Ai4Fapar: How artificial intelligence can help to forecast the seasonal earth observation signal

This paper investigated the potential of a multivariate Transformer model to forecast the temporal trajectory of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) for short (1 month) and long horizon (more than 1 month) periods at the regional level in Europe and North Africa. The input data covers the period from 2002 to 2022 and includes remote sensing and weather data for modelling FAPAR predictions. The model was evaluated using a leave one year out cross-validation and compared with …

africa artificial artificial intelligence cs.lg earth earth observation europe forecast horizon intelligence multivariate observation paper physics.ao-ph regional signal temporal trajectory transformer transformer model