Validation of BiPLS for improving yield estimation of rice paddy from hyperspectral data in West Java, Indonesia

Rice is one of the important agricultural crops and constitutes major staple food for Asian countries, especially in Indonesia. Monitoring and management of paddy fields are one of key factors for ensuring national food security, and remote sensing technology and its data, especially hyperspectral data, are expected to be a highly effective solution. The objective of this paper is to use airborne hyperspectral data and yield data to develop and validate a high performance prediction model based on a statistical technique for yield of rice paddy.