Next Article in Journal
Image Reconstruction and Evaluation: Applications on Micro-Surfaces and Lenna Image Representation
Previous Article in Journal
Automatic Gleason Grading of Prostate Cancer Using Shearlet Transform and Multiple Kernel Learning
Article Menu

Export Article

Open AccessConcept Paper
J. Imaging 2016, 2(3), 26; doi:10.3390/jimaging2030026

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

1
School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, 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
*
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 10 August 2016 / Revised: 5 September 2016 / Accepted: 7 September 2016 / Published: 12 September 2016
View Full-Text   |   Download PDF [7474 KB, uploaded 12 September 2016]   |  

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 that 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. View Full-Text
Keywords: synthetic aperture radar; UAVSAR; levee; classification; radar polarimetry; classification synthetic aperture radar; UAVSAR; levee; classification; radar polarimetry; classification
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Imaging EISSN 2313-433X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top