Comparative Assessment of UAV and CoastSnap Data for Shoreline Change Monitoring Using DSAS Metrics: A Case Study from Southern Brazil

This study assesses the comparative performance of two geotechnologies for shoreline monitoring—Unmanned Aerial Vehicle (UAV) surveys and CoastSnap citizen-science imagery—at Guarita Beach, southern Brazil. The analysis was based on twelve paired monitoring dates distributed over a two-year interval. Shorelines were extracted from the wet–dry line, manually digitized from UAV orthomosaics, and automatically detected from CoastSnap images with subsequent quality control. Shoreline change was quantified in the Digital Shoreline Analysis System (DSAS) using the Shoreline Change Envelope (SCE) and the Linear Regression Rate (LRR). The SCE showed the highest equivalence between methods, with a mean difference close to zero (−0.14 m) and no evidence of systematic bias. For LRR, values derived from CoastSnap tended to be lower than those derived from UAVs (mean difference = −2.14 m year−1), although without statistically significant divergence at the adopted significance level. The results demonstrate that the agreement between CoastSnap and UAV data depends directly on the metric analyzed: SCE was more robust for inter-method comparison, whereas LRR was useful for medium-term trend interpretation but more sensitive to uncertainty propagation. Overall, CoastSnap did not replace UAV surveys, but it proved to be a valuable complementary tool for expanding temporal coverage in coastal monitoring programs.