Abstract
The linear spectral mixture model is presented in its math concept. During this discussion, examples are presented in order to facilitate the reader’s understanding of the concepts involved in the design of the model.
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Burden, R. L., Faires, J. D., & Reynolds, A. C. (1981). Numerical analysis (2nd ed.). Boston: Prindle, Weber and Schmidt.
Conte, S. D., & De Boor, C. (1980). Elementary numerical analysis: An algorithmic approach. McGraw-Hill. 445 p.
Shimabukuro, Y. E., & Smith, J. A. (1995). Fraction images derived from Landsat TM and MSS data for monitoring reforested areas. Canadian Journal of Remote Sensing, 21(1), 67–74.
Spiegel, M. R. (1968). Mathematical handbook of formulas and tables. New York: McGraw-Hill.
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Shimabukuro, Y.E., Ponzoni, F.J. (2019). The Linear Spectral Mixture Model. In: Spectral Mixture for Remote Sensing. Springer Remote Sensing/Photogrammetry. Springer, Cham. https://doi.org/10.1007/978-3-030-02017-0_4
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DOI: https://doi.org/10.1007/978-3-030-02017-0_4
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