The development of non-linear spectral unmixing methods in recent years is introduced. There are mainly two types of models. One is the close-mixing model of mineral sand area and the other is multi-level mixing model of vegetation coverage area. The data-driven nonlinear spectral unmixing algorithms such as kernel methods and manifold learning are presented. Both advantages and disadvantages of these models and algorithms are summarized and the future research trends are analyzed.