The increasing availability of highly detailed and accurate three-dimensional (3D) geospatial data are currently pushing the 3D change detection analysis towards a new 3D mapping frame. In this paper, medium-term changes (8 years) at a coastal rocky cliff are quantified using and comparing 2.5D and 3D methods to estimate the volume of rockfalls and three datasets: one Terrestrial Laser Scanner (TLS) acquired in 2010 and two coincident Unmanned Aerial Vehicles (UAV: multirotor and fixed-wing) datasets acquired in 2018. Advantages and limitations of these techniques, platforms and methods are discussed and the role of Ground Control Points (GCPs) distribution was analysed. Maps of 3D changes were produced by means of the Multiscale-Model-to-Model Cloud-Comparison algorithm (M3C2). The volume of the eroded-deposited material was estimated using two 2.5D and one 3D approaches: 1) rasterizing M3C2 distances using a conventional top-view perspective, 2) rasterizing the M3C2 distances rotated and orientated with the z vector normal and, 3) for the largest rockfalls, the volume was estimated using the Poisson Surface Reconstruction (PSR) algorithm (3D). The 3D models produced using both UAV platforms showed cm-level accuracies with Root Mean Square Error (RMSE) of 0.02 and 0.03 m for the multirotor and the fixed-wing, respectively, and faithfully represented cliff geometry. GCP configuration analysis showed that, at least, two stripes of GCPs evenly distributed at different heights are necessary, but three are recommended. The spatial pattern of change between the TLS and the two UAVs datasets was similar. The quantification of the volume of the eroded-accumulated material (using the M3C2 distances and the two UAV datasets) resulted in significant differences as the fixed-wing underestimated the values calculated using the multirotor dataset. The 2.5D strategies used to quantify the volume of change underestimated the eroded volume of the largest rockfalls (compared to the PSR 3D method), which provided the most accurate volume estimates.