Literature DB >> 26725867

Oil slick morphology derived from AVIRIS measurements of the Deepwater Horizon oil spill: Implications for spatial resolution requirements of remote sensors.

Shaojie Sun1, Chuanmin Hu2, Lian Feng1, Gregg A Swayze3, Jamie Holmes4, George Graettinger5, Ian MacDonald6, Oscar Garcia6, Ira Leifer7.   

Abstract

Using fine spatial resolution (~7.6m) hyperspectral AVIRIS data collected over the Deepwater Horizon oil spill in the Gulf of Mexico, we statistically estimated slick lengths, widths and length/width ratios to characterize oil slick morphology for different thickness classes. For all AVIRIS-detected oil slicks (N=52,100 continuous features) binned into four thickness classes (≤50 μm but thicker than sheen, 50-200 μm, 200-1000 μm, and >1000 μm), the median lengths, widths, and length/width ratios of these classes ranged between 22 and 38 m, 7-11 m, and 2.5-3.3, respectively. The AVIRIS data were further aggregated to 30-m (Landsat resolution) and 300-m (MERIS resolution) spatial bins to determine the fractional oil coverage in each bin. Overall, if 50% fractional pixel coverage were to be required to detect oil with thickness greater than sheen for most oil containing pixels, a 30-m resolution sensor would be needed.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  AVIRIS; Landsat; MERIS; Morphology; Oil spill; Remote sensing

Mesh:

Year:  2015        PMID: 26725867     DOI: 10.1016/j.marpolbul.2015.12.003

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  3 in total

Review 1.  A Review of Oil Spill Remote Sensing.

Authors:  Merv Fingas; Carl E Brown
Journal:  Sensors (Basel)       Date:  2017-12-30       Impact factor: 3.576

2.  Natural and unnatural oil slicks in the Gulf of Mexico.

Authors:  I R MacDonald; O Garcia-Pineda; A Beet; S Daneshgar Asl; L Feng; G Graettinger; D French-McCay; J Holmes; C Hu; F Huffer; I Leifer; F Muller-Karger; A Solow; M Silva; G Swayze
Journal:  J Geophys Res Oceans       Date:  2015-12-28       Impact factor: 3.405

3.  Detecting the Presence of Different Types of Oil in Seawater Using a Fluorometric Index.

Authors:  Emilia Baszanowska; Zbigniew Otremba
Journal:  Sensors (Basel)       Date:  2019-08-31       Impact factor: 3.576

  3 in total

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