Research on Spatial Agglomeration and Development Strategy of

Feed Enterprises Based on GIS Geographic Data Mining

Defa Li

and Changfen Shao

Chongqing Tourism Vocational College, Zhoubai Street, Qianjiang District, Chongqing, China

Keywords: Teed Enterprises, Data Mining, Industrial Agglomeration, Spatial Distribution.

Abstract: Enterprise agglomeration is an important indicator of industrial scale development. Studying the spatial

agglomeration level and regional differences of feed enterprises can provide reference for the development

and spatial layout of feed industry. Based on the spatial distribution data of feed enterprises, ArcGIS spatial

analysis technology was used to study the spatial agglomeration and distribution of feed enterprises in China.

The results showed that: (1) The spatial agglomeration of feed enterprises in China was obvious and had a

certain spatial agglomeration effect. (2) The spatial distribution of China 's feed enterprises has the typical

characteristics of ' Hu Huanyong Line ', showing a dense southeast and sparse northwest; (3) China has

formed a number of feed enterprises gathering center, and the trend of industrial cluster development is

becoming increasingly evident; (4) The regional differences of China 's feed enterprises are large, and the

level of industrial agglomeration needs to be improved. Therefore, it is of great significance to achieve

optimal allocation of resources and optimize the structure of feed industry by strengthening the regional

division of labor and cooperation and playing the leading role of feed enterprise cluster.

1 INTRODUCTION

Industrial agglomeration is an important

phenomenon in the process of economic

development and industrialization, which refers to

the mechanism of a certain number of enterprises in

the same industry to gather in a designated

geographical area to seek agglomeration benefits,

which is a geographical phenomenon in the process

of the evolution of an industry into an advantageous

industry, which plays an important role in promoting

the development of spatial agglomeration of regional

economic entities and achieving economies of scale,

and has become the model choice for promoting

economic development in many regions (Wang

2019). Based on the analysis of the level and process

of industrial agglomeration, the relevant research

results take market size, transportation conditions,

policy support, economic level, resource endowment

and urbanization level as the main factors affecting

industrial agglomeration (GAO 2022, MA 2021). In

terms of the benefit evaluation of industrial

agglomeration, some scholars have studied the role

https://orcid.org/0000-0001-7781-0843

https://orcid.org/0000-0002-4572-6011

and impact of the agglomeration effect of different

industries on socio-economic development and

industrial layout optimization (LI 2021, LIU 2021);

In terms of measuring the level of industrial

agglomeration, some scholars used methods such as

industry concentration, location entropy index,

spatial Gini coefficient, and Moran index to measure

the agglomeration level of relevant industries

(YE

2022). There are also relevant research results from

the perspective of industrial agglomeration, the

countermeasures and measures for the development

of dairy industry and logistics industry

agglomeration and the construction of overseas

industrial agglomeration areas are demonstrated and

analyzed (LI 2016); At the same time, based on

different research scopes and regional differences,

relevant scholars have conducted empirical research

on the characteristics of industrial agglomeration

and the impact of industrial agglomeration on

economic growth (GUO 2021, LUO 2021). In

summary, industrial agglomeration is a spatial

agglomeration of various resource elements formed

within a certain geographical range under the action

of different influencing factors, which plays an

important role in promoting regional social and

economic development.

244

Li, D. and Shao, C.

Research on Spatial Agglomeration and Development Strategy of Feed Enterprises Based on GIS Geographic Data Mining.

DOI: 10.5220/0012072800003624

In Proceedings of the 2nd International Conference on Public Management and Big Data Analysis (PMBDA 2022), pages 244-249

ISBN: 978-989-758-658-3

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Based on the provincial panel data of feed

enterprises, this paper measures the agglomeration

level of feed enterprises from the perspective of

industrial agglomeration development, analyzes the

spatial agglomeration level and spatial distribution

characteristics of feed enterprises, aims to simulate

the development stage and temporal and spatial

evolution characteristics of feed industry, so as to

obtain the level division of spatial agglomeration

development of the national feed industry, and

provide a scientific basis for optimizing the spatial

layout of feed industry, promoting the large-scale

development of feed industry and realizing the

optimal allocation of feed industry resources.

