首先对遥感影象统计分析方法模型进行了回顾和综述，并分析了传统统计分析模型存在的缺陷，然后分别从传统的地学分析方法、神经计算模型、进化计算模型、稳健统计理论等几个不同的角度，提出了遥感数理统计分析模型扩展的方向，并通过几个具体模型对遥感统计分析扩展模型进行了初步探讨。

In this paper, a particular review on traditional remote sensing statistical analysis model is made and their defects are analyzed from several aspects especially brought by the statistical assumption of its unimodal probability density functions and parametrical density distribution model. On the basis of traditonal statistical model, some intelligent ways of extensions are proposed, where the major attentions are paid on integration with geo knowledge processing unit and computation with other artificial intelligence approaches such as fuzzy logic, conventional geo analysis, robust statistics, neural computation, and evolutionary computation. Finally, several detailed approaches of extensions of statistical remote sensing analysis model, such as RBF, GMDD, and knowledge integrated model, are introduced and discussed briefly.