Marine Surveillance with RADARSAT-2: Ship and Oil Slick Detection

Gordon Staples, Jeff Hurley, Gillian Robert, Karen Bannerman

MDA GSI

Richmond, BC

gstaples@mda.ca

© MDA

Outline

Project Objectives

Ship Detection

Oil Slick Detection

Conclusions

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Introduction

Canadian Space Agency EOADP-funded project that started in June 2007 and finished in March 2011. The overall objective was to investigate the use of dual-polarized and quad-polarized SAR data for maritime surveillance, initially in preparation for RADARSAT-2 using ENVISAT and SIR-C data and then follow-on with RADARSAT-2 data.

The project had two focus areas: ship detection and oil slick detection

The objectives of the ship detection were to:– Assess the use dual-polarized (and quad pol) as a function of incidence angle– Assess detection and ship orientation with-respect-to radar look direction

The objectives of the oil slick detection study were to:– Investigate the use of the polarimetric entropy for oil slick characterization– Understand the application of incoherent target decomposition algorithms using

RADARSAT-2 quad-polarized wide-swath modes

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Ship Detection Study Site

Study site was the Strait of Georgia, BC

Access to ship-tracking information from Canada Coast Guard shore-based radars

Ships have predictable routes (e.g. BC Ferries), so it was possible to image the same ship, in the same orientation, but using a different incidence angle

Variable wind speeds, but nothing too extreme

– Wind speeds were typically less than 10 m/s

Strait of Georgia study site showing shipRoutes for ferry traffic between the BCMainland and Vancouver Island

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Vessel tracked from the Maritime Communications and Traffic Services Centre operated by the Canadian Coast Guard (CCG)

The CCG data provided:– continuous tracking– ship name, Lloyd’s registry, type,

length, speed, direction, etc.

The time difference between the CCG ship data and the RADARSAT-2 acquisition was typically less than a few minutes, so positive identification was possible

Ship Validation Data

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Dual-Polarized Data

The data were acquired in ascending mode since previous work with ENVISAT data indicated that in general there was more ship traffic at ~ 6 PM versus ~ 6 AM.

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HH

HV

Wide 1 image (HH+HV) acquired August 4 (left) and wide speed derived from the HH image (top). Note the high wind speeds that appear as bright returns in the HH image, but less pronounced in the HV image.

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Wide 1 + Wide 2 Results (HH + HV) 19.1 - 39.4

HV TCR: ~ constant with incidence angleHH TCR: increases with increasing incidence angle

TCR near range: HV > HH TCR far range: HH > HV At ~ 30 incidence angle, HV and HH TCR are similar Results based on the BC Ferries with lengths between 80 m and 160

m, with the same ships in Wide 1 and Wide 2

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Wide 1 + Wide 3 Results (VV+VH) 19.1 - 31.1 and 38.7 - 45.3

Seven ships between 26 m and 133 m were detected in Wide 1 and Wide 3 TCR near range: HV > HH TCR far range: HH > HV

Wide 1 and Wide 3 - Same Ship Comparison

0

5

10

15

20

25

30

35

40

27

.28

27

.64

27

.75

28

.24

28

.91

29

.04

29

.10

30

.00

31

.00

32

.00

33

.00

34

.00

35

.00

36

.00

37

.00

38

.00

39

.46

40

.82

41

.35

42

.13

42

.25

42

.52

42

.99

Incidence Angles of Target Location

TC

R d

B

VV

VH

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>125 m

<50m

Ship Orientation and TCR

CCG data provides accurate heading/course information on each vessel

All of the vessels +/- 45° from parallel were put in the parallel category, while the remaining were classed as orthogonal

Ships greater > 50 m in length were selected and the TCR estimated for ships that were “parallel” and “perpendicular” to the radar look-direction

As the ship length decreases, itwas difficult to discern orientation (depends on radar resolution – 30 m for this example)

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As ship length increased, there was a trend for the TCR (VV or VH) to be larger whenthe ship was oriented perpendicular to the radar look direction vs. parallel

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Study SiteCantarell Oil Seep

Cantarell oil seep (left) and a subscene of a RADARSAT-2 ScanSAR Narrow image (right) acquired March 5, 2011 showing the Cantarell oil seep. The inset shows an overlay of the FQW15 acquired March 1, 2011. RADARSAT-2 quad-polarized Fine and Standard Wide swath data (50 km az x 25 km rg) were acquired.

