基于多源数据的黄河冰凌监测技术研究

Research on Yellow River ice flfl oe monitoring technology based on multi-source data

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。

Abstract:

To enhance the accuracy and effi ciency of Yellow River ice fl oe monitoring and overcome the limitations ofprecision and effi ciency in traditional manual observations，this study integrates satellite remote sensing，unmannedaerial vehicle（ UAV） remote sensing，and video surveillance technologies to carry out research on ice fl oe monitoringtechnology based on multi-source data. This technology can utilize multispectral remote sensing images combinedwith the snow cover index method to achieve comprehensive monitoring of river ice fl oe. Meanwhile，it preciselyobtains key parameters of ice fl oe with UAV automatic recognition technology and detects and warns about changes inice fl oe density in real time through video surveillance technology. In this research，the error margin for UAV remotesensing parameters is controlled within 5%，and the error for video surveillance technology ranges from a maximumof 7.2% down to a minimum of only 0.1%. Applications by Shandong Yellow River Conservancy Bureau indicatethat this technology not only significantly improves work efficiency but also revolutionizes the traditional ice floemonitoring mode，greatly supporting river management and related operations. It holds signifi cant value for intelligentmonitoring and early warning of river ice disasters in high-latitude regions and also provides reliable image results forvisual ice condition analysis，demonstrating broad application potential in the future.