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

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dc.contributor.authorYang, Yili
dc.contributor.authorRodenhizer, Heidi
dc.contributor.authorRogers, Brendan M.
dc.contributor.authorDean, Jacqueline
dc.contributor.authorSingh, Ridhima
dc.contributor.authorWindholz, Tiffany
dc.contributor.authorPoston, Amanda
dc.contributor.authorPotter, Stefano
dc.contributor.authorZolkos, Scott
dc.contributor.authorFiske, Greg
dc.contributor.authorWatts, Jennifer
dc.contributor.authorHuang, Lingcao
dc.contributor.authorWitharana, Chandi
dc.contributor.authorNitze, Ingmar
dc.contributor.authorNesterova, Nina
dc.contributor.authorBarth, Sophia
dc.contributor.authorGrosse, Guido
dc.contributor.authorLantz, Trevor C.
dc.contributor.authorRunge, Alexandra
dc.contributor.authorLombardo, Luigi
dc.contributor.authorNicu, Ionut Cristi
dc.contributor.authorRubensdotter, Lena
dc.contributor.authorMakopoulou, Eirini
dc.contributor.authorNatali, Susan
dc.date.accessioned2025-03-26T19:41:19Z
dc.date.available2025-03-26T19:41:19Z
dc.date.issued2025
dc.description.abstractArctic 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.
dc.description.reviewstatusReviewed
dc.description.scholarlevelFaculty
dc.description.sponsorshipThis work was supported by the Heising-Simons Foundation (grant #2021-3040) and funding catalysed by the Audacious Project (Permafrost Pathways) for Woodwell-affiliated coauthors. Ionut Cristi Nicu and Lena Rubensdotter were partly supported by the Fram Centre project PermaRICH (Advanced Mapping and Monitoring for Assessing Permafrost Thawing Risks for Modern Infrastructure and Cultural Heritage in Svalbard). Ionut Cristi Nicu, Lena Rubensdotter, and Luigi Lombardo were also supported by the ‘SIOS-Planet cooperation project proposal call to demonstrate the usability of high-resolution Planet data in the Arctic’ project MACROS (Mapping cryospheric hazards towards a spatio-temporal multi-hazard susceptibility modelling). Guido Grosse, Ingmar Nitze, and Sophia Barth were supported by the HGF AI-CORE, BMWK ML4EARTH, and NSF Permafrost Discovery Gateway (awards #1927872, #2052107). Alexandra Runge was supported by the ESA CCI Postdoctoral Fellowships contract No. 4000134121/21/I-NB. Nina Nesterova was supported by a DAAD scholarship (#57588368). Eirini Makopoulou was supported by the KVANTUM Institute within the program Changing Climate and the Northern Environment "HYPERISK, Hybrid Modelling for Improved Permafrost Risk Assessments (2021-2024)".
dc.identifier.citationYang, 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
dc.identifier.urihttps://doi.org/10.1038/s41597-025-04372-7
dc.identifier.urihttps://hdl.handle.net/1828/21685
dc.language.isoen
dc.publisherScientific Data
dc.rightsCC BY 4.0
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectcryospheric science
dc.subjectenvironmental impact
dc.titleA collaborative and scalable geospatial data set for Arctic retrogressive thaw slumps with data standards
dc.typeArticle

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