Skip to main content
SpringerLink
Log in

Designing a Language for Spatial Computing

  • Chapter
  • First Online:
AGILE 2015

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

We present the design rationale underlying a language for spatial computing and sketch a prototypical implementation in Python. The goal of this work is to provide a high-level language for spatial computing that is executable on existing commercial and open source spatial computing platforms, particularly Geographic Information Systems (GIS). The key idea of the approach is to target an abstraction level higher than that of GIS commands and data formats, yet meaningful within and across application domains. The paper describes the underlying theory of spatial information and shows its evolving formal specification. An embedding in Python exemplifies access to commonly available implementations of spatial computations.

“One of the main reasons why software projects fail is the lack of communication between the business users, who actually know the problem domain, and the developers who design and implement the software model.”

(Ghosh 2011).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Industrial products include ModelBuilder in ArcGIS and the Workflow Designer in Autodesk Map 3D.

  2. 2.

    http://en.wikipedia.org/wiki/Santa_Barbara,_California.

  3. 3.

    https://pysal.readthedocs.org, http://www.scipy.org.

  4. 4.

    http://gdal.org/python.

  5. 5.

    http://resources.arcgis.com/en/communities/python.

  6. 6.

    http://pyqgis.org.

  7. 7.

    http://trac.osgeo.org/geotiff.

  8. 8.

    Created by the Open Source Geospatial Foundation, the Geospatial Data Abstraction Library (GDAL, http://www.gdal.org) is a software package that provides an interoperability layer between a variety of raster and vector data formats.

  9. 9.

    https://networkx.github.io.

References

  • Albrecht, J. (1998). Universal analytical GIS operations: A task-oriented systematization of data structure-independent GIS functionality. In H. Onsrud & M. Craglia (Eds.), Geographic information research: Transatlantic perspectives (pp. 577–591). London: Taylor & Francis.

    Google Scholar 

  • Baumann, P. (2010). The OGC web coverage processing service (WCPS) standard. Geoinformatica, 14(4), 447–479.

    Article  Google Scholar 

  • Burrough, P. A., & Frank, A. U. (1996). Geographic objects with indeterminate boundaries. London: Taylor & Francis.

    Google Scholar 

  • Burrough, P. A., & McDonnell, R. (1998). Principles of geographical information systems. Oxford, UK: Oxford University Press.

    Google Scholar 

  • Camara, G., Egenhofer, M. J., Ferreira, K., Andrade, P., Queiroz, G., Sanchez, A., et al. (2014). Fields as a generic data type for big spatial data. In Geographic Information Science (pp. 159–172). Berlin: Springer.

    Google Scholar 

  • Couclelis, H. (1992). People manipulate objects (but cultivate fields): Beyond the raster-vector debate in GIS. In A. U. Frank, I. Campari, & U. Formentini (Eds.), Theories and methods of spatio-temporal reasoning in geographic space (pp. 65–77). Berlin: Springer.

    Chapter  Google Scholar 

  • Degbelo, A., & Kuhn, W. (2012). A Conceptual Analysis of Resolution. In GeoInfo—XIII Brazilian Symposium on GeoInformatics, November 25–28 2012, Campos do Jordão, Brasil (pp. 11–22).

    Google Scholar 

  • Donnelly, M. (2005). Relative Places. Applied Ontology, 1, 55–75.

    Google Scholar 

  • Egenhofer, M. J., & Kuhn, W. (1999). Interacting with Geographic Information Systems. In M. F. Goodchild, D. J. Maguire, D. W. Rhind, & P. Longley (Eds.), Geographical Information Systems: Principles, techniques, applications, and management (2nd ed., Vol. 1, pp. 401–412). New York: Wiley.

    Google Scholar 

  • Galton, A. (2004). Fields and objects in space, time, and space-time. Spatial Cognition & Computation, 4(1), 39–68.

    Article  Google Scholar 

  • Ghosh, D. (2011). DSL for the uninitiated. Communications of the ACM, 54(7), 44.

    Article  Google Scholar 

  • Golledge, R. G. (1995). Primitives of spatial knowledge. In T. L. Nyerges, D. M. Mark, R. Laurini, & M. J. Egenhofer (Eds.), Cognitive aspects of human-computer interaction for geographic information systems (pp. 29–44). Berlin: Springer.

    Google Scholar 

  • Goodchild, M. F., Yuan, M., & Cova, T. J. (2007). Towards a general theory of geographic representation in GIS. International Journal of Geographical Information Science, 21(3), 239–260.

    Article  Google Scholar 

  • Janelle, D. G., & Goodchild, M. F. (2011). Concepts, principles, tools, and challenges in spatially integrated social science. SAGE Publications: In the SAGE Handbook of GIS and Society.

    Book  Google Scholar 

  • Kuhn, W. (2012). Core concepts of spatial information for transdisciplinary research. International Journal of Geographical Information Science, 26(12), 2267–2276 (Special Issue in honor of Michael Goodchild).

    Google Scholar 

  • Newman, M. E. J. (2010). Networks. Oxford: Oxford University Press.

    Google Scholar 

  • Norman, D. A. (1986). Cognitive Engineering. In D. Norman & S. Draper (Eds.), User centered system design (pp. 31–61). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Rosenfeld, A. (1986). “Continuous” functions on digital pictures. Pattern Recognition Letters, 4(3), 177–184.

    Article  Google Scholar 

  • Talmy, L. (1983). How language structures space. In H. L. Pick & L. P. Acredolo (Eds.), Spatial Orientation (pp. 225–282). New York/London: Plenum Press.

    Chapter  Google Scholar 

Download references

Acknowledgments

We gratefully acknowledge contributions to the Python embedding and testing from Michel Zimmer, Marc Tim Thiemann, and Eric Ahlgren as well as funding from the UCSB Center for Spatial Studies.

Author information

Authors and Affiliations

  1. Center for Spatial Studies, Department of Geography, University of California, Santa Barbara, USA

    Werner Kuhn

  2. Center for Spatial Studies, University of California, Santa Barbara, USA

    Andrea Ballatore

Authors
  1. Werner Kuhn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrea Ballatore
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Werner Kuhn .

Editor information

Editors and Affiliations

  1. NOVA IMS, Universidade Nova de Lisboa, Lisboa, Portugal

    Fernando Bacao

  2. School of Engineering, University of Minho, Guimarães, Portugal

    Maribel Yasmina Santos

  3. NOVA IMS, Universidade Nova de Lisboa, Lisboa, Portugal

    Marco Painho

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Kuhn, W., Ballatore, A. (2015). Designing a Language for Spatial Computing. In: Bacao, F., Santos, M., Painho, M. (eds) AGILE 2015. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-16787-9_18

Download citation

Publish with us

Policies and ethics

Search

Navigation