Short-Term Shoreline Trend Detection Patterns Using SPOT-5 Image Fusion in the Northwest of Yucatan, Mexico

Shoreline change is an important morphological feature used to identify impacts on coastal processes caused by coastal infrastructure or natural conditions (e.g., storms or sea level rise), providing insightful information for coastal and shoreline management. While shoreline measurements are not always available, remote sensing data can provide shoreline position in scarce data areas, as well as in large and inaccessible regions. Nevertheless, few studies have used multi-temporal remote sensing data to study gradual changes for time frames of less than 10 years due to the low spatial resolution for detecting small changes. In this study, we explore the use of image data fusion from the Satellite Pour l’Observation de la Terre - 5 (SPOT-5), taking into account the accuracy of shoreline mapping to detect changes in both disturbed and undisturbed coasts during 10 years in the northwestern Yucatan coast. Our results show that using image data fusion in SPOT-5 images is a feasible method to detect shoreline change trends in a relatively short time frame. Based on the proposed method, we were able to identify the factors leading to shoreline trends. This methodology proves useful for shoreline management and is appropriate for the planning of future developments in areas for which data are scarce.