An Accuracy Assessment of Snow Depth Measurements in Agro-Forested Environments by UAV Lidar

Remote Sensing

Michel Baraër¹  Vasana Dharmadasa²  Christophe Kinnard² 

[1] Department of Construction Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada;Department of Environmental Sciences, University of Québec at Trois-Rivières, Trois-Rivieres, QC G8Z 4M3, Canada;

关键词: UAV lidar;    boresight calibration;    strip alignment;    agro-forested landscapes;    ground control points;   

DOI  :  10.3390/rs14071649

来源: DOAJ

【 摘 要 】

This study assesses the performance of UAV lidar system in measuring high-resolution snow depths in agro-forested landscapes in southern Québec, Canada. We used manmade, mobile ground control points in summer and winter surveys to assess the absolute vertical accuracy of the point cloud. Relative accuracy was determined by a repeat flight over one survey block. Estimated absolute and relative errors were within the expected accuracy of the lidar (~5 and ~7 cm, respectively). The validation of lidar-derived snow depths with ground-based measurements showed a good agreement, however with higher uncertainties observed in forested areas compared with open areas. A strip alignment procedure was used to attempt the correction of misalignment between overlapping flight strips. However, the significant improvement of inter-strip relative accuracy brought by this technique was at the cost of the absolute accuracy of the entire point cloud. This phenomenon was further confirmed by the degraded performance of the strip-aligned snow depths compared with ground-based measurements. This study shows that boresight calibrated point clouds without strip alignment are deemed to be adequate to provide centimeter-level accurate snow depth maps with UAV lidar. Moreover, this study provides some of the earliest snow depth mapping results in agro-forested landscapes based on UAV lidar.

【 授权许可】

Unknown