Peer-reviewed articles 17,970 +



Title: AUTOMATED PROCESSING OF SATELLITE RADAR IMAGERY TOWARDS OIL SEEP DETECTION IN THE NORTHERN PART OF THE BLACK SEA

AUTOMATED PROCESSING OF SATELLITE RADAR IMAGERY TOWARDS OIL SEEP DETECTION IN THE NORTHERN PART OF THE BLACK SEA
V. Zamshin;E. Matrosova
1314-2704
English
19
2.2
Here we suggest the method of automated processing of satellite SAR imagery of marine surface aimed at oil spill detection. The method is based on the repeated application of the OSD algorithm built in the SNAP software. Due to the Graph Builder use and process paralleling, the sufficient level of functionality and performance is attained if using a desktop. At the final processing stage, the OSD algorithm results are subjected to a comprehensive analysis in the GIS environment taking into account additional information (proximity of detected slick-like phenomena to shipping routes, oil derricks, natural sources, etc.). Approbation of this method for the case study of the northern regions of the Black Sea has been carried out. SAR imagery of the Black Sea collected by Sentinel-1A/B satellites during spring and summer of 2017 and 2018 were taken as source. The approbation has shown that more than 85 % of true oil slicks can be registered in automated mode with short time required. The method may be effective for long-time monitoring of oil spills in marine water areas.
conference
19th International Multidisciplinary Scientific GeoConference SGEM 2019
19th International Multidisciplinary Scientific GeoConference SGEM 2019, 30 June - 6 July, 2019
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference-SGEM
Bulgarian Acad Sci; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Slovak Acad Sci; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; World Acad Sci; European Acad Sci, Arts & Letters; Ac
485-492
30 June - 6 July, 2019
website
cdrom
5523
SAR imagery; satellite monitoring; oil slicks; the Black Sea; SENTINEL-1