A collaborative and scalable geospatial data set for Arctic retrogressive thaw slumps with data standards

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Yang_yili_Sci.Data_2025.pdf (2.21 MB)

Date

2025

Authors

Yang, Yili
Rodenhizer, Heidi
Rogers, Brendan M.
Dean, Jacqueline
Singh, Ridhima
Windholz, Tiffany
Poston, Amanda
Potter, Stefano
Zolkos, Scott
Fiske, Greg

Journal Title

Journal ISSN

Volume Title

Publisher

Scientific Data

Abstract

Arctic permafrost is undergoing rapid changes due to climate warming in high latitudes. Retrogressive thaw slumps (RTS) are one of the most abrupt and impactful thermal-denudation events that change Arctic landscapes and accelerate carbon feedbacks. Their spatial distribution remains poorly characterised due to time-intensive conventional mapping methods. While numerous RTS studies have published standalone digitisation datasets, the lack of a centralised, unified database has limited their utilisation, affecting the scale of RTS studies and the generalisation ability of deep learning models. To address this, we established the Arctic Retrogressive Thaw Slumps (ARTS) dataset containing 23,529 RTS-present and 20,434 RTS-absent digitisations from 20 standalone datasets. We also proposed a Data Curation Framework as a working standard for RTS digitisations. This dataset is designed to be comprehensive, accessible, contributable, and adaptable for various RTS-related studies. This dataset and its accompanying curation framework establish a foundation for enhanced collaboration in RTS research, facilitating standardised data sharing and comprehensive analyses across the Arctic permafrost research community.

Description

Keywords

cryospheric science, environmental impact

Citation

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., . . . Natali, S. (2025). A collaborative and scalable geospatial data set for Arctic retrogressive thaw slumps with data standards. Scientific Data, 12(1). https://doi.org/10.1038/s41597-025-04372-7

URI

https://doi.org/10.1038/s41597-025-04372-7
 https://hdl.handle.net/1828/21685

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Faculty Publications (Social Sciences)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.