DocumentCode
5065
Title
Sea Ice Concentration Retrieval Using Composite ScanSAR Features in a SAR Data Assimilation Process
Author
Kasapoglu, Necip Gokhan
Author_Institution
Dept. of Phys. & Technol., Univ. of Tromso (UiT)-The Arctic Univ. of Norway, Tromso, Norway
Volume
11
Issue
12
fYear
2014
fDate
Dec. 2014
Firstpage
2085
Lastpage
2089
Abstract
Sensor and target originated variations in the scanning synthetic aperture radar (ScanSAR) images cause increase in variances of observations that affect the performance of data assimilation systems for sea ice analysis. Incidence angle (IA) dependence of radar backscatter along the range direction is one of the largest contributors to this variation. This important aspect can be taken into account both in a forward model and in a feature selection process. In this letter, an incidence-angle-dependent forward model is employed to reduce this variation. Moreover, instead of assimilation of ScanSAR features for the entire swath, individual features for specific IA intervals are used in order to decrease analysis bias and to achieve more consistent results.
Keywords
backscatter; data assimilation; feature extraction; geophysical image processing; oceanographic techniques; radar imaging; sea ice; synthetic aperture radar; SAR data assimilation process; ScanSAR feature assimilation; ScanSAR images; analysis bias; composite ScanSAR features; data assimilation system; feature selection process; incidence-angle-dependent forward model; observation variances; radar backscatter; range direction; scanning synthetic aperture radar images; sea ice analysis; sea ice concentration retrieval; sensor originated variations; target originated variations; Backscatter; Feature extraction; Sea ice; Standards; Synthetic aperture radar; Data assimilation (DA); geophysical signal processing; gray-level co-occurrence matrix (GLCM); sea ice; synthetic aperture radar (SAR); texture;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2014.2319212
Filename
6815673
Link To Document