The need for mapping Submerged Aquatic Vegetation (SAV) is essential because the benthic habitats are important component of the Philippine marine ecosystem and food chain. A classification system was evaluated for mapping and monitoring benthic habitats and bottom types in shallow tropical marine waters using digital aerial images. The study shows that the use of a consumer-based digital camera mounted on an unmanned aerial vehicle can generate an orthophoto for remote sensing application. The subsequent use of support vector machine is a good classification tool which provided a test result of 85% accuracy for seagrass, and an overall accuracy of above 80% for SAV and bottom type mapping. This accuracy sufficiently provides basis for the local government units in administering rules and regulations in preserving and managing their coastlines.

SAV, unmanned aerial vehicle, coastal mapping, SVM, digital image processing.