Identifying an instantaneous coastline through remote sensing data poses a challenge due to various factors, such as the intricate nature of the coast and the selection of the appropriate sensor with its inherent spatial resolution. Even so, accurate identification of the coastline through remote sensing data has immense potential to provide reliable and timely information about the coastal environment. The purpose of this study was to evaluate whether there are spatial differences when detecting a coastline by means of multiple remote sensors. We vectorized orthomosaics from UAV flights during high, mean, and low tides manually, creating three reference baselines. The cross-shore distances from the three vectors were compared to the coastline vectors extracted from a water index, using six different satellite data collected on the nearest possible date to that of the UAV flights, with MODIS Terra, Landsat 8, Sentinel-2, RapidEye, PlanetScope, and Google Earth. The results indicate that the cross-shore distance of the coastline vectors depended directly on the spatial resolution of the sensors. Concerning the mean tide, Google Earth provided the highest accuracy, with a marginal error of 6.7 m, while MODIS provided the largest difference with a margin of 449 m. Our results indicate that future satellite-derived coastline detection approaches should consider the relationship between tide amplitude and spatial resolution on sandy shores.