GOM OI: Oil Slick Thickness and Coverage from Remote Sensing, 2016-2018

NOAA's Deepwater Horizon Lessons Learned Studies produced this dataset on methods to estimate oil slick coverage and thickness. The research combined satellite imagery, airborne imagery, surface characterization, and subsurface data from the chronic MC20 oil discharge site and controlled tests at Ohmsett. Data shown here are from field research at the Mississippi Canyon lease block #20 (MC20) undertaken in 2016, 2017, and 2018.

Use Cases

• Train models to detect oil slick presence based on satellite and airborne imagery mentioned in the description.
• Estimate oil thickness and emulsion mixtures using the multi-platform remote sensing methods described.
• Analyze chronic oil discharge patterns from the MC20 site using the 2016-2018 field research data.
• Benchmark oil spill response technologies with data collected from both field and simulated (Ohmsett) environments.

Strengths

• Data collection was funded by multiple U.S. government agencies including DOI, BSEE, and NOAA.
• Research combines data from a real-world chronic discharge site (MC20) and a controlled test tank (Ohmsett).
• Field research spans three years (2016, 2017, and 2018) at the MC20 site.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Primary file formats are PDF and HTML, which may require extraction for computational analysis.

Provenance

Source

National Oceanic and Atmospheric Administration (NOAA), Department of Commerce

Collection Method

Synoptic collection of satellite imagery, airborne imagery, surface oil characterization, oil and water chemistry, and subsurface oil slick data.

Time Range

2016, 2017, 2018

Freshness

Last updated 2026-03-13 22:24:17.896877; freshness should be verified.

Geography

Mississippi Canyon lease block #20 (MC20) in the Gulf of Mexico and the Oil and Hazardous Materials Simulated Environmental Test Tank (Ohmsett).