TY - JOUR

T1 - Integration of heterogeneous geospatial data in a federated database

AU - Butenuth, Matthias

AU - Gösseln, Guido v.

AU - Tiedge, Michael

AU - Heipke, Christian

AU - Lipeck, Udo

AU - Sester, Monika

N1 - Funding information: This work is part of the Geotechnologien project funded by the Federal Ministry for Education and Research (BMBF) and the German Council (DFG) under contract no. 30F0374A. The IKONOS images are provided by EC-MARS Programme—distributed by European Space Imaging, EUSI, 2004. The support is gratefully acknowledged.

PY - 2007/6/1

Y1 - 2007/6/1

N2 - The integration of heterogeneous geospatial data offers possibilities to manually and automatically derive new information, which are not available when using only a single data source. Furthermore, it allows for a consistent representation and the propagation of updates from one data set to the other. However, different acquisition methods, data schemata and updating cycles of the content can lead to discrepancies in geometric and thematic accuracy and correctness which hamper the combined integration. To overcome these difficulties, appropriate methods for the integration and harmonization of data from different sources and of different types are needed. In this paper we describe two generic cases including novel integration algorithms, namely the integration of two heterogeneous vector data sets, and the integration of raster and vector data. Both algorithms are linked to a federated database which allows for automatic object matching and for managing n:m relationships. We describe and illustrate our work using vector data from topography and the geosciences, as well as multi-spectral imagery.

AB - The integration of heterogeneous geospatial data offers possibilities to manually and automatically derive new information, which are not available when using only a single data source. Furthermore, it allows for a consistent representation and the propagation of updates from one data set to the other. However, different acquisition methods, data schemata and updating cycles of the content can lead to discrepancies in geometric and thematic accuracy and correctness which hamper the combined integration. To overcome these difficulties, appropriate methods for the integration and harmonization of data from different sources and of different types are needed. In this paper we describe two generic cases including novel integration algorithms, namely the integration of two heterogeneous vector data sets, and the integration of raster and vector data. Both algorithms are linked to a federated database which allows for automatic object matching and for managing n:m relationships. We describe and illustrate our work using vector data from topography and the geosciences, as well as multi-spectral imagery.

KW - Federated databases

KW - Image analysis

KW - Integration

KW - Matching

KW - Raster data

KW - Spatial infrastructures

KW - Vector data

UR - http://www.scopus.com/inward/record.url?scp=35148825049&partnerID=8YFLogxK

U2 - 10.1016/j.isprsjprs.2007.04.003

DO - 10.1016/j.isprsjprs.2007.04.003

M3 - Article

AN - SCOPUS:35148825049

VL - 62

SP - 328

EP - 346

JO - ISPRS Journal of Photogrammetry and Remote Sensing

JF - ISPRS Journal of Photogrammetry and Remote Sensing

SN - 0924-2716

IS - 5

ER -