O. FIS Error Modelling in CHaMP & BitBucket Repository

Synopsis of Topic

An FIS can be constructed and implemented in a variety of ways. Before learning how to build our own FIS in the next session, we will focus on how the outputs vary based on what combination of inputs you decide to use. We will look at a variety of FIS outputs by combining different inputs:
  1. Point Density
  2. Slope
  3. Roughness
  4. 3D Point Quality
  5. Interpolation Errors
Each of these inputs can be derived or loaded as an associated surface in GCD.


Examples from two sites of the different inputs and how they vary spatially (Figure from Bangen et al (In Prep)).

Why we're Covering it

This session is intended to help you understand how flexible the GCD framework is for exploring the impact of different FIS error models. The exercise will help reenforce your skills and practical understanding of using FIS error models. We'll also show you a community repository where you can get and contribute FIS error models.

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


Resources

Exercises

Slides and/or Handouts

  •  Lecture Slides?

Other Resources



Relevant or Cited Literature

  • In Prep. Bangen S‡ Wheaton JM, Hensleigh J‡ , and Bailey P. Pragmatic Error Modeling of Digital Elevation Models from Topographic Surveys using Fuzzy Inference Systems. For submission to ESPL. 

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