Abstract
During the COVID-19 lockdown periods, most residents had to stay at home, and apart from essential facilities, other amenities were closed. Catering places were no exception, and some of them integrated with digital systems for taking away (e.g., Meituan), leading to the change of spatial distribution. What is the impact of the COVID-19 pandemic on the spatial distribution of different catering types? This study takes Tangshan city center in China as an example. The POI data of 10 different catering types (i.e., Chinese restaurants, Catering related places, foreign restaurants, fast food restaurants, leisure catering places, coffee shops, tea houses, cold drinks shops, pastry shops and dessert shops), from the classification of source area business model and food category of food POI data by AMAP. Their locations in 2019 and 2022 were collected by development API (Application Programming Interface) provided by the map manufacturer on the network, to explore the changes during the COVID-19 pandemic. Through the Space Syntax analysis, we examine the Integration and the Choice properties at 400m, 800m, 1200m, 2000m, 5000m, 10,000m and n. We select 400m, 800m and 1200m as representative for the micro-scale; 2000m and 5000m for the meso-scale; 10,000m and n for the macro-scale. And then, the results of Space Syntax were analysed with the changes of the spatial distribution of 10 catering types (POI data) between 2019 and 2022. Our results show that during the COVID-19 pandemic, the relation between the distribution of most catering types and the Choice and Integration properties decreased; it was more related to the Integration properties. Before and after the COVID-19 pandemic, the relation between the spatial distribution and Choice properties of Catering related places, tea house,pastry shops increased most. The relation between the spatial distribution and Integration properties of fast food restaurants increased most. It suggests that during the COVID-19 pandemic, the meso and macro scale have a signific