Ocean Imaging Corporation

Solana Beach, CA, United States

Ocean Imaging Corporation

Solana Beach, CA, United States
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Svejkovsky J.,Ocean Imaging Corporation | Lehr W.,National Oceanographic and Atmospheric Administration | Muskat J.,Office of Spill Prevention and Response | Graettinger G.,National Oceanographic and Atmospheric Administration | Mullin J.,Joseph Mullin Consulting LLC
Photogrammetric Engineering and Remote Sensing | Year: 2012

A rapidly deployable aerial multispectral sensor utilizing four channels in the visible-near-IR and one channel in the thermal IR was developed along with processing software to identify oil-on-water and map its spatial extents and thickness distribution patterns. Following validation over natural oil seeps and at Bureau of Safety and Environmental Enforcement's (BSEE's) Ohmsett test tank, the system was utilized operationally on a near-daily basis for three months during the Deepwater Horizon (MC-252) spill in the Gulf of Mexico in summer 2010. Digital, GIS-compatible analyses were produced and disseminated following each flight mission. The analysis products were utilized for a multitude of response activities including daily offshore oil recovery planning, oil trajectory modeling, dispersant application effect documentation, beached oil mapping and documentation of the relative oil amount along the spill's offshore perimeter. The system's prime limitation was its relatively narrow imaging footprint and low sun angle requirement to minimize sunglint, both of which limited the total area that could be imaged each day. This paper discusses the system's various applications as well as limitations that were encountered during its use in the Deepwater Horizon incident. © 2012 American Society for Photogrammetry and Remote Sensing.


Svejkovsky J.,Ocean Imaging Corporation | Nezlin N.P.,Southern California Coastal Water Research Project | Mustain N.M.,Ocean Imaging Corporation | Kum J.B.,Ocean Imaging Corporation
Estuarine, Coastal and Shelf Science | Year: 2010

Spatial-temporal characteristics and environmental factors regulating the behavior of stormwater runoff from the Tijuana River in southern California were analyzed utilizing very high resolution aerial imagery, and time-coincident environmental and bacterial sampling data. Thirty nine multispectral aerial images with 2.1-m spatial resolution were collected after major rainstorms during 2003-2008. Utilizing differences in color reflectance characteristics, the ocean surface was classified into non-plume waters and three components of the runoff plume reflecting differences in age and suspended sediment concentrations. Tijuana River discharge rate was the primary factor regulating the size of the freshest plume component and its shorelong extensions to the north and south. Wave direction was found to affect the shorelong distribution of the shoreline-connected fresh plume components much more strongly than wind direction. Wave-driven sediment resuspension also significantly contributed to the size of the oldest plume component. Surf zone bacterial samples collected near the time of each image acquisition were used to evaluate the contamination characteristics of each plume component. The bacterial contamination of the freshest plume waters was very high (100% of surf zone samples exceeded California standards), but the oldest plume areas were heterogeneous, including both polluted and clean waters. The aerial imagery archive allowed study of river runoff characteristics on a plume component level, not previously done with coarser satellite images. Our findings suggest that high resolution imaging can quickly identify the spatial extents of the most polluted runoff but cannot be relied upon to always identify the entire polluted area. Our results also indicate that wave-driven transport is important in distributing the most contaminated plume areas along the shoreline. © 2010 Elsevier Ltd. All rights reserved.


Leifer I.,University of California at Santa Barbara | Clark R.,U.S. Geological Survey | Jones C.,Jet Propulsion Laboratory | Holt B.,Jet Propulsion Laboratory | And 2 more authors.
Proceedings of the 34th AMOP Technical Seminar on Environmental Contamination and Response | Year: 2011

