Classification of low backscatter ocean regions using log-cumulants

Paper presented at ‘PolInSAR 2015, Frascati, Italy 26–30 January 2015 (ESA SP-729, April 2015)In a synthetic aperture radar image, low backscatter regions of various origin can be observed in ocean areas. Operational oil spill detection services work to discriminate anthropogenic oil spills from natural phenomena such as seeps, low wind fields, thin ice and biogenic slicks. In this paper, we investigate the potential of using matrix log-cumulants for this purpose

Observing Oil Releases from Platforms Using Synthetic Aperture Radar

Poster presented at the SeaSAR2018 workshop, 7-10 May 2018, Rome, Italy. https://seasar2018.esa.int/.Synthetic aperture radar (SAR) is used for operational surveillance of ocean areas and oil spill detection. Oil spills are frequently detected around oil platforms due to the releases of so-called produced water (PW), which is water containing low concentrations of oil that can form surface slicks similar to other oil spills. PW releases are legal within given limits. Understanding the signatures of produced water and how they are related to, e.g., the relative oil volume and/or concentration can be helpful for the operational services. For example, distinguishing a “normal” release of produced water from an “abnormal” release (elevated amounts) in a SAR image is currently an unsolved problem. Very little research on these topics have been done before. The objectiveofthisstudy is to investigate the characteristics of produced water SAR signatures and how they depend on, e.g., the properties of the release (oil volume, concentration), environmental conditions and sensor properties

Multi-frequency polarimetric SAR signatures of lead sea ice and oil spills

Synthetic aperture radar is used to identify and monitor oil spills. Separation from oil spill look-alikes is an important part of a fully automatic oil spill detection scheme. Here we investigate the polarimetric signatures for oil spills and newly formed sea ice (a well-known look-alike) in fully polarimetric Radarsat-2 satellite scenes. Using the fully polarimetric scenes we calculate four different parameters, co-polarization ratio, polarization difference, scattering entropy, and mean alpha angle. Three pairs of satellite scenes with comparable incidence angles are used. We observe that a combination of the co-polarization ratio and the polarization difference enables us to delineate the spills from their surrounding and also to discriminate the oil spills from the newly formed sea ice. The scattering entropy and the alpha values provide additional information about the scattering mechanisms of sea ice and oil spills

From above and standing atop- two views of Norwegian fjord ice

publishedVersio

Measurement of Oil Slick Transport and Evolution in the Gulf of Mexico using L-band Synthetic Aperture Radar

Source at https://www.vde-verlag.de/proceedings-en/454636104.htmlThe transport and evolution of a mineral oil slick originating at a seep in the Gulf of Mexico approximately 16 km offshore of the mouth of the Mississippi River is measured using a series of images acquired at 40 minute intervals with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), an L-band, high resolution, high signal-to-noise instrument operated by the U.S. National Aeronautics and Space Agency (NASA). A series of four images acquired over a 2-hour time period is used in the study. Both VV-intensity images and the VVintensity contrast between the slick and clean water (damping ratio) are used. The intensity images show the spatial development and transport of the slick within an area extending from the source northward to near the Louisiana (USA) coast. The slick initially spreads to the northeast from the origin site, then become entrained in an along-shore current. From there, the direction of transport changes by nearly 180º, and the oil from the slick moves west along a path much closer to the Louisiana shoreline. Concentration of the oil within the slick is observed along fronts and internal waves. The oil that remains on the surface the longest shows increasing damping, which could indicate the formation of more stable emulsions that can persist in the environment

From above and standing atop- two views of Norwegian fjord ice

Poster presentation at the online CIRFA Annual Conference, 12.10.2020 - 14.10.2020 (https://cirfa.uit.no/welcome-to-the-cirfa-annual-conference-2020/), arranged by CIRFA: https://cirfa.uit.no/. In O’Sadnick et al. (2020), estimations of ice extent along the coast of Norway since 2001 determined from MODIS imagery are presented. From our findings, it is evident that the amount of ice in one fjord over time often varies and shows little consistency leading to the next question of ‘Why’? The study continues to relate freezing degree days, rainfall plus snowmelt, and snowfall to values of ice area to determine if significant correlations exist when fjords are grouped into regions. Six out of the ten regions were significantly postiviely correlated to freezing degree days (p < 0.05). Ice area in two regions was positively correlated to daily new snowfall, and in one region negatively correlated to rainfall plus snowmelt. Please see the publication for further description of methods and findings

