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Cited by 663

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The least-squares mixing models to generate fraction images derived from remote sensing multispectral data

Shimabukuro, Y.E., Smith, J.A.·1991·IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/36.103288
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Abstract

Constrained-least-squares (CLS) and weighted-least-squares (WLS) mixing models for generating 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.>

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Metadata

Authors
Shimabukuro, Y. E., & Smith, J. A.
Venue
IEEE Transactions on Geoscience and Remote Sensing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1991
Volume
29
Issue
1
Pages
16-20
ISSN
0196-2892 (ISSN-L)
DOI
10.1109/36.103288
OpenAlex
W2118798900
Cited by
663
References
0
FWCI
19.43
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The least-squares mixing models to generate fraction images derived from remote sensing multispectral data. https://app.cochat.ai/papers/10.1109/36.103288
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Shimabukuro, Y. E., & Smith, J. A. (1991). The least-squares mixing models to generate fraction images derived from remote sensing multispectral data. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/36.103288

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