Abstract
In spatial statistical analyses of geographical phenomena, a region or city under study might be divided into some small areal units such as a regular square tessellation, or into irregular shaped administrative units which have different spatial characteristics. If we are using geographical information science (GIS) to support the analysis, irregular areal units such as cho in Japan are usually represented as one such polygon with geometric attributes. In spatial statistics, an areal unit that has special geometric attributes and maintains significant spatial correlation and spatial interaction close to adjacent units is called a prominent areal unit or an important areal unit. The prominence of areal units can be measured by a prominence or influence-centrality index, which is obtained by using eigenfunctions or the Markov chains method from a spatial weights matrix (Tinkler 1972; Griffith and Jones 1980; Boots 1982; Bavaud 1998; Zhang and Murayama 2003).
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Zhang, C. (2012). Spatial Prominence and Spatial Weights Matrix in Geospatial Analysis. In: Murayama, Y. (eds) Progress in Geospatial Analysis. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54000-7_5
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DOI: https://doi.org/10.1007/978-4-431-54000-7_5
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