Abstract
Abstract. In Japan, population decline is one of the important issues that need to be tackled in socioeconomic fields. We apply an analysis method composed of a spatial autocorrelation analysis to the local population data generated through the 1995 and 2015 national census, and try to detect their spatial dynamics in this study. Through making experimental verification of the distance parameter of the spatial autocorrelation analysis, we newly define 2 indices with respect to the size and area where lower local populations are distributed in urbanized areas. It is shown that the local population dynamics are described by the difference of the 2 indices among 1995 and 2015. The expansion of areas where local population decline occurred seems to be detected by our proposed approach.
Highlights
In Japan, population decline is one of the important issues that need to be tackled in socioeconomic fields (National Institute of Population and Social Security Research, 2012, Kutsuzawa, 2016)
We applied spatial autocorrelation method to local populations for the detection of the sign of population dynamics, especially “Urban spongification”, which potentially reinforces the run-down of a district
Population decline in urbanized areas usually generates vacant land and vacant house a lot
Summary
One of the measures implemented is a land use strategy for living space and urban function In this measure, Residence Attraction Districts and Urban Function Attraction Districts are defined as core areas for maintaining sufficient population density given current and predicted population dynamics (Ministry of Land, Infrastructure, Transport and Tourism, 2014). It is necessary to cope with “Urban spongification” which is the current and future problem with respect to the spatial heterogeneity of local populations around the districts. “Urban spongification” is a phenomenon in which vacant land and vacant houses in urbanized areas randomly occur. This phenomenon is considered as a cause for concern about an impediment to maintaining sufficient population density because of the difficulty of integrated urban redevelopment due to the randomness. We apply an analysis method composed of a spatial autocorrelation analysis to the local population data generated through the 1995 and 2015 national census, and try to detect their spatial features of population dynamics
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