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FieldGML: An Alternative Representation For Fields

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Headway in Spatial Data Handling

Abstract

While we can affirm that the representation, storage and exchange of two-dimensional objects (vector data) in GIS is solved (at least if we consider the de facto standards shapefile and GML), the same cannot be said for fields. Among the GIS community, most people assume that fields are synonymous with raster structures, and thus only representations for these are being used in practice (many formats exist) and have been standardised. In this paper, I present a new GML-based representation for fields in 2D and 3D, one that permits us to represent not only rasters, but also fields in any other forms. This is achieved by storing the original samples of the field, alongside the interpolation method used to reconstruct the field. The solution, called FieldGML, is based on current standards, is flexible, extensible and is also more appropriate than raster structures to model the kind of datasets found in GIS-related applications.

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References

  • Couclelis H (1992) People manipulate objects (but cultivate fields): Beyond the raster-vector debate in GIS. In AU Frank, I Campari, and U Formentini, editors, Theories and Methods of Spatio-Temporal Reasoning in Geographic Space, volume 639 of Lecture Notes in Computer Science, pages 65–77. Springer-Verlag.

    Google Scholar 

  • Cox S (2007) GML encoding of discrete coverages (interleaved pattern). Open Geospatial Consortium inc. Document 06-188r1, version 0.2.0.

    Google Scholar 

  • Fisher PF (1997) The pixel: A snare and a delusion. International Journal of Remote Sensing, 18(3):679–685.

    Article  Google Scholar 

  • Frank AU (1992) Spatial concepts, geometric data models, and geometric data structures. Computers & Geosciences, 18(4):409–417.

    Article  Google Scholar 

  • Gold CM and Edwards G (1992) The Voronoi spatial model: Two- and three-dimensional applications in image analysis. ITC Journal, 1:11–19.

    Google Scholar 

  • Goodchild MF (1992) Geographical data modeling. Computers & Geosciences, 18(4):401–408.

    Article  Google Scholar 

  • Haklay M (2004) Map Calculus in GIS: A proposal and demonstration. International Journal of Geographical Information Science, 18(2):107–125.

    Article  Google Scholar 

  • ISO (2003) ISO 19107: Geographic information—Spatial schema. International Organization for Standardization.

    Google Scholar 

  • ISO (2005) ISO 19123: Geographic information—Schema for coverage geometry and functions. International Organization for Standardization.

    Google Scholar 

  • Kemp KK (1993) Environmental modeling with GIS: A strategy for dealing with spatial continuity. Technical Report 93-3, National Center for Geographic Information and Analysis, University of California, Santa Barbara, USA.

    Google Scholar 

  • Kemp KK and Včvckovski A (1998) Towards an ontology of fields. In Proceedings 3rd International Conference on GeoComputation. Bristol, UK.

    Google Scholar 

  • Kidner D, Dorey M, and Smith D (1999) What’s the point? Interpolation and extrapolation with a regular grid DEM. In Proceedings 4th International Conference on GeoComputation. Mary Washington College Fredericksburg, Virginia, USA.

    Google Scholar 

  • Lake R (2000) Introduction to GML: Geography Markup Language. In Proceedings W3C Workshop on Position Dependent Information Services. Sophia Antipolis, France. Available at http://www.w3.org/Mobile/posdep/GMLIntroduction.html.

    Google Scholar 

  • Ledoux H and Gold CM (2006) A Voronoi-based map algebra. In A Reidl, W Kainz, and G Elmes, editors, Progress in Spatial Data Handling—12th International Symposium on Spatial Data Handling, pages 117–131. Springer.

    Google Scholar 

  • Lu CT, Dos Santos RF, Sripada LN, and Kou Y (2007) Advances in GML for Geospatial Applications. GeoInformatica, 11:131–157.

    Article  Google Scholar 

  • Mark DM (1975) Computer analysis of topography: A comparison of terrain storage methods. Geografiska Annaler, 57A(3–4):179–188.

