NDLI: Flood monitoring and change detection based on unsupervised image segmentation and fusion in multitemporal SAR imagery

Content Provider	IEEE Xplore Digital Library
Author	Avendano, J. Mora, S.F. Vera, J.E. Torres, J.A. Prieto, F.A.
Copyright Year	2015
Description	Author affiliation: Grupo de Autom. (GAUNAL), Univ. Nac. de Colombia, Bogota, Colombia (Prieto, F.A.) \|\| Grupo de Investig. y Desarrollo Tecnol. Aplicado, Univ. Escuela Colombiana de Carreras Ind. Bogota, Bogota, Colombia (Avendano, J.; Mora, S.F.; Vera, J.E.; Torres, J.A.)
Abstract	This paper presents an unsupervised method for change detection and analysis of the behavior of floods using multitemporal SAR (Synthetic Aperture Radar) images. First, images were filtered using the Enhanced Frost Filter in order to reduce the effect of speckle noise. Fuzzy Clustering Means (FCM) and k-means algorithms were used for unsupervised segmentation, and both results were fused using PCA. Subsequently, a Boolean image was created from the change information using a thresholding algorithm. Finally, the area of changes in the scene was calculated with spatial resolution information from the images. For the experiment phase, synthetic images were first created with varying levels of speckle noise, making it possible to evaluate the performance of the proposed method. The results showed an overall accuracy of approximately 99% and a kappa index of 0.76 for images whose Equivalent Number of Looks (ENL) equals 0.7. This shows that the proposed method is efficient in detecting changes in SAR images with an ENL greater than or equal to 0.7. Finally, two SAR images were tested, one before and one after a flood that covered an area of the Magdalena River in Colombia called Plato-Magdalena. Our method found that the river flooded approximately 131.51 hectares of terrain in the case of the studied images.
Starting Page	1
Ending Page	6
File Size	2587423
Page Count	6
File Format	PDF
e-ISBN	9781467378390
DOI	10.1109/ICEEE.2015.7357982
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-28
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Histograms Change detection algorithms Fuses SAR Change Detection Speckle Multitemporal Data Fusion Flood Analysis Synthetic aperture radar Unsupervised Segmentation Principal component analysis
Content Type	Text
Resource Type	Article

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