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The objectives of this study were 1) to evaluate the relationship and agreement of pi ̃non and juniper (P-J) canopy cover estimates, using object-based image analysis (OBIA) techniques and National Agriculture Imagery Program (NAIP, 1-m pixel resolution) imagery with ground measurements, and 2) to investigate the relationship between remotely-sensed P-J canopy cover and ground-measured aboveground biomass. For the OBIA, we used eCognitiont Developer 8.8 software to extract tree canopy cover from NAIP imagery across 12 P-J woodlands within the Sagebrush Steppe Treatment Evaluation Project (SageSTEP) network. The P-J woodlands were categorized based on the dominant tree species found at the individual sites for the analysis (western juniper, Utah juniper, and mixed P-J community). Following tree canopy cover extractions, relationships were assessed
between remotely-sensed canopy cover and ground-measured aboveground biomass. Our OBIA estimates for P-J canopy cover were highly correlated with ground-measured tree canopy cover (averaged across all regions r¼0.92). However, differences between methods occurred for western and Utah juniper sites (P , 0.05), and were more prominent where tree canopy cover was . 40%. There were high degrees of correlation between predicted aboveground biomass estimates with the use of remotely-sensed tree canopy cover and ground-measured aboveground biomass (averaged across all regions r¼0.89). Our results suggest that OBIA methods combined with NAIP imagery can provide land managers with quantitative data that can be used to evaluate P-J woodland cover and aboveground biomass rapidly, on broad scales. Although some accuracy and precision may be lost when utilizing aerial imagery to identify P-J canopy cover and aboveground biomass, it is a reasonable alternative to ground monitoring and inventory practice