Extracting cross sections and water levels of vegetated ditches from LiDAR point clouds |
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| Institution: | 1. Institute of Microelectronics, School of Physical Science and Technology, Lanzhou University, South Tianshui Road 222#, Lanzhou 730000, People''s Republic of China;2. Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education, Lanzhou University, South Tianshui Road 222#, Lanzhou 730000, People''s Republic of China;3. Department of Physics, Shaoxing University, Shaoxing 312000, People''s Republic of China;1. School of Marine Science and Technology, Zhejiang Ocean University, Zhoushan 316000, China;2. SEM School of Electromechanical Engineering, Weifang Engineering Vocational College, Qingzhou 262500, China;3. Institute of Photonics and Optoelectronics, Department of Electrical Engineering, and Center for Emerging Material and Advanced Devices, National Taiwan University, Taipei 106-17, Taiwan;4. School of Electronic and Information Engineering, Tianjin University, Tianjin 300072, China;5. Department of Physics, Zhejiang Ocean University, Zhoushan 316000, China;6. Department of Physics, Xiamen University, Xiamen 361005 China |
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| Abstract: | The hydrologic response of a catchment is sensitive to the morphology of the drainage network. Dimensions of bigger channels are usually well known, however, geometrical data for man-made ditches is often missing as there are many and small. Aerial LiDAR data offers the possibility to extract these small geometrical features. Analysing the three-dimensional point clouds directly will maintain the highest degree of information. A longitudinal and cross-sectional buffer were used to extract the cross-sectional profile points from the LiDAR point cloud. The profile was represented by spline functions fitted through the minimum envelop of the extracted points. The cross-sectional ditch profiles were classified for the presence of water and vegetation based on the normalized difference water index and the spatial characteristics of the points along the profile. The normalized difference water index was created using the RGB and intensity data coupled to the LiDAR points. The mean vertical deviation of 0.14 m found between the extracted and reference cross sections could mainly be attributed to the occurrence of water and partly to vegetation on the banks. In contrast to the cross-sectional area, the extracted width was not influenced by the environment (coefficient of determination R2 = 0.87). Water and vegetation influenced the extracted ditch characteristics, but the proposed method is still robust and therefore facilitates input data acquisition and improves accuracy of spatially explicit hydrological models. |
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| Keywords: | LiDAR Ditch Cross section Intensity RGB |
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