Information content of multi-angular remote sensing data

We take the kernel-driven model as an example, focus on the information content definition and calculation of multi-angular remote sensing (MARS) data. We study four methods to measure the information content of MARS data: Fisher statistic, information entropy, determinant and sum of the diagonal elements of the information matrix, how to use the Fisher statistic theory and information entropy to measure the information content of MARS data, to calculate the information content of the dataset on the three unknowns for different subsets of the data. The analyses show that information entropy is a good tool for measuring information content of MARS data.