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Computational Ecology and Software, 2012, 2(4): 220-225
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Article

Synthetic Aperture Radar (SAR) images features clustering using Fuzzy c-means (FCM) clustering algorithm

Rashid Hussain
Faculty of Engineering Science and Technology, Hamdard University, Karachi 74600, Pakistan

Received 25 June 2012;Accepted 29 July 2012;Published online 1 December 2012
IAEES

Abstract
Remote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses adverse affects on retrieved results. Synthetic Aperture Radar (SAR) technology is used to mitigate such adverse effects. Recently SAR technology re-emerges because of the decrease in the cost of electronic components and tremendous advancement in computing power. This paper provides an application of Fuzzy c-means (FCM) clustering algorithm to SAR Images. The objective of this study is to segment various region of interest in remote sensing images for ecological monitoring.

Keywords Synthetic Aperture Radar (SAR);Fuzzy c-means (FCM) clustering algorithm;satellite radar image;remote sensing;ecological monitoring.

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