Object-Based Mangrove Mapping Comparison on Visible and NIR UAV Sensor

Mangrove ecosystems are natural resources that have potential value for development due to their high productivity. Mapping and identification of mangroves have always played a crucial role in mangrove ecosystem conservation efforts, especially to support the sustainable development goal of coastal resources and climate change issues. Several attempts have been made using Unmanned Aerial Vehicle (UAV) techniques acquisition of high spatial resolution aerial images data with various sensors and object-based classification for image processing with various levels of success. This study aims to identify mangrove objects using UAV with true color and NIR false-color sensors using the OBIA approach. The UAV used in this study was DJI Phantom 3 Pro with a true-color sensor (default) and NIR false-color (modified Canon IXUS 160 cameras). The comparison between the two types of sensor of aerial photographs as a source for mangrove mapping proved that the latter performed better than the former because of the near-infrared band can optimally discriminate between mangrove and non-mangrove objects. This will assist future research directions in the mangrove ecosystems mapping method.