Applications of Sensitivity Analysis in Remote Sensing
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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.
KeywordsRandom variables Error analysis Inverse problems
- This chapter is, essentially, a compilation of material, which can be found in a number of sources. The most prominent publication used here, is the book written by Clive Rodgers (2000). A useful complementary material can be found in Press et al. (1992).Google Scholar
- Rodgers CD (2000) Inverse methods for atmospheric sounding: theory and practice (series on atmospheric, oceanic and planetary physics). World Scientific, SingaporeGoogle Scholar
- Press WS, Flannery BP, Teukolsky SA, Vetterling WT (1992) Numerical recipes in Fortran 77: the art of scientific computing. Cambridge University Press, CambridgeGoogle Scholar