Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Using Restaurant POI Data to Explore Regional Structure of Food Culture Based on Cuisine Preference

Version 1 : Received: 28 December 2020 / Approved: 29 December 2020 / Online: 29 December 2020 (15:35:18 CET)

A peer-reviewed article of this Preprint also exists.

Jiang, S.; Zhang, H.; Wang, H.; Zhou, L.; Tang, G. Using Restaurant POI Data to Explore Regional Structure of Food Culture Based on Cuisine Preference. ISPRS Int. J. Geo-Inf. 2021, 10, 38. Jiang, S.; Zhang, H.; Wang, H.; Zhou, L.; Tang, G. Using Restaurant POI Data to Explore Regional Structure of Food Culture Based on Cuisine Preference. ISPRS Int. J. Geo-Inf. 2021, 10, 38.

Journal reference: ISPRS Int. J. Geo-Inf. 2021, 10, 38
DOI: 10.3390/ijgi10010038

Abstract

As a result of the influence of geographical environment and historical heritage, food preference has significant regional differentiation characteristics. However, the spatial structure of food culture represented by the cuisine culture at the regional level has not yet been explored from the perspective of geography. This study aims to explore such patterns by focusing on the restaurants of the eight most famous cuisines in Mainland China. Initially, the density based geospatial hotspot detector method is proposed to analyze and mapping the spatial quantitative characteristics of the eight major cuisines. A heuristic method for geographical regionalization based on machine learning was used to analyze spatial distribution patterns in accordance with the proportion of these cuisines in each prefecture-level city. Results show that some types of single-category cuisines have a stronger spatial concentration effect in the present, whereas others have a strong diffusion trend. In the comprehensive analysis of multicategory cuisines, the eight major cuisines formed a new structure of geographical regionalization of Chinese cuisine culture. This study is helpful to understand regional structure characteristics of food preference, and the density based hotspot detector proposed in this paper can also be used in the analysis of other type of POI data.

Subject Areas

food culture; cultural regionalization; Chinese cuisines; machine learning; spatial struture

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.