Peripheral areas such as mountainous areas and islands have large portions of land unsuitable for human habitation. In consideration of this fact, in this paper, two methods for improving the usability of small-area statistics are proposed. Additionally, their effectiveness is illustrated by applying them to Dogo, Shimane prefecture. First, I propose a technique called the Clipping Method (CM) for enhancing accuracy and resolution in visualization of small-scale statistics. In Japan, the concept of the inhabitable area (IA/Kajyuchi) is used extensively in government statistics and policies. IA is defined operationally as an area excluding forest and water areas (over 1 km^2). Recently, the National Land Numerical Information System, which is serviced by the Ministry of Land, Infrastructure, Transport and Tourism, started to provide Geographic Information System (GIS) data freely. By using these data, I clipped IA data from various statistics on individual aggregation areal block territories. Furthermore, I excluded blocks with no buildings in topographic maps, following the Arai and Koike (2000) method. Next, I suggested a method called IA-Based Comparability Judging (IBCJ) to judge the comparability of aggregation areal blocks of different statistics in terms of IA sharing. Assuming inhabitants reside only in IAs, different aggregation areas including the same IAs as comparable regardless of correspondence between their territories. The application of these methods in Dogo clearly displayed their effectiveness. A dot map of population distribution after CM processing gave accurate and high-resolution figures of land alterations and population changes. IBCJ greatly enlarged the feasibility of sub-municipal scale comparison. In the case of Dogo, IBCJ enabled comparative analysis of population changes between core and peripheral areas of each municipality.
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