Comparing Land Facet Methodologies in the Columbia Plateau
Dates
Original Data Basin Creation Date
2012-12-19 21:20:28
Original Data Basin Modified Date
2012-12-19 21:35:21
Summary
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 270mCategorization 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 [...]
Summary
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
