Inference of unexploded ordnance (UXO) by probabilistic inversion of magnetic data
نویسندگان
چکیده
منابع مشابه
Genetic Programming for Discrimination of Buried Unexploded Ordnance (UXO)
According to the Department of Defense, over 10 million acres of land in the US need to be cleared of buried unexploded ordnance (UXO). Worldwide, UXO injures thousands each year. Cleanup costs are prohibitively expensive due to the difficulties in discriminating buried UXO from other inert non-UXO objects. Government agencies are actively searching for improved sensor methodologies to detect a...
متن کاملMeasurements and Modeling of Acoustic Scattering from Unexploded Ordnance (UXO) in Shallow Water
Introduction: The gradual development of coastal areas throughout the world in proximity to military training ranges and areas of past conflict has created a need to locate underwater unexploded ordnance (UXO). These ordnance, which may have veered off course and failed to detonate when they were initially released, may still pose a risk of explosion if they are subject to handling. This compli...
متن کاملCharacterization and quantification of magnetic remanence in unexploded ordnance
Under the Range Rule (1997), the Department of Defense defines unexploded ordnance (UXO) as a piece of ordnance that has been deployed, but has not exploded. This study investigated a subset of UXO including artillery shells and mortars (projectiles), but excluding landmines. UXO contaminates approximately 15 million acres of land in the United States alone. The geophysical tools most frequentl...
متن کاملCombining Logistic Regression with Kriging for Mapping the Risk of Occurrence of Unexploded Ordnance (UXO)
1. Abstract This paper presents a methodology that combines logistic regression with kriging for incorporating exhaustive secondary information into the mapping of the risk of occurrence of unexploded ordnance (UXO). Logistic regression, which is appropriate for binary data (indicators) analysis, is used to derive the trend component in simple kriging with varying local means (SKlm). The techni...
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ژورنال
عنوان ژورنال: Geophysical Journal International
سال: 2019
ISSN: 0956-540X,1365-246X
DOI: 10.1093/gji/ggz421