Articles | Volume 17, issue 9
https://doi.org/10.5194/tc-17-4063-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-4063-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Sep 2023
Research article |
| 19 Sep 2023
| 19 Sep 2023
GLAcier Feature Tracking testkit (GLAFT): a statistically and physically based framework for evaluating glacier velocity products derived from optical satellite image feature tracking
Department of Statistics, University of California Berkeley, Berkeley, CA 94720, USA
Center for Space and Remote Sensing Research, National Central University, Zhongli, Taoyuan 320317, Taiwan
Shashank Bhushan
Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
Maximillian Van Wyk De Vries
Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN 55414, USA
School of Environmental Sciences, University of Liverpool, Liverpool, L69 7ZT, UK
School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, UK
William Kochtitzky
Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa K1N 6N5, Canada
School of Marine and Environmental Programs, University of New England, Biddeford, ME 04005, USA
David Shean
Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
Luke Copland
Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa K1N 6N5, Canada
Christine Dow
Department of Geography and Environmental Management, University of Waterloo, Waterloo N2L 3G1, Canada
Renette Jones-Ivey
Institute for Artificial Intelligence and Data Science, University at Buffalo, Buffalo, NY 14260, USA
Fernando Pérez
Department of Statistics, University of California Berkeley, Berkeley, CA 94720, USA
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Cited
11 citations as recorded by crossref.
- Evaluating the geolocation accuracy of FY-3D MERSI-II satellite image in Antarctica based on Landsat 8-OLI reference imagery T. Li et al. https://doi.org/10.1080/10095020.2026.2642551
- Five decades of Abramov glacier dynamics reconstructed with multi-sensor optical remote sensing E. Mattea et al. https://doi.org/10.5194/tc-19-219-2025
- Assessing POT Methods for Large-Displacement Landslide Measurement with Multi-Source Imagery: A Case Study of the Zhenba Landslide Y. Zhang et al. https://doi.org/10.3390/rs18101591
- Glacier slowdown and rapid ice loss in the Tinguiririca and Cachapoal Basin, Central Andes of Chile V. Jó et al. https://doi.org/10.1016/j.gloplacha.2023.104287
- Deriving seasonal and annual surface mass balance for debris-covered glaciers from flow-corrected satellite stereo DEM time series S. Bhushan et al. https://doi.org/10.1017/jog.2024.57
- Investigation of machine learning algorithms to determine glaciers displacements M. Łucka https://doi.org/10.1016/j.rsase.2025.101476
- Quantifying degradation of the Imja Lake moraine dam with fused InSAR and SAR feature tracking time series G. Brencher et al. https://doi.org/10.5194/tc-20-67-2026
- Investigating seasonal velocity variations of selected glaciers in high mountain asia F. Baldacchino et al. https://doi.org/10.1016/j.srs.2025.100266
- How velocity extraction from Sentinel-2A/B affects the accuracy and availability of surface strain rate and stress: a case study of Helheim Glacier C. Zhang et al. https://doi.org/10.1017/jog.2025.10108
- TICOI: an operational Python package to generate regular glacier velocity time series L. Charrier et al. https://doi.org/10.5194/tc-19-4555-2025
- Comparison of remote sensing feature tracking techniques using high-resolution UAV images for small mountain glacier surface velocity measurement S. Sheshangosht et al. https://doi.org/10.1016/j.rsase.2025.101781
11 citations as recorded by crossref.
- Evaluating the geolocation accuracy of FY-3D MERSI-II satellite image in Antarctica based on Landsat 8-OLI reference imagery T. Li et al. https://doi.org/10.1080/10095020.2026.2642551
- Five decades of Abramov glacier dynamics reconstructed with multi-sensor optical remote sensing E. Mattea et al. https://doi.org/10.5194/tc-19-219-2025
- Assessing POT Methods for Large-Displacement Landslide Measurement with Multi-Source Imagery: A Case Study of the Zhenba Landslide Y. Zhang et al. https://doi.org/10.3390/rs18101591
- Glacier slowdown and rapid ice loss in the Tinguiririca and Cachapoal Basin, Central Andes of Chile V. Jó et al. https://doi.org/10.1016/j.gloplacha.2023.104287
- Deriving seasonal and annual surface mass balance for debris-covered glaciers from flow-corrected satellite stereo DEM time series S. Bhushan et al. https://doi.org/10.1017/jog.2024.57
- Investigation of machine learning algorithms to determine glaciers displacements M. Łucka https://doi.org/10.1016/j.rsase.2025.101476
- Quantifying degradation of the Imja Lake moraine dam with fused InSAR and SAR feature tracking time series G. Brencher et al. https://doi.org/10.5194/tc-20-67-2026
- Investigating seasonal velocity variations of selected glaciers in high mountain asia F. Baldacchino et al. https://doi.org/10.1016/j.srs.2025.100266
- How velocity extraction from Sentinel-2A/B affects the accuracy and availability of surface strain rate and stress: a case study of Helheim Glacier C. Zhang et al. https://doi.org/10.1017/jog.2025.10108
- TICOI: an operational Python package to generate regular glacier velocity time series L. Charrier et al. https://doi.org/10.5194/tc-19-4555-2025
- Comparison of remote sensing feature tracking techniques using high-resolution UAV images for small mountain glacier surface velocity measurement S. Sheshangosht et al. https://doi.org/10.1016/j.rsase.2025.101781
Saved (final revised paper)
Latest update: 21 Jul 2026
Short summary
We design and propose a method that can evaluate the quality of glacier velocity maps. The method includes two numbers that we can calculate for each velocity map. Based on statistics and ice flow physics, velocity maps with numbers close to the recommended values are considered to have good quality. We test the method using the data from Kaskawulsh Glacier, Canada, and release an open-sourced software tool called GLAcier Feature Tracking testkit (GLAFT) to help users assess their velocity maps.
We design and propose a method that can evaluate the quality of glacier velocity maps. The...
