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Multispectral imaging of land surface

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Abstract

An airborne spectroscopic image was flown over an intensively used agricultural area and over a location which had suffered from a forest fire. Many surfaces feature details could be indentified either from synthesized near true color images, from the normalized differential vegetation index (NDVI), from a principal component analysis or by treating the data with an unsupervised neural network. A comparison of the individual results demonstrates the strength of each method.

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Authors and Affiliations

  1. Institute of Space Science, Free University Berlin, Fabeckstr. 69, 14195, Berlin, Germany

    Furrer R. (Prof. Dr.)

  2. Berlin Space Institute Inc. (WIB GmbH), Lassenstr. 11–15, 14193, Berlin, Germany

    Furrer R. (Prof. Dr.) & Barsch A. (Dr.)

  3. Institute of Space Science, Free University Berlin, Fabeckstr. 69, 14195, Berlin, Germany

    Olbert C. & Schaale M. (Dr.)

Authors
  1. Furrer R.
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  2. Barsch A.
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  3. Olbert C.
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  4. Schaale M.
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Furrer, R., Barsch, A., Olbert, C. et al. Multispectral imaging of land surface. GeoJournal 32, 7–16 (1994). https://doi.org/10.1007/BF00806350

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  • DOI: https://doi.org/10.1007/BF00806350

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