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Academic Journal of Business & Management, 2023, 5(23); doi: 10.25236/AJBM.2023.052313.

Analysis of spatial distribution and influencing factors of characteristic towns in Guangxi based on ArcGIS

Author(s)

Wang Yilin1, Luo Lijuan2

Corresponding Author:
Luo Lijuan
Affiliation(s)

1School of Economics and Management, Guangxi Normal University, Guilin, China

2Guilin Tourism University, Guilin, China

Abstract

The spatial distribution of characteristic towns presents obvious regional characteristics. Exploring the regional characteristics of characteristic towns provides a theoretical basis for optimizing the spatial development pattern and achieving coordinated regional development. This article is based on the data of 62 characteristic towns in Guangxi Zhuang Autonomous Region, and uses ARCGIS average nearest neighbor index, Voronoi map, geographic concentration index, and kernel density analysis to conduct a study on the spatial distribution pattern and influencing factors of characteristic towns. The results show that the distribution of characteristic towns in Guangxi is uneven, showing a distribution pattern with different models, but in a concentrated distribution trend, with a greater number in northern Guangxi than in southern Guangxi, among them, there are many and scattered characteristic towns in the northern Guangxi region, and the degree of cohesion is not high, showing a phenomenon of clustering from northwest to southeast as a whole. The spatial distribution of characteristic towns is influenced by factors such as characteristic industries, terrain, transportation network, and tourism resources. Therefore, it is necessary to explore industrial characteristics, improve transportation network, and pay attention to ecological civilization, in order to optimize the spatial distribution pattern of characteristic towns in Guangxi.

Keywords

spatial distribution; Influencing factors; Characteristic towns; ArcGIS

Cite This Paper

Wang Yilin, Luo Lijuan. Analysis of spatial distribution and influencing factors of characteristic towns in Guangxi based on ArcGIS. Academic Journal of Business & Management (2023) Vol. 5, Issue 23: 85-90. https://doi.org/10.25236/AJBM.2023.052313.

References

[1] Hu Yakun, Song Jian, Liu Yang. Promoting the standardized and healthy development of characteristic towns [J]. Macroeconomic Management, 2021 (11): 27-32

[2] Zou Hui. Research on high-quality development strategies for characteristic towns [J]. Agricultural Economy, 2020 (11): 123-124

[3] Liu Qingwen, Zhu Linan. The Rise of Rural Tourism Characteristic Towns and the Solution to the Dilemma of Dehomogenization [J]. Agricultural Economy, 2021 (07): 45-47

[4] Zeng Zhihong, Wang Zi'an, Ding Shasha. Research on the Multiple Behaviors and Risk Prevention of Local Governments in the Construction of Characteristic Towns: A Deep Observation Based on M Town in Zhejiang Province [J]. Journal of Hangzhou Normal University (Social Science Edition), 2021, 43 (05): 125-136

[5] Liu Jiwei. Current Status, Hotspots, and Trends in the Study of Characteristic Towns: A Visual Analysis Based on CNKI and CiteSpace [J]. China Agricultural Resources and Regionalization, 2021, 42 (08): 107-117

[6] Yu Hao, Yu Hewen. Construction of a consumption agglomeration path for sports and leisure characteristic towns under the new economic normal [J]. Jiangxi Social Sciences, 2021, 41 (10): 221-228

[7] Li Bohua, Li Xue, Chen Xinxin, Dou Yindi, Liu Peilin. Research on the dual wheel driving mechanism of characteristic tourism town construction under the background of new urbanization [J]. Progress in Geographic Science, 2021, 40 (01): 40-49

[8] Wang Kun, He Qingyun, Zhu Xiang. A Study on the Spatial Relationship between New Era Characteristic Towns and Urban Rural Integrated Development: Taking Zhejiang Province as an Example [J]. Economic Geography, 2022, 42 (08): 72-80

[9] Wang Zhaofeng, Liu Qingfang. Spatial differentiation and formation factors of sports and leisure characteristic towns under the background of industrial integration [J]. Geographic Science, 2020, 40 (08): 1310-1318