Most unexploded ordnance (UXO) at former military training ranges is buried, due to either the force of the initial impact or to later soil deposition. Currently, crews charged with cleaning up UXO sites must rely on metal detectors to locate UXO. They traverse the ground equipped with either hand-held or cart-mounted detectors, with survey times limited by the walking speed of the operator, terrain, vegetation, and number of metallic anomalies present. As is well known in the UXO community, these metal detectors generally are unable to discriminate between buried UXO and other sources of metal, such as ferrous rocks, shrapnel, hubcaps, coins, soup cans, and other sources of cultural debris. Typically, anywhere from 10 to 1,000 metallic items are excavated for every UXO found, depending on the nature of the site.
The main purpose of the analyses was to determine whether statistical properties of anomaly spatial patterns can be used to delineate areas with and without UXO. A second goal was to estimate the expected number of UXO at given locations within former military sites based on the results of airborne surveys.
This study differs from previous research on metallic anomaly data at former military training ranges in that it analyzes the spatial pattern of the discrete locations of the anomalies, rather than the average number of anomalies per unit area.
This project conducted statistical analyses of the spatial pattern of metallic anomalies, buried and on the ground surface, detected during airborne surveys above two former Air Force bombing ranges: the former Pueblo Precision Bombing Range Number 2 in Otero County, Colorado, and the Victorville Precision Bombing Range in San Bernardino County, California.
The results indicate that differences in spatial pattern may be a distinguishing feature between areas that were used for target practice and those that are unlikely to contain UXO, even when a large number of ferrous rocks and other inert metallic anomalies are present. The researchers found that at both former bombing ranges, the anomaly patterns in sample areas that are distant from all known bombing targets are consistent with a complete spatial randomness (CSR) pattern, while those near the target areas fit a radially symmetric, bivariate Gaussian pattern. Furthermore, anomaly location patterns generated by surveys with airborne metal detectors have the same statistical properties as the patterns generated by surveys with on-ground detectors, even though the airborne systems detect only a subset of the anomalies found by the ground-based detectors. Thus, pattern information revealed by airborne surveys with metal detectors can be useful in identifying areas where careful searches for UXO are needed.
As the Department of Defense moves forward with development of airborne systems for UXO detection, the kinds of spatial point-pattern analysis demonstrated in this project can help document the geographic boundaries of areas likely to contain UXO. Where the spatial pattern of anomalies is not consistent with that expected at UXO sites, statistical analysis of the pattern information can provide evidence that the area is not a high priority for exhaustive ground-based searches for UXO. Where the pattern analysis suggests that UXO is present, pattern information can be used to predict the boundaries of former target areas and thus reduce the amount of acreage that must be searched.