Skip to content

Science Topic

Oil pollution

PML routinely monitors areas to detect if oil pollution occurs, so timely action can be taken.

PML have developed a Machine Learning algorithm to automatically detect oil slicks from satellite data. By routinely downloading and processing satellite data after every overpass and applying this automated oil slick detection it is possible to monitor areas for possible slicks and alert government authorities so that timely action can be taken.

The technique was developed in the Malacca strait, one of the busiest shipping lanes in the world, where oil spills are known to have disastrous consequences. It is currently being used as part of the EO4SD project to monitor oil spills off the coast of West Africa. Through this monitoring, regular discharges off the coast of Ghana have been identified. The commercial service developed in EASOS is being offered to government and industry through PML Applications.

Resources and Links

EASOS Marine Watch case study

Capabilities

  • Operational Satellite Data Processing
  • Automated Oil Spill Detection
  • Expertise in image interpretation

Selected publications

Kurekin, AA; Loveday, BR; Clements, O; Quartly, GD; Miller, PI; Wiafe, G; et al. 2019. Operational Monitoring of Illegal Fishing in Ghana through Exploitation of Satellite Earth Observation and AIS Data. Remote Sensing.

People who work in this area of research

Dr Elizabeth C. Atwood

Earth Observation Data Analyst
liat11/30/2022 11:12:11 PM@pml.ac.uk

Dr Dan Clewley

Earth Observation Research Software Engineer
dac11/30/2022 11:12:11 PM@pml.ac.uk

William Jay

Airborne Earth Observation Data Analyst
wja11/30/2022 11:12:11 PM@pml.ac.uk

Dr Andrey Kurekin

Coastal Ocean Colour scientist
anku11/30/2022 11:12:11 PM@pml.ac.uk

Dr Mark Warren

Remote sensing scientist
mark111/30/2022 11:12:11 PM@pml.ac.uk