Effects of GA on the inversion of linear and nonlinear remote sensing models

In this paper, GA is used to invert remote sensing models to identify its applicability in remote sensing. For convenience the linear spectral mixing model and the GOMS model are used as the representation of linear and nonlinear models respectively. The inverse results by GA are compared with two common deterministic search algorithms. Our results show that for linear models, there is only difference in terms of efficiency between algorithms, but for nonlinear models, GA is much better than its counterpart in terms of accuracy, and percentage of successful solutions.