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A framework for integrating multi-accuracy spatial data in geographical applications

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Abstract

In recent years the integration of spatial data coming from different sources has become a crucial issue for many geographical applications, especially in the process of building and maintaining a Spatial Data Infrastructure (SDI). In such context new methodologies are necessary in order to acquire and update spatial datasets by collecting new measurements from different sources. The traditional approach implemented in GIS systems for updating spatial data does not usually consider the accuracy of these data, but just replaces the old geometries with the new ones. The application of such approach in the case of an SDI, where continuous and incremental updates occur, will lead very soon to an inconsistent spatial dataset with respect to spatial relations and relative distances among objects. This paper addresses such problem and proposes a framework for representing multi-accuracy spatial databases, based on a statistical representation of the objects geometry, together with a method for the incremental and consistent update of the objects, that applies a customized version of the Kalman filter. Moreover, the framework considers also the spatial relations among objects, since they represent a particular kind of observation that could be derived from geometries or be observed independently in the real world. Spatial relations among objects need also to be compared in spatial data integration and we show that they are necessary in order to obtain a correct result in merging objects geometries.

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Notes

  1. www.vividsolutions.com/jts/jtshome.htm

  2. In the following, where there is no ambiguity, a hard topological relation will be denoted simply as topological relation.

  3. The buffer operation is a well-known operation available in GIS systems that, given a geometry g and a ray r, computes the region representing the set of points having a distance less or equal to r from g.

  4. Notice that ∩  ID is not commutative

  5. Here we use the notation adopted by the 9-intersection model [7], that is presented in Section 3.2.

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Authors and Affiliations

  1. Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy

    Alberto Belussi & Sara Migliorini

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  1. Alberto Belussi
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  2. Sara Migliorini
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Correspondence to Sara Migliorini.

Appendix

Appendix

This section contains the tables explaining all the possible transitions between topological relations. In each cell distance between the two considered topological relations is reported in round brackets (“req. d” means that the transition is allowed only when the distance between the matrix of the current scene and the requested relation rel is d) and below the operations that have to be applied in order to obtain the requested relation (operations are presented in Tables 4–6). The symbol ND indicates that the target relation rel is not defined for the considered geometric types, while NA means not applicable and indicates that rel cannot be obtained without a human intervention.

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Belussi, A., Migliorini, S. A framework for integrating multi-accuracy spatial data in geographical applications. Geoinformatica 16, 523–561 (2012). https://doi.org/10.1007/s10707-011-0140-9

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