Development of satellite oceanography methods in FEB RAS corporate oceanographic GIS. Andrey V. Golik, Vitaly K. Fischenko, Stepan G. Antushev V.I.Il’ichev Pacific Oceanological Institute Far-Eastern Branch of Russian Academy of Sciences
in FEB RAS corporate oceanographic GIS
Andrey V. Golik,Vitaly K. Fischenko, Stepan G. Antushev
V.I.Il’ichev Pacific Oceanological Institute
Far-Eastern Branch of Russian Academy of Sciences
Space Technology & Geo-Informatics 2006, Pattaya, Thailand, 2006
FEB RAS – Far-Eastern Branch of Russian Academy of Sciences
25 institutes (6 scientific centers), from them
12 institutes specializing in «Earth sciences», from them
5 institutes specializing in «Oceanography»:
Pacific Oceanological Institute (300 scientists), total about 1000 scientists
Main area of researches: Northwestern Pacific (lithosphere, hydrosphere, atmosphere)
( 2 scientific institutes )
Kamchatsky Scientific Center
Institute of Volcanology and Seismology et all (2 institutes)
Sakhalin Scientific Center
Institute of Marine Geology and Geophysics (1 institute)
Primorsky Scientific Center
Pacific Oceanological Institute,
Institute of Marine Biologyet all (4 institutes)
Scientific centers and institutes of FEB RAS,
which perform researches in Northwestern Pacific
(oil spill localized and described)
Bottom sediments in Japan sea
Query for satellite images contain oil spills
CTD station locations in 1958Work with different data layers and types
Current status: 54thematical layers, about 150 Gb of data, 6software tools for analytical data processing, link to 3 remote data storage in FEB RAS network, monitoring of 5 oceanographic internet resources.
GIS contains large collection of different data from satellites ERS-1/2, Envisat, NOAA, Terra/Aqua, etc. (about 2000 images, total volume more than 10 Gb).
Expert interface – add new SAR-image in GIS
Expert interface – phenomena description
Expert use visual analyze and data processing tools from GIS
Expert can copy image from GIS window to clipboard and paste in desktop program
Original image and 5 different filtering results
Spatial-frequency filtering (SFF) of satellite imageusing «global»filter
Original image, Fourier-spectrum, modified Fourier-spectrum, result
«Dynamical» operation – very useful tool for local features analysis
“Dynamicalspectral analysis” of anysatellite image fragment
“Dynamical SFF filtering”
Swell-waves deleted by using local SFF, keep only internal waves
Using «dynamical template matching» for mesoscale ocean eddy moving analysis
Two satellite image with time difference in half hour (maximum of cross correlation function determine shift of eddy structure)
and it approximation
and it approximation
Correlation-spectralanalysis of SAR image
ISC – integral spatial characteristics
IFC – integral frequency characteristics
On this figure presented: original image; 2D Fourier spectrum; 2D correlation function; integral spatial characteristic describing properties of image structure anisotropy; 2 modifications of integral frequency characteristic with results of it’s approximation using one of the correlation-spectral models provided by tool.
Oil pollution recognition (original, binary, recognized)
Important advantage of conception of union geoinformatics and space technologies is opportunity to organize joint work of specialists in different knowledge fields. Such joint work encourages development of both satellite methods and other scientific methods. During trial use of oceanographic GIS FEB RAS there were outlined some «points of interest intersection» for satellite oceanographers and specialists in different oceanography fields.
channel 6GHz - V
channel 6GHz - H
channel 10.65GHz - V
channel 10.65GHz - H
T = fT(Ch1, Ch2, Ch3, Ch4, …)
W = fW(Ch1, Ch2, Ch3, Ch4, …)
restored SST field
restored SSW field
Laboratory of satellite oceanology
Server contains local copies of AMSR-E data
satellite data AMSR-E
(in Japan)Development and research of algorithms of physical field restoration using AMSR-E data and Near-GOOS data
Configuration of task
SAR-image in same time (internal waves?)
Support of seismoacoustic researches on Shultz cape
signal of Earth’s deformations
Fourier-spectrum of signal
Analysis tide effects: 7-days record and result wavelet-filtering tide effects, Fourier-spectrum, continuous wavelet transformation. Detected periods– 12 and 24 hours.
Analysis hydro acoustic signal response: earth microdeformation signal (1 second), Fourier-spectrum, wavelet transform.
Detected base frequency of hydro acoustic signal – 22 Hz.
About possibilities of joint use satellite and seismoacoustic data for tsunami detection.
1. At present time discussed different satellite methods for tsunami detection.
2. Seismoacoustic data allow differ «tsunami-alert» and «tsunami-not alert» underwater earthquakes.
Tsunami-not alert earthquake in Japan sea.
Tsunami-alert earthquake in Japan sea seismoacoustic data for tsunami detection(was not tsunami)
Tsunami-alert earthquake in Adaman sea seismoacoustic data for tsunami detection(was tsunami)
We believe that joint usage of geoinformatics and space technologies by specialists in various fields of science encourages development of both corresponding fields of science and space technologies. As we tried to show in this presentation, it is fair at least for oceanography.
Thank you for your attention!