海岸带无缝水深与地形数字高程模型（Seamless Bathymetric and Topographic Digital Elevation Models, SBT-DEM）对于海啸传播和沿海淹没建模、海岸侵蚀与淤积监测、水动力和沉积物运输建模等具有重要意义。由于常规技术难以精确地测量浅海水深，精细尺度的SBT-DEM构建一直难以实现。本研究基于无人船单波束与无人机激光雷达（Light Detection and Ranging, LiDAR）组成的无人测量系统，进行了海岸带水深与地形无缝测量实验，评估了无人船的抗风浪能力，构建了海岸精细尺度SBT-DEM，开展了海岸带地形特征分析与应用。
主要研究内容：（1）本文利用无人船单波束和无人机LiDAR进行了海岸带水深与地形数据的无缝采集，并根据测量学原理进行了坐标计算与处理，基于测深对照实验评估了无人船近海水深测量的抗风浪能力。（2）利用GIS （Geographic Information System）技术分别构建了海岸陆地与近海海底DEM，进而镶嵌得到海岸精细尺度SBT-DEM，之后对构建的SBT-DEM进行了精度评价。（3）基于构建的SBT-DEM，分析了海岸带微地形地貌特征；基于构建的海岸带地形剖面曲线，分析了不同海岸的地形特征差异；基于构建的近岸海底DEM，分析了近岸海底地形与潮沟空间特征。
主要结论：（1）风力0 ~ 2级、浪高0 ~ 0.3 m是无人船近海水深测量作业的理想阈值。（2）基于无人船单波束与无人机LiDAR组成的无人测量系统，提出的考虑潮汐变化的时空分区测量方法能够解决海岸带水深与地形的无缝测量问题。（3）提出的改进Blend镶嵌算法不仅能够实现陆地和海底DEM的无缝平滑拼接，而且能够最大程度地减少高程精度损失。（4）构建的海岸精细尺度SBT-DEM的空间分辨率高达1 m，高程误差仅为6.2 cm。
创新点：基于新兴的无人船与无人机测量技术，结合GIS空间数据处理技术，本文实现了海岸带精细尺度SBT-DEM的快速与准确构建。其中，提出的时空分区测量方法解决了海岸带水深与地形数据无缝采集难题，改进的Blend镶嵌算法实现了海岸带SBT-DEM的高精度构建。
其他摘要
The seamless bathymetric and topographic digital elevation model (SBT-DEM) is of great significance for tsunami propagation and coastal inundation modeling, coastal erosion and siltation monitoring, hydrodynamic and sediment transport modeling. Since conventional techniques are difficult to accurately measure shallow water depth, fine-scale SBT-DEM construction has been difficult to achieve. We attempt to perform coastal bathymetric and topographic surveys using an SBES (single-beam echo sounder)-equipped unmanned surface vehicle (USV) and a LiDAR (Light Detection and Ranging)-equipped unmanned aerial vehicle (UAV), and construct a fine-scale SBT-DEM using GIS (Geographic Information System) techniques.
Main research contents: (1) We collected and processed coastal bathymetry and topography data using USV SBES and UAV LiDAR. The coordinates were calculated and processed according to the principles of surveying. We quantitatively evaluated the wind and wave resistance of USVs during bathymetry based on control experiments. (2) We constructed coastal land and seabed DEMs using GIS technology, and then constructed coastal fine-scale SBT-DEM using mosaic algorithm, and finally evaluated the accuracy of the constructed SBT-DEM. (3) We analyzed the micro-topography of the coastal zone based on the fine-scale SBT-DEM, compared the topographical differences of different coastal zones, and analyzed the coastal seabed topography based on the constructed submarine DEM.
Main conclusions: (1) Wind force 0 ~ 2 and wave height 0 ~ 0.3 m are the ideal thresholds for coastal bathymetry using USVs. (2) The proposed spatiotemporal divisional measurement method can seamlessly collect coastal topography and bathymetry data. (3) The improved Blend mosaic algorithm not only seamlessly and smoothly stitches the land and seabed DEMs, but also minimizes the loss of elevation accuracy. (4) The fine-scale SBT-DEM constructed in this paper has the advantages of high resolution (Pixel size = 1 m) and high accuracy (RMSE = 6.2 cm).
Innovation points: This thesis realized the fast and accurate construction of fine-scale SBT-DEM of coastal zone based on emerging USVs and UAVs. The proposed spatiotemporal divisional measurement method solved the problem of seamless collection of coastal bathymetric and topographic data, and the improved Blend mosaic algorithm realized the high-precision construction of coastal SBT-DEM.
修改评论