■COVID-19大流行是一种新现象,已经在许多方面影响了人们的生活方式,例如恐慌性购买(所谓的“仓鼠购物”),采用家庭办公室,和零售购物的下降。对于运输规划师和运营商,在COVID-19封锁期间,即封锁前,分析POI(兴趣点)在需求模式中的空间因素作用是很有趣的。
■这项研究说明了POI访问率或受欢迎程度数据以及其他公开可用数据的用例,用于分析像COVID-19这样的高度动态和破坏性事件期间的需求模式和空间因素。我们通过使用锁定(治疗)作为虚拟变量,开发回归模型来分析空间和非空间属性与慕尼黑COVID-19锁定之前和期间POI流行程度的相关性,具有主要和相互作用的影响。
■在我们针对慕尼黑的案例研究中,在解释受欢迎程度时,我们发现停止距离和星期几等特征的一致行为。仅在非线性模型中发现停车区域是相关的。锁定与POI类型的相互作用,停止距离,一周中的一天被发现非常重要。由于存在不同的城市特定因素,结果可能无法转移到其他城市。
■我们案例研究的结果提供了限制对POI的影响的证据,并显示了POI类型和停止距离与POI流行度的显着相关性。这些结果表明,由于限制,影响的局部和时间变化,这可能会影响城市如何在未来的破坏性事件中适应不同的需求和由此产生的交通模式。
UNASSIGNED: The COVID-19 pandemic is a new phenomenon and has affected the population\'s lifestyle in many ways, such as panic buying (the so-called \"hamster shopping\"), adoption of home-office, and decline in retail shopping. For transportation planners and operators, it is interesting to analyze the spatial factors\' role in the demand patterns at a POI (Point of Interest) during the COVID-19 lockdown viz-a-viz before lockdown.
UNASSIGNED: This study illustrates a use-
case of the POI visitation rate or popularity data and other publicly available data to analyze demand patterns and spatial factors during a highly dynamic and disruptive event like COVID-19. We develop regression models to analyze the correlation of the spatial and non-spatial attributes with the POI popularity before and during COVID-19 lockdown in Munich by using lockdown (treatment) as a dummy variable, with main and interaction effects.
UNASSIGNED: In our
case-study for Munich, we find consistent behavior of features like stop distance and day-of-the-week in explaining the popularity. The parking area is found to be correlated only in the non-linear models. Interactions of lockdown with POI type, stop-distance, and day-of-the-week are found to be strongly significant. The results might not be transferable to other cities due to the presence of different city-specific factors.
UNASSIGNED: The findings from our
case-study provide evidence of the impact of the restrictions on
POIs and show the significant correlation of POI-type and stop distance with POI popularity. These results suggest local and temporal variability in the impact due to the restrictions, which can impact how cities adapt their transport services to the distinct demand and resulting mobility patterns during future disruptive events.