基于无人机的LiDAR调查的有效性,以开发数字地形模型和地形纹理分析
Piotr Bartmiński1, Marcin Siłuch1, Waldemar Kociuba1
1Institute of Earth and Environmental Sciences, Maria Curie-Skłodowska University in Lublin, 20-031 Lublin, Poland.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
这项研究比较了无人机平台上的三个LiDAR传感器 (YSM,CHC,L1). 与参考数据相比,DJI Zenmuse L1传感器表现出最高的准确性,与参考数据相比差异最小.
科学领域:
- 地理学就是地质学.
- 遥感 遥感 遥感 遥感
- 无人机技术 无人机技术
背景情况:
- 高分辨率地形数据对于各种应用至关重要.
- 无人驾驶飞行器 (UAV) 为先进的遥感提供了一个平台.
- 激光雷达技术提供准确的3D环境数据.
研究的目的:
- 为了比较安装在无人机上的三个不同的LiDAR传感器 (Yellow Scan Mapper,CHC导航AlphaAir 450,DJI Zenmuse L1) 的性能.
- 评估从这些传感器获得的数字地形模型 (DTM) 与参考数据的准确性.
- 评估基于无人机的LiDAR对于详细的地形绘图的适用性.
主要方法:
- 现场调查使用配备黄色扫描映射器,CHC AlphaAir 450和DJI Zenmuse L1 LiDAR传感器的DJI Matrice 300 RTK无人机进行.
- 波兰东部的一个多样化的测试区域,具有密集植被的沟系统,被选中用于数据采集.
- 来自每个传感器的点云被分类,并生成数字地形模型 (DTM) 并与ISOK项目参考数据进行比较.
主要成果:
- 与ISOK参考数据相比,DJI Zenmuse L1传感器显示出最佳性能,根平均平方误差 (RMSE) 最小的0.31m.
- 在CHC导航AlphaAir 450传感器中,平均高度差异最大,超过2.5米.
- 在测试的LiDAR传感器中观察到数据质量和准确性的显著差异.
结论:
- DJI Zenmuse L1是一款基于无人机的高精度LiDAR传感器,用于生成DTM.
- 基于无人机的LiDAR可以提供非常高分辨率的数据,但需要仔细的现场准备和数据处理.
- 在基于无人机的地形绘图项目中,传感器选择对于实现所需的精度至关重要.
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