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

S. Nussbaum; I. Niemeyer; M.J. Canty

doi:10.1117/12.629581

21 October 2005 Feature recognition in the context of automated object-oriented analysis of remote sensing data monitoring the Iranian nuclear sites

S. Nussbaum, I. Niemeyer, M.J. Canty

Author Affiliations +

Proceedings Volume 5988, Electro-Optical Remote Sensing; 598805 (2005) https://doi.org/10.1117/12.629581
Event: European Symposium on Optics and Photonics for Defence and Security, 2005, Bruges, Belgium

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.

Citation Download Citation

S. Nussbaum, I. Niemeyer, and M.J. Canty "Feature recognition in the context of automated object-oriented analysis of remote sensing data monitoring the Iranian nuclear sites", Proc. SPIE 5988, Electro-Optical Remote Sensing, 598805 (21 October 2005); https://doi.org/10.1117/12.629581

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