Data · dataset · 2022
CloudSEN12 - a global dataset for semantic understanding of cloud and cloud shadow in Sentinel-2
Listed in ScienceDB
CloudSEN12 is a large dataset for cloud semantic understanding that consists of 9880 regions of interest (ROIs).
Description
Each ROI has five 5090x5090 meters image patches (IPs) collected on different dates; we manually choose the images to guarantee that each IP inside an ROI matches one of the following cloud cover groups:- clear (0%)- low-cloudy (1% - 25%) - almost clear (25% - 45%)- mid-cloudy (45% - 65%)- cloudy (65% >)An IP is the core unit in CloudSEN12.
Each IP contains data from Sentinel-2 optical levels 1C and 2A, Sentinel-1 Synthetic Aperture Radar (SAR), digital elevation model, surface water occurrence, land cover classes, and cloud mask results from eight cutting-edge cloud detection algorithms. Besides, in order to support standard, weakly, and self-/semi-supervised learning procedures, cloudSEN12 includes three distinct forms of hand-crafted labelling data: high-quality, scribble, and no annotation.
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Consequently, each ROI is randomly assigned to a different annotation group:2000 ROIs with pixel-level annotation, where the average annotation time is 150 minutes (high-quality group).2000 ROIs with scribble-level annotation, where the annotation time is 15 minutes (scribble group).5880 ROIs with annotation only in the cloud-free (0\%) image (no annotation group).For high-quality labels, we use the Intelligence foR Image Segmentation\cite{iris2019} (IRIS) active learning technology, combining human photo-interpretation and machine learning.
For scribble, ground truth pixels were drawn using IRIS but without ML support. Finally, the no-annotation dataset is generated automatically, with manual annotation only in the clear image patch. A backup of the dataset in STAC format is available here: shorturl.at/cgjtz.
Check out our website cloudsen12.github.io/ for examples.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.06669 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Distributed computing and systems software 68% · Image 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.06669 | 11 d ago | JSON v1 |
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