A key product of the global undisturbed/disturbed earth (GUIDE) program is the development of a soils database of broadband, hyperspectral, and polarized data. As a part of the GUIDE program, the U.S. Army Engineer Research and Development Center (ERDC) conducted a testing series involving a large variety of instrumentation at several sites at the Yuma Test Center (YTC) in fiscal year 2015 under the auspices of the Joint Improvised Explosive Device Defeat Organization (now the Joint Improvised-Threat Defeat Agency), generating approximately 17 terabytes of data. Most of this data, available through the ERDC, comprises hyperspectral polarimetric scientific data in the visible, near-infrared, shortwave infrared, and longwave infrared bands. As part of this testing series the performance of six handheld devices was characterized. We discuss the process of this data collection at YTC focusing on the polarimetric data, including the two handheld devices that relied on polarization for detection. Although some other polarization states discriminate soils better in some other wavelengths, for certain visible and near-infrared bands the Stokes S2 parameter provided the best discrimination.
A significant amount of background airborne data was collected as part of May 2005 tests for airborne minefield detection at an arid site. The locations of false alarms which occurred consistently during different runs, were identified and geo-referenced by MultiSensor Science LLC. Ground truth information, which included pictures, type qualifiers and some hyperspectral data for these identified false alarm locations, was surveyed by ERDC-WES. This collection of background data, and subsequent survey of the false alarm locations, is unique in that it is likely the first such airborne data collection with ground truthed and documented false alarm locations. A library of signatures for different sources of these false alarms was extracted in the form of image chips and organized into a self-contained database by Missouri SandT. The library contains target chips from airborne mid wave infrared (MWIR) and multispectral imaging (MSI) sensors, representing data for different days, different times of day and different altitudes. Target chips for different surface mines were also added to the database. This database of the target signatures is expected to facilitate evaluation of spectral and shape characteristics of the false alarms, to achieve better false alarm mitigation and improve mine and minefield detection for airborne applications. The aim of this paper is to review and summarize the data collection procedure used, present the currently available database of target chips and make some recommendations regarding future data collections.
A high-resolution, ground-based 3D laser scanner was recently evaluated for terrestrial site characterization of variable-surface minefield sites and generation of surface and terrain models. The instrument used to conduct this research was a Leica HDS3000 3D laser scanner. Two study sites located in the mid-western United States were used for this analysis. A very dense vegetation site (Grass Site) and a bare soil site (Dirt Site) with intermittent rocks and sparse vegetation were selected for data collection to simulate both obscured and semi-obscured minefield sites. High-density scans (0.2 cm to 2.0 cm) were utilized for Cyra target acquisition and were commensurate with size and distance to target from scanner location. Medium-density scans (2.0 cm to 5.0 cm) were chosen for point cloud generation of each site with approximately 10 percent overlap between field scans. To provide equivalent, unobstructed viewing perspectives from all scan locations at each site, the scanner was positioned on a trailer-mounted, chain-driven lift and raised to a scan height of 7.62 m above the ground. Final registration to UTM projected coordinate system of the multiple scan locations for the Dirt Site and Grass Site produced mean absolute errors of 0.014 m and 0.017 m, respectively. The laser scanner adequately characterized surface roughness and vegetation height to produce contour and terrain models for the respective site locations. The detailed scans of the sites along with the inherent, natural vegetation characteristics present at each site provide real-time discrimination of site components under contrasting land surface conditions.