Oil spill monitoring from spaceborne and airborne sensors

Oil spill monitoring from spaceborne 

and airborne sensors 

UNIVERSITETET I 

OSLO 

Anne H. Schistad Solberg and Camilla Brekke 

Institutt for informatikk, Universitetet i Oslo 

Contributions from partners in the EU-project Oceanides 

INSTITUTT FOR INFORMATIKK Proof seminar - 1

Agenda 

• State-of-the art in detection of illegal oil spills 

– Airborne and spaceborne sensors 

– Sensor coverage and limitations 

– Monitoring costs 

– Present monitoring: joint aircraft/satellite coverage 

• Automatic methods for oil spill detection 

– SAR imaging of oil spills 

– Algorithms for automatic detection 

– Performance of automatic vs. manual detection 


OSLO 


Illegal oil spills 

Spills from ships in open seas e.g. due to tank cleaning 

Oil spills from oil platforms 

600 000 tons/year in the Mediterranean 

Monitoring used to identify polluters and check if clean-up 

necessary 

Polluter received fine of $3.5M in the US (June 2004) 


OSLO 



OSLO 

Example 

satellite image 

Envisat SAR image from 

Baltic Sea 21 July 2003 

Arrows show oil spills 

Image size ~100x100km 


Spill sources 

Bright spots: ship or 

platforms 

Left: outlets from 

stationary sources 


OSLO 

Right: outlets from 

moving ship 


Temporal development 

Ship releasing oil 


OSLO 

Wind, current and 

waves affect the 

shape of the oil 

Older spills are 

irregular in shape 


Oil spill map of the Baltic Sea (HELCOM) 


OSLO 


Remote sensing of oil spills 


OSLO 

• Aircrafts cover narrow swaths 

– Can identify polluter 

– Determines if clean-up is necessary 

– Can also operate during nighttime 

• Satellites cover large swaths 

– Early warning of oil spills 

– 400x400 km 2 in a single image 

– All-weather/all-day capability 

– Can not identify the polluter 

– Can sometimes confuse oil and algae 


Comparison of Radarsat and aircraft 

SLAR image 

RADARSAT image 


OSLO 

SLAR image 


Comparison of Radarsat and aircraft 

photos 


OSLO 


Aircraft sensors 

Sensor Coverage Capabilities Nighttime operation 

SLAR 30 km Location Yes 

UV 250 m Spatial extent No 

IR 250 m Spatial extent Yes 

Microwave 

Radiometer 

Laser 

Fluorosensor 


OSLO 

250 m Oil thickness Yes 

75 m Oil type 

Oil thickness 

Yes 


Satellite sensors for oil spill 

• Optical sensors: 

– Need cloud-free scenes 

– Cannot operate at night 

– Can be used to discriminate between oil and algae if spatial 

resolution is high 

• Synthetic aperture radar (SAR): 

– Can operate all day and in clouded areas 

– Oil spills visible in wind speed from 3 m/s to approx. 12-15 m/s 

– Covers wide areas 

– Temporal coverage: close to daily 


OSLO 


SAR satellite sensors 

Satellite Launched Owner Frequency/ 


OSLO 

Polarization 

ERS-1 1991-1996 ESA C-band/VV 

ERS-2 1995- ESA C-band/VV 

RADARSAT-1 1995- CSA 

(Canadian) 

ENVISAT 

(ASAR) 

C-band/HH 

2002- ESA C-band/VV and 

HH, alt pol. and 

cross pol. 

