Application of remote sensing data for oil spill monitoring in the Guanabara Bay, Rio de Janeiro, Brazil

Bentz, Cristina Maria; Miranda, Fernando

doi:10.1109/igarss.2001.976149

Cited by 11 publications

(6 citation statements)

References 2 publications

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“…Also, a failed scan-line corrector has impacted ETM+ data since 2003. Landsat data have been used to map oil slicks, although the coarser temporal sampling makes it unsuitable for slick monitoring (Bentz & Pellon de Miranda, 2001). Still, Landsat data could aid extrapolating airborne slick data to larger scales in certain situations.…”

Section: Satellite Visible Oil Slick Remote Sensingmentioning

confidence: 99%

State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill

Leifer

Lehr²,

Simecek-Beatty³

et al. 2012

Remote Sensing of Environment

450

298

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Section: Satellite Visible Oil Slick Remote Sensingmentioning

confidence: 99%

State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill

Leifer

Lehr²,

Simecek-Beatty³

et al. 2012

Remote Sensing of Environment

450

298

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“…For example, Landsat 5 TM (1984-2013 captured the image of an oil spill emergency in the Guanabara Bay, Brazil [26], and Essa et al [27] successfully used Landsat 7 ETM + (1999-present) to detect oil slicks in the Arabian Gulf. Landsat 8 was launched in February 2013 and will provide continuity of 40-year imaging data set.…”

Section: Introductionmentioning

confidence: 99%

Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf

Zhao¹,

Temimi²,

Ghedira³

et al. 2014

Opt. Express

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Remote sensing provides an effective tool for timely oil pollution response. In this paper, the spectral signature in the optical and infrared domains of oil slicks observed in shallow coastal waters of the Arabian Gulf was investigated with MODIS, MERIS, and Landsat data. Images of the Floating Algae Index (FAI) and estimates of sea currents from hydrodynamic models supported the multi-sensor oil tracking technique. Scenes with and without sunglint were studied as the spectral signature of oil slicks in the optical domain depends upon the viewing geometry and the solar angle in addition to the type of oil and its thickness. Depending on the combination of those factors, oil slicks may exhibit dark or bright contrasts with respect to oil-free waters. Three oil spills events were thoroughly analyzed, namely, those detected on May 26 2000 by Landsat 7 ETM + and MODIS/Terra, on October 21 2007 by MERIS and MODIS, and on August 17 2013 by Landsat 8 and MODIS/Aqua. The oil slick with bright contrast observed by Landsat 7 ETM + on May 26 2000 showed lower temperature than oil-free areas. The spectral Rayleigh-corrected reflectance (R(rc)) signature of oil-covered areas indicated higher variability due to differences in oil fractions while the R(rc) spectra of the oil-free area were persistent. Combined with RGB composites, FAI images showed potentials in differentiating oil slicks from algal blooms. Ocean circulation and wind data were used to track oil slicks and forecast their potential landfall. The developed oil spill maps were in agreement with official records. The synergistic use of satellite observations and hydrodynamic modeling is recommended for establishing an early warning and decision support system for oil pollution response.

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“…The chosen classification algorithm was the Unsupervised Semivariogram Textural Classifier (USTC), which was subsequently used in [18], [19] and [20] to identify potential natural oil slicks based on seasurface radar textures in the deepwater mouth of the Amazon River. This classifier was also successfully used to identify mesoscale oceanic features in the offshore Campos Basin, southeastern Brazil [21], and to highlight oil-covered areas on the water surface during the Guanabara Bay spill, Rio de Janeiro, Brazil [22] and [23].…”

Section: Criteria For Selection Of Sar Images and Textural Classmentioning

confidence: 99%

A multi-sensor approach and ranking analysis procedure for oil seeps detection in marine environments

Pedroso

Miranda

Bannerman³

et al. 2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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Accidents involving oil spills from petroleum exploration, production, and transportation facilities have stained the history of major companies. The implementation of monitoring systems as an aid to contingency planning is crucial to guarantee proper environmental performance in offshore activities. On the other hand, natural oil and gas seeps have historically provided invaluable information to oil explorers in frontier areas. The use of Synthetic Aperture Radar (SAR) orbital systems is commonly used for oil slicks detection in the marine environment. Such information can be applied to petroleum exploration (oil seeps detection) and environmental assessment (oil spills monitoring). In combination with SAR satellite images (RADARSAT-1 and ENVISAT ASAR), and essential meteorological and oceanographic data, the proposed technology enhances the detection of oil slicks in the ocean surface based on radar texture.

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Application of remote sensing data for oil spill monitoring in the Guanabara Bay, Rio de Janeiro, Brazil

Cited by 11 publications

References 2 publications

State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill

State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill

Exploring the potential of optical remote sensing for oil spill detection in shallow coastal waters-a case study in the Arabian Gulf

A multi-sensor approach and ranking analysis procedure for oil seeps detection in marine environments

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