Recently, geospatialdata and Geographic Information Systems (GIS) have been increasingly used. As a result, the integration of geospatialdata has become a crucial task for decision makers. Since GIS and geospatial d...
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(纸本)3540482733
Recently, geospatialdata and Geographic Information Systems (GIS) have been increasingly used. As a result, the integration of geospatialdata has become a crucial task for decision makers. Since GIS and geospatialdatabases are designed by different organizations using different representation models and there are diverse levels of detail for the spatial features, it is much more complex to achieve dataintegration in geospatialdatabases. To help matters, context information may be employed to improve two fundamental aspects in geospatial data integration: (1) schema mapping generation and (2) query answering. However, a relevant issue when using context is how to better represent context information. Ontologies are an interesting approach to represent context, since they enable sharing and reusability and help reasoning. In this paper, we propose a context ontology to formally represent context in geospatial data integration. We also present an example where this context ontology is used to improve query processing.
We can adequately study broad global issues and policies only by taking geosciences into *** research and decision-making must share and make effective use of interdisciplinary data sources,models,and *** impedes shar...
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We can adequately study broad global issues and policies only by taking geosciences into *** research and decision-making must share and make effective use of interdisciplinary data sources,models,and *** impedes sharing of data and computing *** from the Open geospatial Consortium(OGC)and other organizations are the basis for successfully deploying a seamless,distributed information infrastructure for the *** specifications now adopted by the OGC consensus process are the result of OGC interoperability *** OGC standards,deployment architectures,and interoperability initiatives are described showing how the OGC standards baseline has been developed and applies to the geosciences.
Since maps are widely available for many areas around the globe, they provide a valuable resource to help understand other geospatial sources such as to identify roads or to annotate buildings in imagery. To utilize t...
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Since maps are widely available for many areas around the globe, they provide a valuable resource to help understand other geospatial sources such as to identify roads or to annotate buildings in imagery. To utilize the maps for understanding other geospatial sources, one of the most valuable types of information we need from the map is the road network, because the roads are common features used across different geospatialdata sets. Specifically, the set of road intersections of the map provides key information about the road network, which includes the location of the road junctions, the number of roads that meet at the intersections (i.e., connectivity), and the orientations of these roads. The set of road intersections helps to identify roads on imagery by serving as initial seed templates to locate road pixels. Moreover, a conflation system can use the road intersections as reference features (i.e., control point set) to align the map with other geospatial sources, such as aerial imagery or vector data. In this paper, we present a framework for automatically and accurately extracting road intersections from raster maps. Identifying the road intersections is difficult because raster maps typically contain much information such as roads, symbols, characters, or even contour lines. We combine a variety of image processing and graphics recognition methods to automatically separate roads from the raster map and then extract the road intersections. The extracted information includes a set of road intersection positions, the road connectivity, and road orientations. For the problem of road intersection extraction, our approach achieves over 95% precision (correctness) with over 75% recall (completeness) on average on a set of 70 raster maps from a variety of sources.
integration of data across multiple independently developed data sources can be challenging due to a variety of heterogeneities that exist across such *** mediation technologies provide approaches for overcoming these...
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integration of data across multiple independently developed data sources can be challenging due to a variety of heterogeneities that exist across such *** mediation technologies provide approaches for overcoming these *** such as Geoscience Markup Language can address some of the heterogeneity issues by providing schema standards which sources can adhere *** article addresses the issue of semantic heterogeneity across information resources by using domain ontologies and registering schema elements and data values to such *** data to ontologies provides a powerful search and dataintegration capability across disparate geoscience information resources.
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