It is estimated that there are at least 100 million military munitions and explosives of concern (MEC) devices in the world of various size, shape, and composition. Millions of these are surface plastic land mines with low-pressure detonation regimes, such as the mass-produced Soviet PFM-1. These aerially deployed land mines are concentrated primarily in postconflict developing countries such as Afghanistan and represent a continued humanitarian threat, while also thwarting economic and social development in impacted regions. Identification of this particular type of MEC category poses a significant geophysical challenge, as these mines contain almost no metal (nonferrous aluminum). As a result, standard MEC detection and remediation methodologies based on geophysical principles of magnetometry and electromagnetic induction prove largely ineffective and possibly dangerous. Low-cost unmanned aerial vehicles can rapidly collect large remotely sensed data sets with no risk to MEC technicians. We present results of an experiment focused on remotely assessing thermal signatures of plastic land mines relative to background geology to show that this type of analysis permits rapid detection of randomly dispersed plastic MECs with a high degree of accuracy and low associated costs.

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