Oil spill identification in visible sensor imaging using automated cross correlation with crude oil image filters

An algorithm for detection of crude oil spills in visible light images has been developed and tested on 50 documented crude oil spill images from Shell Petroleum Development Company (SPDC) Nigeria. A set of three 25 x 25 pixels crude oil filters, with unique red, green, and blue (RGB) colour values, homogeneity, and power spectrum density (PSD) features were cross-correlated with the documented spill images. The final crude oil spill Region of Interest (ROI) was determined by grouping interconnected pixels based on their proximity, and only selecting ROIs with an area greater than 5,000 pixels. The crude oil filter cross correlation algorithm demonstrated a sensitivity of 84% with a False Positive per Image (FPI) of 0.82. Future work includes volume estimation of detected spills using crude oil filters, and utilizing this information in the recommendation of appropriate spill clean-up and remediation procedures for the detected spills. Keywords: Crude Oil Spill Detection, Crude oil image filters, Cross correlation, Visible sensor imaging, Oil Spill Segmentation

NovaSAR and SSTL S1-4: SAR and EO Data Fusion

The NovaSAR and SSTL S1-4 satellites were launched into a 580 km sun-synchronous orbit on 16th September 2018. NovaSAR is an S-band Synthetic Aperture Radar (SAR) platform, and SSTL S1-4 hosts a multi-spectral (RGB, NIR) and panchromatic electro-optical (EO) high-resolution payload1. As the satellites are adjacent in orbit, with NovaSAR leading SSTL S1-4 by ~15 minutes, this provides an opportunity to demonstrate the benefits of using SAR and EO data together. The key demonstration principles are: to show the complementary nature of near-contemporaneous SAR and EO data, tipping and cueing opportunities of a tandem sensor, and to demonstrate the superiority of one technology for a specific application. The ability to undertake enhanced vessel detection using machine learning algorithms, to use bathymetry with EO and SAR imagery to get a more complete picture, and to detect oil spills in SAR imagery have been demonstrated. This proves the capability of the technologies, and their strengths as joint and separate data sources, helping to inform future mission concepts

Sensitivity of delay Doppler map in spaceborne GNSS-R to geophysical variables of the ocean

Global Navigation Satellite Systems reflectometry (GNSS-R) is a particular case of a multistatic radar in which the signals transmitted by navigation satellites are the signals of opportunity. These signals can be processed as a radar scatterometer, as a radar altimeter, or as an unfocused synthetic aperture radar. GNSS-R has shown its potential to infer numerous geophysical variables: over land soil moisture, vegetation height, detection of freeze-thaw state, etc., map sea ice extent and type…, and over the ocean wind speed and direction, significant wave height, altimetric measurements or even more recently NASA has released a marine plastics litter product, and some also claim that sea surface salinity (SSS) can be inferred. In addition, retrieval algorithms neglect some of the variations of the delay Doppler map (DDM) that are linked to the observation geometry, i.e., look angle with respect to the speed vectors of the transmitter and receiver. All these different effects impact the DDM peak value and its shape, and may affect the retrieval of geophysical parameters, and ultimately the data interpretation. In this study, the following factors impacting the DDM peak value are studied: the observation geometry, the sea surface temperature, and SSS, the 10 m height wind speed (U 10 ) and direction (WD), the presence of foam, the sea development state, the presence of swell, currents, rain, and the presence of oil slicks perturbing the sea surface roughness. This illustrates the complexity of the challenges presented when trying to retrieve some of these variables, the required corrections, and their accuracy.This work was supported in part by the Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023 (Spain) under Grant PID2021-126436OB-C21, in part by the European Social Fund, and in part by the GENESIS: GNSS Environmental and Societal Missions – Subproject UPC under Grant PID2021-126436OB-C21.Peer ReviewedPostprint (published version

