A wide range of ground failure such as earthquake faulting (surface rupture), landslides, and liquefaction occur after a large earthquake. In this study, in order to rapidly determine the distribution of failure over a wide area after an earthquake, we combined traditional methods such as aerial photo interpretation and modern methods such as unmanned aerial vehicle (UAV) or interferometric synthetic aperture radar (InSAR) techniques. Moreover, elevation variations obtained using DEMs and the structure from motion and multi-view stereo (SfM-MVS) technique were employed to understand local ground deformation factors, such as reclaimed valley deformation. Using ortho-mosaic images, surface fissures caused by the 2016 Kumamoto Earthquake in Japan were rapidly interpreted and mapped, which enabled early interpretation of the ground failure situation. Furthermore, surface displacement properties extracted from SAR interferograms allowed for more advanced earthquake fault detection; surface displacement associated with liquefaction was also identified from SAR interferograms. In addition, InSAR was used to detect reclaimed valley deformation. Comparing this with the reclaimed valley distribution map created by the SfM-MVS technique improved our understanding of this phenomenon. However, many of these techniques require large amounts of manpower and time and can be influenced by differences in analyst skill level. In future, the development of mechanically automated ground failure identification will improve earthquake disaster responses.