Skip to content

esther-bushuev/morphology_clustering

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 

Repository files navigation

morphology_clustering

Unsupervised classification of seafloor morphology using principle component analysis (PCA) and K-means clustering.

PURPOSE

This code performs an unsupervised classification of seafloor morphology using principle component analysis (PCA) and a K-means clustering algorithm.

WORKFLOW

The required inputs for this exercise are a regularly gridded bathymetry raster (or DEM in terrestrial applications) and various terrain attributes/derivatives, including but not limited to:

  • Slope
  • Bathymetric position index (BPI or TopographicPI for terrestrial)
  • Bathymetric average
  • Curvature
  • Rugosity/ruggedness Attributes can also be calculated with varying neighbourhood/window sizes to capture features at different scales (Misiuk et al., 2021).

There are many ways in which the terrain attribute rasters can be derived; such as:

PCA is performed on the rasters and a K-meansclustering algorithm is then applied to a user defined number of principle components (PC) based on the % variance explained. The number of classes for the clustering are defined arbitrarily but should be greater than what the user may expects in the area to allow for reclassification down the line.

The output layer will be a numerically classified raster. Feature names can then be assigned to each class by the user based on a classification scheme of choice, and/or with reference to pre-existing maps of the study area. Examples in the marine environment include:

  • Geomorphology of the oceans (Harris et al., 2014)
  • A two-part seabed geomorphology classification scheme (Dove et al., 2020)

REFERENCES

Dove, D., Nanson, R., Bjarnadóttir, L.R., Guinan, J., Gafeira, J., Post, A., Dolan, M.F.J., Stewart, H., Arosio, R., Scott, G. (2020). A two-part seabed geomorphology classification scheme: (v.2); Part 1: morphology features glossary, https://doi.org/10.5281/ZENODO.4075248

Harris, P. T., Macmillan-Lawler, M., Rupp, J., & Baker, E. K. (2014). Geomorphology of the oceans. Marine Geology, 352, 4–24, https://doi.org/10.1016/j.margeo.2014.01.011

Ilich, A. R., Misiuk, B., Lecours, V.,; Murawski, S. A. (2021). “MultiscaleDTM”, https://doi.org/10.5281/zenodo.5548338. https://github.com/ailich/MultiscaleDTM.

Misiuk, B., Lecours, V., Dolan, M. F. J., & Robert K., (2021) Evaluating the Suitability of Multi-Scale Terrain Attribute Calculation Approaches for Seabed Mapping Applications, Marine Geodesy, 44:4, 327-385, https://doi.org/10.1080/01490419.2021.1925789

Walbridge, S., Slocum, N., Pobuda, M., Wright, D.J. (2018). Unified Geomorphological Analysis Workflows with Benthic Terrain Modeler. Geosciences, 8, 94, https://doi.org/10.3390/geosciences8030094

AUTHOR INFORMATION

Esther Bushuev (B.Sc., M.Sc. Candidate)

Seascape Ecology & Mapping Lab, Department of Oceanography, Dalhousie University

https://www.seafloormapping.ca/

About

Unsupervised classification of seafloor morphology using principle component analysis (PCA) and K-means clustering.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages