交通驱动下湘西地区旅游城镇集聚场强时空演化及影响机制

doi:10.12342/zgstly.20230042

Abstract

Abstract:

Transportation infrastructure plays a crucial role in the development of integrated regional tourism, significantly influencing the formation and optimization of the agglomeration pattern of tourism towns. By employing composite location entropy and weighted average travel time, the study measures the agglomeration level and transport accessibility of tourist towns in the Xiangxi region from 2000 to 2019. Utilizing an improved gravity model and spatial econometric model, the research explores the spatiotemporal evolution characteristics and influencing mechanisms of agglomeration intensity in typical regions of tourism development. The results show that: (1) During the study period, the agglomeration intensity and transport accessibility in the Xiangxi region exhibited a continuous upward trend, with the optimal transport radiation range within 1.6 hours. (2) The spatial pattern of agglomeration intensity in tourism towns underwent a dynamic transformation from a “unidirectional dominance” to a “bidirectional interactive” pattern, manifested by the emergence of three major high-intensity areas led by Wulingyuan, Yongding, and Fenghuang, shifting away from the dominance of Fenghuang. Meanwhile, transport accessibility demonstrated an irregular concentric structure spreading along the north-south axis, with the central region as the center. (3) Under the comprehensive influence of resource endowment, industrial structure, and living environment conditions, the improvement of transportation conditions brings about the compression effect of space and time, facilitating the agglomeration of population, land, and industries in tourist towns. This, in turn, enhances local tourism economic efficiency and increases the opportunity cost of resource utilization, leading to a spatial structural transformation from “monocentric” to “polycentric” pattern.

Key words: tourism urbanization, tourism traffic, traffic accessibility, traffic radiation, agglomeration field strength

Tan Jiaxin, Ma Xuefeng, Wang Kai. Spatiotemporal evolution and influencing mechanisms of the agglomeration field in tourist towns in Xiangxi region driven by transportation[J].ECOTOURISM, 2023, 13(3): 380-393.

