DEMOSS. Title: Development of Marine Oil Spills/slicks Satellite monitoring System elements for the Black Sea, Caspian Sea and /Kara/Barents Seas

Similar documents
MOPED Monitoring of Oil Pollution using Earth Observation Data

MONRUK Publishable Final Activity Report

Training Course on Radar & Optical RS, IES, Cēsis, Latvia, 5-9 September SAR Marine Applications. Wind and Waves

Arctic Regional Ocean Observing System Arctic ROOS Report from 2012

Currents and Objects

SAR Training Course, MCST, Kalkara, Malta, November SAR Maritime Applications. Wind and Waves

MARINE MONITORING OF THE SOUTH- AND EAST CHINA SEAS BASED ON ENVISAT ASAR

Training Course on Radar & Optical RS, IES, Cēsis, Latvia, 5-9 September SAR Marine Applications. Practicals

Fjernmåling og modellering av oljesøl - på åpen sjø og i is

Investigating Coastal Polynya Thin Sea Ice State in the Laptev Sea Using TerraSAR-X Dual-Pol Stripmap Data

Utilization of SAR and optical images/data for monitoring of the coastal environment

Monitoring Sea Ice with Space-borne Synthetic Aperture Radar

Linking Different Spatial Scales For Retrieval Of Sea Ice Conditions From SAR Images

Sharafat GADIMOVA Azerbaijan National Aerospace Agency (ANASA), Azerbaijan

Remote Sensing for Sea Surface Monitoring. Cristina Bentz PETROBRAS R&D Center Environment Assessment and Monitoring

J2.6 SONAR MEASUREMENTS IN THE GULF STREAM FRONT ON THE SOUTHEAST FLORIDA SHELF COORDINATED WITH TERRASAR-X SATELLITE OVERPASSES

ICE DRIFT IN THE FRAM STRAIT FROM ENVISAT ASAR DATA

The Wind-Wave Tank of Univ Hamburg

SAR Data Help Improving the Monitoring of Intertidal Flats on the German North Sea Coast

Application of Wavelet Spectrum Analysis to Oil Spill Detection by Using Satellite Observation Data

Improved sea-ice monitoring for the Baltic Sea Project summary

OPERATIONAL SATELLITE MONITORING OF OIL SPILL POLLUTION IN THE SOUTHEASTERN BALTIC SEA: 1.5 YEARS EXPERIENCE

The Importance of Microwave Remote Sensing for Operational Sea Ice Services And Challenges

Indonesian seas Numerical Assessment of the Coastal Environment (IndoNACE) Executive Summary

TerraSAR-X and TanDEM-X Applications for Maritime Domain Awereness

DLR s TerraSAR-X contributes to international fleet of radar satellites to map the Arctic and Antarctica

The TOPAZ3 forecasting system. L. Bertino, K.A. Lisæter, Mohn-Sverdrup Center/NERSC

Multisensor monitoring of Peter the Great Bay

ANALYSIS OF ASAR POLARISATION SIGNATURES FROM URBAN AREAS (AO-434)

Ice surveys, meteorological and oceanographic data What is available and up-to-date?

CopernicusEU. the EU's Earth Observation Programme. Sara Zennaro Atre Delegation of the European Union to Japan

Iceberg monitoring service by joint use of drift model, SAR and altimeter data

Experiences with Experimental Spills

1 Introduction. 2 Wind dependent boundary conditions for oil slick detection. 2.1 Some theoretical aspects

Validation of sea ice concentration in the myocean Arctic Monitoring and Forecasting Centre 1

Routine high resolution observation of selected major surface currents from space

Mud Volcanoes in the South Caspian Basin: Activity Inferred From ENVISAT ASAR Images

Space for the Arctic

OIL POLLUTION IN THE SOUTHEASTERN BALTIC SEA IN

Developing integrated remote sensing and GIS procedures for oil spill monitoring on the Libyan coast

PREDICTION OF OIL SPILL TRAJECTORY WITH THE MMD-JMA OIL SPILL MODEL

Making a case for full-polarimetric radar remote sensing

STUDIES OF OCEAN S SCATTERING PROPERTIES BASED ON AIRSAR DATA

COMPLEX MONITORING OF OIL POLLUTION IN THE BALTIC, BLACK AND CASPIAN SEAS

OCEAN SURFACE DRIFT BY WAVELET TRACKING USING ERS-2 AND ENVISAT SAR IMAGES

TOWARDS A TRACKING OF SMALL SCALE EDDIES USING HIGH- RESOLUTION RADARSAT-2 AND TERRASAR-X IMAGERY

INTAROS Integration of the existing Arctic observing systems into a common data frame. Roberta Pirazzini, Finnish Meteorological Institute

Platform measurements of Ka-band sea surface radar Doppler characteristics. Yu. Yu. Yurovsky, Semyon Grodsky (UMD), V. N. Kudryavtsev, and B.

Integrated Space Applications in Transport, Energy & Safety Oil & Gas Exploration

Arctic Observing Systems Challenges, New opportunities and Integration

Operational ice charting in mid-latitudes using Near-Real-Time SAR imagery

RADAR PHOTO SMOOTH OCEAN LONG WAVES. Introduction

Low-Backscatter Ocean Features in Synthetic Aperture Radar Imagery

EXPLOITING SUNGLINT SIGNATURES FROM MERIS AND MODIS IMAGERY IN COMBINATION TO SAR DATA TO DETECT OIL SLICKS

OPTIMIZATION IN OIL SLICK COMBATING STATIONS ALLOCATION. APPLICATION TO THE SEA OF AZOV

EO-Based Ice and Iceberg Monitoring in Support of Offshore Engineering Design and Tactical Operations

Shashi Kumar. Indian Institute of Remote Sensing. (Indian Space Research Organisation)

MESOSCALE VARIABILITIES IN SEA SURFACE CURRENT FIELDS DERIVED THROUGH MULTI-SENSOR TRACKING OF SEA SURFACE FILMS

GEOSC/METEO 597K Kevin Bowley Kaitlin Walsh

Coastal Ocean Applications Demonstrations of ALOS PALSAR Imagery for NOAA CoastWatch

Marine Situational Awareness and Environmental Monitoring using Satellites

C-BAND MULTIPLE POLARIZATION SAR FOR ICE MONITORING WHAT CAN IT DO FOR THE CANADIAN ICE SERVICE

5. TRACKING AND SURVEILLANCE

SYNERGY OF MERIS/ASAR FOR OBSERVING MARINE FILM SLICKS AND SMALL SCALE PROCESSES.

Challenges for SAR operations in the Barents Sea. Tor Einar Berg, Beate Kvamstad

Opportunities for advanced Remote Sensing; an outsider s perspective

SAR data Sensords and examples

Sea Ice Monitoring in the European Arctic Seas Using a Multi-Sensor Approach

Numerical Simulation of the Wind Stress Effect on ALOS PALSAR Images of Far Wakes of Ships Atsushi Fujimura and Alexander Soloviev

Infrastructure monitoring using SAR interferometry

Mersea Oil Spill Drift Forecast Demonstrations in TOP2

ASAR practical training session

K&C Phase 4 Status report. Ice Sheet Monitoring using ALOS-2. University of California, Irvine 2 JPL

Wave Propagation Model for Coherent Scattering from a Randomly Distributed Target

TOSCA RESULTS OVERVIEW

SAR Raw Signal Simulation of Oil Slicks in Ocean Environments

SAWS: Met-Ocean Data & Infrastructure in Support of Industry, Research & Public Good. South Africa-Norway Science Week, 2016

GEOGG141 Principles & Practice of Remote Sensing (PPRS) RADAR III: Applications Revision

British Colombia Knight Inlet Strait of Georgia Strait of Juan de Fuca

1. Regarding the availability of two co-polarized (HH and VV) channels.

PETROLEUM HAZARDS MANAGEMENT BY GEOMATIC SYSTEMS

The 3 rd NOWPAP Joint Training Courses on Remote Sensing Data Analysis. Vladivostok, Russia, 11 October 2011

MARINE AND MARITIME SAR APPLICATIONS: COSMO-SKYMED FROM 1 ST TO 2 ND GENERATION

ABSTRACT 1. INTRODUCTION

EONav Satellite data in support of maritime route optimization

DUAL-POLARIZED COSMO SKYMED SAR DATA TO OBSERVE METALLIC TARGETS AT SEA

Detection, tracking and study of polar lows from satellites Leonid P. Bobylev

Snow property extraction based on polarimetry and differential SAR interferometry

Sentinel-1 Mission Status

Floating Ice: Progress in Addressing Science Goals

Microwave Remote Sensing of Soil Moisture. Y.S. Rao CSRE, IIT, Bombay

Annex VI-1. Draft National Report on Ocean Remote Sensing in China. (Reviewed by the Second Meeting of NOWPAP WG4)

Air-sea Gas Exchange and Bio-surfactants: Low and High Wind Speed Extremes

On the Shape of the Fast Ice Drift Ice Contact Zone

Seatrack Web Developments

On radar imaging of current features: 2. Mesoscale eddy and current front detection

Ice Analyst Workshop Case Study Routine Monitoring Of Ice Islands. WMO IAW-2 Tromso Norway Laurie Weir CIS Vladimir Bessonov AARI June

Amina Rangoonwala and Elijah Ramsey III Wetland and Aquatic Research Center. U.S. Geological Survey. Lafayette, LA

The Polar Ice Sheets Monitoring Project A Coordinated Response from Space Agencies

Studies of Austfonna ice cap (Svalbard) using radar altimetry with other satellite techniques

Transcription:

DEMOSS Title: Development of Marine Oil Spills/slicks Satellite monitoring System elements for the Black Sea, Caspian Sea and /Kara/Barents Seas INTAS Thematic Call on Earth Sciences and Environment in cooperation with with ESA, 2006 by Stein Sandven 1, Vladimir Kudriavtsev 2 and Vladimir Malinovsky 3 1 NERSC, Bergen, Norway 2 NIERSC, St. Petersburg, Russia 3 MHI, Sevastopol, Ukraine With contribution form the other DEMOSSS partners

Partners 1. Nansen Environmental and Remote Sensing Center (NERSC), Norway 2. BOOST Technologies, Brest, France 3. University of Hamburg, Hamburg, Germany 4. Nansen International Environmental and Remote Sensing Center (NIERSC), St.Petersburg, Russia 5. Institute of Applied Physics Russian Academy of Sciences (IAP), Nizhny Novgorod, Russia 6. Marine Hydrophysical Institute of the Ukrainian National Academy of Sciences, Sevastopol, Ukraine 7. Arctic and Antarctic Research Institute (AARI), St.Petersburg, Russia 8. Research Center for Earth Operative Monitoring (NTs OMZ), Moscow, Russia

Project Objectives To develop and demonstrate components of a marine oil spill detection and prediction system based on satellite SAR and other space data in combination with models for oil slick/spill monitoring and prediction

Overview of Tasks Task 1 Task 2 Task 3 Task 4 Task 5 Field experiment with oil slicks in the Black Sea, IAP/MHI Radar Imaging Model Development, NIERSC Algorithm for detection & quantification of oil spills and look-alikes, NIERSC Satellite monitoring of selected areas: * Barents/Kara Sea, NIERSC * Black Sea, MHI * Caspian Sea, NTsOMZ and validation of oil slick detection, BOOST Oil spill modelling and drift forecasting, AARI

SAR acquisition of the study areas 1 2 Region Total* Details 3 The Barents Sea (1) and Kara Sea (2) are relatively clean areas with little ship traffic and offshore exploration has just started. The areas are expected to become much more exposed to oil pollution in the future. The Black Sea (3) and the Caspian Sea (4) have already significant tanker traffic and offshore exploitation has started from several platforms 4 Barents Kara Black Caspian 383 447 182 91 WSM: 131 APM: 12 IMM: 240 WSM: 276 APM: 3 IMM: 168 WSM: 58 APM: 38 IMM: 86 WSM: 38 APM: 1 IMM: 52 * Number of image obtained from ESA rolling archive from May to December 2007. In addition, archived data from earlier years are available for the studies.

Radar scattering modelling DEMOSSS develops an improved model of radar scattering from a sea surface covered by oil and biogenic films to be used in detection and classification of surface film in SAR images Flow diagram of the radar scatter model for simulation of a given surface condition

Wind Waves Spectrum and Effect of Thin OLE Film 10 2 OmniDirectional 10 2 Up Wind Direction Oleic adic (OLE): monomolecular film B(k) 10 4 u10=6m/s OLE E=0.022 B(k,0 0 ) 10 4 10 6 10 1 10 0 10 1 10 2 10 3 10 4 k, rad/m 10 6 10 1 10 0 10 1 10 2 10 3 10 4 k, rad/m 40 40 30 30 Contrast, db 20 Contrast, db 20 10 10 0 10 1 10 0 10 1 10 2 10 3 10 4 k, rad/m 0 10 1 10 0 10 1 10 2 10 3 10 4 k, rad/m

Backscatter from clean and film-covered water in tank experiments (inc. angle 30 ) Blue dots: observed backscatter from clean water Blue circles: observed backscatter from oil films (also triangles and crosses) Blue line: modelled backscatter from clean surface Green line: modelled backscatter from surface film (Ref. Gade at el.,jgr 1998, Kudriavtsev et al, JGR, 2005)

Spectral Contrasts for different surface films: Comparison of models with data Data from tank experiments (Ermakov et al.) 10 2 u10=7m/s Model simulations OLE Vegetable oil Crude oil Diesel oil Spectral Contrast 10 1 OLE E=0.022 VO E=0.012 CO E=0.004 Wavenumber k, rad/cm 10 0 10 1 10 2 10 3 k, rad/m Contrast between wind wave spectrum for clean water and different surface films

Effective Oil Film Viscosity Experimental estimates by Ermakov et al. vs. Jacobs and Jenkins (1997) model Wave damping coefficients as function of film thickness 15 Hz waves 25 Hz waves Oil thickness in mm Oil thickness in mm

Up-wind Radar contrasts vs. oil film thickness at C- and X-band VV&HH contrast in db 20 15 10 5 C band θ=20 0 u 10 =5m/s VV&HH contrast in db 20 15 10 5 X band θ=20 0 u 10 =5m/s 0 10 6 10 5 10 4 10 3 10 2 Film Thickness [m] 0 10 6 10 5 10 4 10 3 10 2 Film Thickness [m] 20 20 VV&HH contrast in db 15 10 5 C band θ=20 0 u 10 =10m/s VV&HH contrast in db 15 10 5 X band θ=20 0 u 10 =10m/s 0 10 6 10 5 10 4 10 3 10 2 Film Thickness [m] 0 10 6 10 5 10 4 10 3 10 2 Film Thickness [m]

Analysis of oil spill signatures in SAR images NRCS Incidence angle direction Wind speed

Comparison of observed (from SAR archive) and modelled C-band backscatter contrasts in oil spill signatures 10 9 8 C band Oil Slicks Contrast, db 7 6 5 4 3 2 20 0 30 0 40 0 1 0 0 2 4 6 8 10 Wnd Speed, m/s

Modelled backscatter of surfactants in an eddy Simulated NRCS field (in db) for an eddy current field in presence of surfactants. Wind speed (a) 5 m/s and (b) 15 m/s. Radar geometry is for ERS SAR.

Field experiment from an offshore tower in the Black Sea Optical system to measure short wave spectrum and surface mean slope Video system to measure wave breaking characteristics

Optical Spectrum Analyzer X-band radar Ka-band radar

Experiments with slick observations from the tower Date, start time 02.10.07 12:30 02.10.07, 16:47 Wind direction No wind 145º (SE) 90º (E) Wind speed Z=4m 0 m/s <0.5 m/s (14:07) 2.5m/s? Wave Vector dir 260º 270º Slick observations VO (13:03) VO (14:15) OLO (15:07) Natural slick (17:12) DF (17:14) Artificial slicks: Veg.Oil, Olive oil, Dodecyl Alcohol, Diesel fuel. Total: 16 03.10.07, 10:27 03.10.07, 15:46 110º No wind 107º (11:43) 90º (12:28) 0 m/s 1-2 m/s 2-3 m/s 1-2 m/s 270º 280º Natural slick (12:00) Natural slick (12:42) Natural slick (12:54) Natural slick (12:59) + VO Natural slick (13:13) OLO (13:43) Natural slick (15:50) Natural slick (16:03) OLO (16:09) Natural slick (16:14) Natural slicks periodic and single bands Total number of slicks: 13 04.10.07, 10:34 120º 0-2 m/s 300º Natural slick (12:37) 04.10.07, 15:46 150º 1-3 m/s 330º Natural slick (17:17) 05.10.07, 10:28 06.10.07, 10:02 0º - 5º 70º 2-4 m/s? 2-4 m/s? 270º 250º VO (12:22) Natural slick (12:30) OLO (12:44) DA (13:00) VO (13:39) VO (15:39) VO (15:50) DA (16:09) OLO (16:23) VO (16:23) OLO (11:55) Periodic Natural slicks ASAR image

