scholarly journals Retrieval of Oil–Water Mixture Ratio at Ocean Surface Using Compact Polarimetry Synthetic Aperture Radar

2019 ◽  
Vol 11 (7) ◽  
pp. 816 ◽  
Author(s):  
Haiyan Li ◽  
William Perrie ◽  
Jin Wu
Keyword(s):  
Synthetic Aperture Radar ◽  
Covariance Matrix ◽  
Oil Spills ◽  
Ocean Surface ◽  
Synthetic Aperture ◽  
Water Mixture ◽  
Mixture Ratio ◽  
Oil Water ◽  
Sar Imagery ◽  
Aperture Radar

The oil–water mixture ratio for oil spills on the ocean surface is an important parameter for volume estimation of oil spills, response strategy for the oil spills, cleanup operations, and remediation planning for the impacts on wildlife. Hybrid-polarized (HP) mode compact polarization (CP) synthetic aperture radar (SAR) imagery will soon be available with the launch of the RADARSAT Constellation Mission. The advantage of the proposed new SAR system is that CP images will have wider swath and shorter revisit time compared to quad-polarization (QP) images, which are presently available from space-borne and air-borne SAR. We present a methodology to retrieve the oil–water mixture ratio at the ocean surface using CP SAR imagery. We emulated the HP mode of CP SAR image using Uninhabited Aerial Vehicle SAR (UAVSAR) L band observations collected on June 23rd 2010 over the site of the Deep Water Horizon drilling rig. The gap between elements ratio of CP SAR covariance matrix and that of QP SAR Sinclair matrix is bridged. Numerical optimization and look up table methods are used to relate the oil–water mixture ratio to elements of the covariance matrix for the HP data backscatter. The mixture ratio estimates determined from the ratio of diagonal elements of the covariance matrix for HP mode CP data are compared with results retrieved from the co-polarization ratio from the original QP SAR observations. Results from the proposed methodology for SAR images captured in the HP mode of CP data are shown to compare favourably to observed in situ data of the mixture ratios.

DETECTION AND MAPPING OF FLOATING OIL EMULSIONS WITH SYNTHETIC APERTURE RADAR (SAR) IMAGERY

2014 ◽  
Vol 2014 (1) ◽  
pp. 300657 ◽  
Author(s):  
Oscar Garcia-Pineda ◽  
Ian MacDonald ◽  
Chuanmin Hu ◽  
Jan Svejkovsky ◽  
Mark Hess ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Ocean Surface ◽  
Synthetic Aperture ◽  
Water Detection ◽  
L Band ◽  
Sar Imagery ◽  
Remote Sensing Techniques ◽  
Oil Emulsions ◽  
Aperture Radar

Detection of floating oil on the ocean surface, and particularly thick layers, is crucial for emergency response to accidental oil discharges. While detection of oil presence on the ocean surface is relatively easy under most conditions with a variety of remote sensing techniques, estimation of the thickness of oil layers is technically challenging. In this paper we use Synthetic Aperture Radar (SAR) imagery collected during the DeepWater Horizon (DWH) oil spill and the Texture Classifier Neural Network Algorithm (TCNNA) to identify SAR image signatures that may correspond to regions of very thick emulsified oil. These locations were generally consistent with sea level observations and optical and thermal remote sensing instruments. Oil emulsions form after crude oil is discharged in the ocean and is subjected to weathering and coagulation processes that increase thicknesses of floating oil layers. The method of detection identifies regions of increased radar backscattering within larger regions of oil-covered water. Detection is dependent on SAR incident angles and the type of SAR beam mode configuration. L-band SAR was found to have the largest window of incidence angles (16 – 38o off-nadir) that could be used to detect oil emulsions. C-band SAR showed a narrower window (18 – 32o off-nadir) than L-band, while X-band SAR had the narrowest window (20 – 31o off-nadir). The results suggest that in case of future spills in the ocean, SAR data may be used to find locations of thick oil to help make management decisions.

scholarly journals COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

2018 ◽  
Author(s):  
Ferdinando Nunziata ◽  
Andrea Buono ◽  
Maurizio Migliaccio
Keyword(s):  
Synthetic Aperture Radar ◽  
Oil Spills ◽  
Oil Pollution ◽  
Deepwater Horizon ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Pollution Event ◽  
The Impact ◽  
Csk Constellation ◽  
Aperture Radar

