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    Author(s): Rachel RiemannBarry T. Wilson
    Date: 2014
    Source: In: Shortridge, A.M.; Messina, J.P.; Kravchenko, S.; Finley, A., eds. Accuracy 2014: [Proceedings] 11th international symposium on spatial accuracy assessment in natural resources and environmental sciences. 2014 July 8-11; East Lansing, MI. [Place of publication unknown]: International Spatial Accuracy Research Association: 100-106.
    Publication Series: Paper (invited, offered, keynote)
    Station: Northern Research Station
    PDF: View PDF  (702.9 KB)

    Description

    Modeled geospatial datasets have been created for 325 tree species across the contiguous United States (CONUS). Effective application of all geospatial datasets depends on their accuracy. Dataset error can be systematic (bias) or unsystematic (scatter), and their magnitude can vary by region and scale. Each of these characteristics affects the locations, scales, uses, and questions to which a dataset is best applied, and the risk involved in doing so. This study uses a suite of assessment metrics to characterize the type, magnitude, frequency, and spatial location of errors in this large dataset. Results are examined with respect to tree species growth habits, level of stand dominance, spatial-distribution characteristics, and the number of plots on which it occur and for any persistent local errors occurring throughout the datasets.

    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

    Riemann, Rachel; Wilson, Barry T. 2014. Characterization and visualization of the accuracy of FIA's CONUS-wide tree species datasets. In: Shortridge, A.M.; Messina, J.P.; Kravchenko, S.; Finley, A., eds. Accuracy 2014: [Proceedings] 11th international symposium on spatial accuracy assessment in natural resources and environmental sciences. 2014 July 8-11; East Lansing, MI. [Place of publication unknown]: International Spatial Accuracy Research Association: 100-106.

    Keywords

    accuracy characterization, continuous variables, comparative assessment, species distributions, FIA, visualization.

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https://www.fs.usda.gov/treesearch/pubs/46519