宁夏乡村旅游重点村空间格局与影响因素分析

doi:10.12118/j.issn.1000-6060.2023.731

Abstract

Abstract:

Establishing key villages as the cornerstone of rural tourism is a pivotal strategy for advancing comprehensive rural revitalization at a higher level. Identifying the spatial pattern and influencing factors of these villages can provide a scientific basis for enhancing rural tourism quality and achieving revitalization goals. This study focuses on 94 key rural tourism villages in the Ningxia Hui Autonomous Region, China, using data from digital elevation models, meteorological data, tourism resources, and socio-economic development indicators. ArcGIS software was employed to integrate various spatial analysis models to explore the spatial patterns and influencing factors of these villages. The results indicate that: (1) The key rural tourism villages in Ningxia exhibit a clustered distribution with significant spatial variability. These villages are predominantly concentrated in an elliptical area with a deviation rate of 0.71 and an angle of 1.74°, forming a “double nucleus” distribution pattern. The northern nucleus shows mature growth, while the southern nucleus is in an embryonic stage of development. (2) There are notable differences in the natural and human geographic spaces among key rural tourism villages in Ningxia. The number of key villages is negatively correlated with altitude and slope. Land resource utilization is primarily focused on agricultural land, and expressways serve as the main mode of rapid and accessible transportation. Generally, key villages are densely distributed in the Ningxia Yellow River Economic Belt and Yinchuan Plain, regions characterized by active economic development and higher population density. (3) The selection of key rural tourism villages in Ningxia results from the combined influence of multiple factors, with per capita urban income identified as the dominant factor. The interaction between these factors influences the spatial agglomeration of the villages. The geographically weighted regression model further confirms that the spatial distribution pattern of key rural tourism villages is associated with the natural environment, transportation infrastructure, socio-economic factors, and resource endowment.

Key words: key rural tourism villages, spatial patterns, geographic differences, influencing factors, Ningxia

SONG Xiaolong, MA Mingde, LI Longtang, MI Wenbao, WANG Peng, WU Yue, REN Jie. Spatial pattern and influencing factors of key rural tourism villages in Ningxia[J].Arid Land Geography, 2024, 47(11): 1957-1969.

Figures/Tables 10

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类型	维度	变量选取	变量解释	单位
被解释变量	-	乡村旅游重点村集中度（y）	重点村落空间格局	-
解释变量	自然环境	河流距离（x₁）	重点村距黄河距离	m
		海拔高度（x₂）	重点村海拔高度	m
		空气质量（x₃）	重点村PM_2.5浓度	μg·m^-3
		平均气温（x₄）	各县区年平均气温	℃
		降水量（x₅）	各县区年平均降雨量	mm
		坡度（x₆）	地形倾斜程度	°
	交通配套	路网密度（x₇）	各县区内道路总长度/县区面积	km·(100km)^-2
	交通配套	城市距离（x₈）	重点村离所在地级市的距离	m
	社会经济	人口密度（x₉）	各县区人口总量/县区面积	人·km^-2
		地区生产总值（x₁₀）	各县区GDP	10⁸元
		城镇人均收入（x₁₁）	各县区城镇人口收入	元
		农业发展水平（x₁₂）	每平方千米第一产业增加值	km²·(10⁸元)^-1
	资源禀赋	A级景区（x₁₃）	重点村所在县区A级景区数量	个

解释变量	地区生产总值	农业发展水平	人口密度	城镇人均收入	路网密度	A级景区	河流距离	海拔高度	空气质量	降水量	坡度	平均气温	城市距离
地区生产总值	0.281
农业发展水平	0.318^#	0.238
人口密度	0.576^#	0.601^#	0.390
城镇人均收入	0.377	0.452^#	0.531^#	0.416
路网密度	0.323^#	0.760^＊	0.482^#	0.791^＊	0.222
A级景区	0.435^#	0.369^#	0.679^#	0.408	0.551^＊	0.303
河流距离	0.244	0.380^#	0.502^#	0.384	0.299	0.523^#	0.346
海拔高度	0.526^#	0.485^#	0.549^#	0.449^#	0.345^#	0.592^#	0.392	0.290
空气质量	0.271	0.394^#	0.462^#	0.578^#	0.605^＊	0.509^＊	0.337	0.434^#	0.181
降水量	0.105	0.326^#	0.507	0.318	0.338^#	0.402^#	0.409^#	0.400^#	0.263^#	0.262
坡度	0.354^#	0.467^＊	0.487	0.612^＊	0.398^＊	0.538^＊	0.043	0.444^#	0.162	0.433^＊	0.144
平均气温	0.404^#	0.428^#	0.521^#	0.573^#	0.414^#	0.551^＊	0.215	0.444^＊	0.223^#	0.497^＊	0.209	0.206
城市距离	0.236	0.415^#	0.555^#	0.531^#	0.350^#	0.464^#	0.434^#	0.313^#	0.489^＊	0.334^#	0.203	0.218	0.282

Spatial pattern and influencing factors of key rural tourism villages in Ningxia

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