Title :
Using multivariate clustering to characterize ecoregion borders
Author :
Hargrove, William W. ; Hoffman, Forrest M.
Author_Institution :
Tennessee Univ., TN, USA
Abstract :
The authors present a geographic clustering technique which unambiguously locates, characterizes, and visualizes ecoregions and their borders. When coded with similarity colors, it can produce planar map views with sharpness contours that are visually rich in ecological information and represent integrated visualizations of complex and massive environmental data sets
Keywords :
biology computing; cartography; data visualisation; ecology; pattern clustering; data visualization; ecological information; ecoregion borders; geographic clustering technique; integrated visualizations; massive environmental data sets; multivariate clustering; planar map views; sharpness contours; similarity colors; Biological system modeling; Birds; Clustering algorithms; Data visualization; Environmental management; Fractals; Iterative algorithms; Logic; Plants (biology); US Department of Agriculture;
Journal_Title :
Computing in Science & Engineering
DOI :
10.1109/5992.774837
