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Application of an assessment protocol to extensive species and total basal area per acre datasets for the eastern coterminous United States

Informally Refereed

Abstract

We recently developed an assessment protocol that provides information on the magnitude, location, frequency and type of error in geospatial datasets of continuous variables (Riemann et al. 2010). The protocol consists of a suite of assessment metrics which include an examination of data distributions and areas estimates, at several scales, examining each in the form of maps, graphics, and summary statistics. In this study we have applied this protocol to the modeled total and species-level basal area/acre datasets recently completed for the eastern coterminous United States (Wilson et al. in review). We were interested in the answers to two questions: (1) how can assessment results be effectively presented over extensive areas, and (2) what is the accuracy of modeled datasets of much less common forest characteristics such as the presence of an individual species, and what might that tell us about the limitations of the current modeled dataset for other less common variables. Results from this study will help fine-tune the type of assessments applied and how they are presented in the metadata available with all geospatial datasets produced by Forest Inventory and Analysis (FIA).

Parent Publication

Keywords

Accuracy assessment, uncertainty, geospatial data, continuous variables, species distribution

Citation

Riemann, Rachel; Wilson, Ty; Lister, Andrew. 2012. Application of an assessment protocol to extensive species and total basal area per acre datasets for the eastern coterminous United States. In: McWilliams, Will; Roesch, Francis A. eds. 2012. Monitoring Across Borders: 2010 Joint Meeting of the Forest Inventory and Analysis (FIA) Symposium and the Southern Mensurationists. e-Gen. Tech. Rep. SRS-157. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 161-174.
https://www.fs.usda.gov/research/treesearch/41003