Mining spatial patterns of food culture in China using restaurant POI data

Abstract

AbstractTraditional studies on food culture mainly focus on types of foods. However, these studies have been limited by the low availability of data. With the rapid advancement of web maps, efficiently obtaining restaurant data is possible. This study examines the food culture of mid‐eastern China using millions of items of restaurant point of interest data and explores different spatial patterns between local and non‐local restaurants. The spatial patterns are first analyzed by the hotspot detector and G‐statistics models in global and local perspectives, and the spatial correlations are then examined between food culture preferences, climate, and social economy. This article presents the following results: (a) The distribution patterns of local (Chinese restaurants and teahouses) and non‐local food (other restaurants and cafes) demonstrate similar numbers but different rates ‐ the social economy also has a remarkable effect on local and non‐local food culture; and (b) Although globalization has a profound effect on Chinese food culture, most local specialty cuisines have been preserved in their respective regions. This study formalizes food culture with GIS methods, opening application opportunities of other GIS techniques to analyze the spatial pattern and correlation of cultural phenomena.