Pixels, blocks of pixels, and polygons: Choosing a spatial unit for thematic accuracy assessment

Pixels, blocks of pixels, and polygons are all potentially viable spatial assessment units for conducting an accuracy assessment. We develop a population-based statistical framework to examine how the spatial unit chosen affects the outcome of an accuracy assessment. The population is conceptualized as a difference map created by overlaying a complete coverage reference classification and the target map being evaluated. The per-class areas of agreement and disagreement derived from this population are summarized by a population error matrix and accuracy parameters (e.g., overall, user's and producer's accuracies). The population and values of the accuracy parameters are strongly affected by the protocols implemented for the response design which include the choice of spatial unit, how within-unit homogeneity is addressed when assigning class labels, and the definition of agreement between the reference and map classification. Several complete coverage populations are used to illustrate how accuracy results are affected by the spatial unit chosen for the assessment and also to evaluate how spatial misregistration of the map and reference locations impacts accuracy results for different spatial units. The sampling design implemented for accuracy assessment does not change the population or values of the accuracy parameters, but the choice of spatial unit will influence decisions regarding use of strata and clusters in the design. A universally best spatial assessment unit does not exist, so it is critical to recognize how the population, values of the accuracy parameters, and sampling design are impacted by the choice of spatial unit.

► Pixels, blocks of pixels, and polygons are viable accuracy assessment spatial units
► The spatial units are evaluated from the perspective of a statistical population
► Complete coverage populations illustrate quantitatively the effect of spatial unit
► The effect of spatial location error is examined
► The choice of spatial unit influences sampling design decisions