Papers by George Graettinger
International Oil Spill Conference Proceedings, 2021
Historically, visual observation is an emergency responder's first ‘tool’ in identifying spil... more Historically, visual observation is an emergency responder's first ‘tool’ in identifying spilled oil. Optical detection has since expanded to include a myriad of signals from space, aircraft, drone, vessel and submersible platforms that can provide critical information for decision-making during spill response efforts. Spill monitoring efforts below the air-water interface have been vastly improved by advances with in situ optical sensors and vehicle platform technology. Optical techniques using fluorescence, scattering, and holography offer a means to determine dissolved versus droplet fractions, provide oil concentration estimates and serve as proxies for dispersion efficiency. For subsurface spills over large space and time scales, Autonomous Underwater Vehicles (AUVs) can be used to provide subsurface plume footprints and estimate oil concentrations. For smaller, more frequent spills, tethered compact Remotely Operated Vehicles (ROVs) may be more appropriate as they are easy...
International Oil Spill Conference Proceedings, 2021
Historically, visual observation is an emergency responder's first ‘tool’ in identifying spil... more Historically, visual observation is an emergency responder's first ‘tool’ in identifying spilled oil. Optical detection has since expanded to include a myriad of signals from space, aircraft, drone, vessel and submersible platforms that can provide critical information for decision-making during spill response efforts. Spill monitoring efforts below the air-water interface have been vastly improved by advances with in situ optical sensors and vehicle platform technology. Optical techniques using fluorescence, scattering, and holography offer a means to determine dissolved versus droplet fractions, provide oil concentration estimates and serve as proxies for dispersion efficiency. For subsurface spills over large space and time scales, Autonomous Underwater Vehicles (AUVs) can be used to provide subsurface plume footprints and estimate oil concentrations. For smaller, more frequent spills, tethered compact Remotely Operated Vehicles (ROVs) may be more appropriate as they are easy...
Photogrammetric Engineering & Remote Sensing, 2012
Oil slick spatial extent and thickness estimation maps derived from a multispectral visible, near... more Oil slick spatial extent and thickness estimation maps derived from a multispectral visible, near-IR and thermal IR aerial imaging system were successfully utilized for multiple applications during the Deepwater Horizon oil spill.
Journal of Geophysical Research: Oceans, 2015
When wind speeds are 2-10 m s 21 , reflective contrasts in the ocean surface make oil slicks visi... more When wind speeds are 2-10 m s 21 , reflective contrasts in the ocean surface make oil slicks visible to synthetic aperture radar (SAR) under all sky conditions. Neural network analysis of satellite SAR images quantified the magnitude and distribution of surface oil in the Gulf of Mexico from persistent, natural seeps and from the Deepwater Horizon (DWH) discharge. This analysis identified 914 natural oil seep zones across the entire Gulf of Mexico in pre-2010 data. Their 0.1 mm slicks covered an aggregated average of 775 km 2. Assuming an average volume of 77.5 m 3 over an 8-24 h lifespan per oil slick, the floating oil indicates a surface flux of 2.5-9.4 3 10 4 m 3 yr 21. Oil from natural slicks was regionally concentrated: 68%, 25%, 7%, and <1% of the total was observed in the NW, SW, NE, and SE Gulf, respectively. This reflects differences in basin history and hydrocarbon generation. SAR images from 2010 showed that the 87 day DWH discharge produced a surface-oil footprint fundamentally different from background seepage, with an average ocean area of 11,200 km 2 (SD 5028) and a volume of 22,600 m 3 (SD 5411). Peak magnitudes of oil were detected during equivalent, 14 day intervals around 23 May and 18 June, when wind speeds remained <5 m s 21. Over this interval, aggregated volume of floating oil decreased by 21%; area covered increased by 49% (p < 0.1), potentially altering its ecological impact. The most likely causes were increased applications of dispersant and surface burning operations.
After the conclusion of emergency response efforts for the Deepwater Horizon (DWH) oil spill in f... more After the conclusion of emergency response efforts for the Deepwater Horizon (DWH) oil spill in fall of 2010, the National Oceanic and Atmospheric Administration (NOAA) initiated the natural resource damage assessment (NRDA) process. The NRDA guidance under the Oil Pollution Act requires trustees of natural resources, including NOAA, to assess the fate and transport of oil and the potential exposure of natural resources to the oil. For a spill with the unprecedented spatial and temporal magnitude of DWH, the only data that could provide a complete picture of the daily spatial coverage of oil slicks were satellite data. NOAA convened a group of remote sensing specialists (the Oil on Water Group) that compiled, analyzed, and reported on results from a diverse and copious array of remote sensing data, including thousands of aerial photographs, multispectral and hyperspectral (AVIRIS) swaths, and hundreds of satellite images from optical (moderate resolution imaging spectroradiometer an...
Endangered Species Research, 2017
The Deepwater Horizon (DWH) oil spill was unprecedented in extent and duration, and affected mari... more The Deepwater Horizon (DWH) oil spill was unprecedented in extent and duration, and affected marine natural resources, including sea turtles, throughout the northern Gulf of Mexico. Consequently, US federal and state Trustees documented and quantified oil exposure and resulting injuries to sea turtles under the DWH Natural Resource Damage Assessment. At-sea rescue operations focused on surface-pelagic juvenile sea turtles, which were especially at risk to oil exposure within oceanic convergence zones, and provided direct observations of the degree that turtles in this young life stage were exposed to DWH oil. In contrast, locations of larger neritic juvenile and adult turtles were documented during aerial surveys, but because these turtles were not captured, their oiling status could not be directly evaluated. Both the rescue operations and aerial surveys were able to observe only a small fraction of sea turtles within the vast spill footprint. We developed a spatio-temporally explicit approach that used direct observations of oiled surface-pelagic juvenile sea turtles and satellite-derived surface oil distributions to statistically estimate the probabilities of oil exposure for all sea turtles that were present within the area of the DWH spill, but whose oiling status was unknown. Our results enabled an expansion of exposure and injury quantification across the entire DWH spill area and period. This approach was conceptually straightforward and used common geospatial and statistical techniques, making it applicable to other situations in which the full extent of oil exposure for marine natural resources must be estimated from an incomplete sample.
