Labeled SAR imagery dataset of ten geophysical phenomena from Sentinel-1 wave mode (TenGeoP-SARwv)

Date 2018
Author(s) Wang Chen1, 2, Mouche AlexisORCID1, Tandeo Pierre2, Stopa Justin1, Longépé Nicolas3, Erhard Guillaume3, Foster Ralph4, Vandemark Douglas5, Chapron Bertrand1
Affiliation(s) 1 : Univ. Brest, CNRS, IRD, Ifremer, Laboratoire d'Océanographie Physique et Spatiale (LOPS), IUEM, 29280, Brest, France
2 : Institut Mines-Télécom Atlantique, UMR 6285 LabSTICC, Université Bretagne Loire, Technopôle Brest-Iroise CS 83818, 29238 Brest Cedex 3, France
3 : Space and Ground Segment, Collecte Localisation Satellites (CLS), Plouzané, France
4 : Applied Physics Laboratory, University of Washington, 1013 NE 40th Street, Seattle, Washington, USA
5 : Ocean Processes Analysis Laboratory, University of New Hampshire, New Hampshire, USA
DOI 10.17882/56796
Publisher SEANOE
Keyword(s) Synthetic aperture radar (SAR), Sentinel-1 wave mode, SAR images, Geophysical phenomena, Classification, Manually labeling

The TenGeoP-SARwv dataset is established based on the acquisitions of Sentinel-1A wave mode (WV) in VV polarization. This dataset consists of more than 37,000 SAR vignettes divided into ten defined geophysical categories, including both oceanic and meteorologic features. These images cover the entire open ocean and are manually selected from Sentinel-1A WV acquisitions in 2016. For each image, only one prevalent geophysical phenomena with its prescribed signature and texture is selected for labeling. The SAR images are processed into a quick-look image provided in the formats of PNG and GeoTIFF as well as the associated labels. They are convenient for both visual inspection and machine-learning-based methods exploitation. The proposed dataset is the first one involving different oceanic or atmospheric phenomena over the open ocean. It seeks to foster the development of strategies or approaches for massive ocean SAR image analysis. A key objective is to allow exploiting the full potential of Sentinel-1 WV SAR acquisitions, which are about 60,000 images per satellite per month and freely available. Such a dataset may be of value to a wide range of users and communities in deep learning, remote sensing, oceanography, and meteorology

Licence CC-BY-NC-SA
Sensor metadata

The ESA Sentinel-1 mission is a constellation of two polar-orbiting, sun-synchronous satellites (S-1 A and S-1 B) launched in April of 2014 and 2016, respectively. These two satellites both have a 12-day repeat cycle at the equator, and are phased at 180 deg to provide an effective 6-day repeat cycle. For each satellite, the expected lifetime is 7 years. Both carry a C-band SAR instrument with a center frequency of 5.405 GHz (5.5 cm wavelength). There are four exclusive imaging modes (Interferometric Wide swath, Extra Wide swath mode, Strip Map and Wave Mode) for the S-1 SAR sensors. WV is the default operational mode over open ocean unless wide-swath SAR images are requested for particular applications.

File Size Format Processing Access
Information of ten defined geophysical categories 164 bytes TEXTE Open access
Information of the labeled SAR images, including file name, labeling, swath, capture time, and centre latitude and longitude 3 MB TEXTE Open access
High quality images for machine learning approach 15 GB IMAGE Processed data Open access
Quick-looks for human visual inspection 16 GB IMAGE Processed data Open access
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How to cite 

Wang Chen, Mouche Alexis, Tandeo Pierre, Stopa Justin, Longépé Nicolas, Erhard Guillaume, Foster Ralph, Vandemark Douglas, Chapron Bertrand (2018). Labeled SAR imagery dataset of ten geophysical phenomena from Sentinel-1 wave mode (TenGeoP-SARwv). SEANOE.

In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :

Wang Chen, Mouche Alexis, Tandeo Pierre, Stopa Justin, Longépé Nicolas, Erhard Guillaume, Foster Ralph C., Vandemark Douglas, Chapron Bertrand (2019). A labelled ocean SAR imagery dataset of ten geophysical phenomena from Sentinel‐1 wave mode. Geoscience Data Journal, 6(2), 105-115. Publisher's official version : , Open Access version :