ANALISA JENIS MANGROVE MENGGUNAKAN CITRA UAV DENGAN KLASIFIKASI OBIA - Woody A. Timisela; Gun Mardiatmoko; Ferad Puturuhu (Program Studi Manajemen Hutan, Pascasarjana Universitas Pattimura, 2020)
The difficulty of the inventory carried out in the mangrove forest area is due to the vast expanse of ​​mangrove forests with a high-density level, so it must use High-Resolution Satellite Imagery (CSRT) which requires high costs. The approach to processing very high-resolution images is the object-based approach (OBIA). UAV technology development using cameras mounted on UAVs has been widely used in forest inventories that have benefits, low costs, and high flexibility. Therefore, this study aims to analyze the types of mangroves using UAV images with OBIA classification and calculate the tree canopy height model in mangrove forests. The results showed that the accuracy-test used a confusion matrix with Producer accuracy for BG 78%, CT 97%, RS 96.63%, RA 91.04%. In comparison, the user accuracy for BG is 88.89%, CT 97.73%, RS 97.73%, and RA 85%. Thus the overall efficiency is 92.98%.