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Land cover classification concept for anisotropy correction in hyperspectral imagery


Weyermann, J; Schläpfer, D; Hueni, A; Kneubühler, M; Itten, K I (2009). Land cover classification concept for anisotropy correction in hyperspectral imagery. In: 6th Workshop on Imaging Spectroscopy, Tel Aviv, Israel, 16 March 2009 - 19 March 2009, 1-6.

Abstract

An empirical (target-) BRDF normalization method has been implemented for hyperspectral data processing, following the approach of Kennedy, published in 1997. Correction results of this method highly depend on the successful application of an appropriate spectral pre-classification
which necessarily must be insensitive to reflectance anisotropy.
A standard classification output (as of ATCOR-4) is first evaluated for its suitability concerning anisotropy normalization. A hierarchical BRDF selection scheme is then set up, covering the most prominent target classes in the image. A classification algorithm is then evaluated on the basis of a standard spectral angle mapper (SAM) approach with the RSL’s spectral database SPECCHIO attached for reference spectra evaluation. Results show that the ATCOR-4 pre-classification output is highly sensitive to the reflectance anisotropy and therewith not suited for pre-classification. The SAM pre-classification is still under investigation, but first tests using reference spectra out of the reflectance data itself showed problems due to the high robustness against brightness differences
since a gradient must be estimated from targets of comparable brightness.

Abstract

An empirical (target-) BRDF normalization method has been implemented for hyperspectral data processing, following the approach of Kennedy, published in 1997. Correction results of this method highly depend on the successful application of an appropriate spectral pre-classification
which necessarily must be insensitive to reflectance anisotropy.
A standard classification output (as of ATCOR-4) is first evaluated for its suitability concerning anisotropy normalization. A hierarchical BRDF selection scheme is then set up, covering the most prominent target classes in the image. A classification algorithm is then evaluated on the basis of a standard spectral angle mapper (SAM) approach with the RSL’s spectral database SPECCHIO attached for reference spectra evaluation. Results show that the ATCOR-4 pre-classification output is highly sensitive to the reflectance anisotropy and therewith not suited for pre-classification. The SAM pre-classification is still under investigation, but first tests using reference spectra out of the reflectance data itself showed problems due to the high robustness against brightness differences
since a gradient must be estimated from targets of comparable brightness.

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Additional indexing

Item Type:Conference or Workshop Item (Other), not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:19 March 2009
Deposited On:22 Oct 2009 15:17
Last Modified:21 Nov 2017 14:24
Publisher:European Association of Remote Sensing Laboratories
Additional Information:The paper will be published in Proceedings of the 6th EARSeL SIG IS workshop
Official URL:http://www.earsel6th.tau.ac.il/Programme.html

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