The oil palm industry in Malaysia experienced substantial growth in 2021, reaching over 5.7 million ha [1]. However, G. boninense pathogen causing basal stem rot (BSR) disease has posed a severe threat to the industry.

Remote sensing, particularly through ground-based [2,3], airborne [4] and satellite platforms [5], has shown promise in efficiently detecting the BSR disease. Ground-based sensing is impractical for big plantations and has limited data coverage. Satellite images are limited since Malaysia's location at the equator makes it hard to have a cloudless sky. Hence, this study proposes a solution to the threat of BSR disease by leveraging unmanned aerial vehicles (UAVs) equipped with multispectral and thermal sensors, combined with machine learning techniques.