This data set contains 1000 annotated imagettes (20x20 km approx.) of Sentinel-1 Wave Mode acquisition in the form of JSON polygons among 10 metocean features down to 50 meters resolution typically (see illustration) :

Atmospheric Fronts

Biological Slicks

Iceberg

Low Wind Area

Micro-Convective Cells

Oceanic Front

Pure Ocean Waves

Rain Cells

Sea-Ice

Wind Streaks

The present data set extends TenGeoP categorization (1 feature per imagette) to pixel-level segmentation among all 10 features listed above. Its main goal is the training of Deep Learning segmenters, with applications in automatic mapping of ocean surface processes [1] and in understanding air-sea interactions. A Jupyter notebook is provided in the dataset archive to consult the annotation. Raw Sentinel-1 sea surface roughness images in this dataset are a 1000 elements subset of the TenGeoP labelled SAR images data set [2, 3], equally balanced between the so-called wave mode 1 and 2 (23 and 36° incidence respectively). A labelling methodology coherent with TenGeoP is here undertaken. The user should refer to [2] to access raw SAR images and read about their processing.