草场资源遥感调查专家系统模型

本文根据专家系统及草场综合分类原理研制了一个草资源遥感调查专家系统原型(GRINS)。GRIES具有与一般专家系统相同的结构,并以模块化编程。系统中设计了一个非精确推理模型以对知识和数据的不确定性与不完全性进行表示和处理。实验结果证明GRIES能充分利用各种辅助信息及专家的知识和经验进行草场资源调查,提高了影象的分类精度。通过对知识库及数据库的适当更改,GRIES还可用于植被、土地利用等遥感资源调查领域。

An Expert System Model of Grass Resource Investigation by Using Remote Sensing Data

According to the theory of expert system and the principle of complex classification of grass land, a prototype of grass resource investigation expert system by remote sensing is developped. The system——GRIES (Grass Resource Investigation Expert System) has the same structure as a usual expert system. The authors design an model of uncertain inference to solve the uncertainty and uncomplety of the knowledge and the data. With the experiments of some examples, a combination of the technique of expert system and remote sensing can make full use of various auxiliary-information to overcome the disadvantages existing in maximum-likelyhood classification. At the meanwhile, GRIES can take the advantage of the knowledge and experiences of the experts to improve the accuracy of classification. After some changes of the knowledge-base and the data-base, GRIES can also be used in the areas such as vegetation field analysis, landuse investigation, predication of growth of crops and other kinds of resources investigation by remote sensing.