地区的野火，还是日益加剧的城市热岛效应。到2050年，几乎70%的世界人口预计将成为城市居民（联合国人居署，2022），在不久的将来，我们将生活在一个更加温暖和高度城市化的环境中。然而，尽管越来越多的证据表明需要迅速采取行动，但真正的集体国际行动仍然缓慢。尽管在最近的联合国气候变化大会（COP28）上在气候融资、损失和损害基金、粮食安全和农业的气候风险等方面取得了一些进展，但COP28也突显了迫切需要重大变革与国家和国际行为者之间的矛盾和竞争行动及利益之间的脱节（Aryal等人，2023）。
https://doi.org/10.1177/23998083241227294琳达·西，奥地利应用系统分析研究所（IIASA）
Exploring flood mitigation governance by estimating first-floor elevation via deep learning and google street view in coastal Texas
通过深度学习和谷歌街景来估算德克萨斯州沿海的一层标高，探索防洪治理
Flood mitigation governance is critical for coastal regions where flooding has caused considerable damage. Raising the First-Floor Elevation (FFE) above the base flood elevation (BFE) is an effective mitigation measure for buildings with a high risk of flooding. In the U.S., measuring FFE is necessary to obtain an Elevation Certificate (E.C.) for the National Flood Insurance Program (NFIP) and has traditionally required labor-consuming field surveys. However, the advances in computer vision technology have facilitated the handling of large image datasets, leading to new FFE measurement approaches. Taking Galveston Island (including the cities of Galveston and Jamaica Beach) in Coastal Texas as a case study, we explore how these new approaches may inform flood risk management and governance, including how FFE estimates may be combined with BFE estimates from flood inundation probability mapping to model the predicted cost of raising buildings’ FFE above their BFE. After establishing the FFE model’s accuracy by comparing its results with previously validated FFE estimates in three districts of Galveston, we generalize the workflow to building footprints across Galveston Island. By combining the FFE data derived from our workflow with multidimensional building information, we further analyze the future flood control and post-disaster maintenance strategies. Our findings present valuable data collection paradigms and methodological concepts that inform flood governance for Galveston Island. The proposed workflow can be extended to flood management and research for other vulnerable coastal communities.洪水缓解治理对于洪水造成相当大破坏的沿海地区至关重要。将一层标高(FFE)提高到基本洪水标高(BFE)以上是一种有效的缓解洪水风险的措施。在美国，测量FFE对于获得国家洪水保险计划(NFIP)的高程证书(E.C.)是必要的，并且传统上需要耗费人力的实地调查。然而，计算机视觉技术的进步促进了大型图像数据集的处理，导致了新的FFE测量方法。以德克萨斯州沿海的加尔维斯顿岛(包括加尔维斯顿市和牙买加海滩市)为例，我们探讨了这些新方法如何为洪水风险管理和治理提供信息，包括如何将FFE估算与洪水淹没概率图的BFE估算相结合，以模拟将建筑物的FFE提高到其BFE以上的预测成本。通过将其结果与加尔维斯顿三个地区先前验证的FFE估计进行比较，建立了FFE模型的准确性之后，我们将工作流程推广到加尔维斯顿岛的足迹建设。通过将从我们的工作流程中获得的FFE数据与多维建筑信息相结合，我们进一步分析了未来的洪水控制和灾后维护策略。我们的研究结果为加尔维斯顿岛的洪水治理提供了有价值的数据收集范例和方法概念。提出的工作流程可以扩展到其他脆弱的沿海社区的洪水管理和研究。
https://doi.org/10.1177/23998083231175681Xinyue Ye，美国德州农工大学景观建筑与城市规划系哈罗德·l·亚当斯特聘教授、地理空间科学、应用与技术中心主任。他的研究专长是人类动力学和城市信息学。
Is national border weakening in technology space? Analysis of inter-urban hierarchy with Chinese patent licensing data
国家边界在技术空间上正在弱化吗?基于中国专利许可数据的城市间层级分析The literature on the diffusion of innovation from the 1970s has found that a domestic inter-urban hierarchy was the most common conduit for the innovation diffusion. Has this hierarchy become obsolete in today’s globalized economy? As less-developed cities within a developing country absorb technological innovation directly from overseas, is the nationality of cities becoming less important? Contemporary economic geography literature tends to answer these questions in the affirmative. This study challenges that resounding yes. Through our analysis of Chinese patent licensing data, we find evidence not only for the survival but also for the reinforcement of the domestic inter-urban hierarchy. While it is true that the number of cities licensing patents to import technology from overseas has been increasing, it is being outmatched by the domestic patent licensing from the top-tier cities within China. This development demonstrates that the role of the nation as a spatial unit of knowledge production and application has remained constant throughout, even as the technological level of its cities has improved under the increasing globalization of the national economy.20世纪70年代以来关于创新扩散的文献发现，国内城市间层级是创新扩散最常见的渠道。这种等级制度在今天的全球化经济中已经过时了吗?当发展中国家的欠发达城市直接从海外吸收技术创新时，城市的国籍是否变得不那么重要了?当代经济地理学文献倾向于肯定地回答这些问题。这项研究挑战了这个响亮的肯定答案。通过对中国专利许可数据的分析，我们发现国内城市间层级不仅存在生存，而且存在强化的证据。虽然从海外进口技术的专利许可城市数量确实在增加，但中国一线城市的国内专利许可数量正在超过这些城市。这一发展表明，即使在国民经济日益全球化的情况下，其城市的技术水平有所提高，但国家作为知识生产和应用的空间单位的作用始终保持不变。