RADARSAT-2 2005 CSA C-band/ 

pol. 

combinations 


ENVISAT Satellite passes pr. month 


OSLO 

• Coverage depends on 

latitude 

• Almost daily coverage 

in Norwegian waters 

Images pr. month 

1-7 

8-11 

12-15 

16-18 

19-24 


Monitoring costs example 

• Example from the EU-project Oceanides 

• Aircraft monitoring (Germany): 

– I flight hour: 4-5000 Euro 

– 12 flight hours to cover a full 400x400km scene 

– Cost of covering the entire Baltic sea: 126 000 Euro 

• Satellite monitoring: 

– Cost of 1 Envisat Near-real time scene: 850 Euro 

– Envisat images to cover the entire Baltic Sea: 2550 Euro 

• International cooperation needed to share costs 


OSLO 


Joint aircraft/satellite monitoring 


OSLO 

• Satellite acquisitions and flight plans 

coordinated 

• Satellite image downloaded and inspected 

at KSAT in Tromsø 

• KSAT reports suspect slicks to surveillance 

aircrafts by fax/email/phone 

• Aircraft flies to reported locations to verify 

• Aircraft tries to catch the polluter and 

collect evidence 

• Service presently used in Sweden, 

Denmark, Finland, Germany, Netherlands, 

UK 


Manual oil spill detection: KSAT 

• Manual inspection by trained operators 

– Information about wind speed used 

– Information about oil rig, pipelines, coastlines etc. is overlaid 

the image 

• Oil spills are assigned confidence levels: 

– Low 

– Medium 

– High 


OSLO 


Manual vs. automatic detection 

• Automatic methods faster 

– Manual: average processing time 10 min 

– Automatic: average processing time 1.45 min 

• Benchmarking studies show that automatic 

algorithms can perform comparable to manual 

detection in detecting verified oil spills 

• Manual verifification of suspect slick should be 

done prior to alarming the aircraft 

• Our automatic system will be installed and run at 

KSAT in Tromsø as part of ESA-project 


OSLO 


Automatic algorithm based on SAR images 

• Starting in 1993, an advanced algorithm for oil spill detection in ERS 

images was developed by the Norwegian Computing Center (NR). 

• Collaboration project 

– NR 

– University of Oslo. 

• The work has been extended to RADARSAT-1 ScanSAR and 

ENVISAT ASAR WideSwath images. 

– Sensor specific modules developed: 


OSLO 

» some differences in the dark spot detector 

» very similar features 

» sensor specific set of rules 


The automatic 

oil spill 

detection 

algorithm 

• Main parts: 

– Dark spot detection 

– Spot feature extraction 

– Spot classification 

» Make a decision if 

oil or look-alike, 

based on a 

statistical model for 

oil in different wind 

conditions and of 

different shapes. 


OSLO 

Oil spill 

desciption 

database 

Preprocessing and 

calibration 

Masking 

Dark spot 

detection 

Spot feature 

extraction 

Spot 

classification 

Warning 

if classified as oil 

INSTITUTT FOR INFORMATIKK Proof seminar - 20 

e 

Weather 

information

Dark spot deteksjon 

• Adaptive thresholding: 

– T is set to k dB below the estimated local mean backscatter 

level. 

– Wind information used to estimate k. 

• Power-to-mean ratio: 

– Local homogeneity is computed by PMR. 

– T is adjusted accordingly. 

• Pyramid approach: 

– Thresholding done in different scales. Result is merged. 

• Thin linear slicks (New ENVISAT approach): 

– Fragments located by thresholding as described, but fixing k at 

a small dB value. 1 st invariant planar moment an indicator of 

elongatedness. 

– Object oriented bounding box for each selected fragment. 

– Bounding box extended in the orientation of the slick and a 

threshold is applied inside the box. 

– Only pixels close to/on an edge are selected. 

– Segmented slicks merged with the original segmented image. 


OSLO 


Dark spot 

detection – 

thin, 

linear slicks 

example 

Large part of oil spill detected as background. 


OSLO 


Oil spill example 

(ENVISAT ASAR 

WideSwath). 

Improved result. Larger part of the oil spill detected 

and still separated from the background.

Feature extraction 

• ENVISAT and RADARSAT uses the same set of features (only 

slight modifications). 

– Simple ship detector tailored for each sensor. 

• The features are a mix of standard region descriptors and features 

tailored to oil spill detection. 

– Spot geometry and shape (e.g. area, width, complexity) 

– Intensity level (e.g. spot border gradient, local contrast) 

– Spot contextual features (e.g. spot local and global neighbours) 

– Texture (PMR) 


OSLO 


Slick classification 

• M spots to be classified as either oil spill or look-alike. 

