中国生态旅游 ›› 2023, Vol. 13 ›› Issue (3): 380-393.doi: 10.12342/zgstly.20230042
收稿日期:
2023-04-10
修回日期:
2023-06-15
出版日期:
2023-06-28
发布日期:
2023-08-04
通讯作者:
*王凯(1969-),男,教授,博士生导师,研究方向为低碳经济、区域旅游发展规划研究。E-mail: kingviry@163.com作者简介:
谭佳欣(1997-),女,博士研究生,研究方向为区域旅游地理研究,E-mail: tanjiaxin1997@163.com
基金资助:
Tan Jiaxin1(), Ma Xuefeng2, Wang Kai1,*(
)
Received:
2023-04-10
Revised:
2023-06-15
Published:
2023-06-28
Online:
2023-08-04
Contact:
*Wang Kai. E-mail: kingviry@163.com摘要:
交通基础设施在区域旅游一体化建设中发挥着重要作用,对旅游城镇集聚格局的形成和优化具有显著影响。本研究运用复合区位熵和加权平均旅行时间,测度湘西地区2000—2019年旅游城镇集聚水平和交通可达性,借助改进的场强模型和空间计量模型,探讨旅游业发展典型区域的旅游城镇集聚场强时空演化特征及影响机制。研究表明:(1)研究期内湘西地区旅游城镇集聚场强值和交通可达性呈不断提升的态势,交通最优辐射范围在1.6h以内。(2)旅游城镇集聚场强空间格局经历了由“单向主导型”到“双向互动型”的动态演变过程,具体表现为以凤凰为主的高场强区转向以武陵源、永定和凤凰为龙头形成的三大高场强区;交通可达性表现为以中部地区为中心沿南北轴线扩散的不规则圈层结构。(3)在资源禀赋、产业结构和人居环境状况等因素的综合影响下,通过改善交通条件而带来的时空压缩效应,促进旅游城镇人口、土地和产业等要素聚集,提升地方旅游经济效率,并增加资源利用的机会成本,进而推动旅游城镇集聚空间结构实现了由“单中心”向“多中心”的转变。
谭佳欣, 麻学锋, 王凯. 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[J]. 中国生态旅游, 2023, 13(3): 380-393.
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.
表2
湘西地区旅游城镇集聚场强值
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 |
表3
回归结果
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 |
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