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Discrimination between oil
spill and look-alike using fractal dimension algorithm from
RADARSAT-1 SAR and AIRSAR/POLSAR data
Maged Marghany* and Mazlan
Hashim
Institute of Geospatial Science and Technology (INSTeG),
UniversitiTeknologi Malaysia 81310 UTM, Skudai, Johore Bahru,
Malaysia.
*Corresponding author. E-mail:
magedupm@hotmail.com.
Accepted 14 March, 2011 |
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This work utilizes a modification of the formula of the
fractal box counting dimension in which a convoluted line of
slick embedded in SAR data was divided into small boxes. The
method is based on the utilization of the
probability distribution formula in the fractal box count.
The purpose of this method is to use it for the
discrimination of oil spill areas from the surrounding
features, for example, sea surface and look-alikes in SAR
data, that is, RADARSAT-1 SAR S2 mode and AIRSAR/POLSAR
data. The results show that the modified formula of the
fractal box counting dimension can discriminate between oil
spills and look-alike areas. The low wind area has the
highest fractal dimension peak of 2.9, as compared to the
oil slick and the surrounding rough sea. Further, modified
formula of fractal box counting dimension is also able to
detect look-alikes and low wind zone areas in AIRSAR/POLSAR
data. It is interesting to find out that oil spill is absent
in AIRSAR/POLSAR data. Both SAR data have a maximum error
standard deviation of 0.45, which performs with fractal
dimension value of 2.9. In conclusion, modification formula
of fractal box counting dimension is a promising technique
for oil spill and look-alikes automatic discrimination in
different sensor of SAR data.
Key words: Oil spill, look-alikes, fractal dimension, RADARSAT-1 SAR,
AIRSAR/POLSAR. |
