[Objective] Through analysis of the model simulated data and ground measured data, the function of principle component transformation method in leaf area index inversion was determined. [ Method] By using PROSPECT and SAIL model,it was simulated under different leaf area index aiming at LANDSAT_5 TM data. Through simulating data, the advantages of principle component transformation method compared with traditional vegetation index were analyzed, and precision verification was carried out through ground measured data. [ Result ] With leaf area index increasing, principle component transformation method could not only effectively weaken the influence of saturation, but also obtain better inversion effect. In 2009,the inversion precision for winter wheat and corn were up to 78% and 91% ,obtaining a higher inversion precision. [Conclusion] The principle component transformation method has a better application prospect in leaf area index inversion.%[目的]通过模型模拟数据和地面实测数据的分析,确定主成分变换方法在叶面积指数反演中的作用.[方法]通过PROSPECT模型和SAIL模型针对LANDSAT_5TM数据进行不同叶面积指数状态下的模拟,通过模拟数据分析主成分变换方法相较于传统植被指数的优势,并通过地面实测数据进行精度验证.[结果]在一定范围内,随着叶面积指数的增大,主成分变换的方法可以在有效减弱饱和现象影响的同时取得较好的反演效果,在2009年冬小麦和玉米的叶面积指数反演中主成分变换方法反演精度达到78％和91％,获得了较高的反演精度.[结论]主成分变换方法在叶面积指数反演方面具有较好的应用前景.
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