https://doi.org/10.1177/23998083231168871Jung Won Sonn，研究集中于区域经济发展的两个主题:技术创新的城市和区域层面，以及东亚经济体国家领土规划的政治分析。他的工作得到了利华休姆信托基金、玛丽居里奖学金、经济和社会研究委员会、韩国国立研究财团等机构的支持。此外，他还担任《国际城市科学杂志》的编辑。
The effect of the perceptible built environment on pedestrians’ walking behaviors in commercial districts: Evidence from Hong Kong
商业区内可感知建筑环境对行人步行行为的影响:来自香港的证据
In order to structure an efficient and comfortable commercial district for pedestrians, we need to understand the interaction between pedestrian walking behavior and the complex elements of the built environment. Previous studies have focused on people’s activities in the context of the neighborhood rather than the commercial district. This study investigates the potential associations between multi-dimensional environmental factors and pedestrians under various temporal distributions in a densely populated commercial district. Multi-source urban data and semantic segmentation technics have been adopted to measure the built environmental quality from four classic dimensions of urban design, and combining the observations of pedestrian volumes of representative streets in the commercial district, we assess the relationship between the two at different times on the basis of a generalized linear model (GLM). The analytical results identify that the Morphology, Visual perception, Function, and Street configuration features of the commercial environment have a significant impact on walking activity, and temporal differences exist. The findings highlight the importance of built environment quality to pedestrians and street attractiveness, and inform designers, stakeholders, and municipalities on the revitalization of traditional commercial districts.为了构建一个高效舒适的步行商业区，我们需要了解行人步行行为与建筑环境的复杂元素之间的相互作用。以前的研究关注的是人们在社区背景下的活动，而不是商业区。本研究探讨了人口密集商业区在不同时间分布下的多维环境因素与行人的潜在关联。采用多源城市数据和语义分割技术，从城市设计的四个经典维度对建成环境质量进行测度，并结合对商业区代表性街道行人量的观测，在广义线性模型(GLM)的基础上，评估两者在不同时间的关系。分析结果表明，商业环境的形态特征、视觉感知特征、功能特征和街道配置特征对步行活动有显著影响，且存在时间差异。研究结果强调了建筑环境质量对行人和街道吸引力的重要性，并为设计师、利益相关者和市政当局提供了振兴传统商业区的信息。
https://doi.org/10.1177/23998083231177699Chendi Yang，香港城市大学建筑及土木工程系博士研究生。主要研究方向为建筑环境、空间分析、人类行为、城市分析。
Intersectional approach of everyday geography
日常地理学的交集方法
Hour-by-hour variations in spatial distribution of gender, age and social class within cities remain poorly explored and combined in the segregation literature mainly centred on home places from a single social dimension. Taking advantage of 49 mobility surveys compiled together (385,000 respondents and 1,711,000 trips) and covering 60% of France’s population, we consider variations in hourly populations of 2572 districts after disaggregating population across gender, age and education level. We first isolate five district hourly profiles (two ‘daytime attractive’, two ‘nighttime attractive’ and one more ‘stable’) with very unequal distributions according to urban gradient but also to social groups. We then explore the intersectional forms of these everyday geographies. Taking as reference the dominant groups (men, middle-age and high educated people) known as concentrating hegemonic power and capital, we analyze specifically whether district hourly profiles of dominant groups diverge from those of the others groups. It is especially in the areas exhibiting strong increase or strong decrease of ambient population during the day that district hourly profiles not only combine the largest dissimilarities all together across gender, age and education level but are also widely more synchronous between dominant groups than between non-dominant groups (women, elderly and low-educated people). These intersectional patterns shed new light on areas where peers are synchronously located over the 24-hour period and thus potentially in better position to interact and to defend their common interests.在城市中，按性别、年龄和社会阶层划分的空间分布的逐小时变化仍然很少被探索，在隔离文献中，主要集中在单一的社会维度上的家庭住所。利用49项流动性调查（包括385,000名受访者和1,711,000次出行）并覆盖了法国人口的60%，我们考虑了2572个地区的逐小时人口变化情况，将人口按性别、年龄和教育水平进行分解。我们首先分离出五个地区的逐小时特征（两个“白天有吸引力”，两个“晚上有吸引力”和一个“稳定”），根据城市梯度和社会群体，这些特征分布极不平等。然后我们探索这些日常地理的交集形式。以被称为集中的霸权力量和资本的主导群体（男性、中年和高学历人群）为参考，我们特别分析主导群体的地区逐小时特征是否与非主导群体的特征不同。特别是在白天人口数量大幅增加或减少的地区，主导群体的地区逐小时特征不仅在性别、年龄和教育水平上的差异最大，而且主导群体之间的同步性远大于非主导群体之间的同步性（女性、老年人和低学历人群）。这些交集模式揭示了24小时期间同龄人同步存在的地区，从而有可能更好地互动和捍卫共同利益。
https://doi.org/10.1177/23998083231174025朱莉·瓦列尔（Julie Vallée）是一位地理学家，在法国国家科学研究中心（CNRS）地理-城市实验室担任高级研究员。她的研究主要关注人们的日常流动和活动空间、城市隔离、邻里效应以及基于场所的社会不平等机制，特别是在健康方面。她是Mobiliscope（www.mobiliscope.cnrs.fr）的负责人——这是一个开放、互动和不断发展的地图平台，揭示了不同国家城市区域内的每小时人口动态变化。
马克西姆·勒诺曼（Maxime Lenormand）是法国南部蒙彼利埃市TETIS实验室的永久成员，在法国农业科学院（INRAE）从事空间分析和空间建模研究，并担任研究助理。加入INRAE之前，他在位于马略卡岛帕尔马的IFISC研究实验室担任博士后研究员。他拥有计算机科学的博士学位和实用数学的硕士学位。他的研究兴趣集中在大数据分析和多学科背景下复杂空间系统的建模。Development and evaluation of probabilistic forecasting methods for small area populations
小范围人口概率预报方法的开发与评估
Planning and development decisions in both the government and business sectors often require small area population forecasts. Unfortunately, current methods often produce forecasts that are inaccurate, particularly for remote areas and those with smaller populations. Such inaccuracy necessitates the development and evaluation of methods to forecast and communicate forecast uncertainty, however, little research has been conducted in this domain for small area populations. In this paper, we evaluate a set of probabilistic forecasting methods which include Autoregressive integrated moving average, Exponential Smoothing, THETA, LightGBM and XGBOOST, to produce point forecasts and 80% prediction intervals for Australian SA2 small area populations. We also investigate methods to combine the intervals to produce ensemble forecasts. Our results show that individual probabilistic methods generally produce prediction intervals which underestimate forecast uncertainty. Combining forecasts improves the overall accuracy of point forecasts and the coverage of their intervals, however, coverage still tends to be less than the expected 80% for all but the most conservative combination method.政府和商业部门的规划和开发决策通常需要小地区人口预测。不幸的是，目前的方法往往产生不准确的预测，特别是对于偏远地区和人口较小的地区。这种不准确性使得开发并评估用于预测和传达预测不确定性的方法成为必要。然而，对于小地区人口，在这个领域的研究还很少。在这篇文章中，我们评估了一套概率预测方法，包括自回归集成移动平均、指数平滑、THETA、LightGBM和XGBOOST，用于为澳大利亚SA2小地区人口提供点预测和80%的预测区间。我们也研究了如何将这些区间结合起来以产生集合预报的方法。我们的结果表明，单个概率预测方法通常会低估预测的不确定性。将预报结合起来可以提高点预报的整体准确性和区间覆盖率，但除了最保守的组合方法外，其他方法的覆盖率往往不到80%。https://doi.org/10.1177/23998083231178817伊琳娜·格罗斯曼是墨尔本大学墨尔本人口与全球健康学院的博士后研究员。她获得了认知神经科学的博士学位，并获得了电气和计算机系统领域的理学学士和工程学士学位（一流的荣誉）。她目前的研究兴趣是宏观人口动态，特别是人口预测方法。
卡森·班达拉获得了理学学士学位。2015年获得斯里兰卡科伦坡大学计算机学院计算机科学荣誉学位，2020年获得澳大利亚莫纳什大学计算机科学博士学位。他目前在澳大利亚能源公司的预测分析分析师和澳大利亚墨尔本大学墨尔本数据科学中心的名誉研究员。他的研究兴趣包括大数据、深度神经网络和时间序列预测。汤姆·威尔逊是墨尔本大学墨尔本人口与全球健康学院的首席研究员。他目前的研究兴趣是人口预测、移民分析、间接估计、家庭建模、老年人口、区域和当地人口变化、土著人口统计和LGBTQ人口统计。迈克尔·柯利是墨尔本数据科学中心的联席主任，也是墨尔本大学计算和信息系统学院的教授。他目前的研究兴趣包括人工智能、机器学习技术和博弈论。
A visibility-based approach to manage the vertical urban development and maintain visual sustainability of urban mountain landscapes: A case of Mufu Mountain in Nanjing, China
基于可见性的城市垂直发展管理与城市山地景观视觉可持续性——以南京木府山为例
China has experienced a continuous population increase in urban areas over the last few decades with limited land for construction, which has prompted upward growth in the urban environment. Rapid urbanization has encroached on mountain landscapes and deteriorated the visual landscape in different parts of China. This study aims to investigate and analyze the proper balance between visual landscape protection of urban mountains and vertical urban development using a visibility-based method. An interactive and quantitative method was developed in this research using multiple digital 2D and 3D platforms based on the specification of prohibited spaces for constructive expansion in building height control. A metropolitan area near Mufu Mountain in Nanjing, China, was selected as a case study to implement the proposed method and simulate multiple vertical urban development scenarios. According to the comparison of different scenarios, there is a better building height layout to simultaneously satisfy the requirement of sustaining the Mufu mountain’s visibility and the construction capacity proposed by the documented plan. Two polynomial models were generated to quantitatively investigate the relationship between the protection of mountain landscapes and vertical urban development and served as a reference basis for urban planners to formulate the construction volume control strategy around Mufu Mountain. The proposed method in this study can help planners and urban managers to seek an appropriate approach to control building heights and achieve visual sustainability.在过去的几十年里，中国城市地区的人口持续增长，而建设用地有限，这促使城市环境向上增长。快速城市化对中国各地山地景观的侵蚀和视觉景观的恶化。本研究旨在运用基于可视性的方法，探讨和分析城市山地视觉景观保护与垂直城市发展之间的适当平衡。基于建筑高度控制中建设性扩展空间的规范，本研究利用多个数字二维和三维平台开发了一种交互式定量方法。以中国南京木府山附近的一个大都市区为例，实施所提出的方法并模拟多个垂直城市发展情景。通过对不同方案的比较，得出了较好的建筑高度布局方案，可以同时满足保持木浮山能见度的要求和文件方案提出的建筑承载力。通过生成两个多项式模型，定量考察山地景观保护与城市垂直发展的关系，为城市规划者制定木浮山周边建设体量控制策略提供参考依据。本研究提出的方法可以帮助规划者和城市管理者寻求适当的方法来控制建筑高度，实现视觉上的可持续性。
https://doi.org/10.1177/23998083231177058Guanting Zhang，现任南京工业大学建筑学院讲师。她于2021年在中国东南大学获得博士学位。主要研究方向为视觉景观，特别是城市自然景观的视觉特征与视觉管理;基于点云的城市空间分析，尤其是城市开放绿地城市公共设计，尤其是景观设计与评价。
Estimating household demand for transit-oriented development: A two-stage hedonic analysis in Kitchener-Waterloo, Canada
估计家庭对交通导向发展的需求:加拿大基奇纳-滑铁卢的两阶段享乐分析
Interest in mass transit investment and transit-oriented development (TOD) is growing as a way to promote smart growth. These investments and policy changes may imply new housing demands, which are not well understood. Using Kitchener-Waterloo, Canada, as a case study, we address the following questions: (1) Do households in this mid-sized region show preferences for TOD neighborhoods? How do preferences for transit accessibility vary across space? (2) What household characteristics are associated with the demand for housing and neighborhood characteristics? With a combined dataset of household survey and housing transactions, we present a novel application of the two-stage hedonic model to understand the housing demand structure impacted by transit policies. This study provides evidence of demand for TOD and LRT accessibility by households with a range of socio-demographics. We thus recommend the region build complete TODs to satisfy a variety of housing needs.作为促进智能增长的一种方式，人们对公共交通投资和公交导向发展(TOD)越来越感兴趣。这些投资和政策变化可能意味着新的住房需求，而这些需求尚未得到很好的理解。以加拿大的基奇纳-滑铁卢为例，我们解决了以下问题:(1)这个中等规模地区的家庭是否对TOD社区有偏好?不同空间对交通可达性的偏好有何不同?(2)哪些家庭特征与住房需求和邻里特征相关?本文结合住户调查和住房交易数据，提出了一种新的两阶段享乐模型应用于理解受交通政策影响的住房需求结构。本研究提供了家庭对TOD和LRT可达性需求的证据，这些家庭具有一系列的社会人口统计学特征。因此，我们建议该地区建立完整的tod，以满足各种住房需求。
https://doi.org/10.1177/23998083231180610Yu Huang，南京大学地理与海洋科学学院副研究员。她在滑铁卢大学获得城市规划博士学位。她目前的研究兴趣包括公共交通导向发展(TOD)，公共交通诱导的中产阶级化，土地利用和交通的相互作用，以及基于主体的建模。
Identifying sinks and sources of human flows: A new approach to characterizing urban structures
识别人流的接收地和来源地：一种描述城市结构的新方法
Human flow data are rich behavioral data relevant to people’s decision-making regarding where to live, work, go shopping, etc., and provide vital information for identifying city centers. However, it is not as easy to understand massive relational data, and datasets have often been reduced merely to the statistics of trip counts at destinations, discarding relational information from origin to destination. In this study, we propose an alternative center identification method based on human mobility data. This method extracts the scalar potential field of human trips based on combinatorial Hodge theory. It detects not only statistically significant attractive locations as the sinks of human trips but also significant origins as the sources of trips. As a case study, we identify the sinks and sources of commuting and shopping trips in the Tokyo metropolitan area. This aim-specific analysis leads to a combinatorial classification of city centers based on the distinct aspects of human mobility. The proposed method can be applied to other mobility datasets with relevant properties and helps us examine the complex spatial structures in contemporary metropolitan areas from the multiple perspectives of human mobility.人流数据是人们生活、工作、购物等决策行为相关的丰富行为数据，为识别城市中心提供了关键信息。然而，理解大规模关系数据并非易事，往往只是简单地将数据降维到目的地的出行统计数据，忽略了从起点到终点的关系信息。本研究提出了一种基于人类移动数据的中心识别替代方法。该方法基于组合霍奇理论提取人类出行标量势场，不仅能检测到具有显著吸引力的统计显著位置作为人流的汇点，还能检测到显著的起点作为出行的源头。作为案例研究，我们识别了东京都市圈通勤和购物出行的人口流动汇点和源头。这种目标导向的分析基于人类移动的多个方面对城市中心进行了组合分类。该方法可以应用于其他具有相关属性的移动数据集，并帮助我们从人类移动的多个角度考察当代大都市区的复杂空间结构。
