热带气象学报2024，Vol.40Issue(6)：918-930,13.DOI:10.16032/j.issn.1004-4965.2024.080
一种基于深度学习的城市道路积水内涝图像识别方法
A Method for Urban Road Waterlogging Image Recognition Based on Deep Learning
摘要
Abstract
To enhance the monitoring and early warning capabilities for waterlogging in megacities,this study addressed the low practicality and insufficient real-time performance of existing waterlogging detection methods through the use of a high-density network of over 90,000 public surveillance cameras in Guangzhou.A road waterlogging image recognition method was established based on the RTMDet model,a deep-learning-based object detection algorithm.Multithreading technology was employed to efficiently acquire images from a large number of cameras.The RTMDet model with instance segmentation capabilities enables rapid detection and identification of waterlogging areas.A set of 8463 images,collected between August 15,2018,and May 23,2020,was used to develop the recognition model.The model was then validated and evaluated using 6106 images collected between June 25,2020,and September 10,2022.The results indicate that during intense precipitation,the model can accurately identify images of obvious waterlogging and the locations of these waterlogged areas.After data cleaning,the overall recognition accuracy of the model was 86.60%.Light interference and image blurring due to precipitation were the two primary factors causing false alarms.Currently,this algorithm has been implemented in Guangzhou's meteorological impact forecasting verification and meteorological decision-making support platform,providing effective support for automatic monitoring and early warning of urban waterlogging.It also offers valuable insights for water management,transportation,and other relevant sectors.关键词
内涝/图像识别/深度学习/公共监控视频Key words
waterlogging/image recognition/deep learning/public surveillance camera分类
天文与地球科学引用本文复制引用
张志坚,伍光胜,黎洁仪,陈雨欣,张静,孙伟忠..一种基于深度学习的城市道路积水内涝图像识别方法[J].热带气象学报,2024,40(6):918-930,13.基金项目
广州市科技计划项目(201803030014) （201803030014）
广州市科技重点研发计划(广州市智慧气象科技协同创新中心建设项目2023B04J0704)共同资助 （广州市智慧气象科技协同创新中心建设项目2023B04J0704）
