TITLE:
Analysis of the Spatial Pattern and Influencing Factors of Green Food Enterprises in Yunnan Province
AUTHORS:
Zhihao Tu, Wujun Xi, Feng Cheng
KEYWORDS:
Green Food Enterprises, Kernel Density Estimation Model, Geographical Detector, Spatial Pattern Differentiation
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.16 No.1,
January
7,
2026
ABSTRACT: The spatial distribution of green food enterprises reflects the level of agricultural modernization and ecological civilization construction within a region. Research into this distribution carries guiding significance for promoting the rational layout of regional food production units and the coordinated development of the social economy. This study utilizes data from the 2024 Green Food Database of the China Green Food Development Center. This study employs the kernel density estimation model as the analytical method, which measures the spatial agglomeration pattern of green food-certified enterprises in Yunnan Province for the year 2024. Furthermore, a geographical detector is applied to conduct a correlation analysis of the influencing factors underlying the spatial distribution pattern of these enterprises. The results show that: 1) Green food-certified enterprises in Yunnan Province in 2024 demonstrate a clear trend of agglomeration in geographical space; 2) The spatial agglomeration locations of different types of green food-certified enterprises vary significantly; 3) The influencing factors on the spatial distribution of green food-certified enterprises are ranked in descending order of impact as follows: provincial average annual precipitation > provincial annual accumulated temperature > provincial topographic slope > total retail sales of consumer goods in prefecture-level cities (autonomous prefectures) > annual Gross Domestic Product (GDP) of prefecture-level cities (autonomous prefectures) > registered household population of prefecture-level cities (autonomous prefectures).