Skip to page content
USDA Forest Service
  
Treesearch

Research & Development Treesearch

 
Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Northern
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern
Help
 

GeoTreesearch


Science.gov - We Participate


USA.gov  Government Made Easy


Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.
20090-6090

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

(143 KB bytes)

Title: Using cluster analysis and a classification and regression tree model to developed cover types in the Sky Islands of southeastern Arizona

Author: Iniguez, Jose M.; Ganey, Joseph L.; Daughtery, Peter J.; Bailey, John D.

Date: 2005

Source: In: Gottfried, Gerald J.; Gebow, Brooke S.; Eskew, Lane G.; Edminster, Carleton B., comps. Connecting mountain islands and desert seas: biodiversity and management of the Madrean Archipelago II. Proc. RMRS-P-36. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: 195-200

Publication Series: Proceedings (P)

   Note: This article is part of a larger document. View the larger document

Description: The objective of this study was to develop a rule based cover type classification system for the forest and woodland vegetation in the Sky Islands of southeastern Arizona. In order to develop such a system we qualitatively and quantitatively compared a hierarchical (Ward’s) and a non-hierarchical (k-means) clustering method. Ecologically, unique groups represented by only a few plots were appropriately distinguished using k-means, while Ward’s combined these unique plots into the large mixed conifer groups. Similarly, plots dominated by more than one species were more appropriately grouped with other mixed-species plots using k-means. The two clustering methods were numerically compared using a classification and regression tree (CART) model. Groups based on the two clustering methods had similar recovery rates, but k-means groups required fewer nodes or decision rules. Based on these results we developed a detailed cover type classification system for the existing vegetation of the Sky Islands in southeastern Arizona. The final cover types were based on the original k-means clusters, with some minor modifications made using CART analysis to compensate for overlapping values. This allowed us to transform the CART output into a dichotomous identification key for 20 detailed cover types. Finally, these detailed cover types were linked to a flexible three-level hierarchical framework that allows users to aggregate or segregate forest lands as needed. The hierarchical organization of this framework is similar to the natural organization of ecosystems, which will aid our understanding of natural processes in these forest and woodlands.

Keywords: cluster analysis, models, regression, cover types, classification, Sky Islands, Arizona

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
  • You may send email to rmrspubrequest@fs.fed.us to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)

XML: View XML

Citation:


Iniguez, Jose M.; Ganey, Joseph L.; Daughtery, Peter J.; Bailey, John D. 2005. Using cluster analysis and a classification and regression tree model to developed cover types in the Sky Islands of southeastern Arizona. In: Gottfried, Gerald J.; Gebow, Brooke S.; Eskew, Lane G.; Edminster, Carleton B., comps. Connecting mountain islands and desert seas: biodiversity and management of the Madrean Archipelago II. Proc. RMRS-P-36. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: 195-200

 


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.