*Ita Carolita Johansyah1, Dede Dirgahayu Domiri1, Jatna Supriatna2, Muhammad Syamsu Rosid2, Anisa Rarasati1, Bambang Hendro Trisasongko 3, Yoga Dwi Putra1
(1.Indonesian National Research and Innovation Agency, 2.Universitas Indonesa, 3.Bogor Agricultural University)
Keywords:Ganoderma, Oil Palm , Optic, SAR
The main factor for the decline in oil palm production in Indonesia is disease. Disease attacks that attack oil palm plants are known to have a major influence on the productivity and quality of oil palm. Root rot disease, also known as Basal stem rot or Ganoderma, is a disease caused by a fungus that attacks the base of oil palm plantations. Symptoms and damage to oil palm plants caused by this disease are clearly visible according to the stage, ranging from changes in leaf color, to the fall of the leaf midrib so that the plant eventually dies. It is possible to use satellites as a tool to detect changes that occur, so that anticipation of Ganoderma attacks can be carried out quickly. This study aims to obtain a Ganoderma attack detection model on oil palm and estimate its severity stage. This study used images with the advantage of having high temporal resolution and having 2 types of sensors, namely optical and SAR. The use of Sentinel 2 and Sentinel 1 in an integrated manner is to take advantage of their respective advantages, where by using Sentinel 2, the optical sensor can take advantage of the sepctral values and their derivatives to identify oil palm conditions, while Sentinel 1, the SAR sensor, can take advantage of the backscatter value which will be more clarify the different conditions of oil palm. The research conducted shows that using optical data, Senitinel 2 gives an estimation of oil palm stiadum with a coefficient of determination of 86% for oil palms aged 11-15 years, while adding SAR data to obtain a higher coefficient of determination.