[1]高 巍,郑文婷,孙鲁桐,等.基于“GIS-GNN”空间评估模型的历史文化街区潜力点识别、评估与更新策略——以青岛中山路为例[J].中国名城,2025,39(12):3.[doi:10.19924/j.cnki.1674-4144.2025.012.001]
　GAO Wei,ZHENG Wenting,SUN Lutong,et al.Potential Points Identification, Evaluation, and Renewal Strategy of Historical and Cultural Blocks Based on the "GIS-GNN" Spatial Evaluation Model: A Case Study of Zhongshan Road in Qingdao City[J].China Ancient City,2025,39(12):3.[doi:10.19924/j.cnki.1674-4144.2025.012.001]
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基于“GIS-GNN”空间评估模型的历史文化街区潜力点识别、评估与更新策略——以青岛中山路为例()

中国名城[ISSN:1674-4144/CN:32-1793/GO]

卷:
39
期数:
2025年12期
页码:
3
栏目:
出版日期:
2025-12-05

文章信息/Info

Title:
Potential Points Identification, Evaluation, and Renewal Strategy of Historical and Cultural Blocks Based on the "GIS-GNN" Spatial Evaluation Model: A Case Study of Zhongshan Road in Qingdao City
文章编号:
1674-4144（2025）012-0003-11
作者:
高 巍; 郑文婷; 孙鲁桐; 赵 玫; 杨皓晨; 焦子怡
高 巍，北京交通大学建筑与艺术学院教授；郑文婷，北京交通大学建筑与艺术学院硕士研究生；孙鲁桐（通信作者），北京交通大学建筑与艺术学院硕士研究生；赵 玫，北京理工大学设计与艺术学院副教授；杨皓晨，北京交通大学建筑与艺术学院硕士研究生；焦子怡，北京交通大学建筑与艺术学院硕士研究生。
Author(s):
GAO Wei; ZHENG Wenting; SUN Lutong; ZHAO Mei; YANG Haochen; JIAO Ziyi
关键词:
历史文化街区; 图神经网络; 潜力点识别; 评估; 城市更新
Keywords:
historical and cultural blocks; graph neural network; potential points identification; evaluation; urban renewal
分类号:
13
DOI:
10.19924/j.cnki.1674-4144.2025.012.001
文献标志码:
A
摘要:
在当前城市化进程中，历史文化街区普遍面临着功能结构复杂、保护单元碎片化和保护更新方法不足的问题，为全面感知街区的历史文化价值带来挑战。基于上述问题，构建结合地理信息系统（GIS）与图神经网络(GNN)的历史街区空间评估模型，提出“高潜力空间挖掘—潜力点识别—文化感知优化”的街区更新路径。以青岛市中山路历史文化街区为实证对象，基于开源路网数据、兴趣点（POI）数据和街景图像，从交通效率、空间活力和视觉感知维度评估街区空间品质与潜力，识别出关键潜力点，旨在整合分散的保护性单元和热点空间，从而提升街区文化感知的连续性和可持续性，提出街区IP和主题游线规划策略，为历史街区保护和更新提供了新的思路和可操作框架。
Abstract:
In the current urbanization process, historical and cultural blocks generally face problems in terms of complex functional structures, fragmented protection units, and insufficient protection and renewal methods, which pose challenges to comprehensively perceiving the historical and cultural value. Based on the above issues, the authors have constructed a spatial evaluation model combining Geographic Information Systems (GIS) and Graph Neural Networks (GNN), and proposed a renewal path of "High Potential Space Mining-Potential Point Recognition-Cultural Perception Optimization". With open-source road network data, point of interest (POI) data, and street view images, this study takes Zhongshan Road Historical and Cultural District in Qingdao City as the empirical object, and evaluates the spatial quality and potential of the district from three dimensions: traffic efficiency, spatial vitality, and visual perception key potential points are identified with the aim of integrating scattered protective units and hotspot spaces to enhance the continuity and sustainability of cultural perception in the district. It identifies 48 potential spatial points to effectively alleviate the problem of insufficient continuity in current hotspot spaces, proposes strategies for block’ IP and themed tour line planning, and provides new ideas and operational frameworks for historical blocks protection and renovation.

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更新日期/Last Update: 2025-12-15