Next Article in Journal / Special Issue
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
Previous Article in Journal
Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement
Previous Article in Special Issue
Contour Detection for UAV-Based Cadastral Mapping
Article

Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers

1
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, CH-8903 Birmensdorf, Switzerland
2
Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, CH-8093 Zurich, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editors: Farid Melgani, Francesco Nex, Norman Kerle and Prasad Thenkabail
Received: 30 November 2016 / Revised: 14 February 2017 / Accepted: 16 February 2017 / Published: 22 February 2017
(This article belongs to the Special Issue Recent Trends in UAV Remote Sensing)
The use of Unmanned Aerial Vehicles (UAV) for photogrammetric surveying has recently gained enormous popularity. Images taken from UAVs are used for generating Digital Surface Models (DSMs) and orthorectified images. In the glaciological context, these can serve for quantifying ice volume change or glacier motion. This study focuses on the accuracy of UAV-derived DSMs. In particular, we analyze the influence of the number and disposition of Ground Control Points (GCPs) needed for georeferencing the derived products. A total of 1321 different DSMs were generated from eight surveys distributed on three glaciers in the Swiss Alps during winter, summer and autumn. The vertical and horizontal accuracy was assessed by cross-validation with thousands of validation points measured with a Global Positioning System. Our results show that the accuracy increases asymptotically with increasing number of GCPs until a certain density of GCPs is reached. We call this the optimal GCP density. The results indicate that DSMs built with this optimal GCP density have a vertical (horizontal) accuracy ranging between 0.10 and 0.25 m (0.03 and 0.09 m) across all datasets. In addition, the impact of the GCP distribution on the DSM accuracy was investigated. The local accuracy of a DSM decreases when increasing the distance to the closest GCP, typically at a rate of 0.09 m per 100-m distance. The impact of the glacier’s surface texture (ice or snow) was also addressed. The results show that besides cases with a surface covered by fresh snow, the surface texture does not significantly influence the DSM accuracy. View Full-Text
Keywords: UAV photogrammetry; glacier; unmanned aerial vehicle; accuracy assessment; digital surface models UAV photogrammetry; glacier; unmanned aerial vehicle; accuracy assessment; digital surface models
Show Figures

Graphical abstract

MDPI and ACS Style

Gindraux, S.; Boesch, R.; Farinotti, D. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers. Remote Sens. 2017, 9, 186. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9020186

AMA Style

Gindraux S, Boesch R, Farinotti D. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers. Remote Sensing. 2017; 9(2):186. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9020186

Chicago/Turabian Style

Gindraux, Saskia, Ruedi Boesch, and Daniel Farinotti. 2017. "Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers" Remote Sensing 9, no. 2: 186. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9020186

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop