Dataset Available

Identification of thick oil features on unmanned aerial system (UAS) imagery

Authors: Garcia-Pineda, Oscar
Published On: Apr 11 2018 16:35 UTC
DOI: https://doi.org/10.7266/N7JS9NTB
UDI: R5.x281.000:0007
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No. of Downloads: 17

No. of Files: 65

File Size: 1.51 GB

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Project Information

Funded By:
Gulf of Mexico Research Initiative

Funding Cycle:
RFP-V

Research Group:
Influence of river induced fronts on hydrocarbon transport

Point of Contact

HeeSook Kang
University of Miami / Rosenstiel School of Marine and Atmospheric Science
hkang@rsmas.miami.edu

Data Collection Period
2016-10-15
to
2017-11-16
Theme keywords

aerial photography, photo survey, Taylor, MC20, unmanned aerial system

ISO 19115-2 Metadata
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Abstract:

This dataset is based on photo-GPS reconnaissance surveys of the floating oil types around the Taylor energy platform, under different environmental conditions. The surveys consist of boat expeditions, aided by aerial photography and satellite imagery, to survey the detailed characteristics of the oil patch (water constituents and floating oil) associated with the Taylor Energy continuous oil leakage site. This dataset contains drone images collected from October 2016 to November 2017.

Suggested Citation:

Garcia-Pineda, Oscar. 2018. Identification of thick oil features on unmanned aerial system (UAS) imagery. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7JS9NTB

Purpose:

To survey the detailed characteristics of the oil patch (water constituents and floating oil) associated with the Taylor Energy continuous oil leakage site.

Data Parameters and Units:

Red green blue (RGB) images taken from drone. Photo file name, Date (MMDDYY), Time (HHMMSS)

Individual Files: