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Introducing SpatialGridBuilder: A new system for creating geo-coded datasets

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  • Steve Pickering

Abstract

Researchers in the conflict research community have become increasingly aware that we can no longer depend on state-aggregated data. Numerous factors at the substate level affect the nature of human interactions, so if we really want to understand conflict, we need to find more appropriate units of analysis. However, while many conflict researchers have realized this, actually taking the next step and performing data analysis on spatial data grids has remained a rather elusive goal for many because of the difficulty of learning the new techniques to perform such analyses. This paper introduces SpatialGridBuilder, a new, freely available, open-source system with the goal of empowering conflict researchers with no background in GIS methods to start their own spatial analyses. SpatialGridBuilder allows the researcher to: (a) create entirely new spatial datasets, based on the needs of their own research; (b) import their own spatial data; (c) easily add a range of important variables to the datasets, including commonly used conflict variables, plus new variables that have not been presented before; and (d) visualize graphical renderings of this data. Having done this, SpatialGridBuilder will then export the dataset for the researcher to analyse using conventional statistical methods. This article introduces the new program, and demonstrates how it can be used to set up such a statistical analysis. It also shows how different results can be achieved by building grids of different resolutions, thereby encouraging researchers to choose grid resolutions appropriate to their research questions and data. The article also introduces a novel means of determining infrastructure complexity, using Google maps.

Suggested Citation

  • Steve Pickering, 2016. "Introducing SpatialGridBuilder: A new system for creating geo-coded datasets," Conflict Management and Peace Science, Peace Science Society (International), vol. 33(4), pages 423-447, September.
  • Handle: RePEc:sae:compsc:v:33:y:2016:i:4:p:423-447
    DOI: 10.1177/0738894215581320
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    Keywords

    GIS; spatial disaggregation;

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