PyTrx : a python-based monoscopic terrestrial photogrammetry toolset for glaciology
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Date
13/02/2020Keywords
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Abstract
Terrestrial time-lapse photogrammetry is a rapidly growing method for deriving measurements from glacial environments because it provides high spatio-temporal resolution records of change. Currently, however, the potential usefulness of time-lapse data is limited by the unavailability of user-friendly photogrammetry toolsets. Such data are used primarily to calculate ice flow velocities or to serve as qualitative records. PyTrx (available at https://github.com/PennyHow/PyTrx) is presented here as a Python-alternative toolset to widen the range of monoscopic photogrammetry (i.e., from a single viewpoint) toolsets on offer to the glaciology community. The toolset holds core photogrammetric functions for template generation, feature-tracking, camea calibration and optimization, image registration, and georectification (using a planar projective transformation model). In addition, PyTrx facilitates areal and line measurements, which can be detected from imagery using either an automated or manual approach. Examples of PyTrx's applications are demonstrated using time-lapse imagery from Kronebreen and Tunabreen, two tidewater glaciers in Svalbard. Products from these applications include ice flow velocities, surface areas of supraglacial lakes and meltwater plumes, and glacier terminus profiles.
Citation
How , P , Hulton , N R J , Buie , L & Benn , D I 2020 , ' PyTrx : a python-based monoscopic terrestrial photogrammetry toolset for glaciology ' , Frontiers in Earth Science , vol. 8 , 21 . https://doi.org/10.3389/feart.2020.00021
Publication
Frontiers in Earth Science
Status
Peer reviewed
ISSN
2296-6463Type
Journal article
Rights
Copyright © 2020 How, Hulton, Buie and Benn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Description
This work was affiliated with the CRIOS project (Calving Rates and Impact On Sea Level), which was supported by the Conoco Phillips-Lundin Northern Area Program. PH was funded by a NERC Ph.D. studentship (reference number 1396698).Collections
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