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Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
28.09.2020
Verantwortlich:
Zhu, Xiaoxiang
Autorinnen / Autoren:
Ebel, Patrick; Meraner, Andrea; Schmitt, Michael; Zhu, Xiaoxiang
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Titel:
SEN12MS-CR
Identifikator:
doi:10.14459/2020mp1554803
Enddatum der Datenerzeugung:
12.08.2020
Fachgebiet:
BAU Bauingenieurwesen, Vermessungswesen; DAT Datenverarbeitung, Informatik; GEO Geowissenschaften
Quellen der Daten:
Abbildungen von Objekten / image of objects
Datentyp:
Bilder / images
Methode der Datenerhebung:
Semi-automatic download and image preparation using Google Earth Engine, Python and GDAL, semi-automatic processing and clean-up
Beschreibung:
The SEN12MS-CR dataset contains 122,218 patch triplets of corresponding Sentinel-1 dual-pol SAR data, Sentinel-2 multi-spectral images, and cloud-covered Sentinel-2 multi-spectral images. The patches are distributed across the land masses of the Earth and spread over all four meteorological seasons. This is reflected by the dataset structure. All patches are provided in the form of 16-bit GeoTiffs containing the following specific information:
- Sentinel-1 SAR: 2 channels corresponding to sigma nought backscatter values in dB scale for VV and VH polarization.
- Sentinel-2 multi-Spectral: 13 channels corresponding to the 13 spectral bands (B1, B2, B3, B4, B5, B6, B7, B8, B8a, B9, B10, B11, B12).
- cloud-covered Sentinel-2 multi-Spectral: 13 channels corresponding to the 13 spectral bands (B1, B2, B3, B4, B5, B6, B7, B8, B8a, B9, B10, B11, B12).
Links:

doi: 10.1109/TGRS.2020.3024744

Schlagworte:
Remote sensing; deep learning; data fusion; synthetic aperture radar imagery; optical imagery; cloud removal
Technische Hinweise:
View and download (272 GB total, 14 files)
The data server also offers downloads with FTP
The data server also offers downloadds with rsync (password m1554803):
rsync rsync://m1554803@dataserv.ub.tum.de/m1554803/
Sprache:
en
Rechte:
by, http://creativecommons.org/licenses/by/4.0
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