Abstract:

This dataset includes oil presence/absence data and delineated oil slick polygons (in the study include Landsat TM, Landsat ETM+, Landsat OLI and Sentinel-2A.shapefiles) from satellite imagery at the MC-20 Taylor oil spill site in 2004-2016. Oil slicks were identified from its spatial contrast with clear water and its unique spectral response comparing to oil look-alikes (like Sargassum or Trichodesmium mats). Identified oil slicks without large cloud blockage are then delineated manually in ArcMAP.

Suggested Citation:

Shaojie Sun and Chuanmin Hu. 2017. Oil spill statistical assessment at MC-20 Taylor oil spill site from satellite imagery in 2004-2016. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7M9072W

Publications:

Sun, S., Hu, C., Garcia-Pineda, O., Kourafalou, V., Le Hénaff, M., & Androulidakis, Y. (2018). Remote sensing assessment of oil spills near a damaged platform in the Gulf of Mexico. Marine Pollution Bulletin, 136, 141–151. doi:10.1016/j.marpolbul.2018.09.004

Garcia-Pineda, O., Androulidakis, Y., Le Hénaff, M., Kourafalou, V., Hole, L. R., Kang, H., … DiPinto, L. (2020). Measuring oil residence time with GPS-drifters, satellites, and Unmanned Aerial Systems (UAS). Marine Pollution Bulletin, 150, 110644. doi:10.1016/j.marpolbul.2019.110644

Purpose:

To objectively document and assess oil spills through remote sensing from the MC-20 Taylor well site in 2004—2016.

Data Parameters and Units:

Delineated oil presence from satellite (area, km2), Year, Month, Day, Oil detected (1=yes or 0=no), Sensor filenames begin with 7 digit number of four digit year and three digit day of year; the rest are sensor name

Individual Files: