Literature DB >> 24759508

Review of oil spill remote sensing.

Merv Fingas1, Carl Brown2.   

Abstract

Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Laser fluorosensor; Oil detection; Oil spill remote sensing; Oil spill surveillance; Oil spill thickness measurement

Mesh:

Substances:

Year:  2014        PMID: 24759508     DOI: 10.1016/j.marpolbul.2014.03.059

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


  15 in total

1.  Synergistic use of an oil drift model and remote sensing observations for oil spill monitoring.

Authors:  Diana De Padova; Michele Mossa; Maria Adamo; Giacomo De Carolis; Guido Pasquariello
Journal:  Environ Sci Pollut Res Int       Date:  2016-12-27       Impact factor: 4.223

2.  Satellite data lift the veil on offshore platforms in the South China Sea.

Authors:  Yongxue Liu; Chao Sun; Jiaqi Sun; Hongyi Li; Wenfeng Zhan; Yuhao Yang; Siyu Zhang
Journal:  Sci Rep       Date:  2016-09-19       Impact factor: 4.379

3.  Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation.

Authors:  Pablo Gil; Beatriz Alacid
Journal:  Sensors (Basel)       Date:  2018-01-08       Impact factor: 3.576

Review 4.  A Review of Oil Spill Remote Sensing.

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

5.  Design and Implementation of a Coastal-Mounted Sensor for Oil Film Detection on Seawater.

Authors:  Yongchao Hou; Ying Li; Bingxin Liu; Yu Liu; Tong Wang
Journal:  Sensors (Basel)       Date:  2017-12-28       Impact factor: 3.576

6.  Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

Authors:  Hao Guo; Danni Wu; Jubai An
Journal:  Sensors (Basel)       Date:  2017-08-09       Impact factor: 3.576

7.  Segmentation of Oil Spills on Side-Looking Airborne Radar Imagery with Autoencoders.

Authors:  Antonio-Javier Gallego; Pablo Gil; Antonio Pertusa; Robert B Fisher
Journal:  Sensors (Basel)       Date:  2018-03-06       Impact factor: 3.576

8.  A New Approach of Oil Spill Detection Using Time-Resolved LIF Combined with Parallel Factors Analysis for Laser Remote Sensing.

Authors:  Deqing Liu; Xiaoning Luan; Jinjia Guo; Tingwei Cui; Jubai An; Ronger Zheng
Journal:  Sensors (Basel)       Date:  2016-08-23       Impact factor: 3.576

9.  Hyperspectral and Radar Airborne Imagery over Controlled Release of Oil at Sea.

Authors:  Sébastien Angelliaume; Xavier Ceamanos; Françoise Viallefont-Robinet; Rémi Baqué; Philippe Déliot; Véronique Miegebielle
Journal:  Sensors (Basel)       Date:  2017-08-02       Impact factor: 3.576

10.  Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction.

Authors:  Bingxin Liu; Ying Li; Chengyu Liu; Feng Xie; Jan-Peter Muller
Journal:  Sensors (Basel)       Date:  2018-01-15       Impact factor: 3.576

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