论文概览 |《Urban Analytics and City Science》2023.06 Vol.50 Issue.5

本次给大家整理的是《Environment and Planning B: Urban Analytics and City Science》杂志2023年6月第50卷第5期的论文的题目和摘要，一共包括19篇SCI论文！

---

论文1

An overview of urban analytical approaches to combating the Covid-19 pandemic

抗击Covid-19大流行的城市分析方法概述

【摘要】

The Covid-19 pandemic has received immeasurable research attention across various scientific fields. We would argue that viewing Covid-19 through the lens of geography and urban analytics plays an essential role in interdisciplinary endeavors to understand and fight the pandemic. First, geographic location and time are the fundamental elements in the spread of infectious diseases, and second, most of the world’s population now lives in urban environments. With geospatial technology and data science playing an ever-increasing role in the field, urban analytics is ideally situated at the hub of interdisciplinary research aiming to understand the patterns and dynamics, social impacts, problems, solutions, possible future outcomes, and other cross-disciplinary topics concerning pandemics.

【摘要翻译】

新冠肺炎大流行在各个科学领域受到了极大的研究关注。我们认为，通过地理和城市分析的视角来看待Covid-19，在跨学科努力中发挥着至关重要的作用，以理解和应对这一流行病。首先，地理位置和时间是传染病传播的基本因素，其次，世界上大多数人口现在都生活在城市环境中。随着地理空间技术和数据科学在该领域发挥越来越大的作用，城市分析理想地位于跨学科研究的中心，旨在了解与流行病有关的模式和动态、社会影响、问题、解决方案、可能的未来结果和其他跨学科主题。

【doi】

https://doi.org/10.1177/23998083231174748

【作者信息】

X. Angela Yao，美国乔治亚州雅典市乔治亚大学地理系

---

论文2

Spatial variations of the third and fourth COVID-19 waves in Hong Kong: A comparative study using built environment and socio-demographic characteristics

香港第三波和第四波COVID-19的空间变化:基于建筑环境和社会人口特征的比较研究

【摘要】

Since the first confirmed case was reported in January 2020, Hong Kong has experienced multiple waves of COVID-19 outbreaks. Recent literature has explored the spatial patterns of disease incidence and their relationships with the built environment and demographic characteristics. Nonetheless, few studies aim at the comparative patterns of different epidemic waves occurring in the same spatial context. This study analyses spatial patterns of the third and fourth COVID-19 epidemic waves and then evaluates the spatial relationship between case incidence and built environment and socio-demographic characteristics. By collecting local-related cases, this study incorporates a two-fold analytical strategy: (1) Using rank-size distribution and log-odd ratio to depict the spatial pattern of COVID-19 incidence rates; (2) through global and local regression models, investigating incidence’s associations with the urban built environment and socio-demographic characteristics. The results reveal that the two different epidemic waves have far distinct spatial tendencies to their infection risk factors, reflecting location-specific associations with the built environments and socio-demographics. Collectively, we discover that the third and fourth COVID-19 waves are likely associated with residential context and urban activities, respectively. Practical implications are discussed that would be of interest to policymakers and health professionals.

【摘要翻译】

自2020年1月报告首例确诊病例以来，香港经历了多波新冠肺炎疫情。最近的文献探讨了疾病发病率的空间格局及其与建筑环境和人口特征的关系。然而，很少有研究针对在同一空间背景下发生的不同流行病波的比较模式。本研究分析了第三波和第四波COVID-19流行的空间格局，并评估了病例发病率与建筑环境和社会人口特征之间的空间关系。本研究通过收集地方相关病例，采用双重分析策略:(1)利用秩-大小分布和对数奇比来描述COVID-19发病率的空间格局;(2)通过全球和局部回归模型，研究发病率与城市建成环境和社会人口特征的关系。结果表明，两种不同的流行波对其感染危险因素具有明显不同的空间趋势，反映了与建筑环境和社会人口统计学的区位特异性关联。总的来说，我们发现第三波和第四波COVID-19可能分别与住宅环境和城市活动有关。讨论了决策者和卫生专业人员感兴趣的实际影响。

【doi】

https://doi.org/10.1177/23998083221107019

【作者信息】

Xintao Liu，香港理工大学土地测量及地理资讯学系助理教授。主要研究方向为地理信息科学、交通地理、复杂网络。

---

论文3

Strategies and inequities in balancing recreation and COVID exposure when visiting green spaces

在访问绿色空间时平衡娱乐和接触COVID的策略和不公平性

【摘要】

Green spaces are beneficial for physical and mental health, especially during and after disasters. The COVID-19 pandemic, however, created a trade-off: parks could be therapeutic but also could expose people to infection. This paradox posed inequities as marginalized populations often have less access to parks and were hit harder by the pandemic. We combined cellphone-generated mobility data with demographic indicators, a neighborhood survey, and local infection rates to examine how residents of Boston, MA, navigated this trade-off in April–August 2020. We hypothesized that they adopted strategies for mitigating infection exposure—including fewer park visits and prioritizing parks that might have lower infection risk, including larger parks with more opportunity for social distancing and parks near home with fewer unfamiliar faces—but that marginalized populations would have less opportunity to do so. We also introduce a novel measure of exposure per visit based on the volume of other visitors, infection rates, and park size. Bostonians made fewer park visits relative to 2019 and prioritized larger parks and parks closer to home. These strategies varied by community. Experiences of the pandemic were influential, as communities that perceived greater risk or had more infections made more park visits, likely because they were a relatively safe activity. Communities with more infections tended to avoid nearby parks. Inequities were also apparent. Communities with more Black residents and infections had greater infection exposure per visit even when controlling for the types of parks visited, highlighting difficulties in escaping the challenges of the pandemic.

