Automatic derivation of land-use from topographic data

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  • Federal Agency for Cartography and Geodesy (BKG)
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Details

Original languageEnglish
Pages (from-to)558-563
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume38
Publication statusPublished - 2010
EventJoint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science - Hong Kong, Hong Kong
Duration: 26 May 201028 May 2010

Abstract

The paper presents an approach for the reclassification and generalization of land-use information from topographic information. Based on a given transformation matrix describing the transition from topographic data to land-use data, a semantic and geometry based generalization of too small features for the target scale is performed. The challenges of the problem are as follows: (1) identification and reclassification of heterogeneous feature classes by local interpretation, (2) presence of concave, narrow or very elongated features, (3) processing of very large data sets. The approach is composed of several steps consisting of aggregation, feature partitioning, identification of mixed feature classes and simplification of feature outlines. The workflow will be presented with examples for generating CORINE Land Cover (CLC) features from German Authoritative Topographic Cartographic Information System (ATKIS) data for the whole are of Germany. The results will be discussed in detail, including runtimes as well as dependency of the result on the parameter setting.

Keywords

    Aggregation, CORINE Land Cover, Generalization, Large Vector Data, Processing

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Automatic derivation of land-use from topographic data. / Thiemann, Frank; Sester, Monika; Bobrich, Joachim.
In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 38, 2010, p. 558-563.

Research output: Contribution to journalConference articleResearchpeer review

Thiemann, F, Sester, M & Bobrich, J 2010, 'Automatic derivation of land-use from topographic data', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. 38, pp. 558-563.
Thiemann, F., Sester, M., & Bobrich, J. (2010). Automatic derivation of land-use from topographic data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 38, 558-563.
Thiemann F, Sester M, Bobrich J. Automatic derivation of land-use from topographic data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2010;38:558-563.
Thiemann, Frank ; Sester, Monika ; Bobrich, Joachim. / Automatic derivation of land-use from topographic data. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2010 ; Vol. 38. pp. 558-563.
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T1 - Automatic derivation of land-use from topographic data

AU - Thiemann, Frank

AU - Sester, Monika

AU - Bobrich, Joachim

PY - 2010

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AB - The paper presents an approach for the reclassification and generalization of land-use information from topographic information. Based on a given transformation matrix describing the transition from topographic data to land-use data, a semantic and geometry based generalization of too small features for the target scale is performed. The challenges of the problem are as follows: (1) identification and reclassification of heterogeneous feature classes by local interpretation, (2) presence of concave, narrow or very elongated features, (3) processing of very large data sets. The approach is composed of several steps consisting of aggregation, feature partitioning, identification of mixed feature classes and simplification of feature outlines. The workflow will be presented with examples for generating CORINE Land Cover (CLC) features from German Authoritative Topographic Cartographic Information System (ATKIS) data for the whole are of Germany. The results will be discussed in detail, including runtimes as well as dependency of the result on the parameter setting.

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