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The Deepwater Horizon (DWH) oil blowout in the Gulf of Mexico (GoM) led to the largest offshore oil spill in U.S. history. The accident resulted in oil slicks that covered between 10,000 and upward of 40,000  km2 of the Gulf between April and July 2010. Quantifying the actual spatial extent of oil over such synoptic scales on an operational basis and, in particular, estimating the oil volume (or slick thickness) of large oil slicks on the ocean surface has proven to be a challenge to researchers and responders alike. This challenge must be addressed to assess and understand impacts on marine and coastal resources and to prepare a response to future spills. We estimated surface oil volume and probability of occurrence of different oil thicknesses during the DWH blowout in the GoM by combining synoptic measurements (2330-km swath) from the satellite-borne NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and near-concurrent, much narrower swath (∼5  km) hyperspectral observations from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). A histogram-matching approach was used to transfer AVIRIS-derived oil volume to MODIS pixel-scale dimensions, after masking clouds under both sun glint and nonglint conditions. Probability functions were used to apply the transformation to 19 MODIS images collected during the DWH event. This generated three types of MODIS oil maps: maps of surface oil volume, maps of relative oil thickness with four different classes (i.e., 0  μm, <0.08  μm, 0.08 to 8  μm, and >8  μm), and maps of probability distributions of different thicknesses. The results were compared with satellite-based synthetic aperture radar measurements and evaluated with concurrent aerial photographs. Although the methods may not be ideal and the results may contain large uncertainties, the current attempt suggests that coarse-resolution optical remote sensing observations can provide estimates of relative oil thickness/volume for large oil slicks captured by satellites.

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Journal of Applied Remote Sensing, v. 12, issue 2

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