Oil spills are adverse events that may be very harmful to ecosystems and food chain. In particular, large sea oil spills are very dramatic occurrence often affecting sea and coastal areas. Therefore the sustainability of oil rig infrastructures and oil transportation via oil tankers are linked to law enforcement based on proper monitoring techniques which are also fundamental to mitigate the impact of such pollution. Within this context, in this study a meaningful showcase is analyzed using remotely sensed measurements collected by the Synthetic Aperture Radar (SAR) operated by the COSMO-SkyMed (CSK) constellation. The showcase presented refers to the Deepwater Horizon (DWH) oil incident that occurred in the Gulf of Mexico in 2010. It is one of the world's largest incidental oil pollution event that affected a sea area larger than 10,000 km2. In this study we exploit, for the first time, dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.

scholarly journals RASF and DEDR-POCS Image Fusion through Multi-layer Perceptron in SAR Imagery Systems

2019 ◽  
pp. 20-26
Author(s):  
Israel Yañez-Vargas ◽  
Joel Quintanilla-Domínguez ◽  
Gabriel Aguilera-Gonzalez
Keyword(s):  
Synthetic Aperture Radar ◽  
Image Fusion ◽  
Low Cost ◽  
Synthetic Aperture ◽  
Discrete Wavelet ◽  
Multi Layer Perceptron ◽  
Robust Adaptive ◽  
Sar Imagery ◽  
Design Regularization ◽  
Aperture Radar

This paper presents a novel multi-layer perceptron (MLP) based image fusion technique, which fuses two synthetic aperture radar (SAR) images, obtained from the same spatial reflectivity map, acquired with a conventional low-cost fractional synthetic aperture radar (Fr-SAR) system, enhanced via two different methodologies. The first image is enhanced using the traditional descriptive experiment design regularization (DEDR) framework through the projection onto convex solution sets (POCS) method; the second image is enhanced with the DEDR framework by incorporating the robust adaptive spatial filtering (RASF) solution operator. This work describes a MLP based technique applied to the pixel level multi-focus fusion problem characterized by the use of image windows with the idea of reducing noise and determining which pixel is clearer between the two images. Experimental results show that the proposed novel method outperforms the discrete wavelet transform based most competing approach.

scholarly journals Refocusing of Multiple Moving Targets Based on the Joint Sparse Processing of One Channel Synthetic Aperture Radar Imagery Patches

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1215 ◽  
Author(s):  
Xin Wang ◽  
Ling Qiao
Keyword(s):  
Synthetic Aperture Radar ◽  
Moving Objects ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Moving Targets ◽  
Lp Norm ◽  
Radar Imagery ◽  
Sar Imagery ◽  
Norm Constraint ◽  
Aperture Radar

A sparse-based refocusing methodology for multiple slow-moving targets (MTs) located inside strong clutter regions is proposed in this paper. The defocused regions of MTs in synthetic aperture radar (SAR) imagery were utilized here instead of the whole original radar data. A joint radar projection operator for the static and moving objects was formulated and employed to construct an optimization problem. The Lp norm constraint was utilized to promote the separation of MT data and the suppression of clutter. After the joint sparse imaging processing, the energy of strong static targets could be suppressed significantly in the reconstructed MT imagery. The static scene imagery could be derived simultaneously without the defocused MT. Finally, numerical simulations were used verify the validity and robustness of the proposed methodology.

Better Utilization of SAR Dynamic Range

1977 ◽  
Vol 21 (3) ◽  
pp. 235-240
Author(s):  
Edward J. Dragavon
Keyword(s):  
Computer Simulation ◽  
Synthetic Aperture Radar ◽  
Real Time ◽  
Image Enhancement ◽  
Dynamic Range ◽  
Synthetic Aperture ◽  
Analytic Methods ◽  
Sar Imagery ◽  
Gray Shade ◽  
Aperture Radar

Three general classes of image enhancement techniques for synthetic aperture radar (SAR) video were investigated through non-real-time computer simulation. The general categories were 1) monochromatic adaptive gray shade transformations, 2) pseudocolor encoding, and 3) feature analytic methods. The class of feature analytic techniques was found to have the greatest potential for improving the operational utility of SAR imagery.

Sign in / Sign up

Export Citation Format

Share Document