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    Author(s): Bonnie Ruefenacht; Greg LiknesAndrew J. Lister; Haans Fisk; Dan Wendt
    Date: 2009
    Source: In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 13 p.
    Publication Series: Proceedings (P)
    Station: Rocky Mountain Research Station
    PDF: View PDF  (394.83 KB)

    Description

    Since 2001, the USDA Forest Service (USFS) has used classification and regression-tree technology to map USFS Forest Inventory and Analysis (FIA) biomass, forest type, forest type groups, and National Forest vegetation. This prior work used Cubist/See5 software for the analyses. The objective of this project, sponsored by the Remote Sensing Steering Committee (RSSC), was to evaluate other software packages, including R, SAS, WEKA, and Orange. These software packages must work with the USFS standard remote-sensing and GIS packages such as ArcGIS and ERDAS Imagine. As part of this project, a Python script was developed that fully integrated these software packages, excluding SAS, with ArcGIS and ERDAS Imagine. Appendix A provides the tutorial for this script. Appendix B provides a tutorial on how to write similar scripts in Python.

    Publication Notes

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    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Ruefenacht, Bonnie; Liknes, Greg; Lister, Andrew J.; Fisk, Haans; Wendt, Dan. 2009. Evaluation of open source data mining software packages. In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 13 p.

    Keywords

    CART, Orange, WEKA, R, random forest, classification trees, regression trees, open-source software

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