摘要
运用平均最邻近、网格维数、核密度、空间自相关分析方法,研究淮河生态经济带优良景区空间结构及影响因素.结果表明:优良景区空间单元上呈凝聚类型,总体态势“东北多,西南少,中部凹”,不同景区级别表现出差异化分布格局;优良景区空间密度表现出由东北至西南递减的空间格局,整体上呈“人”字形走向;优良景区空间分形特征明显,单元尺度围绕徐州、济宁、枣庄、宿迁、淮安等主要城市集聚分布,总体上趋于均衡发展态势,空间复杂性强;优良景区空间格局上呈现显著的相关性,“高—高”集聚区主要位于东北地区,“低—低”集聚区主要位于中部地区;优良景区空间结构主要受区域经济水平、人口数量、交通条件、河流水文状况以及历史文化底蕴等因素影响.
The spatial structure and influencing factors of excellent grade tourist attractions in the Huaihe river ecological economic belt were studied by means of mean nearest neighbor,grid dimension,kernel density and spatial autocorrelation analysis.The results show that Huaihe river economic belt excellent grade tourist attractions distribution type is mainly condensed type.The overall pattern presents“northeast more,southwest less,central concave”distribution characteristics,and different levels of tourist attractions present alienation distribution situation.The spatial density characteristics of excellent grade tourist attractions show a decreasing spatial pattern from northeast to southwest,and the overall trend is shaped like the Chinese character“ren”.The excellent grade tourist attractions have obvious fractal characteristics in spatial distribution.Generally,they cluster and distribute around Xuzhou,Jining,Zaozhuang,Suqian,Huai’an and other major cities,and generally show a trend of balanced development with strong spatial complexity.The excellent grade tourist attractions’spatial pattern shows a significant correlation,the“high-high”cluster mainly in the northeast region,while the“low-low”cluster is mainly in the central region.The spatial structure of fine scenic spots is mainly affected by regional economic level,population,traffic conditions,river hydrological conditions and historical and cultural deposits.
作者
杨晴晴
杨效忠
YANG Qingqing;YANG Xiaozhong(School of Geography and Tourism,Anhui Normal University,Wuhu 241000,China)
出处
《南阳师范学院学报》
CAS
2020年第3期1-9,共9页
Journal of Nanyang Normal University
基金
国家自然科学基金资助项目(41471129)。
关键词
淮河生态经济带
优良景区
空间结构
影响因素
Huaihe river ecological economic belt
excellent grade tourist attractions
spatial structure
influencing factors