Assessing map accuracy from a suite of site-specific, non-site specific, and spatial distribution approaches.

Assessing a map's accuracy and efficacy requires careful consideration calculation of comprehensive set measures, particularly when characteristics in geospatial datasets may be used for addressing multiple objectives. We describe map assessment framework categorical data over large areas that utilizes site-specific (plot-pixel), non-site specific (area estimates), comparative (spatial statistical distributions) methods. This spans the range approaches applied most other studies, maximizing opportunities both within- between-study comparisons. The analysis incorporated recommended good practices sampling design, response protocols, design-based inference providing rigorous estimates precision. Further partitioning disagreement allows users to assess relative importance spatial location versus total abundance classes error; we introduced ratio allocation quantity comparing each across datasets. Assessment fuzzy membership with linguistic scales have minimal effect on overall accuracy, but can provide substantial improvement user's producer's uncommon classes. adapted metrics insights into variability thematic Comparing based reference co-located samples reveal potential issues data. demonstrated example applications all components maps early successional forest land cover western Great Lakes region, USA.