Log-cumulants have proven to be an interesting tool for evaluating the statistical properties of potential oil spills in polarimetric Synthetic Aperture Radar (SAR) data within the common horizontal (H) and vertical (V) polarization basis. The use of first, second, and third order sample log-cumulants has shown potential for evaluating the texture and the statistical distributions, as well as discriminating oil from look-alikes. Log-cumulants are cumulants derived in the log-domain and can be applied to both single-polarization and multipolarization SAR data. This study is the first to investigate the differences between hybrid-polarity (HP) and full-polarimetric (FP) modes based on the sample log-cumulants of various oil slicks and open water from nine Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) scenes acquired off the coast of Norway in 2015.
The sample log-cumulants calculated from the HP intensities show similar statistical behavior to the FP ones, resulting in a similar interpretation of the sample log-cumulants from HP and FP. Approximately eight hours after release the sample log-cumulants representing emulsion slicks have become more similar to the open water compared to plant oil. We find that the sample log-cumulants of the various oil slicks and open water varies between the scenes and also between the slicks and open water. This might be due to changes in ocean and wind condition, the initial slick properties, and/or the difference in the weathering process of the oil slicks.
Evolution of the damping ratio for Bragg wavenumbers in the range 32-43 rad/m is evaluated for oil slicks of different composition released in the open ocean and allowed to develop naturally. The study uses quad-polarimetric L-band airborne synthetic aperture radar data acquired over three mineral oil emulsion releases of different, known oil-to-water ratio, and a near-coincident release of 2-ethylhexyl oleate that served as a biogenic look-alike. The experiment occurred during the 2015 Norwegian oil-on-water exercise in the North Sea during a period of relatively high winds (~12 m/s). NASA’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) was used to repeatedly image the slicks over a period of eight hours, capturing the slicks’ early development and providing a time series from which to track the evolution of the slicks’ size, position, and radiometric characteristics. Particular emphasis is given in this analysis to identification of zones of higher damping ratio within the slicks (zoning) as potential indicators of thicker oil, and to comparison of the evolution of emulsion and plant oil damping ratios. It was found that all mineral oil slicks initially exhibited zoning apparent in VV, HH, and HV intensities, and that the areas of higher damping ratio persisted the longest for the highest oil content emulsion (80% oil by volume). In contrast, zoning was not unambiguously evident for plant oil at any time from 44 minutes to 8.5 hours after release.
Marine oil spills are an important environmental problem, and satellite SAR remote sensing have become a valuable tool for the detection and monitoring of these spills. Natural phenomena with similar appearance as oil in SAR images, producing false detections, compose a challenge for oil spill observation services. One such lookalike phenomena is biogenic slicks produced by marine organisms. In this study we evaluate multi-polarization features for oil spill characterization and oil versus biogenic slick discrimination. During large-scale oil-on-water exercises conducted in the North Sea in June 2011 and June 2012, both mineral oil and plant oil were released and imaged by Radarsat-2 in Fine Quad-polarization mode. The plant oil will form a lm resembling biogenic slicks. The mineral oil spill and simulated look-alike are in this study compared based on multi-polarization features, combining the information in HH and VV channels. The polarimetric measurements from 2011 have earlier been analysed, and a potential for discrimination between mineral oil and biogenic slicks is found. The aim of the current study is to repeat the polarimetric analysis on the new independent data set from 2012. Preliminary results of the 2012 data set reveal both internal and between slick type variations, giving support to our previous findings from 2011.
In maritime applications involving estimation of radar sea clutter properties, non-sea-clutter targets and transitions between statistically different oceanographic conditions in the estimation window may lead to inaccurate modeling. Referring to mixtures in the estimation window as contamination, this work introduces a novel sea clutter contamination test based on log-cumulants from Mellin kind statistics . It measures the significant deviation in log-cumulant space due to the contamination, and appears to be an effective tool for improving the sea clutter estimation or to be a direct first-stage target detector. The proposed contamination test is examined with real single look complex (SLC) fine resolution quad-polarimetric Radarsat-2 synthetic aperture radar (SAR) measurements, from the Norwegian Sea, under various oceanographic conditions.
This work investigates the fixed-point polarimetric whitening filter (FP-PWF) with respect to ship detection
based on polarimetric synthetic aperture radar (SAR) imagery. The purposes of this work are: (i) to investigate
the FP-PWF algorithm that incorporate texture, (ii) to examine the method of log-cumulants (MoLC) for shape
parameter estimation associated with texture, and (iii) to assess the impact of the improved modeling and estimation
on the discrepancy between specified and observed false alarm rate. A modified ship detection algorithm
based on FP-PWF is proposed with improved modeling, estimation and detection performance. Experiments
are performed on simulated radar ocean clutter.
Ship traffic monitoring may be performed using satellite SAR data. The advantage with the SAR sensor is the all
weather and day/night imaging capability. However, the SAR backscatter contrast between a vessel and the
surrounding sea state may be small in high wind conditions and at small incidence angles. The present and future
SAR satellites will have the capability of imaging the earth surface with several incidence angles, and with dual-polarimetry
(HH/HV, VV/VH or HH/VV). The SAR ship/clutter contrast may threrefore be increased by applying
different polarisation combinations, or using higher incidence angles.
We have shown that geocoded ENVISAT ASAR images in the coastal region of Norway can be used to gain
experience in the combined use of satellite SAR and an automatic identification system (AIS) for ship traffic
There are plans for placing AIS systems onboard satellites. It will then be possible to fuse the information from
satellite SAR with those from satellite (or ground-based coastal) AIS and thereby identify all the detected ships
within a SAR image. This data fusion will enable us to develop further knowledge about SAR backscatter properties
from vessel types that may not be detected so well using the SAR data only. On the other side, it will be possible to
pin-point those ship candidates that do not carry an AIS system, and thereby take appropriate security or rescue
Proc. SPIE. 6365, Image and Signal Processing for Remote Sensing XII
KEYWORDS: Defense and security, Detection and tracking algorithms, Data modeling, Synthetic aperture radar, Image segmentation, Inspection, Pollution, Image classification, Chemical elements, Binary data
In this paper, we present results from a study on classifiers for automatic oil slick classification in ENVISAT ASAR images. First, based on our basic statistical classifier, we improve the classification performance by introducing regularization of the covariance matrixes. The new improved classifier reduces the false alarm rate from 19.6% to 13.1%. Second, we compare the statistical classifier with SVM, finding that the statistical classifier outranks SVM for this particular application. Experiments are done on a set of 103 SAR images.