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

Ranga Raju Vatsavai, Budhendra Bhaduri*, Anil Cheriyadat, Lloyd Arrowood, Eddie Bright, Shaun Gleason, Carl Diegert, Aggelos Katsaggelos, Thrasos Pappas, Reid Porter, Jim Bollinger, Barry Chen, Ryan Hohimer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Pages48-51
Number of pages4
DOIs
StatePublished - Dec 1 2010
Event2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 - Honolulu, HI, United States
Duration: Jul 25 2010Jul 30 2010

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
CountryUnited States
CityHonolulu, HI
Period7/25/107/30/10

Keywords

  • Geospatial ontology
  • Low-level features
  • Nuclear proliferation
  • Semantic classification

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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    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. (2010). Geospatial image mining for nuclear proliferation detection: Challenges and new opportunities. In 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 (pp. 48-51). [5649811] (International Geoscience and Remote Sensing Symposium (IGARSS)). https://doi.org/10.1109/IGARSS.2010.5649811