    Article  Google Scholar 

  • Mitas L and Mitasova H (1999) Spatial interpolation. In PA Longley, MF Goodchild, DJ Maguire, and DW Rhind, editors, Geographical Information Systems, pages 481–492. John Wiley & Sons, second edition.

    Google Scholar 

  • Mitasova H and Mitas L (1993) Interpolation by regularized spline with tension: I. Theory and implementation. Mathematical Geology, 25:641–655.

    Article  Google Scholar 

  • Nativi S, Caron J, Davies E, and Domenico B (2005) Design and implementation of netCDF markup language (NcML) and its GML-based extension (NcML-GML). Computers & Geosciences, 31(9):1104–1118.

    Article  Google Scholar 

  • OGC (2007a) Geography Markup Language (GML) Encoding Standard. Open Geospatial Consortium inc. Document 07-036, version 3.2.1.

    Google Scholar 

  • OGC (2007b) Topic 6: Schema for coverage geometry and functions. Open Geospatial Consortium inc. Document 07-011, version 7.0.

    Google Scholar 

  • OGC (2007c) Web Processing Service. Open Geospatial Consortium inc. Document 05-007r7, version 1.0.0.

    Google Scholar 

  • Oliver MA and Webster R (1990) Kriging: A method of interpolation for geographical information systems. International Journal of Geographical Information Systems, 4:313–332.

    Article  Google Scholar 

  • Pebesma EJ and Wesseling CG (1998) Gstat: a program for geostatistical modelling, prediction and simulation. Computers & Geosciences, 24(1):17–31.

    Article  Google Scholar 

  • Peucker TK (1978) Data structures for digital terrain models: Discussion and comparison. In Harvard Papers on Geographic Information Systems. Harvard University Press.

    Google Scholar 

  • Peuquet DJ (1984) A conceptual framework and comparison of spatial data models. Cartographica, 21(4):66–113.

    Google Scholar 

  • Peuquet DJ, Smith B, and Brogaard B (1999) The ontology of fields: Report of a specialist meeting held under the auspices of the VARENIUS project. Technical report, National Center for Geographic Information and Analysis, Santa Barbara, USA.

    Google Scholar 

  • Sen M and Duffy T (2005) GeoSciML: Development of a generic geoscience markup language. Computers & Geosciences, 31(9):1095–1103.

    Article  Google Scholar 

  • Shepard D (1968) A two-dimensional interpolation function for irregularly-spaced data. In Proceedings 23rd ACM National Conference, pages 517–ᾦ#x201C;524.

    Google Scholar 

  • Sibson R (1981) A brief description of natural neighbour interpolation. In V Barnett, editor, Interpreting Multivariate Data, pages 21–36. Wiley, New York, USA.

    Google Scholar 

  • Stephan EM, Včvckovski A, and Bucher F (1993) Virtual Data Set: An Approach for the Integration of Incompatible Data. In Proceedings AutoCarto 11 Conference, pages 93–102. Minneapolis, USA.

    Google Scholar 

  • Včkovski A (1998) Interoperable and Distributed Processing in GIS. Taylor & Francis.

    Google Scholar 

  • Včkovski A and Bucher F (1996) Virtual Data Sets—Smart Data for Environmental Applications. In Proceedings 3rd International Conference/Workshop on Integrating GIS and Environmental Modeling. Santa Fe, USA.

    Google Scholar 

  • Watson DF (1992) Contouring: A guide to the analysis and display of spatial data. Pergamon Press, Oxford, UK.

    Google Scholar 

  • Woolf A and Lowe D (2007) Climate Science Modelling Language Version 2—User’s Manual. http://ndg.badc.rl.ac.uk/csml/.

    Google Scholar 

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Ledoux, H. (2008). FieldGML: An Alternative Representation For Fields. In: Ruas, A., Gold, C. (eds) Headway in Spatial Data Handling. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68566-1_22

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