Forest protection management are important activities and integrated from the forest resource management system. One of the activities in forest protection is evaluating stand health in a particular forest region. These activities are important because it helps decision making to perform sustainable forest management. Evaluating stand health on a bigger scale needs more cost, time, and manpower. To overcome this obstacle, there is a need for supporting technology. The technology also needs to suffice within the development of remote sensing. flying drones is a suitable technology that could evaluate stand health. This research has the goal to determine the spectral characteristics of A.mangium leaf in order to identify the area and position of sick trees. This research is executed in A.mangium stand at KPH Bogor. The method that is being used is hyperspectral imaging analysis to determine the characteristic of RGB (Red,Green,Blue). Spectral analysis is sampled from 85 trees on 7 plot at site 23B RPH Maribaya BKPH Parung Panjang KPH Bogor using simple random sampling. The result of this research shows that trees in healthy condition, sick condition, and the dead condition has different spectral RGB value. RGB value for healthy trees is 121-149(B1),167-189(B2), 120-142(B3). For sick trees the RGB value is 151-165(B1), 183-205(B2), 145-165(B3). For dead trees the RGB values are 192-202(B1), 202-212(B2), 167-199(B3). As trees condition worsen, the RGB value increases. The pattern of RGB band composition is similar but has different values. This indicates the changing process of leaf color from healthy to sick. On the other hand the interval of RGB band is small enough to notice there is a difference in the color of the tree’s status. This research shows that spectral analysis from drone image could be used to analyze forest’s stand health
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