The vast, persistent, and unconstrained oil release from the DeepWater Horizon (DWH) challenged the spill response, which required accurate quantitative oil assessment at synoptic and operational scales. Experienced observers are the mainstay of oil spill response. Key limitations are weather, scene illumination geometry, and few trained observers, leading to potential observer bias. Aiding the response was extensive passive and active satellite and airborne remote sensing, including intelligent system augmentation, reviewed herein. Oil slick appearance strongly depends on many factors like emulsion composition and scene geometry, yielding false positives and great thickness uncertainty. Oil thicknesses and the oil to water ratios for thick slicks were derived quantitatively with a new spectral library approach based on the shape and depth of spectral features related to C-H vibration bands. The approach used near infrared, imaging spectroscopy data from the AVIRIS (Airborne Visual/InfraRed Imaging Spectrometer) instrument on the NASA ER-2 stratospheric airplane. Extrapolation to the total slick used MODIS satellite visual-spectrum broadband data, which observes sunglint reflection from surface slicks; i.e., indicates the presence of oil and/or surfactant slicks. Oil slick emissivity is less than seawater's allowing MODIS thermal infrared (TIR) nighttime identification; however, water temperature variations can cause false positives. Some strong emissivity features near 6.7 and 9.7 μm could be analyzed as for the AVIRIS short wave infrared features, but require high spectral resolution data. TIR spectral trends can allow fresh/weathered oil discrimination. Satellite Synthetic Aperture Radar (SSAR) provided synoptic data under all-sky conditions by observing oil dampening of capillary waves; however, SSAR typically cannot discriminate thick from thin oil slicks. Airborne UAVSAR's significantly greater signal-to-noise ratio and fine spatial resolution allowed successful mapping of oil slick thickness-related patterns. Laser induced fluorescence (LIF) can quantify oil thicknesses by Raman scattering line distortions, but saturates for >20-μm thick oil and depends on oil optical characteristics and sea state. Combined with laser bathymetry LIF can provide submerged oil remote sensing.


Leifer I.,University of California at Santa Barbara | Lehr W.J.,National Oceanic and Atmospheric Administration | Simecek-Beatty D.,National Oceanic and Atmospheric Administration | Bradley E.,University of California at Santa Barbara | And 11 more authors.
Remote Sensing of Environment | Year: 2012

The vast and persistent Deepwater Horizon (DWH) spill challenged response capabilities, which required accurate, quantitative oil assessment at synoptic and operational scales. Although experienced observers are a spill response's mainstay, few trained observers and confounding factors including weather, oil emulsification, and scene illumination geometry present challenges. DWH spill and impact monitoring was aided by extensive airborne and spaceborne passive and active remote sensing.Oil slick thickness and oil-to-water emulsion ratios are key spill response parameters for containment/cleanup and were derived quantitatively for thick (> 0.1. mm) slicks from AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data using a spectral library approach based on the shape and depth of near infrared spectral absorption features. MODIS (Moderate Resolution Imaging Spectroradiometer) satellite, visible-spectrum broadband data of surface-slick modulation of sunglint reflection allowed extrapolation to the total slick. A multispectral expert system used a neural network approach to provide Rapid Response thickness class maps.Airborne and satellite synthetic aperture radar (SAR) provides synoptic data under all-sky conditions; however, SAR generally cannot discriminate thick (> 100 μm) oil slicks from thin sheens (to 0.1 μm). The UAVSAR's (Uninhabited Aerial Vehicle SAR) significantly greater signal-to-noise ratio and finer spatial resolution allowed successful pattern discrimination related to a combination of oil slick thickness, fractional surface coverage, and emulsification.In situ burning and smoke plumes were studied with AVIRIS and corroborated spaceborne CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation) observations of combustion aerosols. CALIPSO and bathymetry lidar data documented shallow subsurface oil, although ancillary data were required for confirmation.Airborne hyperspectral, thermal infrared data have nighttime and overcast collection advantages and were collected as well as MODIS thermal data. However, interpretation challenges and a lack of Rapid Response Products prevented significant use. Rapid Response Products were key to response utilization-data needs are time critical; thus, a high technological readiness level is critical to operational use of remote sensing products. DWH's experience demonstrated that development and operationalization of new spill response remote sensing tools must precede the next major oil spill. © 2012 Elsevier Inc.

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