街景图像深度学习驱动下的历史建筑普查与管控研究——以泉州为例  

Research on Historic Building Census and Management Method Driven by Deep Learning of Street View Images:A Case Study based on Quanzhou

作　　者：潘莹[1] 黄龙英 施瑛 游永熠 PAN Ying;HUANG Longying;SHI Ying;YOU Yongyi

机构地区：[1]华南理工大学建筑学院 [2]亚热带建筑与城市科学全国重点实验室 [3]广州市景观建筑重点实验室 [4]广东省城乡规划设计研究院科技集团股份有限公司

出　　处：《南方建筑》2025年第4期4-13,共10页South Architecture

基　　金：国家自然科学基金重点资助项目(51978275):基于文化地理学的岭南汉民系传统聚落景观的特征、区划与机制研究;亚热带建筑与城市科学全国重点实验室自主研究课题(2023ZB09):三生视角下华南中小型海岛人居景观解析与可持续分类营建策略。

摘　　要：历史建筑作为见证城市演化的物质载体,对于传承文脉、延续风貌具有重要意义。针对历史建筑全域普查工作量大、保护周期长、数量众多、管控困难等问题,以国家历史文化名城泉州为例,结合目标检测、图像分类等深度学习算法与GIS空间分析方法,构建由“传统风貌体系搭建-传统风貌特征检测-现代建筑区分筛除-传统建筑分布分析”组成的历史建筑智能识别模型,从泉州海量街景图像中高效采集传统建筑信息,绘制历史建筑潜在资源地图,并揭示其时空分布特征。研究表明,基于街景图像深度学习的历史建筑智能识别模型具备成本低、效率高、结果稳定等优势,能够在历史建筑普查、建档、管控工作中,通过优化资源分配、快速采集信息与动态检验管理等方式发挥技术效用,适应了宏观空间尺度下历史建筑的高效普查与动态监测需求,为历史建筑普查与管控实践流程优化提供了技术支撑。From the perspective of advancing urbanisation and renewal,historic buildings serve as crucial carriers for inheriting urban–rural contextual information and preserving the urban-rural appearance.However,it is difficult to carry out the census and management of historic buildings due to their large number and scattered distribution.It is crucial to explore a high-efficiency and convenient method that can adapt to the entire region.The emergence of artificial intelligence can help plug this gap.Combining street view big data with wide coverage and low acquisition costs,it can identify and extract traditional architectural information from images to assist surveyors in quickly screening potential historic buildings when preparing field surveys and determining the distribution characteristics of traditional building resource points on the macroscopic spatio-temporal scale.Herein,a case study based on Quanzhou,a national historical and cultural city,was carried out.Deep learning algorithms(e.g.object detection and image classification)and the GIS spatial analysis method are combined to propose an intelligent historical building recognition model composed of"establishing a traditional feature system,detecting traditional architectural features,distinguishing and screening modern buildings,and analyzing the distribution of traditional buildings"was constructed.Firstly,a traditional architectural feature system of Quanzhou—which consists of roof form,door and window styles,and decorative elements—was built according to the principles of externality,identification,and generality.It provides a basic framework for subsequent identification.Next,traditional features were recognized from all street view images of Quanzhou by using the object detection algorithm,and modern pseudo-classic architectures were then deleted using the image classification algorithm.Only street-view images of traditional buildings were retained.In addition,the accuracy of models was evaluated using the Precision,Recall,and F1 score indicators.

关 键 词：深度学习 街景图像 历史建筑 历史保护 遗产管理 泉州 

分 类 号：TU984.18[建筑科学—城市规划与设计]