2 RESEARCH MATERIALS AND

METHODS

2.1 Research Materials

The national basic geographic data required for the

study came from the Resource and Environmental

Science and Data Center (https://www.resdc.cn/) of

the Chinese Academy of Sciences, and the data of

China's provincial administrative boundaries in

2015, which was edited and operated based on

ArcGIS 10.2, and used as the basic map data for

kernel density spatial analysis.

The feed enterprise data comes from the official

website (https://www.tianyancha.com/), and the

directory of feed enterprises with a registered capital

of more than 20 million yuan in each province (city)

in the livestock breeding industry as of April 8, 2022

is obtained, including the enterprise name, registered

capital, date of establishment, number of insured

persons, registered address, business scope and other

characteristic data, and a total of 4,775 feed

enterprises were obtained after screening. ArcGIS

10.2 spatial analysis software was used to spatialize

the obtained feed enterprises according to the

address, and spatially matched with the national

vector map to obtain the point data of the spatial

distribution of feed enterprises (Figure 1).

Figure 1: Feed enterprise spatial point.

2.2 Research Methods

Kernel density estimation (KDE) is a commonly

used spatial analysis method to study the degree of

distribution aggregation of spatial points, which can

convert point features distributed in a geographical

area into density polygons (Yin 2022), which is used

to describe the distribution density and change trend

of geographical events in regional space

(FANG

2013), so as to calculate the following formula

(WANG 2022):



−

)

K((x)F

(1)

In equation (1), Fn(x) represents the kernel

density value, K represents the kernel density

equation, h represents the radius of the search range,

n represents the number of sample points in the

search range, x-xi is the estimated point, and the

distance from x to the sample point xi. In this paper,

the kernel density analysis method was used to

analyze the spatial agglomeration degree and

distribution characteristics of feed enterprises in 30

provinces (cities) in China with the help of ArcGIS

10.2.

3 RESULTS AND ANALYSIS

3.1 Spatial Distribution Characteristics

of Feed Enterprises in China

According to the spatial distribution and

visualization results of feed enterprises (Figure 2),

Research on Spatial Agglomeration and Development Strategy of Feed Enterprises Based on GIS Geographic Data Mining

245

since 1987, the distribution of feed enterprises with

registered capital of more than 20 million yuan has

obvious spatial differentiation characteristics, the

main distribution areas are concentrated in Henan,

Shandong, Inner Mongolia, followed by Hebei,

Heilongjiang, Guizhou and Xinjiang, generally

showing the characteristics of more north and south

and less economically underdeveloped areas than

more economically developed areas, and the

concentrated distribution areas of feed enterprises

are mostly large agricultural planting provinces or

animal husbandry provinces. To a certain extent, it

shows that the geographical environment, economic

conditions, agricultural planting, animal husbandry

and other factors have a certain impact on the

development and spatial layout of feed enterprises.

Figure 2: Spatial distribution of feed enterprises.

3.2 Spatial Evolution and

Agglomeration Characteristics of

Chinese Feed Enterprises

Based on the spatial distribution data of feed

enterprises, use the ArcGIS10.2 spatial analysis

module to analyze the kernel density of feed

enterprises in China from 1984 to 2005, 2006 to

2015, and 2016 to 2022, and obtain the kernel

density of feed enterprises in three different time

periods Distribution map (Fig. 3a-c), the generated

kernel density distribution map mainly reflects the

density changes and hot spots of feed enterprises.

Figure 3(a): 1984-2005 the kernel density distribution of

feed enterprises.

It can be seen from Figure 3(a) that the density

distribution of feed enterprises in China from 1984

to 2005 was dominated by “dot-like” and adjacent

provinces were relatively independent, and a

continuous planar layout had not yet been formed.

However, in Beijing-Tianjin -Hebei-Henan-Hubei-

Hunan (Jiangxi)-Guangdong (Fujian) has shown a

trend of continuous spatial development. The highest

density value during this period was 3.656, which

respectively formed the Beijing-Tianjin-Hebei high-

density area and the high-density area in Henan

Province with Beijing as the core, as well as two

sub-high-density areas in Fujian Province and

Shanghai, and Tibet Autonomous Region and

Qinghai Province. In low-density areas, feed

enterprises present a distribution trend of multiple

agglomeration centers.

Figure 3(b): 2006—2015 the kernel density distribution of

feed enterprises.

