J. Spatially Variable Error


Synopsis of Topic

There is plenty of evidence to suggest that elevation uncertainties are spatially variable in DEMs and there are many reasonable approaches for estimating these spatially variable error terms. In this discussion and demonstration, we cover some common approaches for estimating errors and show you how to load user-derived error surfaces into the Surve Library in GCD.

Why we're Covering it

Should you have the means or need to derive your own error surfaces, it is important to understand how to incorporate those into a GCD analysis.

Learning Outcomes Supported

This topic will help fulfill the following primary learning outcome(s) for the workshop:
  • A comprehensive overview of the theory underpinning geomorphic change detection
  • The fundamental background necessary to design effective repeat topographic monitoring campaigns and distinguish geomorphic changes from noise (with particular focus on restoration applications)
  • Hands-on instruction on use of the GCD software through group-led and self-paced exercises


Slides and/or Handout

Relevant or Cited Literature

  • 2012. Rychkov I, Brasington J and Vericat D. Computational and methodological aspects of terrestrial surface analysis based on point clouds. Computers & Geosciences. 42: 64-70. DOI: 10.1016/j.cageo.2012.02.011.
  • 2011.Williams R, Brasington J, Vericat D, Hicks M, Labrosse F and Neal M.  Chapter Twenty - Monitoring Braided River Change Using Terrestrial Laser Scanning and Optical Bathymetric Mapping. Mike J. Smith PP and James SG (Eds), Developments in Earth Surface Processes. Elsevier, pp. 507-532. DOI:  10.1016/b978-0-444-53446-0.00020-3.
  • 2003. Lane SN, Westaway RM and Hicks DM. Estimation of erosion and deposition volumes in a large, gravel-bed, braided river using synoptic remote sensing. Earth Surface Processes and Landforms. 28(3): 249-271. DOI: 10.1002/esp.483.

Relevant Links

  • PCTools - Point Cloud Tools Software ; see also old 32-bit version here.

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