A Methodology for Selection of Optimal Viewing Angles for an Accurate Estimation of Leaf Area Index based on Information Theory

Abstract

More and more wide-view angle or multi-angular sensors provide the possibility to retrieve vegetation parameters. It is an important issue to access the accuracy and uncertainty of the products retrieved from different view angle observations. This paper presents an approach to evaluate the information content of the multi-angular remote sensing data. The proposed method is based on information theory. By using the entropy difference between all unknown parameters and non-target parameters for the remote sensing data, the information content is quantified. The presented methodology revealed the information content in the remote sensing data. The accuracy of the vegetation parameters retrieved from canopy reflectance depends mainly on the information about target parameter contained within observations. The relationship between information content and the LAI inversion accuracy is listed in this paper.