{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:26:00Z","timestamp":1772252760054,"version":"3.50.1"},"reference-count":20,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2016,9,12]],"date-time":"2016-09-12T00:00:00Z","timestamp":1473638400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OISE-1243539"],"award-info":[{"award-number":["OISE-1243539"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NASA Applied Sciences Division","award":["NNX09AV25G"],"award-info":[{"award-number":["NNX09AV25G"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>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\u2019s (JPL\u2019s) 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.<\/jats:p>","DOI":"10.3390\/jimaging2030026","type":"journal-article","created":{"date-parts":[[2016,9,12]],"date-time":"2016-09-12T10:24:41Z","timestamp":1473675881000},"page":"26","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Supervised Classification Method for Levee Slide Detection Using Complex Synthetic Aperture Radar Imagery"],"prefix":"10.3390","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7329-7218","authenticated-orcid":false,"given":"Ramakalavathi","family":"Marapareddy","sequence":"first","affiliation":[{"name":"School of Computing, University of Southern Mississippi, Hattiesburg, MS 39406, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3594-4189","authenticated-orcid":false,"given":"James","family":"Aanstoos","sequence":"additional","affiliation":[{"name":"Geosystems Research Institute, Mississippi State University, Mississippi State, MS 39759, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Younan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Aanstoos, J.V., Hasan, K., O\u2019Hara, C.G., Prasad, S., Dabbiru, L., Mahrooghy, M., Nobrega, R., Lee, M.L., and Shrestha, B. (2010, January 13\u201315). Use of remote sensing to screen earthen levees. Proceedings of the 39th Applied Imagery Pattern Recognition Workshop (AIPR), Washington, DC, USA.","DOI":"10.1109\/AIPR.2010.5759704"},{"key":"ref_2","unstructured":"Dunbar, J. (2009). Lower Mississippi Valley Engineering Geology and Geomorphology Mapping, US Army Corps of Engineers. Program for Levees."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"235","DOI":"10.2113\/gseegeosci.12.3.235","article-title":"Detection of levee slides using commercially available remotely sensed data","volume":"12","author":"Hossain","year":"2006","journal-title":"Environ. Eng. Geosci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.1016\/j.eswa.2007.08.088","article-title":"Particle swarm optimization for parameter determination and feature selection of support vector machines","volume":"35","author":"Lin","year":"2008","journal-title":"Expert Syst. Appl."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ince, T., Kiranyaz, S., and Gabbouj, M. (2010, January 23\u201326). Classification of Polarimetric SAR Images Using Evolutionary RBF Networks. Proceedings of the 20th International Conference on Pattern Recognition, Istanbul, Turkey.","DOI":"10.1109\/ICPR.2010.1051"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1109\/TGRS.2010.2056375","article-title":"Coherence, polarization, and statistical independence in cloude-pottier\u2019s radar polarimetry","volume":"49","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","unstructured":"Han, Y., and Shao, Y. (2010, January 10\u201312). Full Polarimetric SAR classification based on yamaguchi decomposition model and scattering parameters. Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing (PIC), Shanghai, China."},{"key":"ref_8","unstructured":"Jong-Sen, L., and Pottier, E. (2009). Polarimetric Radar Imaging: From Basics to Applications, CRC Press, Taylor & Francis Group. [1st ed.]."},{"key":"ref_9","first-page":"171","article-title":"Identification of terrain cover using the optimal polarimetric classifier","volume":"2","author":"Kong","year":"1988","journal-title":"J. Electromagnet. Waves Applicat."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2299","DOI":"10.1080\/01431169408954244","article-title":"Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution","volume":"15","author":"Lee","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","first-page":"2249","article-title":"Unsupervised classification using polarimetric decomposition and the complex Whishart classifier","volume":"35","author":"Lee","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/36.551935","article-title":"An entropy based classification scheme for land applications of polarimetric SAR","volume":"35","author":"Cloude","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","unstructured":"Aanstoos, J.V., Dabbiru, L., Gokaraju, B., Hasan, K., Lee, M.A., Mahrooghy, M., Nobrega, R.A.A., O\u2019Hara, C.G., Prasad, S., and Shanker, A. (2012). Levee Assessment via Remote Sensing SERRI Projects, Southeast Region Research Initiative. SERRI Report 80023\u201302."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Aanstoos, J.V., Hasan, K., O\u2019Hara, C., Dabbiru, L., Mahrooghy, M., Nobrega, R.A.A., and Lee, M.M. (2012, January 9\u201311). Detection of Slump Slides on Earthen Levees Using Polarimetric SAR Imagery. Proceedings of the 2012 IEEE Applied Imagery Pattern Recognition Workshop, Washington, DC, USA.","DOI":"10.1109\/AIPR.2012.6528207"},{"key":"ref_15","unstructured":"Exelis Visual Information Solutions User Guides and Tutorials. Available online: http:\/\/www.exelisvis.com\/Learn\/Resources\/Tutorials.aspx."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (1999). Remote Sensing Digital Image Analysis, Springer-Verlag.","DOI":"10.1007\/978-3-662-03978-6"},{"key":"ref_17","first-page":"167","article-title":"Comparison of four classification methods to extract land use and land cover from raw satellite images for some remote arid areas, Kingdom of Saudi Arabia","volume":"20","author":"Hames","year":"2009","journal-title":"Earth Sci."},{"key":"ref_18","unstructured":"Canty, M.J. (2014). Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI\/IDL and Python, CRC Press, Taylor & Francis Group. [3rd ed.]."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3571","DOI":"10.3390\/rs4113571","article-title":"Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach","volume":"4","author":"Pajares","year":"2012","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1016\/j.isprsjprs.2011.09.007","article-title":"Improving the Wishart synthetic aperture radar image classifications through deterministic simulated annealing","volume":"66","author":"Pajares","year":"2011","journal-title":"ISPRS J. Photogram. Remote Sens."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/2\/3\/26\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:30:47Z","timestamp":1760211047000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/2\/3\/26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,12]]},"references-count":20,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2016,9]]}},"alternative-id":["jimaging2030026"],"URL":"https:\/\/doi.org\/10.3390\/jimaging2030026","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201608.0109.v1","asserted-by":"object"}]},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,9,12]]}}}