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Cantarell slicks

The entropy increased with oilviscosity (IFO > Cantarell), but was this increase related to oil properties or incidence angle?

Differences in the Cloude-Pottier entropy were observed between oil types: Intermediate Fuel Oil (IFO) and oilfrom the Cantarell seep

SIR-C

RADARSAT-2

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Entropy divergence correlates with co-polarized divergence

Entropy increased with incidence angle, but entropy is derived from the coherency matrix which is derived from the scattering matrix, so the relationship makes sense oil-type dependency is suspect

RADARSAT-2 data were acquired at larger incidence angles

Sigma-0 divergence for oil-ocean with increasing incidence angle for co-polarized, but invariant for cross-polarized data

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Entropy

Entropy for FQW2 (top) and FQW15 (bottom)

The incidence angle range for FQW2 is 19.1 - 22.7 and 34.4 – 36.0 for FQW15

The scale on the right is from 0 to 1, with low entropy (blue) and high entropy (red)

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Noise Floor and Target Decomposition

Cross-polarized return for oil and ocean and the FQW15 and SQW15 noise floor

The cross-pol (HV) for oil and ocean is at or below the noise floor

For low return targets, the use the cross-polarized data may be noise-limited and impact results for target decomposition

FQW15 HH+HV+VV

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Eigenvalues

Eigenvalues 1 and 2 (top) and 3 (bottom) for oil and ocean calculated from the 3x3 coherency matrix

Ocean scattering: 1 invariant with incidence angle

Oil scattering: 1 dominates to about 25 incidence

angle, and then 2 increases (1 > 2)

For both oil and ocean, 3 << (1 and 2)

3 0 (HV polarization)

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Target Decomposition3x3 vs. 2x2 Coherency Matrix

Incoherent target decomposition (e.g. Cloude-Pottier, Touzi) use co-polarized and cross-polarized data derived from (usually) the 3x3 coherency matrix

The dominance of the first and second eigenvalue (at smaller incidence angles) suggests that the cross-polarized terms in the 3x3 coherency matrix can be neglected

To assess the impact of neglecting the cross-polarized terms, the 2x2 symmetric coherency matrix was formed by setting the cross-polarized terms, SHV = 0

000

0

0

2

1 2**

**2

vvhhvvhhvvhh

vvhhvvhhvvhh

SSSSSS

SSSSSS

T

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Dominant eigenvalue (left) and Touzi scattering type phase (right) derived from 3x3 coherencymatrix (top), 2x2 coherency matrix (middle), and the difference (bottom). The differencesare mainly in the offshore platforms. FQW2 data

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Application of the Touzi Decomposition

Dominant eigenvalue (1)– Limited oil-ocean discrimination

at small incidence angles (FQW2), but better at larger incidence angle (FQW15)

Scattering type phase (S) – good discrimination between oil

and ocean for both images, thus suggesting incidence-angle invariance.

1

S

sFQW2 FQW15

22.7 19.1 34.4 36.0

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Summary

Ship Detection

TCR is larger for:– small incidence angles for HV– large incidence angles for HH or VV

TCR (orthogonal) > TCR (parallel) as ship length increases from ~ 50 m to ~175 m

The use of co/cros-pol data provides good ship detection across a large range of incidence angles

Oil Slick Detection

The entropy increased with incidence angle, so oil-type discrimination requires validation with different oil types

Scattering dominated by 1 and 2 suggesting that 3 can be neglected Work is in progress to further understand the use of incoherent target

decomposition for oil slick discrimination (interslick variability and oil-type differences)