• A statistical classifier model is applied which 

incorporates prior knowledge in terms of loss 

functions, and a rule-based approach. (See Solberg 

et al. 1999 IEEE Trans. on geoscience and remote 

sensing for details). 


OSLO 


Detected oil spill 

ENIVSAT ASAR WS. 

Detected as oil spill by KSAT and our algorithm, verified by Finnish surveillance aircraft, 


OSLO 

21 July 2003. 


Detected oil spill 


OSLO 

ENIVSAT ASAR WS. 

Detected as oil spill by KSAT and our algorithm, 

verified by German surveillance aircraft, 2 September 2003. 


Algorithm compared to manual and semi 

manual approaches 

• Benchmark study 

– Training set: 100 RADARSAT and 64 ENVISAT images. 

– Test set: 32 RADARSAT and 28 ENVISAT images. 

Approach/ 

Detected oil 

spills 


OSLO 

RADARSAT: 

18 oil spills verified by 

aircraft 

KSAT 15 

Our algorithm 

14 

ENVISAT: 

11 oil spills verified by 

aircraft 

QinetiQ 12 

5 


7 

8

Oil spills detected both by RADARSAT and 

ENVISAT ASAR 

Two oil spills verified by aircraft the 21 st July 2003 at 23:26 pm. 

Wind speed 10 m/s. Spot to the right: 59,50 Lat and 21.98 Lon. 

RADARSAT SCN image, 21 st July 2003, 16:05 pm. 

None of the satellite approaches detected the oil spill to 

the right. KSAT, QinetiQ and NR detected the oil spill to 

the left. 


OSLO 

ENVISAT ASAR WS image, 21 st July 2003, 19:54 pm. Oil 

spill to the right detected by KSAT and NR. None of the 

satellite based approaches detected the spill to the left. 


Oil spill missed by satellite 

ENVISAT ASAR WS. Classified as oil by German surveillance aircraft, 3 

August 2003. Not detected by KSAT, our algorithm or QinetiQ. 


OSLO 


Look-alikes and false alarms 

• Look-alikes: 

– Natural films 

– Grease ice 

– Threshold wind speed areas (< 3m/s) 

– Wind sheltering by land 

– Rain cells 

– Shear zones 

– Internal waves 

– Natural oil seepage etc. 

• In certain cases, a SAR sensor alone is not sufficient to 

discriminate between oil, natural films and algae. 

• To detect all true oil spills, a certain number of false 

alarms must be expected. 


OSLO 


Algae 

examples 


OSLO 

ENVISAT ASAR WS. Classified as algae by German surveillance aircraft, 7. august 

2003. 

ENVISAT ASAR WS. Classified as algae by 

Finnish surveillance aircraft, 11. August 2003. 

RADARSAT ScanSAR. Classified as 

algae by aircraft, 1. August 2003. 


Algae study 

• Additional information necessary to distinguish 

between algae and oil spills in SAR images. 

– Suitable sensors: 


OSLO 

» MERIS? 300m spatial resolution. 

» MODIS? 250-300 m spatial resolution. 

» Low resolution. 

» Cloud coverage and light conditions a problem. 

– Algae maps and probabilities of observing algae in different 

areas at different times of the year. 

» Summer months in the Baltic sea. 


Algae in ASAR 

WS image. Length 

of spot ~7050 m 

(pixel size is 75 m).

Summary 

• Future operational oil spill monitoring a combination of 

– SAR satellites (RADARSAT-1/-2, ENVISAT) with wide coverage and a 

spatial resolution

Oil spill statistics 

• >1000 spills observed annualy in European water 

• Oil spill lifetimes range from hours to days 

– Most oil spills are not observed the following day 

• Environmental effect depends on position, 

amount, oil type etc. 


OSLO 


Oil spill statistics – Finland (from SYKE) 


OSLO

Oil spill monitoring from spaceborne and airborne sensors

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