世界核地质科学2025，Vol.42Issue(2)：374-384,11.
基于多任务学习的遥感影像道路属性信息获取方法及其在核电站周边区域的应用
A method for extracting road attribute information from remote sensing images based on multi-task learning and its application in the periphery of nuclear power plants
摘要
Abstract
Roads,as typical man-made objects,have attracted considerable attention in the field of remote sensing.Previous research has predominantly focused on geometrical feature extraction,with relatively insufficient attention paid to road attribute information such as material,classification,and surrounding features.However,road attribute information is crucial for road management,urban planning,and more.Considering the inherent engineering and geographical relationships among these road attributes,this study adopts a multi-task learning approach.We propose a method for extracting road attributes from visible remote sensing images based on multi-task learning,utilizing a residual network integrated with a channel attention module as the backbone.This is further enhanced with a foreground auxiliary module and a feature pyramid module to augment the focus on road targets and the capability for multi-scale processing.Ultimately,the study achieves the classification of road material,classification,and surrounding feature types(background)in visible remote sensing images.and proved the overall accuracy of the network,demonstrating that convolutional networks can effectively extract features and learn engineering and geographical relationships.In the application to the periphery of a nuclear power plants,this method addressed the complex environment and strategic importance of nuclear facilities,validating its effectiveness in practical scenarios,which is of significant importance for ensuring the safe operation of nuclear power plants and the rational planning of surrounding areas.关键词
多任务机器学习/高分辨率遥感影像/遥感场景分类/道路材质/道路分级Key words
multi-task machine learning/high-resolution remote sensing images/remote sensing image classification/road material/road classification分类
信息技术与安全科学引用本文复制引用
苏铁桓,秦凯,赵英俊,安梓嘉,郝予希..基于多任务学习的遥感影像道路属性信息获取方法及其在核电站周边区域的应用[J].世界核地质科学,2025,42(2):374-384,11.基金项目
国家自然科学基金(编号:41602333)资助 Supported by National Natural Science Foundation of China (No.41602333) （编号:41602333）
