资源科学 ›› 2018, Vol. 40 ›› Issue (6): 1196-1208.doi: 10.18402/resci.2018.06.10
收稿日期:
2017-06-22
修回日期:
2017-11-27
出版日期:
2018-06-25
发布日期:
2018-06-22
作者简介:
作者简介:吴春涛,女,四川德阳人,副教授,硕士生导师,主要研究方向为旅游企业及目的地管理、航空旅游和城市旅游。E-mail:
基金资助:
Chuntao WU1(), Longjie LI1, Xiaohe HE1, Jiaoe WANG2,3(
)
Received:
2017-06-22
Revised:
2017-11-27
Online:
2018-06-25
Published:
2018-06-22
摘要:
长江经济带的联动发展及生态廊道建设使旅游景区的空间分布出现剧烈变化,研究旅游景区的空间变化对旅游基础设施的合理布局、制定长江黄金旅游带规划以及实现旅游经济腾飞具有重要作用。本文选取2012年和2016年长江经济带九省二市的旅游景区空间点位数据,综合运用标准差椭圆、平均最近邻分析以及核密度等方法分析了长江经济带旅游景区的空间演变特征。结果表明:长江经济带旅游景区总体分布格局基本沿长江水系发生聚集,聚集程度随时间的推移不断加深;相关政策促进、旅游业市场需求持续增加、交通可达性优化等多重因素的综合作用使区域景区聚集加速;城市休闲型景区以及主题公园兴建为城市景区聚集提供新动力。
吴春涛, 李隆杰, 何小禾, 王姣娥. 长江经济带旅游景区空间格局及演变[J]. 资源科学, 2018, 40(6): 1196-1208.
Chuntao WU, Longjie LI, Xiaohe HE, Jiaoe WANG. Spatial analysis of scenic spots in the Yangtze River Economic Belt[J]. Resources Science, 2018, 40(6): 1196-1208.
表1
2012—2016年长江经济带旅游景区空间分布与变化"
2012年景区 数量/个 | 2016年景区 数量/个 | 景区 增量/个 | 景区数量 增幅/% | |
---|---|---|---|---|
云南 | 140 | 230 | 90 | 64.286 |
四川 | 225 | 383 | 158 | 70.222 |
贵州 | 93 | 178 | 85 | 91.398 |
重庆 | 123 | 209 | 86 | 69.919 |
湖北 | 248 | 280 | 32 | 12.903 |
湖南 | 185 | 298 | 113 | 61.081 |
江西 | 131 | 236 | 105 | 80.153 |
安徽 | 388 | 529 | 141 | 36.340 |
江苏 | 515 | 627 | 112 | 21.748 |
浙江 | 315 | 336 | 21 | 6.667 |
上海 | 73 | 85 | 12 | 16.438 |
总体 | 2 436 | 3 391 | 955 | 39.203 |
Table 2
Distribution of new emerging and delisted scenic spots in the Yangtze River Economic Belt from 2012 to 2016 (个)"
新增人文景区数量 | 新增自然景区数量 | 新增景区总量 | 消失人文景区数量 | 消失自然景区数量 | 消失景区总量 | |
---|---|---|---|---|---|---|
云南 | 75 | 24 | 99 | 6 | 2 | 8 |
四川 | 136 | 43 | 179 | 14 | 6 | 20 |
贵州 | 55 | 41 | 96 | 8 | 2 | 10 |
重庆 | 76 | 26 | 102 | 10 | 5 | 15 |
湖北 | 62 | 14 | 76 | 28 | 20 | 48 |
湖南 | 79 | 43 | 122 | 8 | 1 | 9 |
江西 | 91 | 30 | 121 | 10 | 6 | 16 |
安徽 | 171 | 37 | 208 | 47 | 18 | 65 |
江苏 | 135 | 44 | 179 | 60 | 8 | 68 |
浙江 | 41 | 20 | 61 | 35 | 6 | 41 |
上海 | 18 | 2 | 20 | 8 | 0 | 8 |
合计 | 939 | 324 | 1263 | 234 | 74 | 308 |
Table 3
Classification of new emerging human scenic spots in the Yangtze River Economic Belt from 2012 to 2016 (个)"
康养娱乐 类景区 | 观光农业 类景区 | 特色旅游小镇类景区 | 主题公园类景区 | 遗产遗迹 类景区 | 教育展示 类景区 | 购物消费街区类景区 | 古城镇 类景区 | |
---|---|---|---|---|---|---|---|---|
云南 | 6 | 6 | 13 | 11 | 12 | 14 | 1 | 12 |
