Features are variables that compose the data input of a machine learning (ML) model. In ML, it is typically referred to as input variables or dependent variables. In the context of EO these can be the pixel values of different spectral bands in optical data or the values of backscatter coefficients in different polarisations for SAR data. Moreover, EO features can also be derived from different derived variables, such as vegetation indexes (NDVI ) or HH polarization ratios. The process of using domain knowledge to extract features suitable for training a ML model from raw input data is termed feature engineering.