ArticleData in brief2024
CloudSEN12+: The largest dataset of expert-labeled pixels for cloud and cloud shadow detection in Sentinel-2.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A Sentinel-2 dataset for railway presence classification across metropolitan France.Data in brief · 2026Article
- A multi-label sentinel-2 dataset for deep learning-based energy, transport, and storage infrastructure mapping in Germany.Data in brief · 2026Article
- Enhanced Cloud Detection Using a Unified Multimodal Data Fusion Approach in Remote Images.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
24 authors.
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Abstract
Detecting and screening clouds is the first step in most optical remote sensing analyses. Cloud formation is diverse, presenting many shapes, thicknesses, and altitudes. This variety poses a significant challenge to the development of effective cloud detection algorithms, as most datasets lack an unbiased representation. To address this issue, we have built CloudSEN12+, a significant expansion of the CloudSEN12 dataset. This new dataset doubles the expert-labeled annotations, making it the largest cloud and cloud shadow detection dataset for Sentinel-2 imagery up to date. We have carefully reviewed and refined our previous annotations to ensure maximum trustworthiness. We expect CloudSEN12+ will be a valuable resource for the cloud detection research community.
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