Lookouts, communications, escape routes, and safety zones (LCES) is a well-established protocol for keeping wildland firefighters safe. Typically, LCES is evaluated on the ground as part of daily fire management activities, with little to no geospatial support. However, the landscape characteristics that drive LCES effectiveness are inherently spatial, and can be readily mapped using remote sensing and GIS. For the past decade, the Utah Remote Sensing Applications (URSA) Lab has partnered with the USDA Forest Service to develop novel geospatial solutions for evaluating LCES, collectively referred to as GeoLCES. Driven by airborne lidar, GeoLCES enables the simultaneous, spatially explicit quantification of proportional landscape visibility, evacuation potential, and safety zone suitability. Visibility, a necessity for lookouts and an important driver of communication effectiveness, is mapped using a machine learning model driven by lidar-based viewsheds that predicts the relative proportion of one’s surroundings that could be seen from every pixel in a landscape. Evacuation potential is mapped using the Escape Route Index, which quantifies the proportional speed one could walk in a real landscape relative to a landscape completely devoid of impediments. Safety zone suitability is mapped as the relative degree to which each pixel in a landscape provides sufficient safe separation distance, based on surrounding terrain and vegetation conditions, as well as burning condition and wind speed. When mapped in advance of a fire, GeoLCES has the potential to serve as an important pre-fire decision support tool to improve the efficiency, reliability, and consistency with which LCES is implemented.