Preprint Concept Paper Version 1 NOT YET PEER-REVIEWED

A Supervised Classification Method for Levee Slide Detection Using Complex Synthetic Aperture Radar Imagery

  1. Center for Advanced Vehicular Systems, Mississippi State University, Mississippi State, MS 39759, USA
  2. Geosystems Research Institute, Mississippi State University, Mississippi State, MS 39759, USA
  3. Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA
Version 1 : Received: 10 August 2016 / Approved: 10 August 2016 / Online: 10 August 2016 (11:37:16 CEST)

A peer-reviewed article of this Preprint also exists.

Marapareddy, R.; Aanstoos, J.V.; Younan, N.H. A Supervised Classification Method for Levee Slide Detection Using Complex Synthetic Aperture Radar Imagery. J. Imaging 2016, 2, 26. Marapareddy, R.; Aanstoos, J.V.; Younan, N.H. A Supervised Classification Method for Levee Slide Detection Using Complex Synthetic Aperture Radar Imagery. J. Imaging 2016, 2, 26.

Journal reference: J. Imaging 2016, 2, 26
DOI: 10.3390/jimaging2030026

Abstract

The dynamics of surface and sub-surface water events can lead to slope instability resulting in anomalies such as slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We have implemented a supervised Mahalanobis distance classification algorithm for the detection of slough slides on levees using complex polarimetric Synthetic Aperture Radar (polSAR) data. The classifier output was followed by a spatial majority filter post-processing step which improved the accuracy. The effectiveness of the algorithm is demonstrated using fully quad-polarimetric L-band Synthetic Aperture Radar (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. Slide detection accuracy of up to 98 percent was achieved, although the number of available slides examples was small.

Subject Areas

Synthetic Aperture Radar; UAVSAR; levee; classification; radar polarimetry; classification

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