Stability Analysis of Freely Floating Oil Slick in Multifrequency Airborne SAR Imagery Acquired in S- and L-Band

Author(s):  
Cornelius Quigley ◽  
Camilla Brekke ◽  
Torbjarn Eltoft
2021 ◽  
Author(s):  
Benjamin Holt ◽  
Frank Monaldo ◽  
Cathleen Jones ◽  
Oscar Garcia

<p>We describe an effort to develop a quantifiable approach for determining the thicker components of oil spills using microwave synthetic aperture radar (SAR) imagery that can be utilized in an operational context to guide clean-up efforts. The presence of mineral oil on the surface can suppress the SAR returns in two ways. First, surface oil dampens the capillary waves making those areas darker in SAR imagery, an effect that been used to determine oil extent. The second is by modifying the dielectric properties of the surface from those of clean seawater to either pure oil or a mixture of oil and water as the oil weathers and thickens to form an emulsion. The emulsion provides an intermediate conductive surface layer between the highly conductive ocean itself and the very low, ‘radar transparent’ sheen layers, resulting in a further reduction in the radar returns for areas with thicker oil within an inhomogeneous oil slick. The challenges are to quantify the thickness and conditions for which this thicker layer becomes separable from the thinner oil, determine whether multiple thicker components can be identified, identify which airborne and spaceborne SAR systems can be used for this purpose, and determine under what range of environmental conditions, particularly wind speed, it is possible.</p><p> </p><p>We are planning to hold field campaigns with in situ measurements and SAR and multispectral remote sensor data collections from drones, aircraft, and satellites. The field measurements include surface collections of oil, underwater spectrophotometry, and drone-based infrared, ultraviolet, and optical collections.  Coincident with the field measurements, the airborne L-band NASA-UAVSAR SAR system will image the seep fields to track temporal changes and overpassing satellite acquisitions will be acquired. UAVSAR provides fine resolution, low noise radar imagery under all weather and solar conditions and is fully polarimetric, which enables evaluation of multiple methods to characterize the oil slick. The system noise floor of this instrument, considerably less than all satellite SAR instruments, enables a detailed examination of the zones of reduced backscatter caused by varying oil thickness levels. The primary satellite SAR will be C-band Sentinel-1, accompanied potentially by C-band Radarsat-2 and L-band ALOS-2. Both the UAVSAR and satellite SAR analysis will utilize the contrast ratio, defined as the normalized radar cross section (NRCS) in open water divided by the NRCS in oil-covered water. The larger the ratio, the thicker the oil. The operational algorithm for oil thickness is under development using satellite SAR data and will be staged in NOAA’s SAR Ocean Product System (SAROPS) that currently produces SAR-derived wind speed and oil spill extent operationally, with the latter using the Texture-Classifying Neural Network (TCNNA) to automatically delineate oil versus non-oil covered areas. We are planning field campaigns at the natural oil seep area offshore of Santa Barbara, California, in March 2021 and during the 2022 Norwegian Clean Sea Association for Operating Companies’ (NOFO’s) coordinated releases of oil in the North Sea. Recent field collections and analysis will be shown, as available.</p>


2018 ◽  
Vol 10 (7) ◽  
pp. 1012 ◽  
Author(s):  
Sébastien Angelliaume ◽  
Olivier Boisot ◽  
Charles-Antoine Guérin

2009 ◽  
Vol 64 (5) ◽  
pp. 458-463 ◽  
Author(s):  
Wagner F. Silva ◽  
Bernardo F.T. Rudorff ◽  
Antonio R. Formaggio ◽  
Waldir R. Paradella ◽  
José C. Mura

Author(s):  
A. Maiti ◽  
S. Kumar ◽  
V. Tolpekin ◽  
S. Agarwal

Abstract. The PolSAR calibration ensures that the relationship between the SAR observations and the target characteristics on the ground are consistent and resembles the theoretical estimation which in turn improves the overall data quality. Essentially, calibration prevents the propagation of uncertainty into further analysis to characterise the target. In this study, the UAVSAR L-Band data of Rosamond dry lake bed has been calibrated. The calibration of amplitude and phase are carried out with the help of the corner reflector array present in the Rosamond site. The dataset is further calibrated for the crosstalk and channel imbalance using the Quegan’s distortion model. Since the crosstalk distortion model requires an accurate estimation of the covariance matrix, the optimal kernel size for the its computation is selected based on the distortion model behaviour with varying window sizes. Furthermore, the effectiveness of the calibration process has been studied using polarimetric signatures and other statistical measures.


2021 ◽  
Author(s):  
Georg Pointner ◽  
Annett Bartsch

<p>Millions of lakes and ponds occupy large areas of the Arctic discontinuous and continuous permafrost zones. During most of the year, the surfaces of these lakes remain covered by a thick layer of ice. Synthetic Aperture Radar (SAR) data have shown to be useful for studying the ice on Arctic lakes, especially for monitoring lake ice phenology and the grounding state of the ice (ice frozen to the lakebed versus floating lake ice). Significant backscatter is often observed from the floating ice regime in C-band due to scattering on a rough ice-water interface.</p><p>Recent research has revealed features of anomalously low backscatter in Sentinel-1 C-band SAR imagery on some of the West Siberian lakes that likely belong to the floating ice regime. These anomalies are characterized by prominent shapes and sizes and seem to expand throughout late winter and/or spring. It is currently assumed that some of these features are related to strong emissions of natural gas (methane from hydrocarbon reservoirs), making it important to assess their origin in detail and understand the associated mechanisms. However, in-situ data are still missing.</p><p>Here, we assess the potential of the combined use of C-band Sentinel-1 (freely available) and L-band ALOS PALSAR-2 data  (available through JAXA PI agreement #3068002) to study the backscatter anomalies. We highlight the differences between observed backscatter from the two sensors with respect to different surface types (ground-fast lake ice, floating lake ice and anomalies) and investigate backscatter differences between frozen and melting conditions. Further, polarimetric classification is performed on L-band PALSAR-2 imagery, which reveals differences in scattering mechanisms between anomalies and floating lake ice.</p>


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