DocumentCode
440999
Title
Oil slick detection and characterization by satellite and airborne sensors: experimental results with SAR, hyperspectral and lidar data
Author
Lennon, M. ; Thomas, N. ; Mariette, V. ; Babichenko, S. ; Mercier, G.
Author_Institution
SAS ActiMar, Brest, France
Volume
1
fYear
2005
fDate
25-29 July 2005
Abstract
Efficient observation means are required for regional-scale detection of oil slicks at sea, as well as for local-scale quantitative mapping in order to support operational fight and recovering operations, including reliable choice and guidance of maritime and airborne fighting means. An efficient oil slick detection algorithm based on a multiscale approach is proposed for operational regional-scale detection from satellite SAR images. The potential of combining airborne passive hyperspectral imagery and active fluorescence laser technology is proposed for local-scale quantitative characterization. The ways towards the use of both satellites and airborne remote sensors for use in operational emergency scenarios are discussed.
Keywords
geophysical signal processing; multidimensional signal processing; oceanographic techniques; optical radar; petroleum; remote sensing by laser beam; remote sensing by radar; spaceborne radar; spectral analysis; synthetic aperture radar; water pollution; active fluorescence laser technology; airborne passive hyperspectral imagery; airborne sensors; hyperspectral data; lidar data; oil slick characterization; oil slick detection; operational emergency scenarios; quantitative characterization; satellite SAR images; satellite sensors; Friction; Hyperspectral imaging; Hyperspectral sensors; Laser radar; Optical surface waves; Petroleum; Radiometry; Satellite broadcasting; Sea surface; Sensor phenomena and characterization;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International
Print_ISBN
0-7803-9050-4
Type
conf
DOI
10.1109/IGARSS.2005.1526165
Filename
1526165
Link To Document