From 2011 to 2016, California experienced a millennial-intensity drought, generating high levels of tree mortality. Remote sensing has been used to monitor the long-term impacts of drought; however, discriminating dead from live trees in arid and semiarid deciduous woodlands is challenging. The goals of this study were to assess and map the spatial patterns of drought-induced tree mortality in a blue oak (Quercus douglasii) woodland, a highly drought-tolerant species forming savannas along the lower foothills surrounding California's Central Valley. Airborne hyperspectral imagery was used to identify the most important wavelength regions predicting drought-induced blue oak mortality. The best metric to predict canopy stress was a normalized ratio using the spectral bands 937.53 and 1100.08 nm with a correlation with tree mortality of R2 = 0.83. The image prediction of mortality for nine field plots found that 16 of 98 trees died (17.9%) during the drought. We further evaluated tree mortality in 82 independent plots, and we found the greatest image predictive accuracy for tree mortality between 1% and 10%. When applied at the landscape level, the regression-based index found mortality ranged from 1% to more than 51% in oak stands with an average mortality of 10% over the entire study region. In addition, tree mortality at landscape level showed higher tree mortality in blue oaks on south-facing aspects probably because of higher insolation rates and in sites with low potential for accumulated drainage.