四川 | 5 | 36 | 13 | 20 | 16 | 12 | 5 | 29 |
贵州 | 8 | 12 | 4 | 13 | 1 | 4 | 2 | 11 |
重庆 | 7 | 13 | 5 | 21 | 2 | 16 | 1 | 11 |
湖北 | 9 | 8 | 5 | 12 | 11 | 11 | 2 | 4 |
湖南 | 7 | 9 | 5 | 15 | 12 | 18 | 0 | 13 |
江西 | 11 | 12 | 7 | 18 | 13 | 18 | 1 | 11 |
安徽 | 23 | 30 | 7 | 34 | 24 | 43 | 2 | 8 |
江苏 | 7 | 11 | 8 | 39 | 26 | 34 | 1 | 9 |
浙江 | 9 | 3 | 4 | 7 | 4 | 5 | 1 | 8 |
上海 | 0 | 5 | 1 | 6 | 2 | 2 | 0 | 2 |
合计 | 92 | 145 | 72 | 196 | 123 | 177 | 16 | 118 |
Table 4
Classification of delisted human scenic spots in the Yangtze River Economic Belt from 2012 to 2016 (个)"
康养娱乐 类景区 | 观光农业 类景区 | 特色旅游小镇类景区 | 主题公园类景区 | 遗产遗迹 类景区 | 教育展示 类景区 | 购物消费街区类景区 | 古城镇 类景区 | |
---|---|---|---|---|---|---|---|---|
云南 | 1 | 2 | 0 | 0 | 2 | 0 | 0 | 1 |
四川 | 1 | 1 | 2 | 2 | 0 | 4 | 0 | 4 |
贵州 | 0 | 2 | 0 | 3 | 0 | 0 | 0 | 3 |
重庆 | 5 | 1 | 0 | 3 | 1 | 0 | 0 | 0 |
湖北 | 5 | 1 | 4 | 3 | 6 | 8 | 0 | 1 |
湖南 | 3 | 0 | 0 | 1 | 2 | 2 | 0 | 0 |
江西 | 0 | 2 | 1 | 1 | 0 | 4 | 1 | 1 |
安徽 | 3 | 8 | 6 | 11 | 5 | 8 | 0 | 6 |
江苏 | 5 | 13 | 2 | 11 | 12 | 13 | 3 | 1 |
浙江 | 4 | 5 | 6 | 7 | 5 | 4 | 1 | 3 |
上海 | 0 | 2 | 1 | 1 | 1 | 1 | 0 | 2 |
合计 | 27 | 37 | 22 | 43 | 34 | 44 | 5 | 22 |
表5
2012—2016年长江经济带各省市平均观测距离与平均最近邻指数"
2012年 | 2016年 | ||||||||
---|---|---|---|---|---|---|---|---|---|
平均观测距离 | 预期平均距离 | 平均最近邻指数 | P值 | 平均观测距离 | 预期平均距离 | 平均最近邻指数 | P值 | ||
云南 | 22.158 | 34.872 | 0.635 | 0.000** | 13.927 | 25.183 | 0.553 | 0.000** | |
四川 | 15.753 | 24.120 | 0.653 | 0.000** | 12.346 | 19.365 | 0.638 | 0.000** | |
贵州 | 16.666 | 22.967 | 0.726 | 0.000** | 11.750 | 17.277 | 0.680 | 0.000** | |
重庆 | 11.321 | 17.923 | 0.632 | 0.000** | 8.082 | 14.034 | 0.576 | 0.000** | |
湖北 | 12.145 | 18.229 | 0.666 | 0.000** | 9.401 | 15.629 | 0.602 | 0.000** | |
湖南 | 13.001 | 18.017 | 0.722 | 0.000** | 10.292 | 14.268 | 0.721 | 0.000** | |
江西 | 13.746 | 20.084 | 0.684 | 0.000** | 9.605 | 14.529 | 0.661 | 0.000** | |
安徽 | 7.311 | 12.128 | 0.603 | 0.000** | 5.972 | 10.114 | 0.590 | 0.000** | |
江苏 | 4.475 | 8.708 | 0.514 | 0.000** | 4.641 | 7.899 | 0.588 | 0.000** | |
浙江 | 7.533 | 10.385 | 0.725 | 0.000** | 7.710 | 10.373 | 0.743 | 0.000** | |
上海 | 5.243 | 6.040 | 0.868 | 0.035* | 4.281 | 5.579 | 0.767 | 0.000** | |
总体 | 9.833 | 17.943 | 0.548 | 0.000** | 8.197 | 15.071 | 0.544 | 0.000** |
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