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    Author(s): Qingmin Meng; Chris J. Cieszewski; Roger C. Lowe; Michal Zasada
    Date: 2005
    Source: In: Proceedings of the fifth annual forest inventory and analysis symposium; 2003 November 18-20; New Orleans, LA. Gen. Tech. Rep. WO-69. Washington, DC: U.S. Department of Agriculture Forest Service. 222p.
    Publication Series: General Technical Report (GTR)
    Station: Washington Office
    PDF: View PDF  (135.95 KB)

    Description

    Tree mortality is one of the most complex phenomena of forest growth and yield. Many types of factors affect tree mortality, which is considered difficult to predict. This study presents a new systematic approach to simulate tree mortality based on the integration of statistical models and geographical information systems. This method begins with variable preselection using multiple linear regression models and logistic models and employs spatial autocorrelation detection and random sampling. Three random sampling methods are applied and compared to reduce the effects of spatial autocorrelation, and systematic random sampling significantly reduces the spatial autocorrelation among the observations and is used for the final variable selection and model fitting. Using Forest Inventory and Analysis (FIA) data for the State of Georgia, this systematic approach provides significant implications for future tree mortality studies and other spatial analysis in forestry or geography.

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    Citation

    Meng, Qingmin ; Cieszewski, Chris J.; Lowe , Roger C.; Zasada, Michal. 2005. A Three-Step Approach To Model Tree Mortality in the State of Georgia. In: Proceedings of the fifth annual forest inventory and analysis symposium; 2003 November 18-20; New Orleans, LA. Gen. Tech. Rep. WO-69. Washington, DC: U.S. Department of Agriculture Forest Service. 222p.

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https://www.fs.usda.gov/treesearch/pubs/14281