Figures/Tables 7

Tab. 1

Fig. 1

Fig. 2

Tab. 2

Fig. 3

Tab. 3

Fig. 4

References 37

[1]	刘彦随, 杨忍, 林元城. 中国县域城镇化格局演化与优化路径[J]. 地理学报, 2022, 77(12): 2937-2953. doi: 10.11821/dlxb202212001
	[ Liu Yansui, Yang Ren, Lin Yuancheng. Pattern evolution and optimal paths of county urbanization in China[J]. Acta Geographica Sinica, 2022, 77(12): 2937-2953.] doi: 10.11821/dlxb202212001
[2]	新华社. 中华人民共和国国民经济和社会发展第十四个五年规划和2035年远景目标纲要[EB/OL]. (2021-03-13). http://www.gov.cn/xinwen/2021-03/13/content_5592681.htm.
	[ Xinhua News Agency. The Outline of the 14th Five-Year Plan (2021-2025) for National Economic and Social Development and the Long-Range Objectives through the Year 2035 [EB/OL]. (2021-03-13). http://www.gov.cn/xinwen/2021-03/13/content_5592681.htm.]
[3]	罗霞, 张丽华. 旅游产业集聚与城镇化效应测度及路径研究[J]. 湖南社会科学, 2017(4): 131-137.
	[ Luo Xia, Zhang Lihua. Study on the measurement and path of tourism industry agglomeration and urbanization effect[J]. Social Sciences in Hunan, 2017(4): 131-137.]
[4]	韩鑫. 加快城乡道路客运与旅游融合发展[N]. 人民日报, 2023-03-22(7).
	[ Han Xin. Accelerate the development of urban and rural road passenger transport and tourism integration[N]. People’s Daily, 2023-03-22(7).]
[5]	麻学锋, 谭佳欣, 黄俊. 区域旅游产业集聚过程及其影响因素研究: 以湘西地区为例[J]. 旅游学刊, 2021, 36(9): 13-27.
	[ Ma Xuefeng, Tan Jiaxin, Huang Jun. Study on the agglomeration process and influencing factors of regional tourism industry: A case of the Western Hunan[J]. Tourism Tribune, 2021, 36(9): 13-27.]
[6]	王凯, 刘依飞, 甘畅. 旅游产业集聚对旅游业碳排放效率的空间溢出效应[J]. 生态学报, 2022, 42(10): 3909-3918.
	[ Wang Kai, Liu Yifei, Gan Chang. Spatial spillovers of tourism agglomeration on the carbon emission efficiency of tourism industry[J]. Acta Ecologica Sinica, 2022, 42(10): 3909-3918.]
[7]	王新越, 芦雪静. 中国旅游产业集聚空间格局演变及其对旅游经济的影响: 基于专业化与多样化集聚视角[J]. 地理科学, 2020, 40(7): 1160-1170. doi: 10.13249/j.cnki.sgs.2020.07.013
	[ Wang Xinyue, Lu Xuejing. Evolution of China’s tourism industry agglomeration spatial pattern and its impact on tourism economy based on specialization and diversification agglomeration perspective[J]. Scientia Geographica Sinica, 2020, 40(7): 1160-1170.] doi: 10.13249/j.cnki.sgs.2020.07.013
[8]	杨喜, 卢新海. 空间效应视角下中国城市土地城镇化的驱动因素[J]. 中国人口·资源与环境, 2021, 31(1): 156-164.
	[ Yang Xi, Lu Xinhai. Driving factors of urban land urbanization in China from the perspective of spatial effects[J]. China Population, Resources and Environment, 2021, 31(1): 156-164.]
[9]	施凡基, 徐勇. 中国县域人口城镇化与产业高级化的时空耦合及其影响因素研究[J]. 长江流域资源与环境, 2021, 30(12): 2811-2821.
	[ Shi Fanji, Xu Yong. Spatio-temporal coupling characteristics and its influencing factors between population urbanization and industrial upgrading at county level in China[J]. Resources and Environment in the Yangtze Basin, 2021, 30(12): 2811-2821.]
[10]	Naidu S. Exploring the dynamic effects of urbanization and real effective exchange rate on tourism output of Singapore[J]. Tourism Analysis, 2017, 22: 185-200. doi: 10.3727/108354217X14888192562320
[11]	Hu H S, Qiao X Z, Yang Y, et al. Developing a resilience evaluation index for cultural heritage site: Case study of Jiangwan Town in China[J]. Asia Pacific Journal of Tourism Research, 2021, 26(1): 15-29. doi: 10.1080/10941665.2020.1805476
[12]	Xu X Y, Le T H, Kwek A, et al. Exploring cultural tourist towns: Does authenticity matter?[J]. Tourism Management Perspectives, 2022, 41: 100935. doi: 10.1016/j.tmp.2021.100935
[13]	Wang M D, Liu J M, Zhang S Y, et al. Spatial pattern and micro-location rules of tourism businesses in historic towns: A case study of Pingyao, China[J]. Journal of Destination Marketing & Management, 2022, 25: 100721.
