摘要
为提升黄河冰凌监测的准确性与效率,克服传统人工观测在精度和效率上的局限,通过整合卫星遥感、无人机遥感及视频监控技术,开展基于多源数据的黄河冰凌监测技术研究。该技术能够利用多光谱遥感影像结合雪被指数法,实现对河道冰凌的全面监测,同时,借助无人机自动识别技术精确获取冰凌的关键参数,并通过视频监控技术实时发现并预警冰凌密度变化。在这项研究中,无人机遥感参数的误差被控制在5%以内,视频监控技术的误差最大为7.2%,最小仅为0.1%。基于多源数据的冰凌监测技术在山东黄河河务局的应用表明:该技术不仅显著提高工作效率,还变革传统的冰凌监测模式,极大地支撑河道管理及相关业务工作,对高纬度地区河流冰凌灾害的智能监测预警具有重要价值,也为可视化冰情分析提供可靠的图像成果,未来有着广泛的应用潜力。
To enhance the accuracy and eficiency of Yellow River ice floe monitoring and overcome the limitations of precision and efficiency in taditional mamal observations.this study integrates satellite remote sensing.umanmed aenial vehicle(UAV)remote sensing.and video survillance techmologies to cary out research on ice floe monitoring technology based on muli-source data.This techmology can utilize multispectal remote sensing images combined with the snow cover index method to achieve comprehensive monitoring of niver ice floe.Meanwhile.it precisely obtains key parameters of ice floe with UAV automatic recogmition technology and detects and wams about changes in ice floe density in real time through video survillance techmology.In this research.the eror margin for UAV remote sensing parameters is controlled within 5%,and the error for video surveillance technology ranges fom a maxium of 7.2%down to a minimum of only 0.1%.Applications by Shandong Yellow River Conservancy Bureau indicate that this techmology not only significantly improves work efciency but also revolutionizes the taditional ice floe monitoring mode.greatly supporting river management and related operations.It bholds significant value for itelligent monitoring and early waming of niver ice disasters in high latitude regions and also provides reliable image results for visual ice condition analysis,demonstating broad application potential in the future.
作者
冯士贺
于苹苹
段同苑
刘俊杰
FENG Shihe;YU Pingping;DUAN Tongyuan;LIU Junjie(Shandong Yellow River Information Center,Shandong Yellow River Affairs Bureau,Ji'nan 250013,China)
出处
《水利信息化》
2024年第4期27-32,共6页
Water Resources Informatization
关键词
黄河冰凌监测
多源数据
卫星遥感
无人机遥感
视频监控
冰凌密度
流速估计
可视化冰情分析
Yellow River ice floe monitoring:multi-source data
satellite remote sensing
UAV remote sensing:video surveillance
ice floe density
flow rate estimation
visual ice condition analysis