It can be seen from Figure 3(b) that from 2006 to

2015, China's feed enterprises had an obvious "band-

shaped" distribution feature, and had similar

characteristics with the "Hu Huanyong Line". The

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246

distribution density of feed enterprises in

southeastern China was generally higher than that in

northwest China. The adjacent provinces in the

southeast region are connected in series to form a

belt-like layout, forming the Heilongjiang-Jilin-

Liaoning-Tianjin-Hebei-Shandong-Henan-Hubei

feed enterprise agglomeration development belt. The

highest density value in this period is 16.208,

forming A high-density agglomeration area centered

on Henan Province. Compared with 1984-2005, the

distribution density of feed enterprises in first-tier

provinces and cities such as Beijing-Tianjin-Hebei,

Shanghai and Fujian Province is lower, indicating

that the proportion of feed industry in the national

economy in economically developed areas has

gradually declined, and it has become an area where

feed enterprises have moved out; Tibet The

Autonomous Region and Qinghai Province still

maintain a low distribution density, which to a

certain extent shows that ecological environment

protection is still the main task of local social and

economic development; the distribution density of

feed enterprises in other provinces has increased to a

certain extent, compared with the previous period It

has been expanded outwards, and the overall

distribution situation of "one center and multiple

points" has been shown.

Figure 3(c): 2016—2022 the kernel density distribution of

feed enterprises.

It can be seen from Figure 3(c) that the spatial

distribution of China's feed enterprises from 2016 to

2022 has formed a "plane shape", and continues the

characteristics of denseness in the southeast and

sparseness in the northwest. Developed and formed

four major agglomeration areas of Northeast,

Northwest, Southwest and Henan-Shandong-Hebei

(Henan, Shandong, Hebei), among which the core

density value of the Henan-Shandong-Hebei group

is 22.061, which is the highest in the region, and has

become a national feed enterprise agglomeration

highland. During this period, feed enterprises in

Beijing, Shanghai, Guangdong Province and other

provinces and cities maintained a low distribution

density, and became areas where feed enterprises

moved out; different from the previous period, the

distribution density of feed enterprises in Tibet

Autonomous Region and Qinghai Province showed

an increasing trend , indicating that the development

of feed enterprises has expanded unprecedentedly; at

the same time, the spatial distribution of feed

enterprises in other provinces has also further

expanded, and the density value of the distribution

has been greatly increased, forming a regional

agglomeration center, showing a multi-regional

integrated development trend.

4 SPATIAL DEVELOPMENT

STRATEGY OF FEED

ENTERPRISES IN CHINA

4.1 Optimize and Adjust the Industrial

Structure and Promote the Optimal

Allocation of Resources

From the perspective of the development status and

characteristics of the feed industry, the development

of China's feed industry is in a period of

transformation and development, and the large-scale

benefits generated by feed industry agglomeration

have a positive effect on promoting the development

of the national economy. In the face of the problems

of the overall competitive advantage of China's feed

enterprises is not obvious, the degree of

specialization is not high, etc., it is necessary for all

departments to carry out structural reform from the

supply side, adjust and optimize the spatial layout of

feed enterprises, promote the optimal allocation of

feed resources and the development of feed industry

clusters, improve the overall competitiveness of feed

enterprises, and drive the integrated and coordinated

development of upstream and downstream

industries, so as to form a new economic

development highland and promote the sustainable

development of regional economy.

4.2 Build a Cluster of Key Feed

Enterprises and Play a Leading

Role in Demonstration

From the perspective of industrial clusters and

coordinated regional development, the country

focuses on building four feed enterprise clusters in

Liaojihei (Liaoning, Jilin, Heilongjiang), Shaanxi-

Research on Spatial Agglomeration and Development Strategy of Feed Enterprises Based on GIS Geographic Data Mining

247

Gansu-Ningxia (Shaanxi, Gansu, Ningxia),

Guiguichuan (Guangxi, Guizhou, Sichuan) and

Yuluji (Henan, Shandong, Hebei), giving full play to

the demonstration role of the four feed enterprise

clusters, promoting and driving the coordinated

development of surrounding areas, strengthening

regional resource sharing and the circulation of

production factors, and promoting the high-quality

development of regional feed industry.

