This research aims to analyze land cover/use classes in protected forest areas in Ambon City. The method used in this research is guided classification Maximum Likelihood Classification (MLC), where this method classifies images based on the similarity of the image spectrum to conditions in the field. Based on research results, land cover in the Mount Sirimau protected forest in 2024 consists of 7 land cover classes, namely: primary dry land forest, secondary dry land forest, open land, settlements, dry land agriculture, mixed dry land agriculture, and shrubs. The Mount Nona protected forest in 2024 will have 4 land cover classes, namely: secondary dry land forest, dry land agriculture, mixed dry land agriculture, and shrubs. The image accuracy test was carried out using a confusion matrix (comparison of image interpretation with field conditions) with an accuracy level of 92%.
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