Remotely Piloted Aircraft Systems (RPAS) is a low-cost and useful alternative to track spatial-temporal variations in a rapidly changing environment. However, there is a lack of studies on beach geomorphology characterization in association with visible spectrum reflectance potentialities. The objective of this study was to embrace this technology for coastal change detection. For this purpose, the data set samples are covering the winter season of 2019. The materials used were digital orthophotos, digital terrain models, and geomorphological parameters, such as the Relative Tide Range (RTR) and Omega (Ω). The goals are to (i) classify the beach morphodynamics; (ii) identify the berms, cusps, and rip current channels; (iii) extract RGB indexes to detect the shoreline variability; (iv) assess beach profiles and (v) evaluate the volume of sediments. The study area, Paiva beach, is located in the Northeast of Brazil, which presents significant morphodynamic variations. The results indicate three morphodynamic stages, namely: Rhythmic Bar and Beach (RBB); Transverse Bar and Rip (TBR), and Low Tide Terrace (LTT). The wave climate for the region averaged Dir of 120°, Tp of 9 s, and Hs of 1.8 m. Between June and July, the shoreline had the most significant advance with 51% of the beach extension. On the other hand, between July and August, the beach registered a considerable 88% retreat. The profiles showed a maximum variation of 1.5 m vertically on the berm, a common characteristic of winter profiles, detected in August. For the sediment volume, July and August showed erosion processes with sediment loss of 12,508.58 m3 in the south sector and accretion of 23,052.97 m3 in the north. The planimetric and altimetric mean square error were 2.7 and 4.5 cm, respectively, showing the advantage of high spatial resolution data for morphodynamic classification, and combining it to identify vegetation indexes to detect shoreline variability.