Objective:
Millions of acres of Department of Defense (DoD) or former DoD lands are potentially contaminated with military munitions (MM) or their components. The cost of investigating and remediating such sites is estimated in the tens of billions of dollars. Light Detection and Ranging (LiDAR), especially when accompanied by concurrent digital imagery, has been shown in previous demonstrations to be an effective tool for wide area assessment (WAA). The objectives of this project are to (1) systematically investigate the effect of the type and density of vegetation cover on the effectiveness of airborne LiDAR in MM management, (2) evaluate the ability of current software packages to automatically discriminate ground features typical of munitions sites, and (3) summarize lessons learned in this project and the prior WAA Pilot Program demonstrations into a guidance document. Technology Description: LiDAR is a well-established technology for modeling ground surfaces. The LiDAR system consists of a laser, a rotating mirror that directs the laser pulses to the ground, and a sensor for receiving the return signal, along with a global positioning system (GPS) and inertial measurement unit (IMU) to precisely locate the sensor. These components allow for the accurate determination of the horizontal and vertical position of the point of reflection of the laser signal. LiDAR has been shown to be successful on vegetated munitions sites but operational and analytical parameters have not been developed to date. Multiple software packages are available for extracting features from a three-dimensional modeled surface, but they have not been systematically evaluated for their ability to successfully extract features representative of munitions use. Expected Benefits: LiDAR is becoming an important tool in the assessment of munitions sites. As the technology becomes more widespread, a wider variety of site conditions will be encountered. This project will demonstrate the capabilities and limitations of LiDAR technology on the size, shape, and location of features that can be detected with varying vegetation conditions. The project also will evaluate the ability of current off-the-shelf software packages to automatically discriminate ground features typical of munitions sites. A guidance document will be assembled that includes lessons learned and data on the acquisition, processing, and analysis of LiDAR data. (Anticipated Project Completion - 2009) Principal Investigator: Mr. Robert Selfridge U.S. Army Corps of Engineers ATTN: CEHNC-ED-CS-G/Selfridge 4820 University Square Huntsville, AL 35816-1822 Telephone: (256) 895-1887 Fax: (256) 895-1602 E-mail: Bob.J.Selfridge@hnd01.usace.army.mil | 
