DocumentCode :
1648386
Title :
Earthen levee monitoring with Synthetic Aperture Radar
Author :
Aanstoos, James V. ; Hasan, Khaled ; O´Hara, Charles G. ; Prasad, Saurabh ; Dabbiru, Lalitha ; Mahrooghy, Majid ; Gokaraju, Balakrishna ; Nobrega, Rodrigo
Author_Institution :
Geosystems Res. Inst., Mississippi State Univ., Starkville, MS, USA
fYear :
2011
Firstpage :
1
Lastpage :
6
Abstract :
The latest results are presented from an ongoing study of the use of multi-polarized Synthetic Aperture Radar as an aid in screening earthen levees for weak points. Both L-band airborne and X-band spaceborne radars are studied, using the NASA UAVSAR and the German TerraSAR-X platforms. Feature detection and classification algorithms tested for this application include both radiometric and textural methods. Radiometric features include both the simple backscatter magnitudes of the HH, VV, and HV channels as well as decompositions such as Entropy, Anisotropy, and Alpha angle. Textural methods include grey-level co-occurrence matrix and wavelet features. Classifiers tested include Maximum Likelihood and Artificial Neural Networks. The study area includes 240 km of levees along the lower Mississippi River. Results to date are encouraging but still very preliminary and in need of further validation and testing.
Keywords :
airborne radar; backscatter; feature extraction; floods; geotechnical engineering; image classification; image texture; maximum likelihood estimation; neural nets; radar imaging; radar polarimetry; radiometry; spaceborne radar; structural engineering computing; synthetic aperture radar; wavelet transforms; German TerraSAR-X platform; HH channel; HV channel; L-band airborne spaceborne radar; NASA UAVSAR platform; VV channel; X-band spaceborne radar; alpha angle; anisotropy; artificial neural network; backscatter magnitude; classification algorithm; earthen levee monitoring; earthen levee weak point screening; entropy; feature detection; flooding; grey-level cooccurrence matrix; lower Mississippi River; maximum likelihood classifier; multipolarized synthetic aperture radar; radiometric features; radiometric method; textural method; wavelet feature; Floods; Levee; Remote sensing; Rivers; Soil; Spaceborne radar; earthen levees; levee screening; synthetic aperture radar;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Imagery Pattern Recognition Workshop (AIPR), 2011 IEEE
Conference_Location :
Washington, DC
ISSN :
1550-5219
Print_ISBN :
978-1-4673-0215-9
Type :
conf
DOI :
10.1109/AIPR.2011.6176370
Filename :
6176370
Link To Document :
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