论文推荐 | 利用移动感知街景和计算机视觉方法推断临街商铺空置-规划问道

导读

本期为大家推荐的内容为论文《Inferring storefront vacancy using mobile sensing images and computer vision approaches》（利用移动感知街景和计算机视觉方法推断临街商铺空置），发表在 Computers, Environment and Urban Systems 期刊，欢迎大家学习与交流。

商铺空置一直是一个普遍且全球性的现象，引发了人们对零售景观特征变化、社区活力丧失和城市空心化的担忧。尽管导致这一现象的原因已被广泛讨论，但很少有详细数据可用于及时评估这一问题。因此，本研究旨在开发一种数据驱动的方法，以捕捉临街商铺空置的商业结构，并逐店分析其演变模式。首先，使用移动感知技术以低成本、大规模且高效的方式收集最新的城市街景；然后，开发了一种使用计算机视觉技术的商店空置估计模型，以推断商铺位置、运营状态、业务类别和空置率。三名志愿者花了五天时间搜集了中国西宁市中心城区964平方公里内的街景图像。结果显示，2022年3月该市共识别出93,069家商铺，其中25,488家空置。此外，疫情后商铺空置率显著上升，从2018年的21.8%增加到2022年的30.0%。购物、餐饮和生活服务类商店的空置最多。对商铺空置影响最大的因素依次是，远离商业区、人口密度低和远离城市中心。然而，这些因素以多种复杂的方式影响空置率，未来应充分考虑并区分化地制定城市规划策略以解决空置问题。

论文相关

题目：Inferring storefront vacancy using mobile sensing images and computer vision approaches

（利用移动感知街景和计算机视觉方法推断临街商铺空置）

作者：

Yan Li and Ying Long*

发表刊物：

Computers, Environment and Urban Systems

DOI:

https://doi.org/10.1016/j.compenvurbsys.2023.102071

URL：https://www.sciencedirect.com/science/article/pii/S0198971523001345

摘要ABSTRACT

Storefront vacancy has been a widespread and worldwide phenomenon, raising concerns about the changing characteristic of the retail landscape, loss of community vitality, and hollowing out of cities. Although the causes leading to this phenomenon have been extensively debated, little granular data are available to evaluate the issue in a timely manner. Therefore, this study aims to develop a data-driven approach to capture the commercial structure of vacant storefronts on a store-by-store basis as well as to analyze their evolution patterns. First, street-level images were collected using mobile sensing in a low-cost, large-scale and efficient manner; then, a storefront vacancy estimation model was developed using computer vision techniques to infer the storefront location, operation status, business category, and vacancy rates. Three volunteers spent five days collecting street-level images from an urban area of 964 km2 in the case city of Xining, China. As a result, 93,069 stores were identified in the city in March 2022, of which 25,488 were vacant. Moreover, the storefront vacancy rate increased significantly after the epidemic, from 21.8% in 2018 to 30.0% in 2022. Stores in shopping, catering, and life services had the maximum vacancies. The factors that had the greatest impact on storefront vacancy were, in order of importance, far from commercial zonings, low population density, and far from the urban center. However, these factors influenced the vacancy in diverse and complex ways, and in the future, urban planning strategies to address vacancy issues should be well considered and differentiated.