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    Author(s): Tracey S. FrescinoPaul L. PattersonElizabeth A. FreemanGretchen G. Moisen
    Date: 2012
    Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 74-78.
    Publication Series: Paper (invited, offered, keynote)
    Station: Northern Research Station
    PDF: Download Publication  (396.73 KB)

    Description

    FIESTA (Forest Inventory Estimation for Analysis) is a user-friendly R package that supports the production of estimates for forest resources based on procedures from Bechtold and Patterson (2005). The package produces output consistent with current tools available for the Forest Inventory and Analysis National Program, such as FIDO (Forest Inventory Data Online) and EVALIDator. FIESTA was developed as an alternative data retrieval and reporting tool that is functional within the R environment, allowing customized applications and compatibility with other R-based analyses. FIESTA generates estimates and percent sample errors of the estimates for area, population totals, and ratios, while allowing user-defined boundaries, stratification schemes, and data filters. The features of the tool are demonstrated using temporally sensitive data over diverse areas.

    Publication Notes

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    Citation

    Frescino, Tracey S.; Patterson, Paul L.; Freeman, Elizabeth A.; Moisen, Gretchen G. 2012. Using FIESTA , an R-based tool for analysts, to look at temporal trends in forest estimates. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 74-78.

    Keywords

    statistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring

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