Towards Nationwide Mapping of Seagrasses in the Philippines: Empowering Students through Remote Sensing Education

Abstract

Seagrasses are critical marine ecosystems facing numerous threats in the Philippines. This study aimed to develop a robust methodology for nationwide seagrass mapping using open-access satellite imagery and empower students to contribute through remote sensing education. We achieved this through a two-pronged approach: (1) developing a satellite-based mapping methodology and (2) training students to apply this method across the archipelago. Utilizing Sentinel-2 satellite images, we processed the data using SNAP and Google Earth Engine to identify seagrass beds. Before classification, the images underwent preprocessing steps including land masking, water column correction, and extraction of shallow water bathymetry. These processed layers were then stacked with Sentinel-2 bands 2, 3, 4, 8, and 11. Two classification methods, support vector machine, and random forest, were employed, and their results were compared with existing seagrass maps. Students achieved overall accuracies ranging from 70 to 90 percent. Prior to mapping activities, students received training on remote sensing techniques and seagrass ecology. This project demonstrates the potential of remote sensing for large-scale seagrass mapping and highlights the value of student engagement in marine conservation.