Summary: | This archival information package (AIP) contains Environmental Response Management Application (ERMA) GIS layers of outputs from Synthetic Aperture Radar (SAR) imagery that has been processed using the Texture Classifying Neural Network Algorithm (TCNNA). This algorithm classifies SAR data on a pixel by pixel basis, into oil or not-oil classes. The fully implemented TCNNA routine produces approximately a one megabyte georectified, raster image in which all pixels receive a binary classification of 1 for no oil and 0 for oil. Each classified raster image was converted to polygons and clipped to within approximately 20 kilometers of the coastline. This data was collected from April 29th 2010 to August 11th 2010. These data were collected during the response to the Mississippi Canyon 252 Deepwater Horizon oil spill in the Northern Gulf of Mexico and used as part of the Programmatic Damage Assessment and Restoration Plan (PDARP).
|