【摘要翻译】

绿色空间对身心健康有益，特别是在灾害期间和之后。然而，COVID-19大流行病造成了一种权衡：公园可以起到治疗作用，但也可能使人们感染病毒。这个矛盾造成了不公平，因为边缘化的人口通常更难以获得公园，并且受到疫情的影响更大。我们结合了手机生成的移动数据、人口统计指标、邻里调查和当地感染率，研究了马萨诸塞州波士顿市的居民在2020年4月至8月期间如何应对这一权衡。我们假设他们采取了减少感染暴露的策略，包括减少公园访问次数，并优先考虑可能感染风险较低的公园，包括更大的公园，有更多机会进行社交隔离和靠近家的公园，人流量少、面孔陌生的公园；但边缘化人口没有多少机会这样做。我们还引入了一个基于其他游客数量、感染率以及公园大小的每次访问暴露程度的全新衡量标准。与2019年相比，波士顿市民减少了公园访问次数，并优先考虑了更大的公园和更靠近家的公园。这些策略因社区而异。社区感知到的风险越大或感染率越高，公园访问次数就越多，可能是因为它们是一个相对安全的娱乐活动。感染率较高的社区往往避免靠近家的公园。即使在控制所访问的公园类型的情况下，感染率较高的非裔美国人社区的每次访问感染暴露程度更高，这突显了在疫情挑战面前难以摆脱困境的问题。

【doi】

https://doi.org/10.1177/23998083221114645

【作者信息】

萨琳娜·达斯是纽约州纽约市Flatiron Health公司的数据洞察工程师，她利用机器学习和数据分析推动癌症研究。在东北大学攻读数据科学学士学位期间，她在波士顿地区研究计划中担任研究助理，创建模型和分析数据以评估学校选择算法中的公平性。她的专长是将机器学习应用于解决现实问题。阿丽娜·里斯蒂博士是伦敦大学学院安全与犯罪科学系的一名讲师（助理教授），她对城市现象的时空分析感兴趣，特别关注犯罪问题。她的研究包括研究问题房产的模式、体育赛事周边犯罪的空间分布和预测，以及COVID-19对人们社交活动的影响。她获得了奥地利萨尔茨堡大学地理信息科学的博士学位，并在东北大学波士顿地区研究计划中完成了博士后工作。

丹尼尔·T·奥布莱恩博士是东北大学公共政策与城市事务学院以及犯罪学与刑事司法学院的一名副教授。他的专长是利用现代数字数据集更好地了解城市进程，特别是社区的社会和行为动态。他是波士顿地区研究计划的主任，该计划在研究政策合作方面进行了大量有效模型的建设工作。他的著作《城市公域》（2018年；哈佛大学出版社）获得了美国政治学会颁发的最佳地方和城市政治书籍奖。他获得了纽约州宾厄姆顿大学进化生物学博士学位。

---

论文4

Impact of COVID-19 policies on pedestrian traffic and walking patterns

COVID-19政策对行人交通和步行模式的影响

【摘要】

The spread of COVID-19 pandemic provoked new policies and restrictions, which had an unprecedented impact on urban mobility and traffic on local and global scales. While changes in motorized traffic were investigated and monitored throughout the recent pandemic crisis in many cities around the world, not much was done on the changes in pedestrian street-traffic and walking patterns during this time. This study aims to identify, quantify, and analyze the changes in pedestrian traffic and walking patterns induced by COVID-19 policies. The “first wave” period of COVID-19 policies in Tel-Aviv, Israel, is used as a case study in this work. The analysis includes over 116 million pedestrian movement records documented by a network of 65 Bluetooth sensors, between 1.2.2020 and 26.7.2020, with a comparison to the equivalent time in 2019 that signifies “normal” pre-COVID-19 conditions. The results show clear correlation between the various COVID-19 policy restrictions and pedestrian count. The shifts to work-from-home and closure of businesses were highly correlated with changes in walking patterns during weekdays, while distinguishing changes in commercial and residential street segments. Nevertheless, while the restrictions dramatically influenced pedestrian movement volume and time of walking, it did not significantly change where people chose to walk, signifying the essentialness of attractive streets, parks and squares for citizens living in urban areas. This study shows how policy affects walking behavior in cities, demonstrating the potential of passive crowdsourced sensing technologies to provide urb