Detecting and Processing Clandestine Human Remains with Unmanned Aerial Systems and Multispectral Remote Sensing

Forensic search and recovery (SAR) teams typically use labor- and time-consuming methods to search for and document clandestine human graves and surface remains. A novel approach to the problem is to use small, lightweight, unmanned aircraft systems (UAS) equipped with sensors. However, the rapid expansion of UAS and atypical sensors in forensic sciences requires an understanding of the technological and operational capabilities and constraints of the systems and the strategies for processing and interpreting sensor data. The purpose of the project is to provide SAR teams with flexible scientifically-based best practices and protocols for non-invasive search and documentation of outdoor scenes using UAS equipped with advanced spatial and spectral sensors. The goals of this project are to collect, analyze, and process data to develop flexible best practices and an open source graphical user interface (GUI) for visualization of algorithm outputs that can be used by law enforcement and civilian SAR teams and provide a cost- and time-effective method of obtaining accurate, reliable, and high-resolution output. Multiple UAS flights using different UAS and various sensors will be used to explore the most efficient and effective UAS and sensor parameters needed to collect quality data. The project will be conducted in collaboration with researchers at Texas State University, University of Missouri, and a non-profit search and recovery team. Texas State University has a large outdoor decomposition facility and researchers with expertise in forensic anthropology, decomposition, and SAR. The University of Missouri has the faculty expertise and resources to conduct data collection using UAS and to analyze the sensor data. The SAR team will provide significant real scene feedback. Data will be collected for buried and surface remains at varying stages of decomposition at the Forensic Anthropology Research Facility in central Texas. Additional environmental data will be collected in central Missouri. The project will be implemented in three concurrent phases with six primary tasks. Phase 1 involves data collection and analysis. During Phase 2 supervised and unsupervised algorithms will be evaluated to understand performance across forensic and environmental contexts to identify capabilities and gaps and to make modifications as needed. Phase 3 will include development of best practices and dissemination of the experimental results and GUI source code. Upon completion of the project hands-on workshops for SAR teams and UAS pilots will be conducted annually at Texas State University.

Note: This project contains a research and/or development component, as defined in applicable law, and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14).

CA/NCF