Unmanned Aerial Systems (UAS) are an operational tool for monitoring and assessment of oil spills... more Unmanned Aerial Systems (UAS) are an operational tool for monitoring and assessment of oil spills. At the same time, satellite imagery has been used almost entirely to detect oil presence/absence, yet its ability to discriminate oil emulsions within a detected oil slick has not been fully exploited. Additionally, one of the challenges in the past has been the ability to deliver strategic information derived from satellite remote sensing in a timely fashion to responders in the field. This study presents UAS and satellite methods for the rapid classification of oil types and thicknesses, from which information about thick oil and oil emulsions (i.e., "actionable" oil) can be delivered in an operational timeframe to responders in the field. Experiments carried out at the OHMSETT test facility in New Jersey demonstrate that under specific viewing conditions satellites can record a signal variance between oil thicknesses and emulsions and non-emulsified oil. Furthermore, multi...
&amp;lt;p&amp;gt;The offshore natural oil seeps along the California coast near Santa Bar... more &amp;lt;p&amp;gt;The offshore natural oil seeps along the California coast near Santa Barbara are a natural testing site for the calibration of remote sensing systems aimed at the detection of oil spills. The main difference between these seeps and other permanent sources of floating oil (natural and unnatural seeps in the Gulf of Mexico) is the petroleum composition. Moreover, while it has been documented that most natural seeps worldwide change their rate of oil discharge over time, the Santa Barbara seeps have maintained a high rate, frequently forming thick layers of floating oil in recent years. This allowed us to perform multiple experiments developing floating oil layer thickness measurement techniques from sea-level instruments. These measurements were then used in validation of airborne and satellite remote sensors.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;At the Santa Barbara seeps, we have tested our previously developed method of measuring oil thickness with a crystal tube sampling mechanism that extracts an undisturbed floating oil profile at the sea surface. Samples are then post-processed to quantify the volume of oil captured. Our newer system consists of a submerged spectrophotometer that measures the ultraviolet (UV) and infrared (IR) light attenuation of the floating oil from a fixed UV-IR light source above the water. Both methods have been used for cross validation. The sampling tube is more accurate and precise for thicknesses below 50 um (from silver-rainbow sheens to metallic). Both systems work consistently on thicknesses ranging from &amp;gt;50 um to 350um (the latter was the thickest sample of oil measured at the seep sites). However, the advantage of the submerged spectrophotometer is the real time interpretation of the data. The maximum thickness measured in the laboratory for the submerged spectrophotometer was 2.5mm, while the maximum thickness measured from the sampling tube was 7cm of oil.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;These thickness measuring instruments have been used to validate thermal and multispectral sensors mounted on an Unmanned Aerial System (UAS). By overlaying the thickness measurements collected in the field with synchronous data collected from the UAS sensors we can relate the thermal reflective radiation and multispectral signatures from different oil thicknesses. Maps with oil thickness classifications generated from the UAS data are then used to correlate with quasi-synchronous high resolution satellite images obtained by WorldView2-3, Planet, ALOS-2, and RADARSAT-2, all of which are hosted and viewable on the NOAA-Environmental Response Management Application (ERMA).&amp;amp;#160; Further field expeditions scheduled for 2021 will include the UAVSAR sensor, an L-band airborne synthetic aperture radar operated by the NASA Airborne Science Program. This NASA microwave sensor operates at the same frequency as one of the sensors on the upcoming NASA-ISRO SAR (NISAR) mission scheduled to launch in 2022 and data acquired will be used to both improve thickness algorithm development and simulate the expected performance of the NISAR instrument for oil slick detection and characterization. We will prepare these methods to move to operational use as this new resource comes online adding a significant response asset to oil spill characterization and response.&amp;lt;/p&amp;gt;
Remote Sensing of Environment
Journal of Applied Remote Sensing
Marine pollution bulletin, Jan 8, 2016
Using high-resolution airborne measurements and more synoptic coverage of Landsat measurements, w... more Using high-resolution airborne measurements and more synoptic coverage of Landsat measurements, we estimated the total Sargassum coverage in the northeastern Gulf of Mexico (NE GOM) during 2010, with the ultimate purpose to infer how much Sargassum might have been in contact with oil from the Deepwater Horizon oil spill. Mean Sargassum coverage during the four quarters of 2010 for the study region was estimated to range from ~3148±2355km(2) during January-March to ~7584±2532km(2) during July-September (95% confidence intervals) while estimated Sargassum coverage within the integrated oil footprint ranged from 1296±453km(2) (for areas with >5% thick oil) to 736±257km(2) (for areas with >10% thick oil). Similar to previous studies on estimating Sargassum coverage, a direct validation of such estimates is impossible given the heterogeneity and scarcity of Sargassum occurrence. Nonetheless, these estimates provide preliminary information to understand relative Sargassum abundance ...
Marine pollution bulletin, Jan 22, 2015
Using fine spatial resolution (~7.6m) hyperspectral AVIRIS data collected over the Deepwater Hori... more 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 (≤50μm but thicker than sheen, 50-200μm, 200-1000μm, and >1000μm), the median lengths, widths, and length/width ratios of these classes ranged between 22 and 38m, 7-11m, 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.
Photogrammetric Engineering & Remote Sensing, 2012
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Papers by George Graettinger