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Track: Forestry
William Hargrove
Oak Ridge National Laboratory
PO 2008
Oakridge, TN 37830
Telephone: 423-241-2748
Fax: 423-574-4634
E-mail: hnw@mtqgrass.esd.ornl.gov
Robert J. Luxmoore
A Spatial Clustering Technique for the Identification of Customizable Ecoregions
A spatial clustering technique was used to identify patches which are similar with regard to five edaphic and physiographic variables within a five state area, (Kentucky, Tennessee, North Carolina, South Carolina and Georgia) at 1-km resolution. Fifty-year mean monthly temperature and precipitation, elevation, total plant-available water content of soil, and total organic matter in soil were used as input classification variables. The map was disassembled into 670, 326 1-km cells, each with values for the five environmental variables, and the cells were submitted to a factor analysis and equamax axis rotation using the SAS procedure factor. The factor analysis removes correlations from the input variables, reduces the dimensionality, and normalizes the axis measurements. A cluster analysis was performed on the four principal factor scores using the SAS procedure FASTCLUS, and the cells, with their cluster assignments, were re-integrated into the map. A series of maps dividing the five state area into 10,
15, 25, and 30 custom ecoregions are presented, and these custom regions are compared with the 23 standard Major Land Resource Areas (MLRAs) identified by the NRCS within these states. The resultant custom map can be used like a paint-by-numbers picture to extrapolate measured or simulated data over space. The number of final clusters is under user's control, so that homogeneous patches in the final map can be made coarse or fine.
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