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Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs

Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs

Dion J. Wiseman, Jurjen van der Sluijs
Copyright: © 2019 |Pages: 22
ISBN13: 9781522583653|ISBN10: 1522583653|EISBN13: 9781522583660
DOI: 10.4018/978-1-5225-8365-3.ch011
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MLA

Wiseman, Dion J., and Jurjen van der Sluijs. "Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs." Unmanned Aerial Vehicles: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2019, pp. 249-270. https://doi.org/10.4018/978-1-5225-8365-3.ch011

APA

Wiseman, D. J. & van der Sluijs, J. (2019). Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs. In I. Management Association (Ed.), Unmanned Aerial Vehicles: Breakthroughs in Research and Practice (pp. 249-270). IGI Global. https://doi.org/10.4018/978-1-5225-8365-3.ch011

Chicago

Wiseman, Dion J., and Jurjen van der Sluijs. "Alternative Methods for Developing and Assessing the Accuracy of UAV-Derived DEMs." In Unmanned Aerial Vehicles: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 249-270. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8365-3.ch011

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Abstract

Digital terrain models are invaluable datasets that are frequently used for visualizing, modeling, and analyzing Earth surface processes. Accurate models covering local scale landscape features are often very expensive and have poor temporal resolution. This research investigates the utility of UAV acquired imagery for generating high resolution terrain models and provides a detailed accuracy assessment according to recommended protocols. High resolution UAV imagery was acquired over a localized dune complex in southwestern Manitoba, Canada and two alternative workflows were evaluated for extracting point clouds. UAV-derived data points were then compared to reference data sets acquired using mapping grade GPS receivers and a total station. Results indicated that the UAV imagery was capable of producing dense point clouds and high resolution terrain models with mean errors as low as -0.15 m and RMSE values of 0.42 m depending on the resolution of the image dataset and workflow employed.

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