Classification of airborne laser scanning data in wadden sea areas using conditional random fields

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Schmidt, A.; Rottensteiner, F.; Soergel, U.: Classification of airborne laser scanning data in wadden sea areas using conditional random fields. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences [XXII ISPRS Congress, Technical Commission I] 39 (2012), Nr. B3, S. 161-166. DOI:

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Sum total of downloads: 76

In this paper we investigate the influence of contextual knowledge for the classification of airborne laser scanning data in Wadden Sea areas. For this propose we use Conditional Random Fields (CRF) for the classification of the point cloud into the classes water, mudflat, and mussel bed based on geometric and intensity features. We learn typical structures in a training step and combine local descriptors with context information in a CRF framework. It is shown that the point-based classification result, especially the completeness rate for water and mussel bed as well as the correction rate of water, can be significantly improved if contextual knowledge is integrated. We evaluate our approach on a test side of the German part of the Wadden Sea and compare the results with a Maximum Likelihood Classification.
License of this version: CC BY 3.0
Document Type: article
Publishing status: publishedVersion
Issue Date: 2012
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 62 81.58%
2 image of flag of United States United States 2 2.63%
3 image of flag of Canada Canada 2 2.63%
4 image of flag of Brazil Brazil 2 2.63%
5 image of flag of Netherlands Netherlands 1 1.32%
6 image of flag of Italy Italy 1 1.32%
7 image of flag of India India 1 1.32%
8 image of flag of Greece Greece 1 1.32%
9 image of flag of France France 1 1.32%
10 image of flag of Switzerland Switzerland 1 1.32%
    other countries 2 2.63%

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