Modeling Microwave Scattering From Rough Sea Ice Surfaces

In this paper, COMSOL Multiphysics® was used to simulate the microwave scattering from the rough sea ice surface. A nonperiodic model and a periodic model were built. The nonperiodic model considers the rough surface of finite length and introduces a tapered incident wave. In this model, the strategy of total and scattered-field decomposition (TSFD) was used to formulate the finite-element method (FEM). The computational area was split into a scattered-field region and a total-field region so that the incident wave can be impressed closer to the rough sea ice surface. The periodic model considers the periodic rough surface by introducing Floquet periodic boundary conditions. The incident wave is excited by the port boundary condition so this model is based on the total-field formulation. The two models were tested to simulate the radar cross section (RCS) of scattering from sea ice surfaces at C band (frequency 5.4GHz). The results were compared with the Small Perturbation Method (SPM) and good agreements were achieved

Numerical Analysis of Microwave Scattering from Layered Sea Ice Based on the Finite Element Method

Source at https://doi.org/10.3390/rs10091332.A two-dimensional scattering model based on the Finite Element Method (FEM) is built for simulating the microwave scattering of sea ice, which is a layered medium. The scattering problem solved by the FEM is formulated following a total- and scattered-field decomposition strategy. The model set-up is first validated with good agreements by comparing the results of the FEM with those of the small perturbation method and the method of moment. Subsequently, the model is applied to two cases of layered sea ice to study the effect of subsurface scattering. The first case is newly formed sea ice which has scattering from both air–ice and ice–water interfaces. It is found that the backscattering has a strong oscillation with the variation of sea ice thickness. The found oscillation effects can increase the difficulty of retrieving the thickness of newly formed sea ice from the backscattering data. The second case is first-year sea ice with C-shaped salinity profiles. The scattering model accounts for the variations in the salinity profile by approximating the profile as consisting of a number of homogeneous layers. It is found that the salinity profile variations have very little influence on the backscattering for both C- and L-bands. The results show that the sea ice can be considered to be homogeneous with a constant salinity value in modelling the backscattering and it is difficult to sense the salinity profile of sea ice from the backscattering data, because the backscattering is insensitive to the salinity profile

Numerical Simulation of Microwave Scattering from Sea Ice Based on The Finite Element Method

Embargo of 24 months from date of publishing on accepted manuscript version.Link to publisher's version:Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International Copyright notice: “© © 20xx IEEE policy"In this paper, a 2-dimensional scattering model for sea ice based on the Finite Element Method (FEM) is presented. The scattering problem is formulated following a physics-separate strategy. The wave in the air domain is expressed by the scattered field formulation, while the wave in the sea ice domain is expressed by the total field formulation. The two separate physics and formulations are coupled through the boundary conditions at the air-sea ice interface. The proposed FEM is tested for simulating the radar cross section (RCS) of homogeneous sea ice at C and L bands. By comparing the results of the FEM with the Small Perturbation Method (SPM), good agreements are achieve

Automatic Detection of Low-Backscatter Targets in the Arctic Using Wide Swath Sentinel-1 Imagery

Low backscatter signatures in synthetic aperture radar (SAR) imagery are characteristic to surfaces that are highly smooth and specular reflective of microwave radiation. In the Arctic, these typically represent newly formed sea ice, oil spills, and localized weather phenomena such as low wind or rain cells. The operational monitoring of low backscatter targets can benefit from a stronger integration of freely available SAR imagery from Sentinel-1. We, therefore, propose a detection method applicable to Sentinel-1 extra wide-swath (EW) SAR scenes. Using intensity values coupled with incidence angle and noise-equivalent sigma zero (NESZ) information, the image segmentation method is able to detect the low backscatter targets as one segment across subswaths. We use the Barents Sea as a test site due to the abundant presence of low backscatter targets with different origins, and of long-term operational monitoring services that help cross-validate our observations. Utilizing a large set of scenes acquired in the Barents Sea during the freezing season (November–April), we demonstrate the potential of performing large-scale operational monitoring of local phenomena with low backscatter signatures