FN Archimer Export Format
PT J
TI Operational oil-slick characterization by SAR imagery and synergistic data
BT 
AF ARDHUIN, Fanny
   MERCIER, G
   COLLARD, F
   GARELLO, R
AS 1:1,3;2:1;3:2;4:1;
FF 1:PDG-DOP-DCB-OPS-LOS;2:;3:;4:;
C1 ENSTB, GET, F-29238 Brest, France.
   BOOST, F-29280 Plouzane, France.
C2 ENSTB, FRANCE
   BOOST, FRANCE
   IFREMER, FRANCE
SI BREST
SE PDG-DOP-DCB-OPS-LOS
IN WOS Ifremer jusqu'en 2018
   copubli-france
IF 0.873
TC 50
UR https://archimer.ifremer.fr/doc/2005/publication-1132.pdf
LA English
DT Article
DE ;Synthetic aperture radar SAR;Satellite measurement;Oil pollution;Image analysis
AB A methodology is proposed for the semiautomatic detection, characterization, and classification of slicks detected in C-band Synthetic Aperture Radar (SAR). For the first detection step, automatic algorithms were tested on Environmental Research Satellite (ERS) and Environmental Satellite (EnviSat) images acquired during the Prestige tanker accident. These tests reveal that simple filter or segmentation methods efficiently detect slicks with high contrasts and simple shapes, while a new and more complex multiscale method is able to detect a wider range of slicks. The characteristics of automatically detected slicks are then combined with meteooceanic data in order to eliminate slicks related to wind anomalies and current fronts. The data suggest that slicks in cold upwelling waters are natural, and confirm that slicks are heavy oils when high sea states are present. This detection-classification methodology is validated with aircraft slick-tracking maps. In most cases, joint SAR and environmental data are sufficient to classify the slicks.
PY 2005
PD JUN
SO IEEE Journal of Oceanic Engineering
SN 0364-9059
PU IEEE
VL 30
IS 3
UT 000235420300003
BP 487
EP 495
DI 10.1109/JOE.2005.857526
ID 1132
ER

EF