TY - GEN
T1 - Geospatial image mining for nuclear proliferation detection
T2 - 2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
AU - Vatsavai, Ranga Raju
AU - Bhaduri, Budhendra
AU - Cheriyadat, Anil
AU - Arrowood, Lloyd
AU - Bright, Eddie
AU - Gleason, Shaun
AU - Diegert, Carl
AU - Katsaggelos, Aggelos
AU - Pappas, Thrasos
AU - Porter, Reid
AU - Bollinger, Jim
AU - Chen, Barry
AU - Hohimer, Ryan
PY - 2010/12/1
Y1 - 2010/12/1
N2 - 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.
AB - 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.
KW - Geospatial ontology
KW - Low-level features
KW - Nuclear proliferation
KW - Semantic classification
UR - http://www.scopus.com/inward/record.url?scp=78650866045&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650866045&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2010.5649811
DO - 10.1109/IGARSS.2010.5649811
M3 - Conference contribution
AN - SCOPUS:78650866045
SN - 9781424495658
SN - 9781424495665
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 48
EP - 51
BT - 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Y2 - 25 July 2010 through 30 July 2010
ER -