A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards
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...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04372-7 |
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| author | Yili Yang Heidi Rodenhizer Brendan M. Rogers Jacqueline Dean Ridhima Singh Tiffany Windholz Amanda Poston Stefano Potter Scott Zolkos Greg Fiske Jennifer Watts Lingcao Huang Chandi Witharana Ingmar Nitze Nina Nesterova Sophia Barth Guido Grosse Trevor Lantz Alexandra Runge Luigi Lombardo Ionut Cristi Nicu Lena Rubensdotter Eirini Makopoulou Susan Natali |
| author_facet | Yili Yang Heidi Rodenhizer Brendan M. Rogers Jacqueline Dean Ridhima Singh Tiffany Windholz Amanda Poston Stefano Potter Scott Zolkos Greg Fiske Jennifer Watts Lingcao Huang Chandi Witharana Ingmar Nitze Nina Nesterova Sophia Barth Guido Grosse Trevor Lantz Alexandra Runge Luigi Lombardo Ionut Cristi Nicu Lena Rubensdotter Eirini Makopoulou Susan Natali |
| author_sort | Yili Yang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c48786e1ba3a4a3597b6a5b6d55de0a5 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-c48786e1ba3a4a3597b6a5b6d55de0a52025-01-12T12:07:45ZengNature PortfolioScientific Data2052-44632025-01-0112111110.1038/s41597-025-04372-7A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data StandardsYili Yang0Heidi Rodenhizer1Brendan M. Rogers2Jacqueline Dean3Ridhima Singh4Tiffany Windholz5Amanda Poston6Stefano Potter7Scott Zolkos8Greg Fiske9Jennifer Watts10Lingcao Huang11Chandi Witharana12Ingmar Nitze13Nina Nesterova14Sophia Barth15Guido Grosse16Trevor Lantz17Alexandra Runge18Luigi Lombardo19Ionut Cristi Nicu20Lena Rubensdotter21Eirini Makopoulou22Susan Natali23Woodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterWoodwell Climate Research CenterInstitute of Space and Earth Information Science, The Chinese University of Hong KongDepartment of Natural Resources and the Environment, University of ConnecticutAlfred Wegener Institute, Permafrost Research SectionAlfred Wegener Institute, Permafrost Research SectionAlfred Wegener Institute, Permafrost Research SectionAlfred Wegener Institute, Permafrost Research SectionSchool of Environmental Studies, University of Victoria David Turpin BuildingHelmholtz Centre Potsdam GFZ German Research Centre for GeosciencesFaculty of Geo-Information Science and Earth Observation, University of TwenteHigh North Department, Norwegian Institute for Cultural Heritage Research (NIKU), Fram CentreGeohazard and Earth Observation, Geological Survey of Norway (NGU)Geography Research Unit, University of OuluWoodwell Climate Research CenterAbstract 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.https://doi.org/10.1038/s41597-025-04372-7 |
| spellingShingle | Yili Yang Heidi Rodenhizer Brendan M. Rogers Jacqueline Dean Ridhima Singh Tiffany Windholz Amanda Poston Stefano Potter Scott Zolkos Greg Fiske Jennifer Watts Lingcao Huang Chandi Witharana Ingmar Nitze Nina Nesterova Sophia Barth Guido Grosse Trevor Lantz Alexandra Runge Luigi Lombardo Ionut Cristi Nicu Lena Rubensdotter Eirini Makopoulou Susan Natali A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards Scientific Data |
| title | A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards |
| title_full | A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards |
| title_fullStr | A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards |
| title_full_unstemmed | A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards |
| title_short | A Collaborative and Scalable Geospatial Data Set for Arctic Retrogressive Thaw Slumps with Data Standards |
| title_sort | collaborative and scalable geospatial data set for arctic retrogressive thaw slumps with data standards |
| url | https://doi.org/10.1038/s41597-025-04372-7 |
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