Abstract:

This dataset contains satellite-borne synthetic aperture radar (SAR) images from offshore Louisiana, 2004-2012. SAR images provided by the Center for Spatial Technologies and Remote Sensing (CSTARS), the European Space Agency (ESA), and the National Aeronautics and Space Administration (NASA). Images associated with Gulf oil spills were processed using either the Texture Classifying Neural Network Algorithm (TCCNA) or the digitizing tool in ArcGIS to manually identify oil slicks. This dataset supports the publication: Asl, S.D., Amos, J., Woods, P., Garcia-Pineda, O., and MacDonald, I.R. (2015). Chronic, Anthropogenic Hydrocarbon Discharges in the Gulf of Mexico. Deep Sea Research Part II: Topical Studies in Oceanography 129: 187-195.

Suggested Citation:

Ian MacDonald. 2016. Remote Sensing Data for Anthropogenic Chronic Oil Discharge - Offshore Louisiana, 2004-2012. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7R78C7C

Publications:

Asl, S. D., Amos, J., Woods, P., Garcia-Pineda, O., & MacDonald, I. R. (2014). Chronic, anthropogenic Hydrocarbon Discharges in the gulf of Mexico. Deep Sea Research Part II: Topical Studies in Oceanography. doi:10.1016/j.dsr2.2014.12.006

Purpose:

Satellite-borne Synthetic Aperture Radar (SAR) was used to obtain more precise estimates of the magnitude of the chronic hydrocarbon discharges described in qualitative pollution reports associated with the production and transportation network of the U.S. coast of the Gulf of Mexico.

Data Parameters and Units:

TCNNA Extracted Oil Slicks: Image files (.tif) Manually Extracted Oil Slicks: ArcGIS shapefiles (.shp)

Methods:

The National Response Center (NRCen) oil spill reports in the Gulf of Mexico were collected. We matched the times and the locations of the reported oil spills against the coverage and acquisition times of the SAR images and determined whether the reports coincided with archived SAR images. When matches were found, we used the Texture Classifying Neural Network Algorithm (TCNNA) to determine the location and extent of oil-covered water. The TCNNA is not trained for COSMO-SkyMed images; therefore, we used the digitizing tool of ArcGIS to manually delineate oil slicks in COSMO-SkyMed images. After oil slicks had been extracted, we used ArcToolbox’s Conversion and Spatial Statistics tools to calculate the area and location of the extracted oil slicks.

Individual Files: