Rivo Uiboupin

Detection of oil spills on SAR images, identification of polluters and forecast of the slicks trajectory

SAR images from the Estonian coastal area were analyzed to identify oil spills. Slicks were detected on five images in February and March 2008. The analysis showed that the slicks occurred on the ship track. Seatrack Web model (SMHI) that includes ship automatic identification (AIS) data provides a possibility to identify the polluters. In two cases the hindcast model together with AIS information system enabled to detect the possible polluters.

Elimination of oil spill like structures from radar image using MODIS data

Oil-spill detection from radar imagery is complicated task in Estonian coastal sea where look-alikes caused by ice, upwelling events, cyanobacterial blooms may occur. We compared SAR image with the MODIS optical imagery and look-alikes caused by upwelling event and cyanobacterial bloom were detected from images of August 7, 2007. Analysis of MODIS imagery from years 2000-2006 showed that during the ice free period upwellings occur frequently in the Gulf of Finland and they are strongest during summertime stratification period. Cyanobacterial blooms occurred in July and August in Estonian coastal sea. Some ice cover is present in Estonian coastal sea every winter.

Analysis of natural background and dredging-induced changes in TSM concentration from MERIS images near commercial harbours in the Estonian coastal sea

Medium Resolution Imaging Spectrometer (MERIS) products with 300 m resolution from 2006 to 2011 were used to evaluate the local background of total suspended matter (TSM) in the vicinity of commercial harbours located along the Estonian coastline in the Baltic Sea. The difference between background TSM maps (mainly influenced by spring bloom, cyanobacterial bloom, resuspension, and river inflow) and dredging period mean maps was used for the estimation of dredging-induced turbidity at the time of dredging operations. Validation of Case II Regional (C2 R) and Free University of Berlin (FUB) MERIS processors with point measurements showed that both processors represent the changes in TSM concentration adequately. C2 R processors showed better statistics (R2 = 0.61, root mean square error = 0.82 mg l–1, SD = 0.77 mg l–1, mean bias = –0.28 mg l–1) compared to the FUB processor. Analysis of monthly mean TSM maps revealed that the variability of TSM concentration, showing the resilience level of the local ecosystem, is very different along the Estonian coastline – varying between 0.75 and 2.60 mg l–1 near the Port of Tallinn, located in the Gulf of Finland, and between 10.04 and 24.23 mg l–1 near the Port of Pärnu, located in the Gulf of Riga. The viability of the method for dredging impact detection was tested by evaluating the dredging-induced turbidity on monthly mean TSM maps for the dredging period in autumn 2008 in Pakri Bay, which is an environmentally sensitive area. A threshold TSM concentration value of >2.26 mg l–1 difference from background TSM was defined as a criterion for dredging impact detection for Pakri Bay. The area of dredging-induced turbidity was between 0.56 and 1.25 km2 and did not reach the environmentally sensitive NATURA 2000 region adjoining Paldiski South Harbour.

Oil Spill statistics from SAR images in the North Eastern Baltic Sea ship route in 2007–2009

A large number of illegal oil pollutions impose considerable threat to marine environment especially in marginal seas like the Baltic Sea. Illegal spills are mainly detected on essential navigation routes. The monitoring of Oil Spills (OS) using remote sensing imagery (SAR data) was performed on the northeastern Baltic Sea ship route. The pre-analyzed satellite images for detecting marine pollution were provided to marine surveillance agency in Estonia. Out of 137 detected potential pollutions 76 were confirmed by aerial surveillance missions within two-year period. OS were mainly of low confidence, had small area, low contrast with surrounding water and smeared edges. The entrance to the Gulf of Finland was classified as the area where illegal spills of oil and bilge water take place, mainly. Between 30–50% of actual oil pollutions are not detected by SAR.

Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument Imagery in the Baltic Sea

The launch of Ocean and Land Colour Instrument (OLCI) on board Sentinel-3A in 2016 is the beginning of a new era in long time, continuous, high frequency water quality monitoring of coastal waters. ...

Upwelling Parameters From Bias-Corrected Composite Satellite SST Maps in the Gulf of Finland (Baltic Sea)

This letter proposes a method for using the operational ship of opportunity temperature data at a fixed depth for bias correction of satellite sea surface temperature (SST) images. The bias-corrected SST imagery from MODerate Resolution Imaging Spectroradiometer (MODIS) and Advanced Along-Track Scanning Radiometer (AATSR) sensors were used to calculate mean upwelling characteristics in the Gulf of Finland (GoF, Baltic Sea). First, we determined that the operational flow through temperature data at a 4-m depth can be used for validation and bias correction of satellite SST images in cases of wind speed over 5 m · s-1. The composite sea temperature maps were calculated from bias-corrected images collected during upwelling events in the GoF, in 2000-2009. Mean upwelling characteristics were estimated from composite maps for both the northern and southern coasts of the gulf.

Analysis of historical MERIS and MODIS data to evaluate the impact of dredging to monthly mean surface TSM concentration

We studied the changes of total suspended matter (TSM) distribution in Estonian coastal sea with special focus onPaldiskiharbor at the Pakri Bay (SW Gulf Of Finland). The purpose of current study was to examine the suitability of remote sensing data for detection of turbidity differences caused by dredged sediments on monthly mean surface TSM concentration, retrieved from satellite images. The MERIS (FSG) products with 300m resolution and MODIS band 1 data with 250m resolution from years 2006-2010 were used in theanalysis. MERIS images were processed using the Case-2 water processors available in BEAM software. Validation of the two processors (C2R and FUB) with in situ measurements of TSM gave reliable correlation between satellite data and in situ TSM measurements: r2 was 0.43 for FUB processor and 0.47 for C2R processor. An empirical algorithm was established for conversion of MODIS band 1 reflectance (620-670 nm) data to TSM concentration. We found reliable (r2=0.43) relationship between MODIS reflectance at band 1and TSM concentration measured fromwater samples. The monthly average TSM maps in the harbor region were calculated from MERIS and MODIS data using validated conversion algorithms in order to describe TSM variability and to analyzeenvironmental impact of dredging.

SAR imagery and Seatrack Web as decision making tools for illegal oil spill combating — a case study

The number of marine pollution arising from illegal oil discharges from ship tank or bilge pumping is much greater than those spectacular ship accidents. Illegal spills are mainly detected on essential navigation routes. In every country, marine surveillance agencies are responsible for oil spill combating and on identification of illegal polluters. They rely on information that has been provided on potential oil spills by responsible institution. The first information is usually provided by satellite remote sensing. The decisions about oil combating action is taken based not only on SAR imagery, but checking confirmation from aerial surveillance and using oil spill modeling, also. SAR imagery and aerial surveillance does not provide information about the type of spilled oil, which is important input information for oil spill modeling. Different types of oil have different behavior in water and may affect the decisions about which oil combating activities should be taken. The aim of this study was to show how different type of oil behaves in water according to the Seatrack Web oil drift model, which is the main modeling tool of Estonian Border Guard who is responsible in oil combating. Current study is based on illegal oil spill accident that happened in the eastern Baltic Proper on 10 April 2010. Potential oil pollution was detected on SAR image at 9:08 UTC. Consecutive SAR image was obtained at 9:40 UTC showing no significant change of the slicks area and shape in such a short time. Oil pollution was also confirmed by aerial surveillance at 11:10 UTC. Report that was based on visual observations said that it was probably a bilge water, which started to vanish due to ship traffic. The pollution was also recorded by Side Looking Aperture Radar (SLAR). Seatrack Web model (STW) was used for the forecast of oil slick drift. The input of light and medium oil was chosen. The results showed rather different results about oil drift as well as about oil fate. In case of medium oil 20% of oil was expected to evaporate within a couple of hours and the rest stayed in water surface. In the case of light oil 20% was evaporated, but the rest of the oil was expected to disperse in to the water column and emerge on the surface in time to time. The light oil was simulated to drift to the NWW, while medium oil to the SW. Laboratory analyses of the sample that was taken at 14:30 UTC showed that heavy fraction of the oil (hydrocarbons C16-C36) was maintained in the water until then. In conclusion, this study shows that the information about the type of spilled oil is needed as soon as possible after the oil detection to make appropriate decision on oil combating activities.

Sea state in the Baltic Sea from space-borne high-resolution synthetic aperture radar imagery

ABSTRACT In this work, remote sensing synthetic aperture radar (SAR) data from X-band TerraSAR-X and TanDEM-X (TS-X and TD-X) satellites have been used to adopt the algorithms for estimating sea state parameters in the specific condition of the Baltic Sea with archipelago islands and where short steep sea state dominates. Since the moving targets can be defocused and shifted in SAR images, sea state consisting of short windsea waves with strong local orbital velocities and wave breaking needs additional effort for accurate estimation of the total significant wave height that consists of swell and windsea parts. The XWAVE_C algorithm, developed for the North Sea, where the long swell waves coming from the Atlantic Ocean are present during storms, was further enhanced for the short steep windsea which dominates under ordinary storm conditions in the Baltics. For the empirical XWAVE_C model function, based on the spectral analysis of subscenes as well as on local wind information, an additional term was incorporated for assessment the minimal windsea significant wave height by applying JONSWAP wave spectra. A term to compensate spectral distortions triggered by windsea waves moving in SAR flight direction has also been introduced. In total, 95 TS-X/TD-X StripMap scenes between 2012 and 2017 were acquired in Eastern Baltic Sea, processed and analysed. The wave height results from SAR images were compared with collocated in situ data from 11 available buoys. The analysed data include both high and low windsea conditions. The comparison of SAR-derived wave heights with measured wave heights shows high agreement with a correlation coefficient r of 0.88. The wind speed, estimated from SAR images, was compared to measurements from 14 collocated in situ stations, yielding a high agreement with an r value of 0.90. This article is focused on the algorithm developments; however, it is also the first study of sea state retrieval in the Baltic Sea using high-resolution satellite-based techniques. The results show the local variability in the wave fields connected to atmospheric features. The observed local wave height can increase by 1–2 m in kilometre-size cells that are accompanied by wind gusts. The developed algorithms are installed in the German Aerospace Center’s (DLR) ground station Neustrelitz and can also be used in near-real-time.

Applicability of SAR-based wave retrieval for wind–wave interaction analysis in the fetch-limited Baltic

ABSTRACT In this article, a method for the detection of wave field parameters from synthetic aperture radar (SAR) imagery in the fetch-limited Baltic Sea is presented. Over the Baltic Sea region, common southwest (SW) and west (W) winds induce steep waves with shorter wavelengths compared with ocean waves. Thus, with the use of previous SAR sensors (e.g. ENVISAT/ASAR), it was not possible to detect individual waves and retrieve image wave number spectra. Since the year 2007, when TerraSAR-X (TS-X) reached its orbit, high spatial resolution data is available for measuring the sea-state parameters: the individual waves up to 30 m wavelength and their refraction can be distinguished. The main objective of this work was to demonstrate the capability of detecting wave field parameter from (TS-X) imagery in the Baltic Sea. The wave field parameters obtained from the SAR imagery were compared with in situ measurements and the Simulating WAves Nearshore (SWAN) wave model. The comparison of SAR-based wave field information with buoy measurements showed high agreement in case of wave propagation direction (r = 0.95) and wavelength (r = 0.83). A significant correlation is also seen between SWAN- and SAR-derived wave propagation direction (r = 0.87) and wavelengths (r = 0.91). With the case studies, it is shown that SAR data enables one to detect land shadow effects and small-scale wave field variations in the coastal zone. It was shown that SAR data is also valuable for improving and interpreting the wave model results. In consequence of common slanting fetch cases over the Baltic Sea region, it was demonstrated that the peak wave directions differ from the mean wind directions up to 43°.