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We used Trimble eCognition Developer to 1) develop efficient methods to estimate land cover classes found in P-J woodlands; 2) determine the relationship between ground measurements and object-based image analysis (OBIA) land cover measurements for the following classes: trees (live, burned, cut, and masticated), shrubs, perennial herbaceous vegetation, litter (including annual species), and bare ground; and 3) evaluate eCognition rule-sets (models) across four spatial scales (subplot, site, region, and network) using untreated P-J woodland imagery. At the site scale, the overall accuracy of our thematic maps for untreated P-J woodlands was 84% with a kappa statistic of 0.80. For treatments, the overall accuracy and kappa statistic for prescribed fire was 85% and 0.81; cut and fell 82% and 0.77, and mastication 84% and 0.80, respectively, each indicating strong agreement between OBIA classification and ground measured data.