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On-site geometric calibration of RPAS mounted sensors for SfM photogrammetric geomorphological surveys

Lookup NU author(s): Dr Johannes Senn, Professor Jon MillsORCiD, Professor Claire WalshORCiD, Dr Maria-Valasia PeppaORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

The application of structure from motion (SfM) photogrammetry for digital elevationmodel (DEM) and orthophoto generation from visible imagery enjoys ever-growingpopularity in geomorphological research. Photogrammetry experts, however, urgethat a rigorous approach is a prerequisite for reliable results—a requirement that mayconflict with real-world survey. We present a method that unites the two disciplines,using the example of a challenging SfM photogrammetric survey at a Scottish river.Using simultaneous geometric pre-calibration of a multi-sensor remotely piloted air-craft system (RPAS), the method facilitates time-efficient topography mapping andthe integration of other wavelengths to create orthophotos providing additional sur-face information. The approach utilizes an on-site 3D structure—for example, a build-ing, as calibration object, by extracting coordinates of natural features from lidarscans and sensor imagery. We assess the workflow with specialized calibration soft-ware (VMS) and widely applied commercial SfM photogrammetric software (AM),using a DJI Phantom optical and a Workswell thermal sensor. We achieved calibra-tion accuracies below one-third (optical) and one-quarter (thermal) of a pixel. Subse-quently, we transfer the sensor parameters to pre-calibrate the SfM application andcompare the results to a self-calibrated workflow. In a systematic experiment usingthe optical river survey dataset, we assess the effectiveness of pre-calibration,oblique imagery, scale variation and masking to mitigate systematic DEM errors.Opposing trends show between the calibration strategies. Decreasing network com-plexity (i.e., flying heights/view angles) improves pre-calibrated but compromisesself-calibrated scenarios. Pre-calibrating (VMS) imagery from a single height (30 mnadir) yielded the best results. This finding could have implications for geomorpho-logical surveys, in which single-scale datasets are widespread practice, despite theliterature’s urge towards more complex imaging networks. The self-calibrated resultslegitimise this insistence: The same dataset resulted in pronounced dome-shapedDEM distortion, indicating systematic errors, whereas additional flying heights andangles significantly improved the results.

Publication metadata

Author(s): Senn JA, Mills J, Walsh CL, Addy S, Peppa M-V

Publication type: Article

Publication status: Published

Journal: Earth Surface Processes and Landforms

Year: 2022

Volume: 47

Issue: 6

Pages: 1615-1634

Print publication date: 01/05/2022

Online publication date: 07/02/2022

Acceptance date: 25/01/2022

Date deposited: 09/03/2022

ISSN (print): 0197-9337

ISSN (electronic): 1096-9837

Publisher: John Wiley & Sons Ltd

URL: https://doi.org/10.1002/esp.5338

DOI: 10.1002/esp.5338

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