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Proceedings Paper

Feature recognition in the context of automated object-oriented analysis of remote sensing data monitoring the Iranian nuclear sites
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Paper Abstract

Against the background of nuclear safeguards applications using commercially available satellite imagery, procedures for wide-area monitoring of the Iranian nuclear fuel cycle are investigated. Specifically, object-oriented classification combined with statistical change detection is applied to high-resolution imagery. In this context, a feature recognition and analysis tool, called SEaTH, has been developed for automatic selection of optimal object class features for subsequent classification. The application of SEaTH is presented in a case study of the NFRPC Esfahan, Iran. The transferability of classification models is discussed regarding the necessity for automation of extensive monitoring tasks.

Paper Details

Date Published: 21 October 2005
PDF: 9 pages
Proc. SPIE 5988, Electro-Optical Remote Sensing, 598805 (21 October 2005); doi: 10.1117/12.629581
Show Author Affiliations
S. Nussbaum, Research Ctr. Juelich (Germany)
I. Niemeyer, Freiberg Univ. of Mining and Technology (Germany)
M.J. Canty, Research Ctr. Juelich (Germany)

Published in SPIE Proceedings Vol. 5988:
Electro-Optical Remote Sensing
Gary W. Kamerman; David V. Willetts, Editor(s)

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