VDS2RAW

The dataset described in the provided information is called VDS2RAW (Vessel Detection from Sentinel-2 Raw). It is a collection of raw granules derived from Sentinel-2 products, specifically focusing on vessels in Danish coastal areas. The dataset is utilized for ship detection and analysis purposes. To construct this, a reference dataset containing Sentinel-2 L1C tiles, including vessel images, was initially identified. This reference dataset was obtained from the work of Ruiloba et al. (2020), consisting of Sentinel-2 L1C tiles acquired in 2019. The dataset contained 1426 ship images in 24x24 pixel dimensions.

To download the specific granules of interest (L0 granules), a polygon encompassing the region of interest (ROI) and a date range was defined. The download process retrieved all L0 granules where the reference band (B02) intersected the ROI during the specified time period. By applying a sufficient margin to ensure the inclusion of all relevant bands, a polygon surrounding the ROI and all the ships for each of the eight acquisition days was used.

A total of 390 L0 granules were downloaded and decompressed to obtain raw processable data. To label the dataset, bounding boxes were manually created around each ship using bands B02, B03, and B04. The coarse spatial coregistration technique, described in (Meoni et al., 2023), was applied to enable manual labeling. Missing elements due to coregistration procedures were filled using adjacent granule pixels when possible, and in other cases, the areas with missing pixels were cropped. Consequently, the granules had varying pixel areas. After labeling, a subset of 166 raw granules was selected from the initially downloaded 390 granules. The dataset was further divided into training (105), validation (27), and test (34) sets. The number of ship annotations in each set was 483, 119, and 93, respectively. The average pixel area of the granules in the dataset was calculated as 2588.971 pixels by 1669.44 pixels, while the mean annotation area was 13.59 square pixels by 15.67 square pixels.