Abstract
The National Aeronautics and Space Administration’s airborne Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) was deployed in June 2010 in response to the Deepwater Horizon oil spill in the Gulf of Mexico. UAVSAR is a fully polarimetric L-band Synthetic Aperture Radar (SAR) sensor for obtaining data at high spatial resolutions. Starting a month prior to the UAVSAR collections, visual observations confirmed oil impacts along shorelines within northeastern Barataria Bay waters in eastern coastal Louisiana. UAVSAR data along several flight lines over Barataria Bay were collected on 23 June 2010, including the repeat flight line for which data were collected in June 2009. Our analysis of calibrated single-look complex data for these flight lines shows that structural damage of shoreline marsh accompanied by oil occurrence manifested as anomalous features not evident in pre-spill data. Freeman-Durden (FD) and Cloude-Pottier (CP) decompositions of the polarimetric data and Wishart classifications seeded with the FD and CP classes also highlighted these nearshore features as a change in dominant scattering mechanism. All decompositions and classifications also identify a class of interior marshes that reproduce the spatially extensive changes in backscatter indicated by the pre- and post-spill comparison of multi-polarization radar backscatter data. FD and CP decompositions reveal that those changes indicate a transform of dominant scatter from primarily surface or volumetric to double or even bounce. Given supportive evidence that oil-polluted waters penetrated into the interior marshes, it is reasonable that these backscatter changes correspond with oil exposure; however, multiple factors prevent unambiguous determination of whether UAVSAR detected oil in interior marshes.
Highlights
During the Deepwater Horizon (DWH) oil spill, which occurred between 20 April and 15 July 2010, 4.4 × 106 ± 20% barrels of crude oil entered the Gulf of Mexico (GOM) waters [1]
In order to substantiate that these patterns resulted from the presence and absence of surface water oil, polarimetric response plots (Figure 15) were created from multilooked complex (MLC) data extracted from inland tidal channels and Barataria Bay waters from the pre- and post-spill Mississippi River Delta (MRD) flight lines (sample locations, Figures 11 (a,b))
We analyzed Uninhabited Aerial Vehicle Synthetic Aperture Radar (SAR) (UAVSAR) data collected during the 2010 Deepwater Horizon oil spill to assess the ability of a high-performance, fully polarimetric L-band SAR sensor system to detect oil occurrences in wetlands, including oil coating plant stalks and soil in the lower marsh canopy
Summary
During the Deepwater Horizon (DWH) oil spill, which occurred between 20 April and 15 July 2010, 4.4 × 106 ± 20% barrels of crude oil entered the Gulf of Mexico (GOM) waters [1]. We used the measured multi-polarization backscatter intensity from pre-spill and post-spill UAVSAR collections over Barataria Bay, Louisiana, to determine whether changes in the polarimetric signature are related to the presence of oil As part of this overall objective, we studied the capabilities of remote sensing technology to detect when oil occurred in the subcanopy as a coating on some portion of the plants or soil surface that was not evident at the canopy surface. Because decomposition of fully polarimetric SAR data can produce maps with intrinsic physical implications without requiring a priori knowledge of the target [11,12,13], we have considered this method for rapid production of targeted oil-impact maps during emergency response Because this is a new research undertaking, we employed the two most widely used polarimetric decomposition methods, Cloude-Pottier and Freeman-Durden, and the Wishart unsupervised classification method seeded with input from the two decomposition methods to more thoroughly evaluate the relative merits of the different techniques in producing oil extent maps for oil spill monitoring in coastal wetlands. After presenting the data and methods used (Section 2) and the analysis results (Section 3), we discuss the utility of PolSAR for detecting oil within coastal marshes and waterways (Section 4) based upon our evaluation of the consistency within and between the different methods studied
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