https://doi.org/10.1177/23998083231180608
Three-dimensional land-use configuration and property prices: A spatially filtered multi-level modelling perspective
三维土地利用配置和房地产价格:一个空间过滤的多层次建模视角
The influence of neighbourhood characteristics on housing prices has gained increasing attention from scholars in recent decades. However, studies on the three-dimensional nature of urban space, and particularly the vertical dimension, have remained limited. This study investigates previously unexplored variables that can capture the vertical and horizontal dimensions of land-use configuration. In addition, this study proposes a spatially filtered multi-level approach to modelling variations in property values which can capture both spatial and multi-level effects. The research findings reveal a price premium for housing located in immediate neighbourhoods with more open mid-rise buildings and low plants. The results also demonstrate the varying effects of determinants of house pricing in spatially heterogeneous zones.近几十年来，邻里特征对房价的影响越来越受到学者们的关注。然而，对城市空间的三维性质，特别是垂直维度的研究仍然有限。本研究调查了以前未探索的变量，这些变量可以捕捉土地利用配置的垂直和水平维度。此外，本研究提出了一种空间过滤的多层次方法来模拟属性值的变化，该方法可以捕获空间和多层次的影响。研究结果显示，位于有更多开放式中层建筑和低矮植物的邻近社区的住房价格更高。结果还表明，在空间异质性区域，房价决定因素的影响是不同的。
https://doi.org/10.1177/23998083231180213Mingshu Wang，英国格拉斯哥大学地理与地球科学学院地理空间数据科学高级讲师(终身副教授)。他的研究整合了地理空间数据和计算方法来理解城市系统。
A hybrid estimation of carbon footprints for urban commuting transportation via path reconstruction
基于路径重建的城市通勤交通碳足迹混合估算
The transportation sector is a major source of carbon emissions, and it is of great significance to study the estimation method of carbon emissions from urban commuting traffic for energy conservation and emission reduction. In view of the difficulty of collecting detailed trip trajectory data, this paper first reconstructs the trip paths via an improved modal choice model and a modified path planning model based on the O-D trip matrix, taking seven single traffic modals and two combined modals into account. In order to estimate the carbon footprints with theoretical accuracy, the bottom-up method is adopted considering the trip modal, vehicle type, power source, vehicle occupancy, operation characteristics and traffic conditions. Meanwhile, faced with the converted carbon emissions from electric vehicles, factors like charging efficiency, vehicular load, regional power structure and transmission loss are further considered in the estimation function. A case study of Changzhou City has been performed to verify the feasibility of the proposed models, where the volume distribution of commuting trips is predicted upon a modified network traffic assignment by TransCAD, and the spatial distribution of carbon emission intensity has further expanded to the adjacent areas via ArcMap analysis tools. The total carbon emission and the average link emission intensity of daily commuting in the study area are about 14.7 × 105 kg/day and 870 kg/km respectively. The discussion results indicate that the CO2 emission of fuel-driven vehicles accounts for over 86%, and the equivalent carbon emission of electric vehicles accounts for about 14% under given modal choices. The correlations of carbon emissions to road levels and zone attributes get further revealed and discussed based on the estimation results.交通运输部门是碳排放的主要来源，研究城市通勤交通碳排放估算方法对节能减排具有重要意义。针对详细出行轨迹数据难以采集的问题，本文首先考虑7种单一交通模式和2种组合交通模式，采用改进的模式选择模型和基于O-D出行矩阵的改进路径规划模型重构出行路径。考虑出行方式、车辆类型、动力源、车辆占用率、运行特性和交通状况等因素，采用自下而上的方法估算碳足迹，以达到理论精度。同时，面对电动汽车的碳排放转化，在估计函数中进一步考虑了充电效率、车辆负荷、区域电力结构和输电损耗等因素。以常州市为例，利用TransCAD对交通流量分配进行修正，预测了常州市通勤出行量分布，并利用ArcMap分析工具将碳排放强度的空间分布进一步扩展到邻近区域，验证了模型的可行性。研究区日常通勤的碳排放总量约为14.7 × 105 kg/d，平均链路排放强度约为870 kg/km。讨论结果表明，在给定的模式选择下，燃油驱动汽车的二氧化碳排放量占比超过86%，电动汽车的当量碳排放量约占14%。在此基础上进一步揭示和讨论了碳排放与道路水平和区域属性的相关性。
https://doi.org/10.1177/23998083231181918Jun Zhang，2017年获长安大学交通运输工程专业硕士学位，2021年获同济大学交通运输工程专业博士学位。他目前是扬州大学交通工程系助理教授。他拥有3项专利和20多篇论文。主要研究方向为交通运输低碳规划、交通运输安全分析与风险防范
Simple agents –complex emergent path systems: Agent-based modelling of pedestrian movement
