摘要
在建设“全域旅游”的背景下,区域尺度的游憩服务发展将从单一景点景区的建设转向旅游目的地的综合统筹,助力乡村振兴和区域协调发展。然而,在全域旅游“连点成片”的过程中,如何根据本地独特的环境禀赋识别出具有较高游憩潜力的区域并据此评估发展的优先程度,仍是研究与实践的热点和难点。基于此,本研究以鄂西地区为例,引入生态系统文化服务理论中潜力评估的研究方法,运用社会-生态多源数据构建了一个结合集成机器学习的SDM模型。该模型对研究区域内336个已知游憩服务热点的环境特征进行了剖析,并预测了连续空间中高游憩潜力区域的概率分布。本研究提供了一条从环境特征变量数值关系角度理解区域尺度游憩空间规律的技术路径,旨在为全域旅游和乡村振兴的空间发展策略提供参考。
Under the call for“all-for-one tourism”development,the focus of regional-scale recreational services is shifting from the construction of individual scenic spots and tourist areas towards the comprehensive planning of tourist destinations,so as to propel China’s rural revitalization and regional coordinated development.In research and practice,however,it is still challenging to identity and evaluate spatial locations for developing tourism according their cultural and environmental resource and characteristics and prioritizing the high-potential ones.Employing the whole western Hubei region as a case study,this paper proposes a method of assessing recreation potential within the research framework on cultural ecosystem services,and uses multi-sourced socialecological data to develop an SDM model via ensemble machine learning.Through analyses of the environmental features of 336 recreational hotspots in the study area,the model predicts the areas with high recreation potential in continuous areas.This study intends to establish a technique path to examine the regional-scale pattern of recreational spaces via numerical analysis of environmental features,and to provide a reference for relevant spatial development strategies of all-for-one tourism and rural revitalization.
作者
文晨
茶静
徐利权
徐海韵
WEN Chen;CHA Jing;XU Liquan;XU Haiyun(School of Architecture and Urban Planning,Huazhong University of Science and Technology,Wuhan 430074,China;Key Laboratory of City Simulation,Ministry of Natural Resources,Wuhan 430074,China;Built Heritage Research Center,Huazhong University of Science and Technology,Wuhan 430074,China;School of Architecture and Urban Planning,Beijing University of Civil Engineering and Architecture,Beijing 100044,China)
出处
《景观设计学（中英文）》
CSCD
2022年第5期8-31,共24页
Landscape Architecture Frontiers
关键词
全域旅游
游憩服务
生态系统文化服务
空间潜力预测
机器学习
鄂西
All-for-One Tourism
Recreational Services
Cultural Ecosystem Services
Spatial Potential Prediction
Machine Learning
Western Hubei
