Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain
Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain
复制标题
复杂高山地形雪深分布测绘无人机平台对比
DOI：
10.1016/j.coldregions.2021.103344
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
J. López‐Moreno
中科院分区：
文献类型：
--
作者：
J. Revuelto;E. Alonso‐González;Ixeia Vidaller;Emilien Lacroix;E. Izagirre;G. Rodríguez;J. López‐Moreno
无人机（UAV）在无法进入的研究区域获取图像时提供了极大的灵活性，然后通过运动恢复结构（SfM）算法使用立体匹配技术进行处理。该过程允许生成高空间分辨率的3D点云。这些3D模型的高精度允许通过比较不同日期的点云来制作详细的雪深分布图。通过这种方式，无人机可以监控以前无法实现的偏远地区。迄今为止，大量评估这种新技术的工作还没有对不同无人机设备的同时积雪观测进行系统评估。考虑到这一点，并记住，这种技术的潜在用户可能有兴趣利用现成的商业设备，我们进行了评估的积雪深度分布图与不同的商业无人机。在2018-19雪季期间，两个多旋翼（Parrot AnafiandDJI Mavic Pro2）和一个固定翼设备（SenseFly eBee plus）在三个不同的日期在比利牛斯山脉中部Izas实验流域的一个小测试区域（5公顷）内使用。同时，积雪分布检索与地面激光扫描仪（TLS，RIEGL LPM-321），被认为是地面真相。三种不同的地理参考方法（地面控制点，ICP算法在无雪地区和RTK-GPS定位）进行了测试，表现出相同的性能在最佳照明条件下。此外，对于三个采集日期，两个多旋翼在两个不同的高度（50和75米）飞行，以评估对所获得的雪深图的影响。使用TLS进行的评估表明，两种多旋翼的性能相当，平均RMSE低于0.23 m，最大体积偏差小于5%。在所获得的地图中，飞行高度没有显示出显著差异。这些结果是在对比雪面特征下得到的。这项研究表明，在良好的照明条件下，在相对较小的区域，负担得起的商业无人机提供可靠的估计雪分布相比，更复杂和昂贵的近距离遥感技术。在阴天下获得的结果很差，表明无人机观测需要晴朗的天空条件和中午左右的采集，以保证研究区域的均匀照明。
Unmanned Aerial Vehicles (UAVs) offer great flexibility in acquiring images in inaccessible study areas, which are then processed with stereo-matching techniques through Structure-from-Motion (SfM) algorithms. This procedure allows generating high spatial resolution 3D point clouds. The high accuracy of these 3D models allows the production of detailed snow depth distribution maps through the comparison of point clouds from different dates. In this way, UAVs allow monitoring of remote areas that were not achievable previously. The large number of works evaluating this novel technique has not, to date, conducted a systematic evaluation of concurrent snowpack observations with different UAV devices. Taking into account this, and also bearing in mind that potential users of this technique may be interested in exploiting ready-to-use commercial devices, we conducted an evaluation of the snow depth distribution maps with different commercial UAVs. During the 2018–19 snow season, two multi-rotors (Parrot AnafiandDJI Mavic Pro2) and one fixed-wing device (SenseFly eBee plus) were used on three different dates over a small test area (5 ha) within Izas Experimental Catchment in the Central Pyrenees. Simultaneously, snowpack distribution was retrieved with a Terrestrial Laser Scanner (TLS,RIEGL LPM-321) and was considered as ground truth. Three different georeferencing methods (Ground Control Points, ICP algorithm over snow-free areas and RTK-GPS positioning) were tested, showing equivalent performances under optimum illumination conditions. Additionally, for the three acquisition dates, both multi-rotors were flown at two distinct altitudes (50 and 75 m) to evaluate impact on the obtained snow depth maps. The evaluation with the TLS showed an equivalent performance of the two multi-rotors, with mean RMSE below 0.23 m and maximum volume deviations of less than 5%. Flying altitudes did not show significant differences in the obtained maps. These results were obtained under contrasted snow surface characteristics. This study reveals that under good illumination conditions and in relatively small areas, affordable commercial UAVs provide reliable estimations of snow distribution compared to more sophisticated and expensive close-range remote sensing techniques. Results obtained under overcast skies were poor, demonstrating that UAV observations require clear-sky conditions and acquisitions around noon to guarantee a homogenous illumination of the study area.
DOI：
10.1016/j.isprsjprs.2013.04.009
发表时间：
2013-08-01
影响因子：
12.7
作者：
Lague, Dimitri;Brodu, Nicolas;Leroux, Jerome
通讯作者：
Leroux, Jerome