An expert lidar data analysis toolset for explosive debris plumes

Martin Pieck; John R. Stephens; Steven B. Brumby; Paul A. Pope; Ryan A. Channell; Eva R. Birnbaum

doi:10.1117/12.692452

3 October 2006 An expert lidar data analysis toolset for explosive debris plumes

Martin Pieck, John R. Stephens, Steven B. Brumby, Paul A. Pope, Ryan A. Channell, Eva R. Birnbaum

Proceedings Volume 6367, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II; 63670E (2006) https://doi.org/10.1117/12.692452
Event: SPIE Remote Sensing, 2006, Stockholm, Sweden

Abstract

Open-air explosive activities are carried out by a variety of institutions, including government agencies and private organizations. These activities result in debris plumes that contain elements of the explosive package as well as substantial amounts of entrained environmental materials. While Lidar monitoring technology for these situations has been around for years we developed a unique, interactive, post-experiment Lidar Data Analysis Toolset (LIDATO) that allows the expert user to determine the location, backscatter intensity distribution, volume, and boundaries for general debris plumes at any given time. This is true with the exception of the early development and transport of the plume where the plume is typically opaque to the Lidar and only the plume edge facing the Lidar system can be mapped. For this reason we incorporated video coverage using multiple cameras. While the analysis of the video is handled separately we used the resulting plume position data and combined them with the LIDATO results. The data-fusion product refines the separately gained results and increases the data set accuracy in all aspects for the early stages of the explosion.

Citation Download Citation

Martin Pieck, John R. Stephens, Steven B. Brumby, Paul A. Pope, Ryan A. Channell, and Eva R. Birnbaum "An expert lidar data analysis toolset for explosive debris plumes", Proc. SPIE 6367, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II, 63670E (3 October 2006); https://doi.org/10.1117/12.692452

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