Please use this identifier to cite or link to this item:
Title: Applying DINEOF algorithm on cloudy sea-surface temperature satellite data over the eastern mediterranean sea
Authors: Nikolaidis, Andreas 
Georgiou, Georgios C. 
Hadjimitsis, Diofantos G. 
Akylas, Evangelos 
Keywords: Data reconstruction;DINEOF;Remote sensing;Sea-surface temperature
Category: Earth and Related Environmental Sciences
Field: Natural Sciences
Issue Date: 1-Apr-2013
Publisher: SPIE
Source: 1st International Conference on Remote Sensing and Geoinformation of the Environment, RSCy 2013; Paphos; Cyprus; 8 April 2013 through 10 April 2013
DOI: 10.1117/12.2029085
Abstract: Data Interpolating Empirical Orthogonal Functions (DINEOF) is a special technique which is based on Empirical Orthogonal Functions (EOF) in order to reconstruct missing data from satellite images. It is an innovative method, especially useful for filling in missing data from geophysical fields. Interesting examples could be clouds in sea-surface temperature (SST). Past studies have shown that filtering the temporal covariance matrix allows to reduce spurious variability and therefore a more realistic data reconstruction can be obtained. There is also provision in the estimation of the error covariance of the reconstruction of the data. Moreover, the error fields can be obtained with some calculation rearrangement. Error fields reflect the data-coverage structure and furthermore the covariance of the physical fields. Successful experiments on the Western Mediterranean encouraged the extension of the application of the method eastwards using similar experimental implementation. The present study summarizes the experimental work done, the implementation of the method and its ability in reconstructing the sea-surface temperature field over the Eastern Mediterranean basin, and specifically over Levantine sea and Cyprus.
ISBN: 978-081949638-6
Rights: © 2013 SPIE.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

Show full item record

Page view(s)

Last Week
Last month
checked on Oct 14, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.