简单代理-复杂紧急路径系统:基于代理的行人运动建模
In well-planned open and semi-open urban areas, it is common to observe desire paths on the ground, which shows how pedestrians themselves enhance the walkability and affordance of road systems. To better understand how these paths are formed, we present an agent-based modelling approach that simulates real pedestrian movement to generate complex path systems. By using heterogeneous ground affordance and visit frequency of hotspots as environmental settings and by modelling pedestrians as agents, path systems emerge from collective interactions between agents and their environment. Our model employs two visual parameters, angle and depth of vision, and two guiding principles, global conception and local adaptation. To examine the model’s visual parameters and their effects on the cost-efficiency of the emergent path systems, we conducted a randomly generated simulation and validated the model using desire paths observed in real scenarios. The results show that (1) the angle (found to be limited to a narrow range of 90–120°) has a more significant impact on path patterns than the depth of vision, which aligns with Space Syntax theories that also emphasize the importance of angle for modelling pedestrian movement; (2) the depth of vision is closely related to the scale-invariance of path patterns on different map scales; and (3) the angle has a negative exponential correlation with path efficiency and a positive correlation with path costs. Our proposed model can help urban planners predict or generate cost-efficient path installations in well- and poorly designed urban areas and may inspire further approaches rooted in generative science for future cities.在规划良好的开放和半开放的城市地区，通常可以在地面上观察到理想的路径，这表明行人自己如何增强道路系统的可步行性和可用性。为了更好地理解这些路径是如何形成的，我们提出了一种基于智能体的建模方法，该方法模拟真实的行人运动来生成复杂的路径系统。通过使用热点的异构地面功能和访问频率作为环境设置，并将行人建模为代理，路径系统从代理与其环境之间的集体相互作用中产生。该模型采用视角和视觉深度两个视觉参数，以及全局概念和局部适应两个指导原则。为了检验模型的视觉参数及其对应急路径系统成本效率的影响，我们进行了随机生成的模拟，并使用在真实场景中观察到的愿望路径验证了模型。结果表明:(1)角度(限定在90-120°的狭窄范围内)对路径模式的影响比视觉深度更显著，这与空间句法理论一致，该理论也强调角度对行人运动建模的重要性;(2)不同地图比例尺上路径模式的尺度不变性与视觉深度密切相关;(3)角度与路径效率呈负指数相关，与路径成本呈正相关。我们提出的模型可以帮助城市规划者在设计良好和糟糕的城市地区预测或产生具有成本效益的道路装置，并可能启发基于生成科学的未来城市的进一步方法。
https://doi.org/10.1177/23998083231184884Lei Ma，拥有瑞典Gävle大学地理空间信息科学博士学位。他的主要研究兴趣包括城市结构的分形建模，基于智能体的城市动态建模，以及机器学习在城市研究中的应用
Is the noise still going on? Predicting repeat noise complaints with historical time course and random forest classifiers
噪音还在继续吗?利用历史时间过程和随机森林分类器预测重复噪声投诉
Noise can have serious adverse effects on residents' physical and mental health. Since the COVID-19 pandemic, the City of Westminster in London has seen a continuous increase in noise complaints, with a significant number of repeat complaints from the same address within a short time scale. The authorities' ability to respond to complaints is challenged. This study explores a method for predicting and identifying repeat complaints to improve the efficiency of the authorities in dealing with noise complaints. Taking the noise complaint records of the City of Westminster during 2018–2022 as research objects, the research explores the cumulative distribution characteristics and clustering pattern of noise complaints in different spatial and temporal dimensions. On this basis, for a noise complaint from a specific address, the study fits random forest classifiers to predict whether the same address is likely to have another noise complaint in future time scales. It is found that about 18.5% of all complaints had at least one previous complaint at the same address in the previous 7 days; during the lock-down period caused by the COVID-19 pandemic, areas with active commercial activities and higher housing prices experienced a significant decrease in complaints, while areas adjacent to parks and green spaces can share a similar upward trend in noise complaints. Prediction of repeat noise complaints with random forest classifiers is proved feasible. F1 scores of models to predict repeat complaints within 0 to 2nd days, 0 to 7th days and 0 to 30th days in the future are 0.55, 0.66 and 0.75, respectively. Suggestions are provided for local authorities to improve resource allocation related to noise complaint management.噪音会对居民的身心健康产生严重的不利影响。自2019冠状病毒病大流行以来，伦敦威斯敏斯特市的噪音投诉持续增加，在短时间内，同一地址的大量重复投诉。当局对投诉作出回应的能力受到质疑。本研究旨在探讨一种预测和识别重复投诉的方法，以提高当局处理噪音投诉的效率。以2018-2022年威斯敏斯特市噪声投诉记录为研究对象，探索不同时空维度噪声投诉的累积分布特征和聚类模式。在此基础上，对于来自特定地址的噪声投诉，研究拟合随机森林分类器来预测同一地址在未来时间尺度上是否可能有另一个噪声投诉。调查发现，约18.5%的投诉在过去7天内曾在同一地址至少投诉过一次;在新冠肺炎疫情封城期间，商业活动活跃、房价较高的地区的投诉量明显下降，而毗邻公园和绿地的地区的噪音投诉量也有类似的上升趋势。用随机森林分类器预测重复噪声投诉是可行的。预测未来0 ~ 2天、0 ~ 7天和0 ~ 30天重复投诉的模型F1得分分别为0.55、0.66和0.75。为地方当局提供建议，以改善与噪音投诉管理有关的资源分配。
