This study reports on the use of the commercially available ENVI Deep Learning module to (i) automatically extract GIS ready rooftop polygons directly from high-resolution night-time thermal infrared (TIR) airborne imagery and (ii) define the optimal spatial resolution for deep learning rooftop delineation. It also (iii) compares results from multi-spatial resolution models based on a single TIR image vs. a derived three channel image and (iv) introduces two new object-based accuracy assessment methods for comparing the visual fit of the segmented rooftops.