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http://dx.doi.org/10.22640/lxsiri.2017.47.2.79

Detection of Settlement Areas from Object-Oriented Classification using Speckle Divergence of High-Resolution SAR Image  

Song, Yeong Sun (Department of Aerial Geoinformatics, Inha technical College)
Publication Information
Journal of Cadastre & Land InformatiX / v.47, no.2, 2017 , pp. 79-90 More about this Journal
Abstract
Urban environment represent one of the most dynamic regions on earth. As in other countries, forests, green areas, agricultural lands are rapidly changing into residential or industrial areas in South Korea. Monitoring such rapid changes in land use requires rapid data acquisition, and satellite imagery can be an effective method to this demand. In general, SAR(Synthetic Aperture Radar) satellites acquire images with an active system, so the brightness of the image is determined by the surface roughness. Therefore, the water areas appears dark due to low reflection intensity, In the residential area where the artificial structures are distributed, the brightness value is higher than other areas due to the strong reflection intensity. If we use these characteristics of SAR images, settlement areas can be extracted efficiently. In this study, extraction of settlement areas was performed using TerraSAR-X of German high-resolution X-band SAR satellite and KOMPSAT-5 of South Korea, and object-oriented image classification method using the image segmentation technique is applied for extraction. In addition, to improve the accuracy of image segmentation, the speckle divergence was first calculated to adjust the reflection intensity of settlement areas. In order to evaluate the accuracy of the two satellite images, settlement areas are classified by applying a pixel-based K-means image classification method. As a result, in the case of TerraSAR-X, the accuracy of the object-oriented image classification technique was 88.5%, that of the pixel-based image classification was 75.9%, and that of KOMPSAT-5 was 87.3% and 74.4%, respectively.
Keywords
Object-oriented Classification; Settlement Areas; Speckle Divergence; KOMPSAT-5; TerraSAR-X;
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