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These layers each depict one suite of methodological choices for designating land facets. Scroll through them to see how different choices affect land facet patterns.
Methodological choices:
Resolution: 1km or 270m
Categorization approach:
Categorical overlay- each variable is categorized into ecologically meaningful classes. Land facets are created from unique combinations of those classes.
K-means clustering- an algorithm clusters the continuous variables into a designated number of facets. The Hartigan index was used to identify the optimal number of facets.
Hybrid approach- a combination of the categorical overlay and a clustering method. Topographic data were categorized, and within each topographic class all other variables were clustered using a fuzzy c-means algorithm
Variable selection:
Topographic variables
Elevation
Slope
Soil variables
organic matter
bulk density
soil horizon depth
accumulated water content
Geology (categorized into 9 types of geological groupings after Anderson)
Normalization: variables normalized (where necessary) within ecoregion or across 14 NW ecoregions
Layers in this dataset are based on combinations of the following options.
You may choose from these options to select a specific layer on the map page.