| 基于LiDAR点云提取海岸线的二值图像化改进方法 |
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| 引用本文： | 于彩霞,王家耀,黄文骞,许坚.基于LiDAR点云提取海岸线的二值图像化改进方法[J].武汉大学学报(信息科学版),2017,42(7):897-903. |
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| 作者姓名： | 于彩霞 王家耀 黄文骞 许坚 |
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| 作者单位： | 1.信息工程大学地理空间信息学院, 河南 郑州, 450052 |
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| 基金项目： | 国家自然科学基金青-基金41501500地理信息工程国家重点实验室开放研究基金SKLGIE2014-M-3-2地理信息工程国家重点实验室开放研究基金SKLGIE2016-M-4-1国家自然科学基金41471380国家自然科学基金41601498大连舰艇学院2110工程三期资助学术预研课题DLJY-XY2014016 |
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| 摘 要： | 针对当前从激光雷达测量（light detection and ranging，LiDAR）点云中提取海岸线的二值图像化方法过于复杂，且无法评估提取岸线可靠性的现状，提出了一种改进方法。首先对LiDAR点云去噪，然后以平均大潮高潮面（mean high water springs，MHWS）高程为阈值，直接将LiDAR点云分割成水陆二值图像，通过水陆目标识别等图像处理过程，提取潮汐特征海岸线。实验表明，利用提出的二值图像化改进方法提取的海岸线可靠性高于当前已有方法的结果，且提取过程更简单，效率更高。
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| 关 键 词： | LiDAR 二值图像 海岸线 平均大潮高潮面 痕迹岸线 |
| 收稿时间： | 2015-08-28 |
An Improved Binary Image Method of Extracting Shoreline Based on LiDAR Data |
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| Affiliation: | 1.Institute of Geographic Spatial Information, Information Engineering University, Zhengzhou 450052, China2.State Key Laboratory of Geo-information Engineering, Xi'an 710054, China3.Dalian Navy Academy, Dalian 116018, China |
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| Abstract: | The binary image method can automate extraction of tidal datum referenced shorelines from light detection and ranging (LiDAR) data. With this method, spatially detailed and continuous shorelines can be derived. In this paper, an improved binary image method is developed in order to promote efficiency. Firstly, data preprocess is applied to the LiDAR data, including coordinate transformation and noise reduction, with the exception that no filter is used to generate an LiDAR DEM. Secondly, the LiDAR data is segmented into a binary image by intersection with the MHWS (mean high water springs) datum surface, whose height calculated by the tide gauge data or tidal model. Thirdly, the tidal datum referenced shorelines from the LiDAR data are extracted by a chain of image processing procedures, including object recognition, bogus-objects deletion, and edge detection. Finally, the accuracy of shorelines is evaluated by the comparison of LiDAR-derived shorelines with the ground survey data. An application shows that the improved method is more efficient and more reliably than the binary image method. |
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