Dataset Available

Daily Surface Oil Grids, Gulf of Mexico, April 24 to August 11, 2010, Textural Classifier Neural Netwark Algorithm(TCNNA)

Authors: Garcia-Pineda, Oscar, et al.
Published On: Oct 06 2015 22:12 UTC
DOI: https://doi.org/10.7266/N7736NVZ
UDI: Y1.x047.000:0002
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Individual Files

No. of Downloads: 28

No. of Files: 340

File Size: 515.17 MB

File Format(s):
shapefiles

Project Information

Funded By:
Gulf of Mexico Research Initiative

Funding Cycle:
Florida Institute of Oceanography (FIO)

Research Group:
Coast Watch: Remote Sensing and Verification Sampling of Oil Spill Impact on Florida Coast

Point of Contact

Ian MacDonald
Florida State University / Department of Earth, Ocean, and Atmospheric Science
imacdonald@fsu.edu

Data Collection Period
2010-04-24
to
2013-01-30
Theme keywords

spatial extent of oil, mapping oil, remote sensing

ISO 19115-2 Metadata
  View Metadata
Abstract:

This dataset contains the daily grids of the Textural Classifier Neural Netwark Algorithm TCNNA outputs. Reference: Garcia-Pineda, O. ; MacDonald, I.R. ;Li, X. ; Jackson, C.R. Pichel, W.G. 2013. Oil Spill Mapping and Measurement in the Gulf of Mexico With Textural Classifier Neural Network Algorithm (TCNNA). IEEE Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Volume 6. Issue 6.

Suggested Citation:

Garcia-Pineda, Oscar, et al.. 2015. Daily Surface Oil Grids, Gulf of Mexico, April 24 to August 11, 2010, Textural Classifier Neural Netwark Algorithm(TCNNA). Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7736NVZ

Publications:

Garcia-Pineda, O., MacDonald, I. R., Li, X., Jackson, C. R., & Pichel, W. G. (2013). Oil Spill Mapping and Measurement in the Gulf of Mexico With Textural Classifier Neural Network Algorithm (TCNNA). IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing, 6(6), 2517–2525. doi:10.1109/jstars.2013.2244061

Purpose:

To analyze the presence of oil from the Deep Water Horizon

Data Parameters and Units:

Shapefile attribute table - Count_, classification of pixels into 'oil pixel value' = 1 or 'non-oil pixel value' = 0, geometry type polygon, id fields - Id, ET_ID,FID_1, ET_Index

Individual Files: