# Mass Processing of Sentinel-1 Images for
## 1 Introduction  
Maritime surveillance can be defined as the monitoring of human activities at sea. The surveillance is intended to support efforts related with security (e.g., irregular sea border crossing, and smuggling of illegal goods or substances), safety (e.g., Search and Rescue, and shipping traffic), and environmental and sustainability (e.g., fishing control, and pollution) aspects. This paper focuses on shipping activities, although some views on non-shipping activities (e.g., fixed oil and gas platforms, aquaculture equipment, or offshore wind farms) are also gained as a by-product. Shipping monitoring systems can broadly be classified in two groups: cooperative and non-cooperative. Cooperative systems rely on the ships reporting information about themselves (e.g., identification, position, and speed). Commonly used self-reporting systems are the Automatic Identification System (AIS [1]), Long Range Identification and Tracking (LRIT [2]) and Vessel Monitoring System (VMS [3, 4]). Some of the most widely used non-cooperative systems employ radar sensors (coastal, shipborne, airborne, and spaceborne) to detect the ships from the backgroundsea clutter without relying on the ships' cooperation. This study concerns the use of spaceborne SAR sensors for ship detection and the fusion of this information with AIS reports. Ship detection in satellite SAR images is operationally used in various regions, for instance in Canada [5] and in Europe [6]. Maritime surveillance conducted with such images does not require the vessels' cooperation, provides wide-area monitoring even of remote regions, and can be operated day and night and regardless of cloud cover conditions (although weather phenomena such as strong wind and strong precipitation will hamper the performance). Most SAR ship detection techniques rely on the idea that the ships reflect the radar signal differently to how the sea surface does it, thus affecting some property (intensity and polarimetry) of the signal that is received back by the sensor, and therefore allowing the discrimination of the ships against the background sea clutter. See [7; 8] for more details on ship detection approaches. Validation of these techniques is not an easy task since it involves a precise knowledge of the shipping activity in an area, which can be uncontrollable especially in wide areas, and because the performance of the techniques depends on many different variables (sea state, wind, ship's size, material and geometry, radar resolution and incidence angle, and aspect angle). See [9; 10; 11; 12; 13; 14; 15] for some validation efforts. Sentinel-1 is the SAR satellite constellation of the European Union's Copernicus programme for Earth Observation, operated by the European Space Agency (ESA). It consists of two units, Sentinel-1A launched on 3 April 2014 and Sentinel-1B launched on 25 April 2016, which entered into operation on 3 October 2014 and 26 September 2016, respectively. It uses a C-band instrument (frequency 5.405 GHz), and can operate in four acquisition modes: Extra Wide (EW), Interferometric Wide (IW), Stripmap (SM) and Wave (WV). The data can be processed to various types of image product, and the Ground Range Detected High resolution (GRDH) product [16; 17] is the one used in this study. The radar can transmit in vertical (V) or horizontal (H) polarisation, and can receive in H, V or in both of them simultaneously. A Sentinel-1 product can therefore have one of the following combinations of polarisations: single channel HH, VV, HV or VH, or dual HH + HV or VV + VH, the first letter being the transmitted polarisation and the second one the received polarisation [16].