THE LEAST-SQUARES MIXING MODELS TO GENERATE FRACTION IMAGES DERIVED FROM REMOTE-SENSING MULTISPECTRAL DATA

被引：432

作者：

SHIMABUKURO, YE ^{[1
]}

SMITH, JA ^{[1
]}

机构：

[1] NASA,GODDARD SPACE FLIGHT CTR,GREENBELT,MD 20771

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 1991年 / 29卷 / 01期

关键词：

D O I：

10.1109/36.103288

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：

The remote sensing instrumentation measures the spectral radiance reflected or emitted within its instantaneous field of view (IFOV). At target level, this means to sense the spectral radiance reflected or emitted by a finite target area (pixel). The pixel size in present-day remote sensing systems is large enough to include different types of land cover. The Constrained Least Squares (CLS) and Weighted Least Squares (WLS) mixing models to generate fraction images derived from remote sensing multispectral data are presented. An experiment considering three components within the pixels-eucalyptus, soil (understory), and shade-was performed. The generated fraction images for shade (shade image) derived from these two methods were compared by considering the performance and computer time. The derived shade images are related to the observed variation in forest structure; i.e., the fraction of inferred shade in the pixel is related to different eucalyptus ages.

引用

页码：16 / 20

页数：5

共 13 条

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