Geodetic Documentation Centers collect geodetic and cartographic resources. The resources include spatial data and their metadata. European Union INSPIRE directive imposes an obligation on GDC to publish selected data in the Internet. In this paper, an adequate form of publication is discussed on the base of iGeoMap application.

The Internet application iGeoMap merges data from various resources. Depending on the data to present, different types of resources are used. The application can publish spatial data from files (text or binary), a database specialized in spatial data service (PostgreSQL, ORACLE), or web services (Web Map Service, Web Feature Service). Utilization of various data sources by the application is presented in this paper.

As a part of the subject, searches of the most popular data (parcels, address points, and control points) are discussed. Various data sources and searching mechanisms involved by the searches in iGeoMap are presented in use cases.

https://link.springer.com/content/pdf/10.1007%2F978-3-642-31095-9_35.pdf

Publication of geodetic documentation center resources on internet

Spatial analysis is a spatial data analysis technique based on the location and the shape of the geographical object. In this paper, we introduce two spatial data types provided by SQL Server 2008 which refers to Geometry and Geography. As with Shapefile data structure supported by ESRI, Geometry and Geography are object oriented data structures which make it more easily to store semantic information and spatial relationship. In this paper, the spatial analytic characteristics of Geometry and Geography are discussed based on the Geometry data structure with its supported algorithms for spatial analysis and reasoning. An example of finding interested objects within a defined distance to a city road is discussed. At last, some future research in the area of semantics-enabled analysis of geographic information in terms of ontology combining with spatial database engine of Microsoft SQL Server are bring forward.

Spatial analysis on SQL Geography and Geometry data

An efficient processing of k nearest neighbors queries is of critical importance to location based server with the ever-increasing deployment and use of mobile technologies. Voronoi diagram is applied broadly to query neighbors in geospatial context with which the definition of validity region and influence sets of a query q can be described. However, the quantity of neighbors of a spatial object in the Voronoi diagram is computed by connected relationship of polygons in the diagram which is influenced by the spatial distribution of local spatial objects. So, sometimes, it is impossible to determine the k nearest neighbors from Voronoi diagram directly. With the spatial reasoning processing, a method for the k nearest neighbors query processing is discussed in this paper.

Algorithm of the k nearest neighbor for the mobility inquirer

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Spatial analysis on SQL Geography and Geometry data

Algorithm of the k nearest neighbor for the mobility inquirer