ARTS: a scalable data set for Arctic Retrogressive Thaw Slumps
- 1Woodwell Climate Research Center, Arctic, United States of America (yyang@woodwellclimate.org)
- 2Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
- 3Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT 06269, USA
- 4Alfred Wegener Institute, Permafrost Research Section, Telegrafenberg A45, 14473 Potsdam, Germany
- 5School of Environmental Studies, University of Victoria David Turpin Building, B243 Victoria BC Canada
- 6Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
- 7Faculty of Geo-Information Science and Earth Observation, University of Twente, the Netherlands
- *A full list of authors appears at the end of the abstract
Retrogressive thaw slumps (RTS) are one of the most rapid abrupt thaw events that have a positive feedback on climate warming. RTS are not yet well understood because of the lack of geospatial products describing abrupt thaw distribution and changes over time in the Arctic. Although many standalone RTS digitisation data sets have been archived, it is challenging to find, access and pool the existing data sets into a comprehensive and unified one due to the lack of common data curation standards. Therefore we collected the existing RTS digitisation data sets known to date and compiled them into a scalable and uniform data set - Arctic Retrogressive Thaw Slumps (ARTS). Besides, we developed an RTS data curation framework, which provides guidelines for RTS remote sensing data digitisation, metadata formatting, RTS indexing, storage format, contribution guidelines and more. So far the ARTS data set contains around 24,000 RTS digitisations and 3,300 non-RTS background labels. This data set will empower a wide range of Arctic studies, especially beneficial for deep learning studies that are highly data-intensive.
Yili Yang1, Heidi Rodenhizer1, Brendan M. Rogers1, Jacqueline Dean1, Ridhima Singh1, Tiffany Windholz1, Amanda Poston1, Stefano Potter1, Scott Zolkos1, Greg Fiske1, Jennifer Watts1, Lingcao Huang2, Chandi Witharana3, Ingmar Nitze4, Nina Nesterova4, Sophia Barth4, Guido Grosse4, Trevor Lantz5, Alexandra Runge6, Luigi Lombardo7, Ionut Cristi Nicu8, Lena Rubensdotter9,10, and Sue Natali1
How to cite: Yang, Y., Rodenhizer, H., Rogers, B. M., Dean, J., Singh, R., Windholz, T., Poston, A., Potter, S., Zolkos, S., Fiske, G., Watts, J., Huang, L., Witharana, C., Nitze, I., Nesterova, N., Barth, S., Grosse, G., Lantz, T., Runge, A., and Lombardo, L. and the coauthors: ARTS: a scalable data set for Arctic Retrogressive Thaw Slumps, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1365, https://doi.org/10.5194/egusphere-egu24-1365, 2024.
