ADVANCED INFORMATION MANAGEMENT TO FACILITATE GEOPHYSICAL ANOMALY CLASSIFICATION AT MUNITIONS SITES

Abstract

This paper presents an advanced information management system deployed to facilitate and improve geophysical data collection and analysis for production surveys where munitions anomaly classification is required. This work demonstrates that comprehensive and rigorous information technologies are essential to effectively integrate geophysical classification methods at Military Munitions Response (MMR) sites. Recently, advanced electromagnetic (EM) sensors utilizing multi-axis, time-domain transmitter and receiver arrays have proven effective for classifying buried targets as either munitions and explosives of concern (MEC), including unexploded ordnance (UXO), or non-threatening debris or scrap. Coupled with sophisticated analysis methods, also proven effective, this methodology has potential to significantly reduce UXO remediation costs. One major barrier to wide use of classification technologies is the challenge related to management of diverse and voluminous information developed during the surveys. Demonstrations of HDR’s new Classification Information Management System (CIMS) were conducted at recent on-going MMR sites. Test grids were selected to conduct anomaly classification utilizing CIMS as part of ongoing projects. HDR deployed its MetalMapper survey to collect data and perform in-field quality control (QC), and CIMS was utilized to streamline collection, classification, data management and reporting. Evaluated elements of the geophysical classification included; (1) project planning and site suitability for sensor platforms; (2) instrument verification to validate system performance; (3) HDR3D MetalMapper data collection and dissemination; (4) in-field QC of collected data; (5) production of daily QC reports; (6) tracking anomalies requiring re-interrogation; (7) off-site anomaly classification; (8) QC target selection; (9) intrusive groundtruth collection; and (10) data and information presentation for review and reporting. Data management during classification surveys is critical, and the CIMS architecture proved effective for comprehensive data management. The CIMS manages all survey information from original digital geophysical mapping (DGM) surveys through to intrusive actions using a comprehensive database architecture and associated geographical information system (GIS) access and reporting tools. The CIMS also establishes a data manifesting and communication framework allowing access to essential classification information during dynamic and on-going projects.