摘要
为了解铁路沿线工务设备植被绿化覆盖情况,采用无人机携带的数码摄像机对铁路沿线进行分辨率优于4 cm的航空摄影,并以获取的高分影像生产数字正射影像图(DOM);再通过深度学习配合人工辅助采集策略建立铁路沿线植被覆盖档案库;综合利用GIS技术实现铁路沿线绿化覆盖结果提取与线路要素的建档与集成。研究表明,该系统机器自动检测识别准确率达到85%以上,实现了基于时空数据库技术对绿化覆盖数据实时的多人协同整治管理。
In order to investigate the vegetation coverage for the permanent equipment along the railway,the digital camera carried by the UAV was used to carry out aerial photography with a high-resolution of more than 4 cm along the railway.The digital orthophoto map(DOM)was produced with the obtained high-resolution image;The vegetation coverage archives along the railway was established through deep learning and manual assistance mapping strategy;Finally,the archive and integration of the vegetation coverage and line base element along the railway was developed by GIS technology.The multi-person collaborative management of greening vegetation coverage data at actual time was enabled based on spatiotemporal database technology,and the the accuracy rate of automatic detection and recognition was more than 85%.
作者
吕晓煜
熊丹
赵振洋
LYU Xiaoyu;XIONG Dan;ZHAO Zhenyang(China Railway Design Corporation,Tianjin 300308,China;China Railway Nanchang Group Corporation,Nanchang 330002,China)
出处
《铁道勘察》
2023年第2期19-22,共4页
Railway Investigation and Surveying
基金
中国铁路设计集团有限公司科技开发计划重点课题(N2020T005)。
关键词
植被覆盖
无人机
空中检测
地理信息系统
智能识别
vegetation coverage
UAV
aerial photogrammetry
aerial detecting
geographic information system
intelligent detection
