Summary
A general trend in remote sensing image analysis can be observed today away from multispectral methods towards structural analysis. Multispectral information is, however, indispensable for land cover identification in agriculture, forestry and the natural environment. This contribution tries to point out the synergetic effects to be achieved by combined use of multispectral and of structural concepts. Spatial subpixel analysis as a preprocessing step for segmentation and multispectral classification is described. A procedure for combined subpixel-fine segmentation and classification is presented. Possibilities for radiometric calibration for enabling the use of general spectral knowledge sources are proposed.
*This work was financed by the Austrian “Fonds zur Forderung der wissenschaftlichen Forschung” (project S7003).
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References
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© 1999 Springer-Verlag Berlin · Heidelberg
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Schneider, W. (1999). Land Cover Mapping from Optical Satellite Images Employing Subpixel Segmentation and Radiometric Calibration*. In: Kanellopoulos, I., Wilkinson, G.G., Moons, T. (eds) Machine Vision and Advanced Image Processing in Remote Sensing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60105-7_21
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DOI: https://doi.org/10.1007/978-3-642-60105-7_21
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