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Titel:

SEN12MS

Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
06.06.2019
Verantwortlich:
Schmitt, Michael
Autorinnen / Autoren:
Schmitt, Michael; Hughes, Lloyd
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Identifikator:
doi:10.14459/2019mp1474000
Enddatum der Datenerzeugung:
14.01.2019
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
Beschreibung:
The SEN12MS dataset contains 180,662 patch triplets of corresponding Sentinel-1 dual-pol SAR data, Sentinel-2 multi-spectral images, and MODIS-derived land cover maps. 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).
- MODIS Land Cover: 4 channels corresponding to IGBP, LCCS Land Cover, LCCS Land Use, and LCCS Surface Hydrology layers.
Links:

SEN12MS – A CURATED DATASET OF GEOREFERENCED MULTI-SPECTRAL SENTINEL-1/2 IMAGERY FOR DEEP LEARNING AND DATA FUSION   

Schlagworte:
Remote sensing, deep learning, data fusion, synthetic aperture radar imagery, optical imagery, land cover, classification
Technische Hinweise:
View and download (510 GB, 542.000 files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1474000):
rsync rsync://m1474000@dataserv.ub.tum.de/m1474000/
Sprache:
en
Rechte:
by, http://creativecommons.org/licenses/by/4.0
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