[14]	谭皓方, 任太增, 谭征. 基于城镇要素集聚能力的河南省区域发展空间非均衡性研究[J]. 地域研究与开发, 2019, 38(6): 34-39.
	[ Tan Haofang, Ren Taizeng, Tan Zheng. Non-equilibrium study of regional development in Henan Province based on urban factor agglomeration capability[J]. Areal Research and Development, 2019, 38(6): 34-39.]
[15]	Raza S, Qureshi M, Ahmed M, et al. Non-linear relationship between tourism, economic growth, urbanization, and environmental degradation: Evidence from smooth transition models[J]. Environmental Science and Pollution Research, 2021, 28(2): 1426-1442. doi: 10.1007/s11356-020-10179-3
[16]	麻学锋, 谭佳欣. 湘西地区交通可达性对旅游环境系统韧性的影响及空间溢出效应[J]. 地理科学, 2023, 43(2): 291-300. doi: 10.13249/j.cnki.sgs.2023.02.011
	[ Ma Xuefeng, Tan Jiaxin. Impact of traffic accessibility on the resilience of tourism environment system and spatial spillover effects in Xiangxi Area[J]. Scientia Geographica Sinica, 2023, 43(2): 291-300.] doi: 10.13249/j.cnki.sgs.2023.02.011
[17]	Kanwal S, Rasheed M I, Pitafi A H, et al. Road and transport infrastructure development and community support for tourism: The role of perceived benefits, and community satisfaction[J]. Tourism Management, 2020, 77: 104014. doi: 10.1016/j.tourman.2019.104014
[18]	汪德根, 钱佳, 牛玉. 高铁网络化下中国城市旅游场强空间格局及演化[J]. 地理学报, 2016, 71(10): 1784-1800. doi: 10.11821/dlxb201610010
	[ Wang Degen, Qian Jia, Niu Yu. Evolution and spatial characteristics of tourism field strength of cities under high-speed rail network in China[J]. Acta Geographica Sinica, 2016, 71(10): 1784-1800.] doi: 10.11821/dlxb201610010
[19]	杨仲元, 卢松. 交通发展对区域旅游空间结构的影响研: 以皖南旅游区为例[J]. 地理科学, 2013, 33(7): 806-814. doi: 10.13249/j.cnki.sgs.2013.07.806
	[ Yang Zhongyuan, Lu Song. The impacts of traffic improvements on spatial structure of regional tourism: Case of southern Anhui[J]. Scientia Geographica Sinica, 2013, 33(7): 806-814.] doi: 10.13249/j.cnki.sgs.2013.07.806
[20]	章锦河, 张捷, 刘泽华. 基于旅游场理论的区域旅游空间竞争研究[J]. 地理科学, 2005, 25(2): 248-256.
	[ Zhang Jinhe, Zhang Jie, Liu Zehua. A study on spatial competition among tourism regions based on the theory of tourism field[J]. Scientia Geographica Sinica, 2005, 25(2): 248-256.] doi: 10.13249/j.cnki.sgs.2005.02.248
[21]	樊晓霞, 刘敏, 冯卫红, 等. 山西省转型期旅游场强时空异质性特征及机制[J]. 人文地理, 2020, 35(6): 132-139.
	[ Fan Xiaoxia, Liu Min, Feng Weihong, et al. Spatial-temporal heterogeneity and evolution mechanism of tourism field strength in Shanxi Province during the transition period[J]. Human Geography, 2020, 35(6): 132-139.]
[22]	胡美娟, 沈一忱, 郭向阳, 等. 长三角城市群旅游场强时空异质性及演化机理[J]. 长江流域资源与环境, 2019, 28(8): 1801-1810.
	[ Hu Meijuan, Shen Yichen, Guo Xiangyang, et al. Spatial and temporal heterogeneity and evolution mechanism of tourism field strength in Yangtze River Delta urban agglomeration[J]. Resources and Environment in the Yangtze Basin, 2019, 28(8): 1801-1810.]
[23]	Wang D G, Niu Y, Sun F, et al. Evolution and spatial characteristics of tourism field strength of cities linked by high-speed rail (HSR) network in China[J]. Journal of Geographical Sciences, 2017, 27(7): 835-856. doi: 10. 1007/s11442-017-1409-1
[24]	Ferrari C, Parola F, Gattorna E. Measuring the quality of port hinterland accessibility: The Ligurian case[J]. Transport Policy, 2011, 18(2): 382-391. doi: 10.1016/j.tranpol.2010.11.002
[25]	王姣娥, 李涛. 交通强国背景下中国交旅融合研究进展与展望[J]. 中国生态旅游, 2022, 12(1): 1-15. doi: 10.12342/zgstly.20220005
	[ Wang Jiaoe, Li Tao. Research progress and prospect of transport and tourism integration in China in the context of building national strength in transportation[J]. Journal of Chinese Ecotourism, 2022, 12(1): 1-15.] doi: 10.12342/zgstly.20220005
