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  • Enhanced Route Reconnaissance—Generation 1

    Abstract: The movement of soldiers and materiel across battlespace is critical to a successful military operation. Knowledge of the road network condition ensures safe and successful vehicle maneuver. This research focused on remote assessment of poor-quality paved road networks for vehicle maneuver using data products derived from three-dimensional point clouds. Point clouds were generated from lidar sensors deployed from ground and airborne platforms to enable engineering analysis of the pavement surface. A series of algorithms developed to extract roughness, grade, radius of curvature, and width along the road network ensured storage of information for graphical display. A vehicle speed lookup table was calculated by conducting computer simulations using the NATO Reference Mobility Model over a range of road parameters. The lookup table enabled determination of the maximum allowable speed for a given vehicle type associated with the extracted road parameters. A graphical interface, developed for displaying the percentage speed reduction as either red, amber, or green squares along the road network, provided visual assessments of road condition. This report summarizes developing a software suite to calculate and visualize speed reduction over a road network as a function of route geometry, condition, and vehicle type. The interface developed can aid in critical logistical decisions that influence the success of military maneuver operations.
  • Continued Investigation of Thermal and Lidar Surveys of Building Infrastructure

    ABSTRACT: We conducted a combined lidar and thermal infrared survey from both ground-based and Unmanned Aerial System (UAS) platforms at McMurdo Station, Antarctica, in February 2020 to assess the building thermal envelope and infrastructure of the Crary Lab and the wet utility corridor (utilidor). These high-accuracy, coregistered data produced a 3-D model with assigned temperature values for measured surfaces, useful in identifying thermal anomalies and areas for potential improvements and for assessing building and utilidor infrastructure by locating and quantifying areas settlement and structural anomalies. The ground-based survey of the Crary Lab was similar to previous work performed by the team at both Palmer (2015) and South Pole (2017) Stations. The UAS platform focused on approximately 10,500 linear-feet of utilidor throughout McMurdo Station. The datasets of the two survey areas overlapped, allowing us to combine them into a single, georeferenced 3-D model of McMurdo Station. Coincident exterior temperature and atmospheric measurements and Global Navigation Satellite System real-time kinematic surveys provided further insights. Finally, we assessed the thermal envelope of the Crary Lab and the structural features of the utilidor. The resulting dataset is available for analysis and quantification.
  • PUBLICATION NOTICE: Creation, Transformation, and Orientation Adjustment of a Building Façade Model for Feature Segmentation: Transforming 3D Building Point Cloud Models into 2D Georeferenced Feature Overlays

     The US Army Engineer Research and Development Center has published the report/note described and linked below. Approved for public release; distribution is unlimited.Report Number: ERDC/GRL TR-19-2Link: http://dx.doi.org/10.21079/11681/35115Title: Creation, Transformation, and Orientation Adjustment of a Building Façade Model for Feature