The Caribbean is one of the world’s most vulnerable regions to the projected impacts of climate change, and changes in coral reef ecosystems have been studied over the last two decades. Lately, new technology-based methods using satellites and unmanned vehicles, among others have emerged as tools to aid the governance of these ecosystems by providing managers with high-quality data for decision-making processes. This paper addresses the development of a Google Earth Engine (GEE)-based application for use in the management processes of shallow coral reef ecosystems, using images acquired with Remotely Piloted Aircraft Systems (RPAS) known as drones, at the Old Providence McBean Lagoon National Natural Park; a Marine Protected Area (MPA) located northwest of Old Providence Island, Colombia. Image acquisition and processing, known as drone imagery, is first described for flights performed using an RTK multispectral drone at five different monitoring stations within the MPA. Then, the use of the GEE app is described and illustrated. The user executes four simple steps starting with the selection of the orthomosaics uploaded to GEE and obtaining the reef habitat classification for four categories: coral, macroalgae, sand, and rubble, at any of the five monitoring stations. Results show that these classes can be effectively mapped using different machine-learning (ML) algorithms available inside GEE, helping the manager obtain high-quality information about the reef. This remote-sensing application represents an easy-to-use tool for managers that can be integrated into modern ecosystem monitoring protocols, supporting effective reef governance within a digitized society with more demanding stakeholders.

This study assesses Hurricane Iota’s impact on Providencia island’s reef environments, using Google Earth Engine, Satellite Derived Bathymetry, and machine learning to calculate a supervised classification process to delineate six geomorphic reef units. Results reveal dynamic changes, including erosion in the Lagoon unit (4.47% pre-Iota, 2.27% post-Iota), loss on the Back Reef (38.14%), and Rock Terrace (6.15%). Reef Ridge showed minimal change, acting as an effective wave barrier. Back Reef and the deep Rock Terrace experienced significant erosion (−3 to −14 m) to the northeast, with sedimentary dynamics observed in deeper units (up to 22 m). The high thematic accuracies found (Kappa 99%) illustrate the effectiveness of the assessment to (i) map the reef rapidly, (ii) provide tools for long-term monitoring of changes over time and (iii) improve management strategies and decision-making.