Local and regional urban surface heterogeneity produces diverse urban climates, significantly impacting water use, energy consumption, and human health. This study examines urban energy flux variability across landcover and climate gradients for 2123 km2 of urbanized Los Angeles County, USA, by using high resolution remote sensing combined with spatially distributed simulations with an urban energy balance model, covering the complete diurnal cycle of the remote sensing flights. Localized parameters, including landcover, plant type, albedo, building and tree height, and irrigation, were derived from hyperspectral and LiDAR imagery, and GIS. Modeled latent heat fluxes (LE) were linearly correlated with measured land surface temperature at the neighborhood scale (R2 = 0.51), and modeled Bowen ratio values closely agreed with previous values derived from eddy covariance observations. LE across the region displayed spatial and temporal responses to irrigation and regional climate. Peak LE occurred 3 h before solar noon, driven by early morning irrigation characteristic of the region. This suggests that schedule-based water conservation policies could reduce the cooling capacity of urban vegetation in late afternoon. Additionally, a negative effect of distance from the coast on LE was observed to strengthen through the day, reducing LE in interior areas relative to coastal areas.