Estimation of rubber tree healthiness level using spectral indices / Aini Mardhiah Azmi

Rubber trees play an important role as a carbon dioxide sequester from the atmosphere at a rate comparable to if not better than the natural forest. Rubberwood is economically and socially important. Rubberwood has traditionally been used as a low-cost source of supports the effectiveness in most countries where rubber plantations are plentiful, such as for industrial brick burning, tobacco curing, or locomotive engine fueling. This study aims to using image classification and vegetation indices to find the rubber trees. In this study Sentinel 2 image will be used for healthiness detection using vegetation analysis. The goals of this study were to I examine the precision of unsupervised classification for determining to identify NDVI of Rubber tree in year 2015,2018 and 2021 and to analysis the healthiness of rubber tree. NDVI was used in the study to identify vegetation indexes. This study is very important for farmers to produce better rubber tree products by using remote sensing methods as well as identifying the location where rubber trees are located. The results will be proven by analyzing the accuracy of image classification and creating a Vegetation index map. For the determination of the environmental impact of the rubber tree plantation, which will result in greater rubber tree productivity, accurate information about rubber tree plantations and the healthiness of the plantations will be of great assistance.