4.3 The Two Sides Will Strengthen

Regional Division of Labor and

Cooperation to Achieve

Complementary Regional

Advantages

From the perspective of regional differentiated

development, regions with high agglomeration

levels of feed enterprises should increase policy

support and capital investment to develop the feed

industry as a pillar industry; Areas with a high level

of feed enterprise agglomeration can improve the

regional competitive advantage of the feed industry

by improving infrastructure construction, increasing

industrial innovation, and strengthening the division

of labor and cooperation between regions;

Economically developed areas should increase

scientific and technological investment in feed

enterprises and develop technology-intensive and

knowledge-intensive feed industries; The

development of feed industry in ecologically

protected areas should adhere to the ecological

bottom line, develop green or pollution-free feed

enterprises, and achieve the goal of coordinated

development of development and protection.

5 CONCLUSION AND OUTLOOK

5.1 Main Conclusions

Based on ArcGIS spatial analysis technology, this

paper uses kernel density estimation and statistical

analysis to study the spatial agglomeration of feed

enterprises in China, analyzes the development

process of China's feed industry and its spatial

distribution characteristics, and obtains the

following main conclusions:

(1) Combined with the actual development of

China's feed processing industry and the distribution

characteristics of the registration sequence of feed

enterprises with a registered capital of more than 20

million, the development process of feed industry

can be divided into four stages: start-up period

(1974-1983), development period (1984-2005),

mature period (2006-2015), and transition period

(2016-2022), China's feed processing industry

generally presents the characteristics of late start and

rapid development, slow development in the early

stage, and mainly policy-oriented. In the later stage,

it grew rapidly, mainly based on market

mechanisms, and actively responded to the call of

national policies at all stages to promote regional

national economic growth.

(2) From the overall temporal and spatial

evolution and spatial distribution characteristics of

feed enterprise layout, it can be seen that the

development and layout of feed enterprises are

affected by relevant factors such as geographical

environment, economic conditions, related

industries, regional policies, etc., and the overall

spatial agglomeration phenomenon of Chinese feed

enterprises is significant, and the agglomeration area

is mainly concentrated in the southeast region, and

the spatial agglomeration phenomenon becomes

more obvious with the passage of time, showing that

Henan, Shandong, Jilin, Guizhou, Ningxia and other

places as the agglomeration center spreads to the

peripheral areas, forming a "point-line-surface" The

evolution of the spatial distribution of feed

enterprises.

(3) The spatial agglomeration phenomenon of

China's feed enterprises is obvious, but the level of

spatial agglomeration is not high, and there is a lack

of competitive advantage in the industrial

composition, and the degree of clustering and

specialization of feed enterprises need to be

improved. At the same time, the regional difference

in the spatial agglomeration level of feed enterprises

is obvious, and there is a lack of high-level industrial

agglomeration areas, and the three regions of

Guangxi, Liaoning and Shandong have comparative

advantages over other regions, and the level of feed

enterprise clustering and specialization is relatively

high, becoming a national feed industry

development highland.

5.2 Research Outlook

Limited to the limitations of research materials and

methods, there are still the following shortcomings:

first, the analysis of the development stage of the

feed industry is mainly based on the changes in the

number of feed enterprises, without considering the

industrial output value, scientific and technological

innovation, policy environment and other variables,

and multiple variables can be introduced for multi-

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248

variable comprehensive analysis in the future, so as

to more accurately divide its development stage;

Secondly, the spatial agglomeration of feed

enterprises is affected by the comprehensive effect

of a variety of influencing factors, limited by data

acquisition, and cannot comprehensively consider

multiple factors, so the next research will conduct

spatial superposition analysis from many aspects

such as the number of enterprises, enterprise scale,

industrial output value, operating income, etc., and

comprehensively reflect the agglomeration level and

spatial distribution characteristics of feed

enterprises. Finally, the research method of spatial

agglomeration of feed enterprises in this paper is not

perfect, which will affect the change of spatial

agglomeration level of feed industry, and new feed

enterprise clusters will appear with the development

of feed industry, so further research on the

agglomeration level of feed enterprises and its

development changes needs to be further studied.

FUND

2022 Chongqing Municipal Education Commission

Science and Technology Research Program

(KJQN202204608, KJQN201904605); 2022

Chongqing Tourism Vocational College Research

Project (XJ2202)

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