Accuracy Analysis Comparison of Supervised Classification Methods for Anomaly Detection on Levees Using SAR Imagery

Ramakalavathi Marapareddy,James Aanstoos,Nicolas Younan

doi:10.3390/electronics6040083

Abstract

This paper analyzes the use of a synthetic aperture radar (SAR) imagery to support levee condition assessment by detecting potential slide areas in an efficient and cost-effective manner. Levees are prone to a failure in the form of internal erosion within the earthen structure and landslides (also called slough or slump slides). If not repaired, slough slides may lead to levee failures. In this paper, we compare the accuracy of the supervised classification methods minimum distance (MD) using Euclidean and Mahalanobis distance, support vector machine (SVM), and maximum likelihood (ML), using SAR technology to detect slough slides on earthen levees. In this work, the effectiveness of the algorithms was 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.

Highlights

Over the entire US, there are approximately 200,000 km of levee structures of varying designs and conditions
We compare the accuracy of the supervised classification methods minimum distance maximum likelihood (ML), using synthetic aperture radar (SAR) technology to detect slough slides on earthen levees
Supervised classification methods based on the minimum distance (MD) using Euclidean and Mahalanobis distance, support vector machine (SVM), and maximum likelihood (ML) classification for earthen levee slide detection using uninhabited aerial vehicle synthetic aperture radar (UAVSAR) imagery were presented

Summary

Introduction

Over the entire US, there are approximately 200,000 km of levee structures of varying designs and conditions. Slough slides are slope failures along a levee, which leave areas of the levee vulnerable to seepage and failure during high water events. These failures can develop over months to years, and are not quickly noticeable unless they depict some sort of visual identification [5,6,7,8]. Polarimetric synthetic aperture radar (PolSAR) data includes a variety of information which relates to the physical properties of the terrain.

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Conclusion