| 基于无人机激光点云的树障检测与砍伐树木数量估算 |
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| 作者姓名： | 张苏 齐立忠 韩文军 朱笑笑 习晓环 王成 王濮 聂胜 |
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| 作者单位： | 1. 国网经济技术研究院有限公司 电网工程航空遥感与线路智能巡检联合实验室, 北京 102209;
2. 中国科学院遥感与数字地球研究所 数字地球重点实验室, 北京 100094;
3. 中国科学院大学, 北京 100049 |
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| 基金项目： | 国网经济技术研究院有限公司自主投入科技项目（ZZKJ-2019-11）和中国科学院青年创新促进会项目（2019130）资助 |
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| 摘 要： | 电力走廊的树木生长会对输电线路的安全运营造成巨大影响，精确检测出影响线路安全的树木并将其砍伐至关重要。因此，提出一种基于无人机激光点云的树障检测与砍伐树木数量估算方法。首先，对激光点云进行快速自动化处理，先后精确提取地面点、电力线点与植被点；其次，基于电力线点进行分段，并分析电力线与植被点的安全距离，进而确定树障区域的位置和范围；最后，对树障区域植被点云进行单木分割，并统计单木数量，最终实现砍伐树木数量的精准估算。研究结果表明，无人机激光点云可以实现输电通道树障的有效检测与砍伐树木数量的精确估算，总体树木砍伐数量估算精度可达92.3%，可为输电线路安全运营提供遥感技术支撑，也可为电网运维单位制订树木砍伐计划提供可靠依据。
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| 关 键 词： | 激光雷达 树障检测 单木分割 砍伐树木数量估算 电力线提取 |
| 收稿时间： | 2019-10-17 |
| 修稿时间： | 2019-12-31 |
Danger tree detection and tree number estimation based on UAV LiDAR data |
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| Authors: | ZHANG Su QI Lizhong HAN Wenjun ZHU Xiaoxiao XI Xiaohuan WANG Cheng WANG Pu NIE Sheng |
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| Institution: | 1. Joint Laboratory of Airborne Remote Sensing and Line Routing Inspection for Power Grid Engineering, State Grid Economic and Technological Research Institute Co, LTD, Beijing 102209, China;
2. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | The growth of trees in the transmission corridor has a great impact on the transmission line. It is essential to accurately detect the trees that significantly affected the safety of transmission line. Therefore, a method of danger tree detection and tree number estimation based on UAV LiDAR data was proposed in this paper. Firstly, the power line points, ground points, and vegetation points were accurately extracted by rapidly automatic processing the laser point cloud in the transmission corridor. Secondly, the power line was segmented, and then the location and range of tree barrier area were determined by analyzing the safe distance between power lines and vegetation points. Finally, the point clouds in the tree barrier area were divided into single trees, and the number of single trees was counted to achieve accurate estimation of the number of danger trees. The results indicates that the UAV laser point cloud effectively detect the tree barrier in the transmission channel and accurately estimate the number of trees need to be felled with an overall accuracy of 92.3%, which provides not only remote sensing technology support for the safety of transmission line, but also reliable basis for the grid operation and maintenance units to make plan for tree cutting. |
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| Keywords: | LiDAR danger tree detection danger tree number estimation individual tree segmentation power line extraction |
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