Morphological, Morphometric, and Distribution Pattern Characteristics of Optimal Harvest Phase Sago in Forest Area Based on Drone Imagery

The development of remote sensing systems is considered an important innovation in supporting the optimization of today's food crop production, especially the development of sensor technology that can capture detailed variations in plant information. On the other hand, Sago is one of the food crops that is considered to have the potential for development to improve the community's economy and increase global food security. The main objective of this study is to extract the morphological characteristics, morphometry, and distribution patterns of sago in the optimal harvest phase in non-cultivated areas. Very high-resolution Drone imagery was produced through recording with a flight height of 50 meters above the ground using the DJI Mavic 3 Pro. Samples of sago stand coordinates in the optimal harvest phase were collected through field observations. The characteristics of each sample were extracted through a visual interpretation approach and the nearest neighbor analysis technique. The results showed that the morphological and morphometric characteristics of sago stands in the optimal harvest phase can be assessed from Drone Imagery. Each sample shows the same pattern with the shape of trees, leaflets, and canopies that stand out in one clump and have 3-6 young leaflets. The average morphometric parameters of the optimal harvest phase showed low correlation and were randomly distributed with very sparse distances between stands (around 7 trees/ha).