Data Publications

TopoMetricUncertainty - Calculating Topographic Metric Uncertainty and Optimal Grid Resolution

  • Deutsches GeoForschungsZentrum GFZ
  • 2019
  • TopoMetricUncertainty - Calculating Topographic Metric Uncertainty and Optimal Grid Resolution
  • 10.5880/fidgeo.2019.017
  • Aspect
  • DEM
  • Lidar
  • Slope
  • Topographic Uncertainty
  • This python software (version 1.0) is linked to the publication "Determining the Optimal Grid Resolution for Topographic Analysis on an Airborne Lidar Dataset" by T. Smith, A. Rheinwalt, and B. Bookhagen (2019). Software updates can be found at:, TopoMetricUncertainty is a set of python codes which can be used to determine the optimal grid resolution of a given lidar dataset which minimizes overall uncertainties in slope and aspect calculations. The software contains examples with both synthetic and real gridded data covering the Santa Cruz Island, California. The following components are included in this software release: (1) code used to create the synthetic surfaces used in Smith et al. (2019) (2) code used to calculate truncation error and propagated elevation uncertainty (3) the detailed description of several gridding methods for lidar data, including the ones used in this paper, can be found here: (4) A full example and script for choosing the optimal grid resolution is included in the 'example' directory. This directory contains elevation and elevation standard deviation estimates for a subset of SCI from 2m to 30m resolution. Running the included script will generate a simple figure showing the optimal grid resolution for that region, given that error model. (5) is one other potential method of finding the optimal grid spacing directly from a lidar dataset. This method was not used in the above linked paper but is included in this software publication and available via github.
GCMD Sciencekeywords describing the dataset. Click on Keyword to find similar datasets