LAI INVERSION USING A BACKPROPAGATION NEURAL-NETWORK TRAINED WITH A MULTIPLE-SCATTERING MODEL

被引：74

作者：

SMITH, JA

机构：

[1] NASA Goddard Space Flight Center, Greenbelt

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 1993年 / 31卷 / 05期

关键词：

D O I：

10.1109/36.263783

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Standard regression methods applied to canopies within a single homogeneous soil type yield good results for estimating leaf area index (LAI) but perform unacceptably when applied across soil boundaries. In contrast, the neural network reported here generally yielded absolute percentage errors of < 30%. The network was applied, without retraining, to a Landsat TM.

引用

页码：1102 / 1106

页数：5

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