2008 Volume 117 Issue 2 Pages 370-386
Enormous amounts of statistics have been published since the start of the Japanese modern era. Among all of these statistics, modern statistics published in the Meiji era are fundamental for grasping the historical geography of Japan. GIS can be powerful analytical tool for applying such modern statistics to historical regional analyses.
Although GIS has potential for historical regional analyses using modern Japanese statistics, studies are not making significant progress at the present time. A background factor is that municipal polygon data and digitized statistics in the Japanese modern era are not available to the public. As a result, in 2004, the authors established the open web-based database titled “Historical regional statistics,” which contains a variety of municipal polygon data and digitized statistics from the modern era. The purpose of this study is to review some digitized statistics and municipal polygon data contained in “Historical regional statistics,” and discus their availability through a case study.
“Historical regional statistics” contains eight groups of statistics (39 statistics) and four groups of municipal maps (213 maps). Among these data, military statistics, “Meiji 24 Nen Chohatsu Bukken Ichiranhyo (Requisition Order List in 1891)”, “Fuken Tokei Hyo (Prefectural Statistics)” and “Consolidation of municipalities database” are available and provide versatility. The case study, which analyzes the regional structure of central Japan in the mid-Meiji era, applies the 1890 “Consolidation of municipalities database” and military statistics, “Meiji 24 nen Chohatsu Bukken Ichiranhyo (Requisition order list in 1891)”. Factor and cluster analyses are applied to explain the regional structure. In the factor analysis, eight factors are abstracted from 35 variables. Then, by applying the cluster analysis to the factor matrix, central Japan is classified into six regional types.
Complicated research processes for handling or building of data are reduced by digitized statistics and municipal polygons. The regional structure analyzed in the case study can be understood from existing findings of historical geography in Japan. These points show the possible availability of “Historical regional statistics” for historical regional analyses with GIS. On the other hand, it is shown that data used in the case study contain some errors. This point is common to other data in “Historical regional statistics,” and needs to be corrected with the user's cooperation.