Comparing 3D Lidar Geometry to Vetted Urban Geometry Via CT-Analyst (registered trademark)

Abstract

Airborne lidar measurements of a 3D urban region provide a digital geometry database of 3D buildings and urban terrain that is within a few percent of a vetted geometry database painstakingly assembled from satellite or aircraft stereo imagery. The pacing item in preparing CT-Analyst (registered trademark) contaminant transport software for real time use in a new urban region has been the labor-intensive weeks to months needed to assemble the 1-meter resolution 3D geometry used to precompute the building influences on urban wind fields. The assembly of a good geometry database from lidar now can take only a day or two. NRL CT-Analyst force-protection software predicts the transport and dispersion of airborne contaminants over complicated-geometry landscapes. This fast (milliseconds) laptop system is also accurate because it is based on 18 wind field maps called NomografsTM that are precalculated for a built-up region. A set of nomografs typically covers a 12 km by 12 km urban region at 5-meter resolution. These nomografs are derived from 3D Computational Fluid Dynamics simulations taking a couple of days on a modest high-performance parallel cluster. This report compares the CT-Analyst contaminant density predictions, using 2-meter resolution nomografs, for a 4 km by 4 km area of downtown Denver based on an existing vetted 3D geometry and the corresponding geometry derived from airborne lidar measurements. The IDA Measure of Effectiveness (MoE), a cloud-to-cloud comparison metric computed at specific times, is used to compare predictions based on the two different geometry datasets. This report shows that lidar-based geometry allows good quality CT-Analyst predictions with much less investment in labor and preparation lead time.

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Document Details

Document Type
Technical Report
Publication Date
Jan 26, 2023
Accession Number
AD1194595

Entities

People

  • Adam J. Moses
  • Gopal Patnaik
  • Jay Boris
  • Keith S. Obenschain
  • Kiran M. Donnelly

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Civil Defense
  • Computational Fluid Dynamics
  • Computations
  • Contamination
  • Coordinate Systems
  • Data Processing
  • Emergencies
  • Environmental Pollutants
  • First Responders
  • Fluid Dynamics
  • Force Protection
  • Geographic Regions
  • Geometry
  • Physics
  • Physics Laboratories
  • Point Clouds
  • Simulations
  • Terrain
  • Time Dependence
  • Two Dimensional
  • Wind Direction

Readers

  • Atmospheric Remote Sensing.
  • Computational Modeling and Simulation
  • Urban Planning and Geography.

Technology Areas

  • Space