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.
| Original language | English |
|---|---|
| Article number | 110852 |
| Journal | Data in Brief |
| Volume | 56 |
| DOIs | |
| State | Published - Oct 2024 |
Keywords
- Cloud shadow
- Global dataset
- IRIS
- Sentinel-2
- Thin cloud
- U-net
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