Applications of Sensitivity Analysis in Remote Sensing

Abstract

In this chapter we consider the practical applications of sensitivity analysis in remote sensing. After a brief review of various types of sensitivities, we consider three main areas of applications: the error analyses of input and output parameters and the solution of inverse problems. The error analysis of output parameters with given errors of input parameters is most straightforward. The corresponding algorithm involves, essentially, only matrix multiplication. The error analysis of input parameters with given requirements to errors of output parameters becomes more complicated if the matrix of sensitivities cannot be inverted directly. The solution of inverse problems is the most sophisticated area of application of sensitivity analysis. Here, the simple forms of least squares method and of the method of statistical regularization are presented.