https://doi.org/10.1177/23998083231184254Zicheng Fan，新加坡国立大学建筑系Ubran分析实验室的博士生。他的研究重点是3D GIS和Digital Twins在揭示3D建筑环境和动态城市场景中各种人与空间互动方面的广泛应用。毕业于伦敦大学学院，获硕士学位
BikeDNA: A tool for bicycle infrastructure data and network assessment
BikeDNA：一种用于自行车基础设施数据和网络评估的工具
Building high-quality bicycle networks requires knowledge of existing bicycle infrastructure. However, bicycle network data from governmental agencies or crowdsourced projects like OpenStreetMap often suffer from unknown, heterogeneous, or low quality, which hampers the green transition of human mobility. In particular, bicycle-specific data have peculiarities that require a tailor-made, reproducible quality assessment pipeline: For example, bicycle networks are much more fragmented than road networks, or are mapped with inconsistent data models. To fill this gap, we introduce BikeDNA, an open-source tool for reproducible quality assessment tailored to bicycle infrastructure data with a focus on network structure and connectivity. BikeDNA performs either a standalone analysis of one data set or a comparative analysis between OpenStreetMap and a reference data set, including feature matching. Data quality metrics are considered both globally for the entire study area and locally on grid cell level, thus exposing spatial variation in data quality. Interactive maps and HTML/PDF reports are generated to facilitate the visual exploration and communication of results. BikeDNA supports quality assessments of bicycle infrastructure data for a wide range of applications—from urban planning to OpenStreetMap data improvement or network research for sustainable mobility.建设高质量的自行车网络需要了解现有的自行车基础设施。然而，来自政府机构或像OpenStreetMap这样的众包项目的自行车网络数据往往存在未知的、异构的或低质量的问题，这阻碍了人类移动的绿色转型。特别是自行车专有数据具有特殊性，需要一个定制的可重复质量评估管道：例如，自行车网络比道路网络更加分散，或者使用不一致的数据模型进行映射。为了填补这一空白，我们介绍了一个针对自行车基础设施数据量身定制的开源工具BikeDNA，重点在于网络结构和连通性。BikeDNA可以对一个数据集进行独立分析，也可以对OpenStreetMap和参考数据集进行比较分析，包括特征匹配。考虑了数据质量的全局和局部网格单元格水平，因此暴露了数据质量的时空变化。生成交互式地图和HTML/PDF报告，以促进结果的视觉探索和交流。BikeDNA支持自行车基础设施数据的各种应用的质量评估，包括城市规划、OpenStreetMap数据改进或网络研究可持续交通等。
https://doi.org/10.1177/23998083231184471安妮·拉赫贝克·维耶罗（丹麦哥本哈根信息科技大学）
阿纳斯塔西娅·维博尔诺娃（意大利都灵ISI基金会）
The effects of street environment features on road running: An analysis using crowdsourced fitness tracker data and machine learning
街道环境特征对道路跑步的影响:使用众包健身追踪器数据和机器学习的分析
Urban streets provide environment for road running. The study proposes a non-parametric approach that uses machine learning models to predict road running intensity. The models were developed using route check-in data from Keep, a mobile exercise application, and street geographic information data in Beijing’s core district. The results show that blue space and trail continuity are the most important factors in improving road running intensity. There is an optimum design value for the sky openness and the street enclosure, which need to be balanced with shade while meeting the light of the road. And it is also important to provide appropriate visual permeability. Furthermore, unlike daily activities, it was found that higher function mixture and function density did not have significant positive effects on the road running intensity. This study provides empirical evidence on road running and highlights the key factors that planners, landscape architects, and city managers should consider when design running-friendly urban streets.城市街道为路跑提供了环境。该研究提出了一种非参数方法，使用机器学习模型来预测道路跑步强度。这些模型是利用移动锻炼应用Keep的路线签到数据和北京核心区的街道地理信息数据开发的。结果表明:蓝色空间和步道连续性是提高道路跑步强度的最重要因素。天空的开放和街道的围合有一个最佳设计值，在满足道路光线的同时，需要与阴影平衡。提供适当的视觉渗透性也很重要。此外，与日常活动不同，较高的功能混合和功能密度对道路跑步强度没有显著的正向影响。本研究提供了关于道路跑步的实证证据，并强调了规划师、景观设计师和城市管理者在设计适合跑步的城市街道时应考虑的关键因素。
