Coseismic surface fault displacement presents a serious potential hazard for structures and for lifeline infrastructure. Distributed lifeline infrastructure tends to cover large distances and may cross faults in multiple locations, especially in active tectonic regions like California. However, fault displacement measurements for engineering applications are quite sparse, rendering the development of predictive models extremely difficult and fraught with large uncertainties. Detailed fault surface rupture mapping products exist for a few documented cases, but they may not capture the full width of ground deformations that are likely to impact distributed infrastructure. The 2019 Ridgecrest earthquake sequence presented an ideal opportunity to collect data and evaluate the ability of different techniques to capture coseismic deformations on and near the fault ruptures. Both the M 6.5 and 7.1 events ruptured the surface in sparsely populated desert areas where little vegetation is present to obscure surficial features. Two study areas (~400 m × 500 m each) around the surface ruptures from the two events were selected. Teams of researchers were deployed and coordinated to gather data in three ways: field measurements and photographs, imagery from small uninhabited aerial systems, and imagery from airborne light detection and ranging. Each of these techniques requires different amounts of resources in terms of cost, labor, and time associated with the data collection, processing, and interpretation efforts. This article presents the data collection methods used for the two study areas, and qualitative and quantitative comparisons of the results interpretations. While all three techniques capture the key features that are important for displacement design of distributed infrastructure, the use of remote sensing methods in combination with field measurements presents an advantage over the use of any single technique.