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Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach

Ewertowski, Marek; Tomczyk, Aleksandra; Evans, David JA; Roberts, David H; Ewertowski, Wojciech

Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach Thumbnail


Authors

Marek Ewertowski

Aleksandra Tomczyk

Wojciech Ewertowski



Abstract

This study presents the operational framework for rapid, very-high resolution mapping of glacial geomorphology, with the use of budget Unmanned Aerial Vehicles and a structure-from-motion approach. The proposed workflow comprises seven stages: (1) Preparation and selection of the appropriate platform; (2) transport; (3) preliminary on-site activities (including optional ground-control-point collection); (4) pre-flight setup and checks; (5) conducting the mission; (6) data processing; and (7) mapping and change detection. The application of the proposed framework has been illustrated by a mapping case study on the glacial foreland of Hørbyebreen, Svalbard, Norway. A consumer-grade quadcopter (DJI Phantom) was used to collect the data, while images were processed using the structure-from-motion approach. The resultant orthomosaic (1.9 cm ground sampling distance—GSD) and digital elevation model (7.9 cm GSD) were used to map the glacial-related landforms in detail. It demonstrated the applicability of the proposed framework to map and potentially monitor detailed changes in a rapidly evolving proglacial environment, using a low-cost approach. Its coverage of multiple aspects ensures that the proposed framework is universal and can be applied in a broader range of settings.

Citation

Ewertowski, M., Tomczyk, A., Evans, D. J., Roberts, D. H., & Ewertowski, W. (2019). Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach. Remote Sensing, 11(1), Article 65. https://doi.org/10.3390/rs11010065

Journal Article Type Article
Acceptance Date Dec 24, 2018
Online Publication Date Jan 1, 2019
Publication Date Jan 1, 2019
Deposit Date Jan 15, 2019
Publicly Available Date Jan 15, 2019
Journal Remote Sensing
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 11
Issue 1
Article Number 65
DOI https://doi.org/10.3390/rs11010065

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Published Journal Article (26.2 Mb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).





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