[26]	王兆峰, 李丹. 基于交通网络的区域旅游空间合作效率评价与差异变化分析: 以湘西地区为例[J]. 地理科学, 2016, 36(11): 1697-1705. doi: 10.13249/j.cnki.sgs.2016.11.012
	[ Wang Zhaofeng, Li Dan. Regional tourism space cooperation efficiency evaluation and difference change based on traffic network: A case of the Western Hunan, China[J]. Scientia Geographica Sinica, 2016, 36(11): 1697-1705.] doi: 10.13249/j.cnki.sgs.2016.11.012
[27]	Chen A, Bi Z, Li F. Spatial disparity and influencing factors of coupling coordination development of economy-environment-tourism-traffic: A case study in the middle reaches of Yangtze River urban agglomerations[J]. International Journal of Environmental Research and Public Health, 2021, 18(15): 7947. doi: 10.3390/ijerph18157947
[28]	湖南省统计局. 湖南统计年鉴[M]. 北京: 中国统计出版社, 2020.
	[ Statistical Bureau of Hunan Province. Hunan Statistical Yearbook[M]. Beijing: China Statistics Press, 2020.]
[29]	陈莲芳, 严良. 基于复合区位熵的中国油气资源产业集群识别[J]. 中国人口·资源与环境, 2012, 22(2): 152-158.
	[ Chen Lianfang, Yan Liang. Indentification of industrial clusters of oil and gas in China based on composite location quotient[J]. China Population, Resources and Environment, 2012, 22(2): 152-158.]
[30]	麻学锋, 张艳芳. 山地旅游区空间聚散效应及影响因素分析: 以武陵山片区为例[J]. 中国生态旅游, 2022, 12(6): 923-937. doi: 10.12342/zgstly.20220001
	[ Ma Xuefeng, Zhang Yanfang. Research on the spatial aggregation-diffusivity effect and analysis of its influencing factors in mountainous tourism area: A case study of Wuling Mountain area[J]. Journal of Chinese Ecotourism, 2022, 12(6): 923-937.] doi: 10.12342/zgstly.20220001
[31]	Gutiérrez J. Location, economic potential and daily accessibility: An analysis of the accessibility impact of the high-speed line Madrid-Barcelona-French border[J]. Journal of Transport Geography, 2001, 9(4): 229-242. doi: 10.1016/S0966-6923(01)00017-5
[32]	焦胜, 张冰洁, 韩宗伟. 近70年湘西地区陆路可达性及经济联系时空演变[J]. 经济地理, 2020, 40(6): 137-146.
	[ Jiao Sheng, Zhang Bingjie, Han Zongwei. Spatial-temporal evolution of land transportation accessibility and economic contact in Xiangxi area in recent 70 years[J]. Economic Geography, 2020, 40(6): 137-146.]
[33]	王丽, 邓羽, 刘盛和, 等. 基于改进场模型的城市影响范围动态演变: 以中国中部地区为例[J]. 地理学报, 2011, 66(2): 189-198.
	[ Wang Li, Deng Yu, Liu Shenghe, et al. The study of urban spheres of influence based on improved field model and its applications: A case study of central China[J]. Acta Geographica Sinica, 2011, 66(2): 189-198.]
[34]	侯秀英, 邱荣祖, 林玉英, 等. 交通可达性反贫困作用的空间分异分析: 以福建省为例[J]. 资源科学, 2019, 41(11): 2094-2106. doi: 10.18402/resci.2019.11.12
	[ Hou Xiuying, Qiu Rongzu, Lin Yuying, et al. Spatial differentiation of the anti-poverty effects of traffic accessibility at the county level: A case of Fujian Province[J]. Resources Science, 2019, 41(11): 2094-2106.] doi: 10.18402/resci.2019.11.12
[35]	Wang J H, Ma J W. Has tourism industry agglomeration improved the total factor productivity of Chinese urban agglomerations? —The moderating effect of public epidemic[J]. Frontiers in Public Health, 2022, 10: 854681. doi: 10.3389/fpubh.2022.854681
[36]	郭向阳, 穆学青, 丁正山, 等. “交旅”融合下旅游效率与高速交通协调格局研究: 以长三角41市为例[J]. 地理研究, 2021, 40(4): 1042-1063. doi: 10.11821/dlyj020200390
	[ Guo Xiangyang, Mu Xueqing, Ding Zhengshan, et al. The coordination pattern of tourism efficiency and high-speed transportation: A case study of 41 cities in the Yangtze River Delta[J]. Geographical Research, 2021, 40(4): 1042-1063.] doi: 10.11821/dlyj020200390
[37]	苗长虹, 魏也华, 吕拉昌. 新经济地理学[M]. 北京: 科学出版社, 2011.
	[ Miao Changhong, Wei Yehua, Lv Lachang. New Economic Geographies[M]. Beijing: Science Press, 2011.]

