Analysis of the health level of oil palm plants using drone multispectral data in Part of Dumai City, Riau Province

Abstract Drone technology is currently increasingly developing, one of which is with multispectral sensors. Multispectral drones are very suitable for vegetation identification. Oil palm plants are the main commodity in Dumai, but they have varying health conditions. The aim of this research is to analyze the health level of oil palm plants in parts of Dumai City, Riau Province, and to determine the distribution of health types of oil palm plants. The method used is drone photography, followed by processing it into an analysis of the health level of oil palm plants. The classification of the health level of oil palm plants utilizes the Normalized Difference Vegetation Index (NDVI) method based on the greenness of the plants. The research results show three classifications of oil palm plant health levels: healthy palms, unhealthy palms, and dead palms. Healthy palms have a value range of 0.33 – 0.98, unhealthy palms have a value range of 0 – 0.32, and dead palms have a value range of -1 – 0. The results in Dumai City are predominantly healthy oil palms, totaling 14,674 trees. This is followed by unhealthy oil palms with 7,921 trees, and the lowest is dead oil palms with 19 trees. This study was limited to determine the health level of oil palm plants. Impact for future work that is for the mapper if you want to know the analysis of the health level of oil palm plants can use the NDVI method as in this study.