SST fusion analysis based on Kalman Filter and Spatiotemporal dimension

Na Liu; Lingyu Xu; Yijun Xu; Jian Wang

doi:10.1117/12.2013925

13 March 2013 SST fusion analysis based on Kalman Filter and Spatiotemporal dimension

Na Liu, Lingyu Xu, Yijun Xu, Jian Wang

Proceedings Volume 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing; 87830V (2013) https://doi.org/10.1117/12.2013925
Event: Fifth International Conference on Machine Vision (ICMV 12), 2012, Wuhan, China

Abstract

As for the problem of quality evaluation method of sea surface temperature (SST) observed by satellite remote sensing. An analysis model of SST is proposed based on the combination of observations at different time, different places and with different techniques. According to this model, Kalman Filter and the principle of non-negative matrix factorization can be used to fuse the SST data in temporal and spatial dimension when the data absence occurs. Through which an accurate estimation of SST observations will be made. The experiment results with SST data obtained in East China Sea in 2006, showed that the model presented in this article can obviously improve the precision of SST data estimation, which can provide accurate reference for the quality evaluation of marine information.

Citation Download Citation

Na Liu, Lingyu Xu, Yijun Xu, and Jian Wang "SST fusion analysis based on Kalman Filter and Spatiotemporal dimension", Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 87830V (13 March 2013); https://doi.org/10.1117/12.2013925

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available