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Spatial biases analysis and mitigation methods in SMOS images

Author
Corbella, I.; Torres, F.; Wu, L.; Duffo, N.; Duran, I.; Martín, M.
Type of activity
Presentation of work at congresses
Name of edition
33rd IEEE International Geoscience and Remote Sensing Symposium
Date of publication
2013
Presentation's date
2013-07-22
Book of congress proceedings
2013 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 21–26, 2013: Melbourne, Australia
First page
3415
Last page
3418
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/IGARSS.2013.6723562 Open in new window
Repository
http://hdl.handle.net/2117/21934 Open in new window
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06723562 Open in new window
Abstract
SMOS brightness temperature images show some residual artifacts as a function of spatial directions. Due to having different antenna patterns in each element, even if knowing them perfectly, a minimum reconstruction error inherent to the inversion algorithm exists. On top of that, antenna patterns measurement errors and other effects such as cross-polarization terms, increase the spatial biases. Accurate characterization of these sources of error allows improving the quality of the SMOS images. ...
Citation
Corbella, I. [et al.]. Spatial biases analysis and mitigation methods in SMOS images. A: IEEE International Geoscience and Remote Sensing Symposium. "2013 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 21–26, 2013: Melbourne, Australia". Melboune: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 3415-3418.
Keywords
Geophysical image processing, Geophysical techniques, Image reconstruction, Remote sensing
Group of research
RF&MW - Laboratory of RF & microwave systems, devices and materials
RSLAB - Remote Sensing Lab

Participants