Geospatial image mining for nuclear proliferation detection: Challenges and new opportunities

• Published in: 2010 IEEE International Geoscience and Remote Sensing Symposium pp. 48 - 51
• Main Authors: Vatsavai, R R, Bhaduri, B, Cheriyadat, A, Arrowood, L, Bright, E, Gleason, S, Diegert, C, Katsaggelos, A, Pappas, T, Porter, R, Bollinger, J, Chen, B, Hohimer, R
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2010
• Subjects: Data mining; Feature extraction; Geospatial analysis; geospatial ontology; Laboratories; low-level features; Nuclear proliferation; Ontologies; semantic classification; Semantics; USA Councils
• ISBN: 1424495652; 9781424495658
• ISSN: 2153-6996; 2153-7003
• DOI: 10.1109/IGARSS.2010.5649811

With increasing understanding and availability of nuclear technologies, and increasing persuasion of nuclear technologies by several new countries, it is increasingly becoming important to monitor the nuclear proliferation activities. There is a great need for developing technologies to automatically or semi-automatically detect nuclear proliferation activities using remote sensing. Images acquired from earth observation satellites is an important source of information in detecting proliferation activities. High-resolution remote sensing images are highly useful in verifying the correctness, as well as completeness of any nuclear program. DOE national laboratories are interested in detecting nuclear proliferation by developing advanced geospatial image mining algorithms. In this paper we describe the current understanding of geospatial image mining techniques and enumerate key gaps and identify future research needs in the context of nuclear proliferation.