| 摘要: |
| 为满足遗产地文化保护、社区生活质量提升与景区
旅游发展等多维需求，传承和完善鼓浪屿遗产地社区景观风貌
成为当下焦点。遵循“限定范围、分类人群、挖掘风貌体验需
求与兴趣点、总结体验冲突点”的鼓浪屿遗产地社区景观风貌
管理研究思路，首先以游客、本岛居民为研究对象，利用线下
问卷和社交网络文本进行调研，挖掘人们对于鼓浪屿景观风貌
现状的体验需求；其次，开展鼓浪屿POI、人流运动定位和空
间热力分布研究，分析人们的活动行为与鼓浪屿景观风貌特色
空间的联系；随后，在旅居体验与行为叠加影响下，总结出人
们对于鼓浪屿遗产地社区景观风貌的关注兴趣点和体验冲突
点；最后提出基于旅居兴趣的鼓浪屿遗产地社区景观风貌管理
建议，为今后鼓浪屿建设管理提供参考意见，对遗产地社区景
观风貌管理有一定的借鉴意义。 |
| 关键词: 风景园林 景观风貌 遗产地社区 旅居体验 多维需求 分词聚类 |
| DOI： |
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| 基金项目: |
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| Community Landscape of the World CulturalHeritage Site under the Traveling Experience—Taking Gulangyu Island in Xiamen as the Example |
| LIU Yan,DING Meichen,LAN Siren |
| Abstract: |
| To meet the multi-dimensional needs of heritage site
cultural protection, community life quality improvement and
scenic tourism development, the inheritance and improvement of
community landscape features in heritage areas has become the
focus of current research in Gulangyu Island. Following the idea
of "the limited scope, the classification of people, the demand and
interest points of exploring landscape experience, and the summary
of experience conflict points", this article takes tourists and residents
of the island as research objects, using offline questionnaires and
social network texts, to explore the need for people to experience
the current state of Gulangyu Island's landscape. Followed by POI,
location of human flow movement and spatial thermal analysis,
the study analyzes the relationship between people's activities and
the characteristic space of the Gulangyu Island landscape, and then
under the influence of the combination of the sojourn experience
and behavior, it sums up the points of interest and conflict of
experience about the community landscape of Gulangyu Island
heritage. Finally, based on the suggestions of community landscape
management of Gulangyu Island heritage sites, the paper provides
some suggestions for future construction and management of
Gulangyu Island heritage sites, which can be used for reference. |
| Key words: landscape architecture landscape style heritage site
community sojourn experience multi-dimensional needs word
segmentation clustering |
