NDLI: An innovative approach to detect anomalies on earthen levees using unsupervised classification of polarimetric SAR imagery

Content Provider	IEEE Xplore Digital Library
Author	Marapareddy, R. Aanstoos, J.V. Younan, N.H.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Mississippi State Univ., Starkville, MS, USA (Younan, N.H.) \|\| Geosystems Res. Inst., Mississippi State Univ., Starkville, MS, USA (Marapareddy, R.; Aanstoos, J.V.)
Abstract	The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We used L-band synthetic aperture radar (SAR) to screen levees for anomalies. Using Entropy (H), Anisotropy (A), and alpha (α) parameters, we implemented several unsupervised classification algorithms for the identification of anomalies on the levee. The classification techniques applied are: H/α, H/A, A/α, wishart H/α, and wishart H/A/α classification. The effectiveness of the algorithms is demonstrated using quad-polarimetric L-band SAR imagery from the NASA Jet Propulsion Laboratory's (JPL's) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the southern USA, where earthen flood control levees are maintained by the US Army Corps of Engineers.
Starting Page	381
Ending Page	384
File Size	767370
Page Count	4
File Format	PDF
e-ISBN	9781479979295
DOI	10.1109/IGARSS.2015.7325780
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Scattering Synthetic aperture radar Levee Entropy Eigenvalues and eigenfunctions Anisotropic magnetoresistance Remote sensing Polarimetry Synthetic Aperture Radar Earthen Levees UAVSAR Classification
Content Type	Text
Resource Type	Article

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Classification of polarimetric SAR imagery using unsupervised H/α and extended H/α schemes to detect anomalies on earthen levees

Advanced Unsupervised Classification Methods to Detect Anomalies on Earthen Levees Using Polarimetric SAR Imagery

Detection of slump slides on earthen levees using polarimetric SAR imagery

AN INNOVATIVE APPROACH TO DETECT ANOMALIES ON EARTHEN LEVEES USING UNSUPERVISED CLASSIFICATION OF POLARIMETRIC SAR IMAGERY

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