新型冠状病毒肺炎疫情前后天津市中心城区智能包裹柜空间分布变化分析

Mengyue Ding, Nadeem Ullah, Sara Grigoryan, Yike Hu, Yan Song
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引用次数: 1

摘要

新冠肺炎疫情导致电子商务大幅增长,这促使居民将购买习惯从线下转向线上。因此,智能包裹寄存柜(SPLs)已成为一种无障碍的端到端快递服务,符合保持社交距离和不接触协议的大流行战略。虽然有许多研究从不同的角度考察了城市规划空间,但很少有研究从城市规划的角度分析城市规划空间分布,这可以促进该领域其他学科的发展。为了解决这一差距,我们采用核密度估计、平均近邻分析、标准差椭圆和地理检测器等方法研究了疫情前后(即2019年和2022年)天津市中心城区SPLs的分布情况。我们的研究结果表明,在三年内,SPLs的数量从51个增加到479个,并且大多数安装在住宅社区(即2019年为92.2%,2022年为97.7%)。我们发现,疫情发生前,小城镇小城镇是随机分布的,疫情发生后,小城镇小城镇小城镇呈聚集性分布,并遵循了天津市的发展规律。本文确定了8个影响土壤养分空间分布的因素,并讨论了它们的单独效应和复合效应。我们的讨论重点是潜在的空间分布分析,如动态布局规划,以改善城市规划和城市物流中的特殊物品配置。
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Variations in the Spatial Distribution of Smart Parcel Lockers in the Central Metropolitan Region of Tianjin, China: A Comparative Analysis before and after COVID-19
The COVID-19 pandemic has led to a significant increase in e-commerce, which has prompted residents to shift their purchasing habits from offline to online. As a result, Smart Parcel Lockers (SPLs) have emerged as an accessible end-to-end delivery service that fits into the pandemic strategy of maintaining social distance and no-contact protocols. Although numerous studies have examined SPLs from various perspectives, few have analyzed their spatial distribution from an urban planning perspective, which could enhance the development of other disciplines in this field. To address this gap, we investigate the distribution of SPLs in Tianjin’s central urban area before and after the pandemic (i.e., 2019 and 2022) using kernel density estimation, average nearest neighbor analysis, standard deviation elliptic, and geographical detector. Our results show that, in three years, the number of SPLs has increased from 51 to 479, and a majority were installed in residential communities (i.e., 92.2% in 2019, and 97.7% in 2022). We find that SPLs were distributed randomly before the pandemic, but after the pandemic, SPLs agglomerated and followed Tianjin’s development pattern. We identify eight influential factors on the spatial distribution of SPLs and discuss their individual and compound effects. Our discussion highlights potential spatial distribution analysis, such as dynamic layout planning, to improve the allocation of SPLs in city planning and city logistics.
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