Contrasts in slicks observed on 05 Oct 2007 1000 OSA 10 Radars Photo Contrast 100 10 Ka-band X-band Contrast OSA 1 0 1 10 Wavenumber, rad/cm 1 0 1 10 Wavenumber, rad/cm Dodecyl alcohol slick (film elasticity E=50-70 mn/m) Vegetable oil slick (film elasticity E=12-15 mn/m) Wind velocity 2-4 m/s

SAR observation of experimental oil spills

NRCS profile across a slick observed in ASAR APP data Results from SAR analysis of AP images form 2003: The largest slick has a contrast of about 15 db compared to the surrounding clean water

Another slick observation in SAR APP image Subset of ENVISAT ASAR AP image on 23 August 2003 off Novorossisk coast: (a) VV-pol (b) HH-pol (c) Pol ratio (PR) For clean seas PR is defined by contribution of bragg scattering and wave breaking, with typical value of 5 for this inc angle. In slicks bragg waves disappear and PR becomes close to 1

Distribution of oil spills in the Black Sea derived from 68 SAR images SAR images from ERS-2 and ENVISAT were analyzed for a period of three years (2001-2004), resulting in 68 images with 424 likely oil spill events. The distribution of the spills are concentrated along the main shipping lanes and in the offshore drilling area in the western Black Sea

Example from the Caspian Sea The ASAR Wideswath image from 04 July 2007 covers most of the Caspian Sea (left figure). A subset of the image (above) was analyzed for the area off Baku (red circle) where a spill event could be detected. The SARTool provided by BOOST Technologies was used to detect and quantify the oil spill area.

Oil spill event Kerch Strait 11 November 2007 C-band: RADARSAT X-band: TerraSAR L-band: ALOS PALSAR Courtesy: Scanex Courtesy: DLR Images obtained 16 November - > case study for model comparison

Comparison with previous SIR-C/X SAR data and field experiments

Oil drift modelling Oil spill input oil spill location oil spill volume and spill rate oil properties fractional composition of the oil Oil spill simulation spreading of the spillets advection evaporation advection turbulent diffusion evaporation emulsification dispersion photo-oxidation bio-oxidation Sea state input currents wind wind waves thermohaline structure bathymetry ice conditions AARI is developing an oil drift model, OilMARS, based on the components shown in the diagram. The model has been tested in the Barents and Kara Seas. Oil spill output Oil slick spatial distribution Oil mass balance

Oil spill modelling in Kara Sea: open water AARI uses its oil spill model OilMARS to simulate oil drift in the Kara Sea. The figures show the spreading of a spill over a period of 20 days. The red area indicate where oil reached the coast and caused pollution at the beach.

Oil spill modelling in Kara Sea: sea ice waters AARI uses its oil spill model Oilmars to simulate oil drift in the Kara Sea. The figures show the spreading of a spill over a period of 20 days in winter when the sea ice icecovered. Black indicates oil spill in open water, blue indicate oil spill on top of th eice and red is oil spill under the ice.

Summary and further work Radar scattering modelling tools is ready for use Field experiments with artificial oil spills at the tower in the Black Sea were performed in 2007, more experiments are planned in 2008 Lab experiments with radar observation of wave damping by various oil types have been conducted Build-up of SAR data base for the study regions have started, primarily with ASAR data. Will be supplemented by other SAR data (X- and L-band) Analysis of SAR data for slick and other ocean surface features, including comparison with models has started Verify hypothesis that PR can be used to identify oil and natural slicks and discriminate them from look-alikes Establish monitoring scheme using satellite data in combination with models and in situ data for validation

Acknowledgement The SAR data for the study is provided ESA through AOBE-2780) The research is supported by INTAS (contract no. 06-1000025-9264), EU FP6 (contract no. 031001- MONRUK), and national projects