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Comparison of different approaches of selecting endmembers to classify agricultural land by means of hyperspectral data (DAIS7915) - Zurich Open Repository and Archive


Kneubühler, Mathias; Schaepman, Michael E; Kellenberger, Tobias W (1998). Comparison of different approaches of selecting endmembers to classify agricultural land by means of hyperspectral data (DAIS7915). In: IGARSS 1998, Seattle, USA, 6 July 1998 - 10 July 1998, 888-890.

Abstract

A major problem in classification of hyperspectral datasets is the reliable selection of reference spectra to classify heterogeneous vegetated areas. In this work, different approaches of end-member collection for spectral unmixing of hyperspectral data are presented, evaluated and compared to each other. The selected methods include high resolution ground spectroradiometric measurements, a scene based approach and modelling of the end-member spectra using a SVAT (soil-vegetation-atmosphere-transfer) approach. The presented methods are discussed and verified with an extensive ground truth collected in the observed area.

Abstract

A major problem in classification of hyperspectral datasets is the reliable selection of reference spectra to classify heterogeneous vegetated areas. In this work, different approaches of end-member collection for spectral unmixing of hyperspectral data are presented, evaluated and compared to each other. The selected methods include high resolution ground spectroradiometric measurements, a scene based approach and modelling of the end-member spectra using a SVAT (soil-vegetation-atmosphere-transfer) approach. The presented methods are discussed and verified with an extensive ground truth collected in the observed area.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:10 July 1998
Deposited On:17 Jun 2014 14:50
Last Modified:20 Feb 2017 08:24
Publisher:s.n.
ISBN:0-7803-4403-0
Publisher DOI:https://doi.org/10.1109/IGARSS.1998.699616
Official URL:http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=699616&tag=1

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