Topobathymetric scanning LiDAR deployed on unmanned aerial systems (UAS) is a powerful tool for high-resolution mapping of the dynamic interface between topography and bathymetry. However, standardized methods for empirical resolution validation have not been widely adopted across LiDAR applications. While theoretical models of idealized LiDAR sampling resolution can be used to describe topographical resolution, misrepresented or unknown behaviors in an instrument, platform, or environment can degrade expected performance or introduce georeferencing inaccuracies. Furthermore, bathymetric resolution is strongly dependent on water surface and column conditions. Thus, only empirical methods for evaluating resolution will provide reliable estimates for both topographic and bathymetric surveys. Presented is an extension of standard modulation transfer function (MTF) methods used by passive imaging systems applied to high-resolution scanning LiDAR. Compact retroreflectors characterized as point and line sources are employed to empirically assess effective LiDAR system resolution through MTF analysis in topographic and bathymetric scenes. These targets enable MTF analyses using range-height measurements without reliance on intensity data, promoting widespread applicability among LiDAR systems. Empirical MTFs calculated using these targets are compared against theory-derived counterparts as empirical measurements elucidate influences by elements that are unknown or difficult to model. Simulated point cloud data were incorporated into theoretical MTF descriptions to better represent empirically-derived topographic MTFs, revealing mirror pointing uncertainties in the across-track axis. Similarly, theoretical bathymetric MTFs augmented with simulated, subaqueous data enabled water surface slope estimation using empirical measurements of submerged retroreflector targets, where rough water surfaces strongly influenced beam steering and the corresponding point spread MTFs.