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1.贵州师范大学 地理与环境科学学院,贵州 贵阳 550025
2.中国科学院 地理科学与资源研究所,北京 100101
3.南京师范大学 地理科学学院,江苏 南京 210023
李瑞,男,博士,副教授,从事旅游地开发与影响研究,liruigznu2008@163.com。
纸质出版日期:2024-08-25,
收稿日期:2023-11-21,
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李瑞, 黄梅, 王忠玲, 等. 喀斯特山地旅游地生态系统文化服务的空间分异及其影响因素—以黔西南州万峰林景区为例[J]. 西北大学学报(自然科学版), 2024,54(4):601-614.
LI Rui, HAUNG Mei, WANG Zhongling, et al. The spatial differentiation and influencing factors of ecosystem cultural services in karst mountainous tourism destinations—Taking Wanfenglin scenic spot in Southwest Guizhou of China as an example[J]. Journal of Northwest University (Natural Science Edition), 2024,54(4):601-614.
李瑞, 黄梅, 王忠玲, 等. 喀斯特山地旅游地生态系统文化服务的空间分异及其影响因素—以黔西南州万峰林景区为例[J]. 西北大学学报(自然科学版), 2024,54(4):601-614. DOI: 10.16152/j.cnki.xdxbzr.2024-04-004.
LI Rui, HAUNG Mei, WANG Zhongling, et al. The spatial differentiation and influencing factors of ecosystem cultural services in karst mountainous tourism destinations—Taking Wanfenglin scenic spot in Southwest Guizhou of China as an example[J]. Journal of Northwest University (Natural Science Edition), 2024,54(4):601-614. DOI: 10.16152/j.cnki.xdxbzr.2024-04-004.
喀斯特山地旅游地是一个典型的社会-生态系统,具有较高的生态系统服务价值,但针对其为公众提供的非物质收益却鲜有研究。该研究以黔西南州万峰林景区为典型案例地,采用Amazon Rekognition图像识别技术,结合社交媒体照片内容分析法、GIS空间分析法、地理探测器模型等方法,识别和分析喀斯特山地旅游地生态系统文化服务(CES)空间分异与影响因素。研究表明:①喀斯特山地旅游地具有美学、游憩、生物多样性、地方认同感、文化多元性和教育价值6种CES类型;②景区CES均存在显著的空间正相关性,总体CES热点区呈多核心分布态势,主要集聚在景区北部、中部和南部,且面积由北向南逐渐增大,形成了公众感知喀斯特峰林群和布依族文化景观的集聚区,而冷点区则少量集聚在景区中部东北向和南部东南向等区域;③距水系距离、距道路距离、高程和NDVI因子是影响总体CES的主导因子,土地利用类型、服务设施密度、村庄密度因子为次要因子,总体CES的多因子交互作用呈现出非线性增强多于双因子增强的交互类型特征,且自然与社会维度交互因子均提高了总体CES空间分异的解释力度。该研究为明晰和提升公众对喀斯特山地旅游地生态系统的非物质收益和社会文化福祉提供了实践参考。
Karst mountainous tourism destinations are typically social-ecological systems with high ecosystem service values
but there is little research on the intangible benefits they provide to the public. This study takes the Wanfenglin scenic spot in Southwest Guizhou of China as a typical case
combined with social media photo content analysis
GIS spatial analysis
geographic detector to identify and analyze the spatial differentiation and influencing factors of CES in karst mountainous tourism destinations using Amazon Rekognition image recognition technology. The results have shown that: ① Karst mountainous tourism destinations have six types of CES: aesthetics
recreation
biodiversity
local identity
cultural diversity
and educational value. ② There is a significantly and spatially positive correlation in the CES of scenic spot. The hot spots of overall CES show a multi-core distribution
mainly concentrated in the northern
central
and southern parts of the scenic spot. The covered area gradually increases from north to south
forming a gathering area for the public to perceive the karst peak forest group and Buyi minority cultural scenery. However
the cold spots are slightly concentrated in the northeast and southeast areas of the central and southern parts of the scenic spot. ③ The factors such as distance from the river system
distance from the road
elevation
and NDVI are the dominant factors affecting the overall CES; the factors such as land use type
service facility density
and village density factors are secondary factors. The multi-factor interaction of overall CES exhibits a non-linear enhancement rather than a dual factor enhancement
and natural and social dimension of interaction factors enhance the explanatory power of the spatial differentiation of overall CES. This study provides the practical reference for clarifying and enhancing the public’s understanding of the intangible benefits and social-cultural well-being of the ecosystem for karst mountainous tourism destinations.
喀斯特山地旅游生态系统文化服务照片内容分析法万峰林
karstmountainous tourismecosystem cultural servicesphoto content analysisWanfenglin
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