Shipboard acoustic observations of flow rate from a seafloor-sourced oil spill

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Loranger, S., & Weber, T. C. . Shipboard acoustic observations of flow rate from a seafloor-sourced oil spill. Journal of Geophysical Research: Oceans, 125(10), (2020): e2020JC016274, https://doi.org/10.1029/2020JC016274.In 2004 a debris flow generated by Hurricane Ivan toppled an oil production platform in Mississippi Canyon lease block 20 (MC20). Between 2004 and the installation of a containment system in 2019 MC20 became an in situ laboratory for a wide range of hydrocarbon in the sea‐related research, including different methods of assessing the volumetric flow rate of hydrocarbons spanning different temporal scales. In 2017 a shipboard acoustic Doppler current profiler (ADCP) and high‐frequency (90 to 154 kHz) broadband echosounder were deployed to assess the flow rate of liquid and gas phase hydrocarbons. Measurements of horizontal currents were combined with acoustic mapping to determine the rise velocity of the seep as it moved downstream. Models of the rise velocity for fluid particles were used to predict the size of oil droplets and gas bubbles in the seep. The amplitude and shape of the broadband acoustic backscatter were then used to differentiate between, and determine the flow rate of, hydrocarbons. Oil flow rate in the seep was estimated to be 56 to 86 barrels/day (mean urn:x-wiley:jgrc:media:jgrc24228:jgrc24228-math-0001 barrels/day) while the flow rate of gaseous hydrocarbons was estimated to be 98 to 359 m3/day (mean urn:x-wiley:jgrc:media:jgrc24228:jgrc24228-math-0002 m3/day).The work was supported by the National Oceanic and Atmospheric Administration (Grant NA15NOS4000200)

Assessing ocean ensemble drift predictions by comparison with observed oil slicks

Geophysical models are cornerstone pieces in marine forecasting of floating objects and pollution, such as marine surface oil slicks. Trajectory forecasts of oil spills inherit the uncertainties from the underlying geophysical forcing. In this work we compare the forecast capabilities of an ocean ensemble prediction system (EPS) to those from a higher resolution deterministic model on the representation of oil slick drift. As reference, we use produced water (PW) slicks detected and delineated from 41 C–band Sentinel-1A/B satellite synthetic aperture radar images between April and December, 2021. We found that the EPS provided at least equivalent member-wise results relative to simulations forced with the deterministic model. Ensemble verification through rank histograms and spread-error relationship showed that including the ocean fields is necessary to address model uncertainties. Whether considering the ocean field or not, the modeled slicks were counterclockwise rotated between 20° and 30° relative to the ones observed in the satellite images, and these were deflected about 45° to the right of the observed wind direction

The Role of Detailed Geomorphic Variability in the Vulnerability Assessment of Potential Oil Spill Events on Mixed Sand and Gravel Beaches: The Cases of Two Adriatic Sites

The role of short to medium term geomorphic variation is analysed in two Italian mixed sand and gravel beaches to better understand how it could affect the vulnerability assessment to oil spill events. The study sites, Portonovo and Sirolo, are in one of the most congested areas for oil transportation in the Adriatic Sea (Ancona port). A "snapshot" situation populated with field data collected in April 2015 is compared to a "changing" situation built with previous field datasets (topographic surveys and surface sediment samplings) available for the two beaches. According to the ESI guidelines established by the National Oceanic and Atmospheric Administration (NOAA) in 2002, both Portonovo and Sirolo can be ranked as ESI 5 or 6A in most of the cases. Sediment size resulted the most decisive factor for the ESI assessment. As consequence of the bimodal direction of storms, the high geomorphic variability on the two sites is mainly related to storm berms which lead to rapid burial processes on both beaches. In oil spill circumstances, burial is considered the most alarming factor, especially on microtidal mixed beaches that develop storm berms so high and close to the shoreline. A quantification of the maximum potential depth reachable by the oil in the beach body is therefore needed for the most dynamic beaches: this could be achieved with repeated field measurements to be performed in the period between two consecutive ESI updates (5-7 years) and the addition of an appendix in the ESI maps dealing with the geomorphic characteristics of the beach. The significance of a changing ESI rank is that the authorities in charge of responding to the oil spill could be improperly prepared for the conditions that exist at a spill site if the geomorphology has changed from when it was first given an ESI rank

Natural occuring oil seepages as a consequence of bottom trawling?

Bottom trawling is used to capture fish species that live in the seabed. The damage on the seabed trawling causes has been discussed for many years. This thesis aims to investigate whether bottom trawling for sand eels can be a cause for some of the detected oil seepages in the North Sea. We investigated this using manual delineation of oil seepages in Synthetic Aperture Radar (SAR) satellite images to create statistics of when and where oil observations have been made; in total three areas were investigated. The SAR observations have been coupled together with wind speed data and trawling tracks. In 2020, an average of 76 % of the oil seepage observations were made during the sand eel trawling season. In 2021 there was a sudden drop in trawling activity with half the total number of trawling tracks. The sudden drop in trawling activ- ity for 2021 greatly reduced the number of observations of oil slicks, but one of the three investigated areas showed a similar number of observations in- side the trawling season. Using the trawling track information it was observed that areas with higher amounts of trawling activity have a higher number of seepage observations. For three of the datasets a p-value below 0.05 was con- firmed, based on a null hypothesis of neither favouring observation of an oil slick during or outside of sand eel trawling season. Notably the statistics of observations implies a significant correlation between trawling activity and oil slick observations, which warrants further study or observation