人民长江2025，Vol.56Issue(3)：230-236,7.DOI:10.16232/j.cnki.1001-4179.2025.03.031
基于无人机全景影像的河道岸线地物变化检测方法
Variation detection of river shoreline features based on UAV panoramic image
摘要
Abstract
In order to improve detection accuracy of illegal buildings and illegal occupation targets along river shorelines,based on the Drone-YOLO target detection baseline model,and by integrating a data enhancement module that simulates the river shoreline area characteristics,and by combining the BiFPN feature pyramid network structure,a Drone-YOLO-RCD instance segmentation algorithm based on multi-scale UAV image was designed and implemented.Then,a set of ground object variation detection system was constructed according to the algorithm,and a variation detection method of river shoreline features based on UAV panoramic image was formed.The experimental results on the self-made dataset PGIS_RCD showed that compared with the Drone-YOLO benchmark algorithm,the average accuracy(mAP@0.5)of the Drone-YOLO-RCD algorithm on six types of ground objects was improved by 4.4%,which realized the accurate identification of illegal buildings and illegal occupation prob-lems,as well as the detection of ground object changes.The research results have promoted digital management on the ecological environment along river shorelines,and can provide strong technical support for scientifically grasping the range of construction ac-tivities along river shorelines.关键词
地物变化检测/河道岸线巡检/Drone-YOLO/实例分割算法/无人机全景影像Key words
detection of ground object changes/shoreline patrol inspection/Drone-YOLO/instance segmentation algorithm/UAV image分类
信息技术与安全科学引用本文复制引用
黄育华,吴念辉,陈杰,梁文俊,赵薛强,管继祥..基于无人机全景影像的河道岸线地物变化检测方法[J].人民长江,2025,56(3):230-236,7.基金项目
国家重点研发计划项目"高度城镇化地区防洪排涝实时调度决策支持平台与示范应用"(2018YFC1508206) （2018YFC1508206）
