ASSESSING MAP ACCURACY IN A REMOTELY-SENSED, ECOREGION-SCALE COVER MAP

Landscape- and ecoregion-based conservation efforts increasingly use a spatial component to organize data for analysis and interpretation. A challenge particular to remotely sensed cover maps generated from the se efforts is how best to assess the accuracy of the cover maps, espec ially when they can exceed 1000 s/km(2) in size. Here we develop and d escribe a methodological approach for assessing the accuracy of large- area cover maps, using as a test case the 21.9 million ha cover map de veloped for Utah Gap Analysis. As part of our design process, we first reviewed the effect of intracluster correlation and a simple cost fun ction on the relative efficiency of cluster sample designs to simple r andom designs. Our design ultimately combined clustered and subsampled field data stratified by ecological modeling unit and accessibility ( hereafter a mixed design). We next outline estimation formulas for sim ple map accuracy measures under our mixed design and report results fo r eight major cover types and the three ecoregions mapped as part of t he Utah Gap Analysis. Overall accuracy of the map was 83.2% (SE=1.4). Within ecoregions, accuracy ranged from 78.9% to 85.0%. Accuracy by co ver type varied, ranging from a low of 50.4% for barren to a high of 9 0.6% for man modified. In addition, we examined gains in efficiency of our mixed design compared with a simple random sample approach. In re gard to precision, our mixed design was more precise than a simple ran dom design, given fixed sample costs. We close with a discussion of th e logistical constraints facing attempts to assess the accuracy of lar ge-area, remotely sensed cover maps.