Abstract:
Mangroves are important trees that live in swamp areas. Many mangroves are damaged and need preservation. Monitoring
mangroves is important for preservation, but it is difficult access by ground and requires a lot of effort and time. There is currently
no system specifically to monitor mangrove forest. Therefore this research created mangrove forest density health system. The system
gather data using drone to easily gather data from the forest. Then mangrove tree is being detected using YOLO object detector.
Experiment shows that YOLO object detector is able to detect mangrove tree accurately with 95% recall, 88.3% IoU, and 22ms
processing time. Then the system calculates the density for mangrove forest health. With this system, environmental surveys and
monitoring for mangrove forest can be conducted, and resulting density data can be used for effective preservation action.
