DARTS: Multi-year database of AI-detected retrogressive thaw slumps in the circum-arctic permafrost region

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Authors

Ingmar Nitze , Konrad Heidler, Nina Nesterova, Jonas Küpper, Emma Schütt, Tobias Hölzer, Sophia Barth, Mark Lara, Anna K Liljedahl, Guido Grosse

Abstract

Retrogressive Thaw Slumps (RTS) and Active Layer Detachment Slides (ALD) are widespread thermal mass-wasting hillslope failures triggered by thawing permafrost. Despite increasing rates of these failures, knowledge about their pan-arctic spatial and temporal distribution remains limited. We present the Database of AI-detected Arctic RTS and ALD footprints (DARTS), the largest hillslope thermokarst database with over 43,000 individual features. which spans approximately 1.6 million km² for 2018 to 2023 and at least annual coverage in 2021 to 2023 for a ~900,000 km² region. DARTS is freely available in two processing levels: sub-annual and annually aggregated polygon footprints. The database was created with a fully automated workflow that leverages deep learning-based segmentation of PlanetScope multi-spectral imagery (3-5m spatial resolution) with minimum annual coverage. We validated DARTS using different datasets, achieving F1 scores ranging from 0 to 0.519, with more accurate results in RTS-rich areas. The DARTS database will be valuable for mapping, quantifying, and understanding hillslope thermokarst distribution and change over time across the circum-arctic permafrost region.

DOI

https://doi.org/10.31223/X5740Z

Subjects

Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geomorphology, Physical Sciences and Mathematics

Keywords

Permafrost, retrogressive thaw slumps, Dataset, pan-arctic, Deep learning, Artificial Intelligence, thermokarst, active layer detachment slides, hillslope thermokarst, remote sensing, Segmentation

Dates

Published: 2024-10-20 09:21

Last Updated: 2024-10-20 16:21

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None