Review of oil spill remote sensing

Fingas, Mervin F.; Brown, Carl E.

doi:10.1016/j.marpolbul.2014.03.059

Cited by 466 publications

(245 citation statements)

References 81 publications

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“…Oil spills have been widely monitored, although RS data seem to only complement rather than fully replace airborne observations, due to the particularities of oil spills (Leifer et al 2012). SAR data are mainly used to detect oil spills in oceans, because of their all weather and illumination condition monitoring, wide coverage, and the ability to separate oil from surrounding water area, under low or moderate wind (Fingas and Brown 2014), where oil surface appears significantly smoother. Mera et al (2012) used ENVISAT Advanced SAR (ASAR) data with an Adaptive thresholding algorithm to almost perfectly label oil spill pixels in Iberian Peninsula.…”

Section: Forestry Monitoringmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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Recognizing the imperative need for biodiversity protection, the Convention on Biological Diversity (CBD) has recently established new targets towards 2020, the so-called Aichi targets, and updated proposed sets of indicators to quantitatively monitor the progress towards these targets. Remote sensing has been increasingly contributing to timely, accurate, and cost-effective assessment of biodiversity-related characteristics and functions during the last years. However, most relevant studies constitute individual research efforts, rarely related with the extraction of widely adopted CBD biodiversity indicators. Furthermore, systematic operational use of remote sensing data by managing authorities has still been limited. In this study, the Aichi targets and the related CBD indicators whose monitoring can be facilitated by remote sensing are identified. For each headline indicator a number of recent remote sensing approaches able for the extraction of related properties are reviewed. Methods cover a wide range of fields, including: habitat extent and condition monitoring; species distribution; pressures from unsustainable management, pollution and climate change; ecosystem service monitoring; and conservation status assessment of protected areas. The advantages and limitations of different remote sensing data and algorithms are discussed. Sorting of the methods based on their reported accuracies is attempted, when possible. The extensive literature survey aims at reviewing highly performing methods that can be used for large-area, effective, and timely biodiversity assessment, to encourage the more systematic use of remote sensing solutions in monitoring progress towards the Aichi targets, and to decrease the gaps between the remote sensing and management communities.

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Section: Forestry Monitoringmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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“…Many remote sensing techniques (spectral imaging, radars, UV/IR scanners etc.) are used to detect oil spills by observation of various oil-mediated sea surface roughness modifications (Fingas and Brown 2014). In that regard, multiple sensors can be combined for improving the reliability of oil detection and decrease the false alarm rate.…”

Section: Introductionmentioning

confidence: 99%

Compact HLIF LiDAR for marine applications

Babichenko

Poryvkina

Rebane

et al. 2016

International Journal of Remote Sensing

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The accidental discharge or accumulated pollution in seawater constitutes high risk of damage to the marine environment. Early detection of deviations in water quality allows taking preventive measures in order to minimize harmful influence of pollution or to implement adequate response actions before the pollution becomes a major spill. This requires regular monitoring of risk areas with effective, reliable, and economically sustainable solutions. The Hyperspectral Laser Induced Fluorescence (HLIF) LiDAR (light detection and ranging) combines highly sensitive and selective oil-in-water detection with characterization capabilities based on feature extraction and pattern recognition in HLIF spectra. Therefore, this technique is equally effective for oil detection in open and coastal waters. Operated in unattended mode as a payload of marine vehicles, it delivers the real-time analytical capabilities directly on site. This article describes the development of HLIF LiDAR and its application on board of operational vessels in the Norwegian Sea, Barents Sea, and the Baltic Sea during the period

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“…For marine oil spill management, science and technology such as remote sensing are essential for management agencies to make timely decision and effective response when an oil spill accident happens (Fingas and Brown, 2014;Xu et al, 2014). Compared with the current development and actual requirement, although the R&D activities in China have been rapidly developed in recent years, there are still shortcomings that need to be addressed in the future.…”

Section: Randd Projectsmentioning

confidence: 99%