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Measuring spatial co-agglomeration patterns by extending ESDA techniques

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Abstract

An emerging topic in spatial statistics is the analysis of agglomerations within a regional context. Often, these ‘spatial clusters’ are formed by effects of spatial co-agglomeration. This article introduces an extended bivariate Moran’s I statistic in a case study of German furniture industries. It allows to jointly account for the clustering of two different industries. The method is integrated into the context of Exploratory Spatial Data Analyses. Results show that the approach is a suitable tool for the detection and delineation of co-agglomerations in space by adding self-inclusion of cluster cores and by offering measures of statistical significance.

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Authors and Affiliations

  1. Research Institute for Regional and Urban Development (ILS), Brüderweg 22–24, 44135, Dortmund, Germany

    Karsten Rusche

  2. Wald-Zentrum (Centre of Forest Ecosystems), Westfälische Wilhelms-Universität, Robert-Koch-Str. 27, 48149, Münster, Germany

    Uwe Kies & Andreas Schulte

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  1. Karsten Rusche
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  2. Uwe Kies
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  3. Andreas Schulte
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Correspondence to Karsten Rusche.

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Rusche, K., Kies, U. & Schulte, A. Measuring spatial co-agglomeration patterns by extending ESDA techniques. Jahrb Reg wiss 31, 11–25 (2011). https://doi.org/10.1007/s10037-011-0051-0

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