Articles | Volume 17, issue 9
https://doi.org/10.5194/tc-17-4063-2023
https://doi.org/10.5194/tc-17-4063-2023
Research article
 | 
19 Sep 2023
Research article |  | 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

Whyjay Zheng, Shashank Bhushan, Maximillian Van Wyk De Vries, William Kochtitzky, David Shean, Luke Copland, Christine Dow, Renette Jones-Ivey, and Fernando Pérez

Related authors

Glacier geometry and flow speed determine how Arctic marine-terminating glaciers respond to lubricated beds
Whyjay Zheng
The Cryosphere, 16, 1431–1445, https://doi.org/10.5194/tc-16-1431-2022,https://doi.org/10.5194/tc-16-1431-2022, 2022
Short summary

Related subject area

Discipline: Glaciers | Subject: Remote Sensing
Lake ice break-up in Greenland: timing and spatiotemporal variability
Christoph Posch, Jakob Abermann, and Tiago Silva
The Cryosphere, 18, 2035–2059, https://doi.org/10.5194/tc-18-2035-2024,https://doi.org/10.5194/tc-18-2035-2024, 2024
Short summary
Improved records of glacier flow instabilities using customized NASA autoRIFT applied to PlanetScope imagery
Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle
EGUsphere, https://doi.org/10.5194/egusphere-2024-374,https://doi.org/10.5194/egusphere-2024-374, 2024
Short summary
A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography
Jérôme Messmer and Alexander Raphael Groos
The Cryosphere, 18, 719–746, https://doi.org/10.5194/tc-18-719-2024,https://doi.org/10.5194/tc-18-719-2024, 2024
Short summary
Refined glacial lake extraction in a high-Asia region by deep neural network and superpixel-based conditional random field methods
Yungang Cao, Rumeng Pan, Meng Pan, Ruodan Lei, Puying Du, and Xueqin Bai
The Cryosphere, 18, 153–168, https://doi.org/10.5194/tc-18-153-2024,https://doi.org/10.5194/tc-18-153-2024, 2024
Short summary
Annual to seasonal glacier mass balance in High Mountain Asia derived from Pléiades stereo images: examples from the Pamir and the Tibetan Plateau
Daniel Falaschi, Atanu Bhattacharya, Gregoire Guillet, Lei Huang, Owen King, Kriti Mukherjee, Philipp Rastner, Tandong Yao, and Tobias Bolch
The Cryosphere, 17, 5435–5458, https://doi.org/10.5194/tc-17-5435-2023,https://doi.org/10.5194/tc-17-5435-2023, 2023
Short summary

Cited articles

Abe, T. and Furuya, M.: Winter speed-up of quiescent surge-type glaciers in Yukon, Canada, The Cryosphere, 9, 1183–1190, https://doi.org/10.5194/tc-9-1183-2015, 2015. a
Ahn, Y. and Howat, I. M.: Efficient Automated Glacier Surface Velocity Measurement From Repeat Images Using Multi-Image/Multichip and Null Exclusion Feature Tracking, IEEE T. Geosci. Remote, 49, 2838–2846, https://doi.org/10.1109/TGRS.2011.2114891, 2011. a
Altena, B. and Kääb, A.: Ensemble matching of repeat satellite images applied to measure fast-changing ice flow, verified with mountain climber trajectories on Khumbu icefall, Mount Everest, J. Glaciol., 66, 905–915, https://doi.org/10.1017/jog.2020.66, 2020. a, b
Altena, B., Scambos, T., Fahnestock, M., and Kääb, A.: Extracting recent short-term glacier velocity evolution over southern Alaska and the Yukon from a large collection of Landsat data, The Cryosphere, 13, 795–814, https://doi.org/10.5194/tc-13-795-2019, 2019. a, b
Altena, B., Kääb, A., and Wouters, B.: Correlation dispersion as a measure to better estimate uncertainty in remotely sensed glacier displacements, The Cryosphere, 16, 2285–2300, https://doi.org/10.5194/tc-16-2285-2022, 2022. a
Download
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.