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A snake-based approach for TIGER data conflation / W. Song in Cartography and Geographic Information Science, vol 33 n° 4 (October 2006)  

Public [article]  inCartography and Geographic Information Science > vol 33 n° 4 (October 2006) . - pp 287 - 298 Titre : A snake-based approach for TIGER data conflation Type de document : Article/Communication Auteurs : W. Song, Auteur ; L. Haithcoat, Auteur ; J.M. Keller, Auteur Année de publication : 2006 Article en page(s) : pp 287 - 298 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] axe médian [Termes IGN] données vectorielles [Termes IGN] fusion de données multisource [Termes IGN] intégration de données [Termes IGN] noeud [Termes IGN] précision de localisation [Termes IGN] réseau routier [Termes IGN] route [Termes IGN] Topologically Integrated Geographic Encoding and Referencing Résumé : (Auteur) The TIGER (Topologically Integrated Geographic Encoding and Referencing) system has served the U.S. Census Bureau and other agencies' geographic needs successfully for two decades. Poor positional accuracy has however made it extremely difficult to integrate TIGER with advanced technologies and data sources such as GPS, high resolution imagery, and state/local GIS data. In this paper, a potential solution for conflation of TIGER road centerline data with other geospatial data is presented. The first two steps of the approach (feature matching and map alignment) remain the same as in traditional conflation. Following these steps, a third is added in which active contour models (snakes) are used to automatically move the vertices of TIGER roads to high-accuracy roads, rather than transferring attributes between the two datasets. This approach has benefits over traditional conflation methodology. It overcomes the problem of splitting vector road line segments, and it can be extended for vector imagery conflation as well. Thus, a variety of data sources (GIS, GPS, and Remote Sensing) could be used to improve TIGER data. Preliminary test results indicate that the three-step approach proposed in this paper performs very well. The positional accuracy of TIGER road centerline can be improved from an original 100 plus meters' RMS error to only 3 meters. Such an improvement can make TIGER data more useful for much broader application. Copyright CaGISociety Numéro de notice : A2006-589 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1559/152304006779500669 En ligne : https://doi.org/10.1559/152304006779500669 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28312 [article]

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