高校地质学报2026，Vol.32Issue(2)：179-191,13.DOI:10.16108/j.issn1006-7493.2025029
基于深度学习的全新世中期古水坝智能识别:以良渚古城及其周边地区为例
Intelligent Identification of Mid-Holocene Ancient Dams Based on Deep Learning:A Case Study of Liangzhu Ancient City and Its Surrounding Areas
摘要
Abstract
Since the Middle Holocene,multiple ancient civilizations in the middle and lower reaches of the Yangtze River have constructed ancient dams for flood control and irrigation as a response to environmental changes.However,due to erosion,sedimentation and human activities,it is difficult for traditional archaeological methods to quickly identify and discover these ancient dams,which restricts the development of hydraulic archaeology.This paper proposes an efficient method for large-scale identification of ancient dams based on historical remote sensing images and deep learning technology,and evaluates the method by taking the ancient dams in Liangzhu Ancient City and its surrounding areas as research cases.This method collects aerial and satellite images from the 1940s to 1970s,labels 132 confirmed ancient dams in the study area,selects the YOLOv5 as the basic architecture,and optimizes the model by introducing the Generalized Intersection over Union(GIoU)loss function,coordinate attention mechanism and supplementary detection layer.The results show that the optimized model achieves a recall rate of 70%and a precision of 68%for ancient dams in the study area,which is significantly higher in efficiency and accuracy than traditional visual interpretation and field archaeological methods.This method provides an automatic tool for large-scale census of ancient water conservancy facilities,and is of great significance for revealing the spatio-temporal evolution characteristics of ancient water conservancy facilities,clarifying the human-land relationship model in which ancient people actively responded to environmental changes by constructing water conservancy projects under the background of climate change,and understanding the development process of ancient civilizations.关键词
古水坝/历史遥感影像/深度学习/良渚文化Key words
ancient dams/historical remote sensing images/deep learning/Liangzhu Culture分类
建筑与水利引用本文复制引用
王奕然,董少春,王晓琪,尹宏伟,张依欣,张涛..基于深度学习的全新世中期古水坝智能识别:以良渚古城及其周边地区为例[J].高校地质学报,2026,32(2):179-191,13.基金项目
可持续发展大数据国际研究中心(CBAS-南京大学节点培育项目) （CBAS-南京大学节点培育项目）
基于遥感与地理信息系统的古代水利遗迹调查关键技术研究与示范应用 （）
2024年国家文保专项-浙江省水利遗址(山塘类)调查勘探 （山塘类）
