A Sentinel-2 semantic segmentation dataset for thermokarst-associated lake and pond water surfaces in Arctic permafrost lowlands

Abstract. Lake and pond water surfaces in thermokarst-affected Arctic permafrost lowlands are important for hydrological, habitat, and carbon-cycle studies. Existing inland-water products rarely provide georeferenced image-mask pairs designed for supervised segmentation of small Arctic water bodies. We present a Sentinel-2 semantic segmentation dataset for thermokarst-associated lake and pond water surfaces across 23 selected permafrost-lowland areas of interest (AOIs) spanning Alaska, northwestern Canada, European Russia, Yamal, and Siberia. The supervised target is visible summer lake and pond water, while separate tile-level fields record thermokarst relevance and non-target-water risk. The dataset contains 5513 image-mask pairs derived from summer 2023 Sentinel-2 Level-2A surface-reflectance composites. Each image is a 256 by 256 pixel GeoTIFF with five bands (B2, B3, B4, B8, and B11), accompanied by a binary water mask and a quality-assurance (QA) mask for invalid observations and ambiguous margins. The train, validation, and test splits contain 3982, 739, and 792 tiles, respectively. The masks contain 29,141,595 positive pixels, representing 8.07 % of all pixels and a pixel-count-equivalent area of approximately 2914.2 km2; 88.35 % of target-water pixels lie north of or on the Arctic Circle at 66°34′ N. The package includes 16539 image, water-mask and QA GeoTIFF files, with sample metadata, source records, processing settings, split definitions and a 150-tile low-water subset index. A geometry audit identified cross-split overlap in the legacy development split and in the original Mackenzie Delta holdout. After removing overlapping and nearby development samples and retraining with QA-aware loss, the Mackenzie Delta experiment reached a target-agreement intersection-over-union (IoU) of 0.659 (spatial-cluster bootstrap interval 0.587–0.728). The Yamal and European Russia holdout had no detected test–development footprint overlap and retained its previously reported target-agreement IoU of 0.936. These values measure agreement with the released supervision targets; independent human-reference accuracy remains to be established. The release is designed for supervised segmentation and controlled model comparison within the represented 2023 Arctic permafrost-lowland settings. The dataset is available from the National Cryosphere Desert Data Center at https://doi.org/10.12072/ncdc.permafrost.db7645.2026 (Guo, 2026). The accompanying model-output dataset is available on Zenodo at https://doi.org/10.5281/zenodo.22965055 (Zhang et al., 2026).

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Publication Details

Journal
Earth System Science Data Discussions
Published
2026-10-28
DOI
https://doi.org/10.5194/essd-2026-581
Primary Topic
Climate change and permafrost
Type
preprint

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preprint

A Sentinel-2 semantic segmentation dataset for thermokarst-associated lake and pond water surfaces in Arctic permafrost lowlands

Jinbang Zhai, Leonid Gagarin, Ze Zhang, Andrei Zhang et al.
3 links
Earth System Science Data Discussions
Climate change and permafrost
preprint

A Sentinel-2 semantic segmentation dataset for thermokarst-associated lake and pond water surfaces in Arctic permafrost lowlands

Jinbang Zhai, Leonid Gagarin, Ze Zhang, Andrei Zhang, Ziyou Guo, Nikolai Torgovkin, Qingkai Yan
preprint en

Abstract

Abstract. Lake and pond water surfaces in thermokarst-affected Arctic permafrost lowlands are important for hydrological, habitat, and carbon-cycle studies. Existing inland-water products rarely provide georeferenced image-mask pairs designed for supervised segmentation of small Arctic water bodies. We present a Sentinel-2 semantic segmentation dataset for thermokarst-associated lake and pond water surfaces across 23 selected permafrost-lowland areas of interest (AOIs) spanning Alaska, northwestern Canada, European Russia, Yamal, and Siberia. The supervised target is visible summer lake and pond water, while separate tile-level fields record thermokarst relevance and non-target-water risk. The dataset contains 5513 image-mask pairs derived from summer 2023 Sentinel-2 Level-2A surface-reflectance composites. Each image is a 256 by 256 pixel GeoTIFF with five bands (B2, B3, B4, B8, and B11), accompanied by a binary water mask and a quality-assurance (QA) mask for invalid observations and ambiguous margins. The train, validation, and test splits contain 3982, 739, and 792 tiles, respectively. The masks contain 29,141,595 positive pixels, representing 8.07 % of all pixels and a pixel-count-equivalent area of approximately 2914.2 km2; 88.35 % of target-water pixels lie north of or on the Arctic Circle at 66°34′ N. The package includes 16539 image, water-mask and QA GeoTIFF files, with sample metadata, source records, processing settings, split definitions and a 150-tile low-water subset index. A geometry audit identified cross-split overlap in the legacy development split and in the original Mackenzie Delta holdout. After removing overlapping and nearby development samples and retraining with QA-aware loss, the Mackenzie Delta experiment reached a target-agreement intersection-over-union (IoU) of 0.659 (spatial-cluster bootstrap interval 0.587–0.728). The Yamal and European Russia holdout had no detected test–development footprint overlap and retained its previously reported target-agreement IoU of 0.936. These values measure agreement with the released supervision targets; independent human-reference accuracy remains to be established. The release is designed for supervised segmentation and controlled model comparison within the represented 2023 Arctic permafrost-lowland settings. The dataset is available from the National Cryosphere Desert Data Center at https://doi.org/10.12072/ncdc.permafrost.db7645.2026 (Guo, 2026). The accompanying model-output dataset is available on Zenodo at https://doi.org/10.5281/zenodo.22965055 (Zhang et al., 2026).

Earth System Science Data Discussions
Heilongjiang International University (CN), Melnikov Permafrost Institute of the Siberian Branch of the Russian Academy of Science (RU), Northeast Forestry University (CN)
Ministry of Science and Higher Education of the Russian Federation, National Key Research and Development Program of China
Clean water and sanitation, Climate action
Climate change and permafrost
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