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TxDOT Road Elevation Model Dataset

  • Liu, Yan | Oak Ridge National Laboratory
  • Maidment, David R | University of Texas at Austin
  • Carter, Andy | University of Texas at Austin
  • Whiteaker, Timothy L | University of Texas at Austin
  • Evans, Harold R | University of Texas at Austin
  • Thies, Christine | University of Texas at Austin
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Overview

Description

This dataset provides three formats of Road Elevation Model (REM) data: 3D road line/polygon GeoPackage (GPKG), road lidar LAZ and COPC LAZ, and road digital surface model (DSM) GeoTIFF. Data are produced from the ~50TB TxGIO (formerly TNRIS) state lidar collections. This dataset is currently organized by maintenance section in each TxDOT district. Computation is done on GPU computing resources at Oak Ridge National Laboratory (ORNL), through a Strategic Partnership Project with UT Austin and an NSF ACCESS computing allocation award that enables fast massive data movement between TACC Corral and ORNL CADES/OLCF using Globus. In addition to this release from ORNL, a copy of this dataset can also be downloaded at https://web.corral.tacc.utexas.edu/nfiedata/road3d/.

Funding Resources

DOE Contract Number

AC05-00OR22725

Originating Research Organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Other Contributing Organizations

National Oceanic and Atmospheric Administration (NOAA)

Sponsoring Organization

University of Texas at Austin

Related Resources

Details

DOI

10.13139/ORNLNCCS/2574440

Release Date

August 7, 2025

Dataset

Dataset Type

IM Interactive Maps/GIS Data

Software

QGIS, ArcGIS, GDAL, PDAL, or copc laz viewer software

Other Contract Number(s)

NOAA CIROH NA22NWS4320003; ORNL SPP # NFE-24-10489

Acknowledgements

Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:

This work was carried out [in part] at Oak Ridge National Laboratory, managed by UT-Battelle, LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725.

Category

  • 13 HYDRO ENERGY

Keywords

  • GPU Graphical Processing Units,
  • high-performance computing,
  • flood inundation mapping,
  • GIS,
  • hydrology,
  • Transportation,
  • Lidar