Abstract
In this work, we use deep neural autoencoders to segment oil spills from Side-Looking Airborne Radar (SLAR) imagery. Synthetic Aperture Radar (SAR) has been much exploited for ocean surface monitoring, especially for oil pollution detection, but few approaches in the literature use SLAR. Our sensor consists of two SAR antennas mounted on an aircraft, enabling a quicker response than satellite sensors for emergency services when an oil spill occurs. Experiments on TERMA radar were carried out to detect oil spills on Spanish coasts using deep selectional autoencoders and RED-nets (very deep Residual Encoder-Decoder Networks). Different configurations of these networks were evaluated and the best topology significantly outperformed previous approaches, correctly detecting 100% of the spills and obtaining an score of 93.01% at the pixel level. The proposed autoencoders perform accurately in SLAR imagery that has artifacts and noise caused by the aircraft maneuvers, in different weather conditions and with the presence of look-alikes due to natural phenomena such as shoals of fish and seaweed.
Highlights
A quick response from governments is required in situations of marine pollution due to oil spills [1]
Governments use mainly two kinds of sensors to carry out the monitoring of the sea surface: Synthetic Aperture Radar (SAR) installed on satellites (ERS-1/2, JERS-1, Envisat ASAR, RADARSAT-1, RADARSAT-2, COSMO-SkyMed, Sentinel-1, Sentinel-2, ALOS-2, TerraSAR-X among others) as in CleanSeaNet, and Side-Looking Airborne Radar (SLAR) or another airborne miniaturized radar as in [5]
We propose using autoencoders that receive as input the signal of SLAR sensors and return as output the areas detected as oil spills
Summary
A quick response from governments is required in situations of marine pollution due to oil spills [1]. When an oil slick is detected, the authorities activate the emergency protocols in order to control the environmental impact and the ecological damage in the sea. Governments use mainly two kinds of sensors to carry out the monitoring of the sea surface: Synthetic Aperture Radar (SAR) installed on satellites (ERS-1/2, JERS-1, Envisat ASAR, RADARSAT-1, RADARSAT-2, COSMO-SkyMed, Sentinel-1, Sentinel-2, ALOS-2, TerraSAR-X among others) as in CleanSeaNet, and Side-Looking Airborne Radar (SLAR) or another airborne miniaturized radar as in [5]. Both sensors can be used for oil slick detection
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