区县	2000年	2010年	2019年	区县	2000年	2010年	2019年
永顺	68.933	89.954	94.326	麻阳	7.904	8.105	9.895
龙山	53.872	50.731	77.035	会同	68.613	171.469	181.208
凤凰	201.110	224.990	225.234	芷江	94.609	124.423	100.154
保靖	57.000	65.471	127.343	中方	30.735	44.151	46.412
泸溪	109.118	125.896	130.540	通道	16.000	120.408	181.590
花垣	18.090	21.168	116.896	靖州	127.631	141.220	183.681
吉首	18.350	38.972	153.301	新晃	174.110	174.434	125.266
古丈	120.000	159.734	170.163	鹤城	6.740	13.053	89.882
溆浦	17.667	23.139	79.739	桑植	33.857	85.690	137.234
洪江	101.652	145.738	153.436	慈利	114.269	88.453	190.547
辰溪	30.413	36.323	46.820	永定	170.841	211.461	383.380
沅陵	8.016	13.810	88.237	武陵源	430.760	224.990	204.870

变量	普通回归模型（OLS）	空间滞后模型（SLM）	空间误差模型（SEM）
_cons	-0.098	—	—
X₁	0.082	0.114^**	0.111^**
X₂	0.142	0.081	0.082
X₃	0.680^***	0.780^***	0.786^***
X₄	-0.212^**	-0.023	-0.024
X₅	0.123	-0.134	-0.133
X₆	0.013	0.073	0.078
X₇	0.315^***	0.348^***	0.341^***
ρ	—	-0.019	—
λ	—	—	0.025
R²	0.664	0.684	0.679
Log-Likelihood	—	66.225	66.219
AIC	-102.126	-114.451	-114.438

Spatiotemporal evolution and influencing mechanisms of the agglomeration field in tourist towns in Xiangxi region driven by transportation

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 7

References 37

Related Articles 3

Metrics

Comments

年份	空间对象	公路					铁路		默认值
年份	空间对象	高速公路	国道	省道	县道	乡道	高速铁路	普通铁路	非道路区域
2000	速度（km/h）	—	80	60	40	20	—	60	5
2000	时间成本（min）	—	0.75	1	1.5	3	—	1	12
2010	速度（km/h）	100	80	60	40	30	—	100	5
2010	时间成本（min）	0.6	0.75	1	1.5	2	—	0.6	12
2019	速度（km/h）	100	80	60	40	30	300	120	5
2019	时间成本（min）	0.6	0.75	1	1.5	2	0.2	0.5	12

[1]	Yu Hu. Tourism cities in the decentralized perspective: From spatial imbalance to equilibrium development [J]. ECOTOURISM, 2022, 12(6): 1021-1037.
[2]	Ma Xuefeng, Zhang Yanfang. Research on the spatial aggregation-diffusivity effect and analysis of its influencing factors in mountainous tourism area: A case study of Wuling Mountain area [J]. ECOTOURISM, 2022, 12(6): 923-937.
[3]	WANG Zhaofeng, TANG Guilin, ZHANG Haiyan. Research on the coupling of tourism urbanization and ecosystem service value in Zhangjiajie [J]. ECOTOURISM, 2021, 11(5): 780-797.