https://doi.org/10.1177/23998083231185589Nianxiong Liu，清华大学建筑学院建筑系教授。1993年毕业于清华大学建筑学院，获建筑学学士学位，1998年获建筑学硕士学位，1998年获工程学博士学位。1998年起任教于清华大学建筑学院，从事建筑设计研究与教学工作，并担任建筑热环境专业讲师。他的研究方向是建筑科学及其在建筑设计中的应用，尤其关注能源和环境，以及建筑空间和围护结构的创新设计，以实现低能耗。2005年赴英国谢菲尔德大学做访问学者，从事虚拟物理环境模拟在建筑设计中的应用研究
Relational Reprojection Platform: Non-linear distance transformations of spatial data in R
关系重构平台：R中空间数据的非线性距离变换
When mapping relationships across multiple spatial scales, prevailing visualization techniques treat every mile of distance equally, which may not be appropriate for studying phenomena with long-tail distributions of distances from a common point of reference (e.g., retail customer locations, remittance flows, and migration data). While quantitative geography has long acknowledged that non-Cartesian spaces and distances are often more appropriate for analyzing and visualizing real-world data and complex spatial phenomena, commonly available GIS software solutions make working with non-linear distances extremely difficult. Our Relational Reprojection Platform (RRP) fills this gap with a simple stereographic projection engine centering any given data point to the rest of the set, and transforming great circle distances from this point to the other locations using a set of broadly applicable non-linear functions as options. This method of reprojecting data allows users to quickly and easily explore how non-linear distance transformations (including square root and logarithmic reprojections) reveal more complex spatial patterns within datasets than standard projections allow. Our initial release allows users to upload comma separated value (CSV) files with geographic coordinates and data columns and minimal cleaning and explore a variety of spatial transformations of their data. We hope this heuristic tool will enhance the exploratory stages of social research using spatial data.在跨多个空间尺度建立关系时，现有的可视化技术对待处理的距离单位同等对待，这可能不适合研究从共同参考点距离分布呈尾部长的现象（例如，零售客户位置、汇款流动和移民数据）。虽然定量地理学早就认识到非笛卡尔空间和距离对于分析和可视化现实世界数据和复杂空间现象更为合适，但现有的GIS软件解决方案很难处理非线性距离。我们的关系再投射平台（RRP）通过一个简单的球面投影引擎，将任意给定点集的中心作为中心，并使用一系列广泛适用的非线性函数作为选项，将该点与其他位置之间的经纬度距离进行变换。这种数据再投射的方法允许用户快速轻松地探索非线性距离变换（包括平方根和对数再投射）如何揭示数据集中比标准投影允许的更复杂的空间模式。我们发布的初始版本允许用户上传包含地理坐标和数据列的逗号分隔值（CSV）文件，并进行简单的清理工作，探索数据的各种空间变换。我们希望这个启发式工具能够增强使用空间数据的社会研究探索阶段。
https://doi.org/10.1177/23998083231215463威尔·B.佩恩是罗格斯大学Edward J. Bloustein计划与公共政策学院地理信息科学助理教授。他使用定性和定量方法研究地理空间技术和城市不平等之间的关系，并开发开源工具进行空间数据可视化和计算研究。
伊万杰琳·麦格尼根拥有地理学博士学位，并专门研究科学和技术研究。她是哈佛大学中东研究中心灾害研究领域的博士后研究员。在学术生涯之前，她在人道主义部门担任GIS专家。她的研究兴趣包括灾后城市景观和视觉方言的关键方法。
Synthetic population data for small area estimation in the United States
美国小区域估算的综合人口数据
Small area estimation is critical for a wide range of applications, including urban planning, funding distribution, and policy formulation. Individual-level population data, which typically include each individual’s socio-demographic characteristics and small area location, are a rich source of information for small area estimation. However, individual-level population data are often not made public due to confidentiality concerns. This paper describes the development of a public-use synthetic individual-level population dataset in the United States that can be useful for small area estimation. This dataset contains characteristics of housing type, age, sex, race, and Hispanic or Latino origin for all 308,745,538 individuals in the United States at the census block group level, based on publicly available aggregated data from the 2010 Census. Experimental results suggest the validity of the synthetic data by comparing it to different data sources, and we show examples of how this dataset can be used in small area estimation.小面积估算对于广泛的应用至关重要，包括城市规划、资金分配和政策制定。个人层面的人口数据通常包括每个人的社会人口特征和小区域位置，是小区域估计的丰富信息来源。但是，出于保密考虑，个人一级的人口数据往往不公开。本文描述了美国公共使用的综合个人人口数据集的开发，该数据集可用于小区域估计。本数据集基于2010年人口普查中公开的汇总数据，包含了美国所有308,745,538名人口普查群体的住房类型、年龄、性别、种族和西班牙裔或拉丁裔的特征。实验结果通过与不同数据源的比较表明了合成数据的有效性，并展示了如何将该数据集用于小面积估计的示例。
https://doi.org/10.1177/23998083231215825Yue Lin，芝加哥大学空间数据科学中心的助理教学教授。她的研究兴趣包括空间数据科学、地理计算和数字隐私
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