TY - JOUR
T1 - PyTrx
T2 - A Python-based monoscopic terrestrial photogrammetry toolset for glaciology
AU - How, Penelope
AU - Hulton, Nicholas R.J.
AU - Buie, Lynne
AU - Benn, Douglas I.
N1 - Funding Information:
A pre-print of this paper is available as How et al. (2018). The DEM of Kongsfjorden was provided by the Norwegian Polar Institute under the CC BY 4.0 license. The DEM of Tempelfjorden was provided by ArcticDEM (DigitalGlobe, Inc.) and funded under National Science Foundation awards 1043681, 1559691, and 1542736. We would like to thank the University of Edinburgh GeoSciences Mechanical Workshop for manufacturing the camera enclosures, Adrian Luckman for his feedback on the manuscript, and Timothy C. Bartholomaus (scientific editor), Andrew J. Sole and Robert McNabb (reviewers) for their constructive comments throughout the review process. Funding. 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).
Publisher Copyright:
© Copyright © 2020 How, Hulton, Buie and Benn.
PY - 2020/2/13
Y1 - 2020/2/13
N2 - 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.
AB - 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.
KW - glacier dynamics
KW - photogrammetry
KW - python
KW - tidewater glaciers
KW - time-lapse
UR - http://www.scopus.com/inward/record.url?scp=85085247923&partnerID=8YFLogxK
U2 - 10.3389/feart.2020.00021
DO - 10.3389/feart.2020.00021
M3 - Article
AN - SCOPUS:85085247923
SN - 2296-6463
VL - 8
JO - Frontiers in Earth Science
JF - Frontiers in Earth Science
M1 - 21
ER -