Depopulation is likely to cause multiple regional issues such as decreasing demands for large-scale land developments, declination of rural areas and middle-size cities, increasing gaps between cities, and so on.
This study began from a common interest of Korea and Japan - how geospatial big data would be used to address the regional issues that declining population would cause in the near future. The study seeks to review policies and usage trends of geospatial big data in the two countries and to derive a new method where geospatial big data are employed to diagnose regional problems due to future population decreases.
For the entire territories of Japan and Korea, the study compared life vulnerability (LV) at present to that of 2040, a time point when both countries would lose a substantial amount of population, at a fine spatial resolution of 500m square grid cells. For the comparison, the research teams of Korea and Japan collaboratively developed a spatial analysis method for the estimation and evaluation of LV due to depopulation.
They then applied the method to analyze Korean and Japanese data, and used the results to derive new implications for regional and spatial information policies. Population growth has been slowed down since 2011 in Korea. It is projected that the Korean population would increase up to about 52 million by 2030 and then would decrease to about 44 million around 2040. Due to growing recognition of depopulation risks and strengthening focus on human-centered regional policies, Korean governments are struggling to improve life conditions of underdeveloped regions and create new living zones through urban revitalization. Nonetheless, there are no concrete, comprehensive strategies of shaping regional policies that could deal with new challenges from population declination.
In contrast, population is already decreasing in Japan after its peak of about 128 million in 2008. It is projected that in 2060 the ratio of elder population would become 39.9% and the total population would reach about 87 million. To respond to depopulation, the Japanese government is struggling to revitalize regions through policy strategies such as ‘Compact+Network.’It also formulated ‘The National Grand Design 2050’to better inform its people of future changes in national territories and local areas. The Japanese government is also making efforts, such as sharing detailed data of future population distribution, the results of territorial monitoring, and micro geo data, in order to interest its people of current status and future directions of territorial and regional policies.
Recently new attempts have been made in both private and public sectors of Korea to develop geospatial big data from diverse information based on small spatial units and apply the results to problem solving.
Private sectors are producing information of floating population and regional economy indicators from mobile phone data, credit card transactions data, and others so as to better business decision-making and improve customer services. Contrastingly, few attempts have been made so far to utilize similar big data in addressing regional problems due to
depopulation or associated policy-making.
To fill this gap, the study conducted an empirical analysis to examine how decreasing demands (population) would affect people’s living conditions in the future. The research teams of Korea and Japan first formulated a GIS-based analysis model through collaboration. They then collected and processed geospatial big data for Korea and Japan, respectively. Thirdly, the teams estimated the geographical distributions of future population in a 500m grid and identified underpopulated areas.
Fourthly, the teams simulated which living-related infrastructures such as elementary schools, hospitals, etc. would be closed in the future. Lastly, they calculated indices of LV for the present and 2040, and examined how the distribution of life deserts would change in Korea and Japan.
The analysis results of the study showed that underpopulated areas would expand in both Korea and Japan. These problematic areas were especially located around inland mountainous areas. Areas with a higher rate of depopulation would also face more severe levels of decrease in accessing living-related infrastructures, having increased levels of LV. From the analysis, the research teams found geospatial big data useful in identifying and monitoring underpopulated, life-vulnerable areas in detail.
This capability of geospatial big data would be helpful for providing policy supports in a preemptive fashion for local areas with a high level of depopulation risk.
The study demonstrated that geospatial big data were useful in both Korea and Japan for identifying future areas with low levels of LV. It also examined the similarities and differences of geospatial big data between the two countries and suggested which aspect to improve. Japan already has a time-series dataset of future population distribution at a
500m or 1km square grid for every five year. On the contrary, data of future population is available in Korea only at 16 Si-Do administrative units. Although latest data of buildings and living-related facilities were available in Korea due to its recent recognition of the importance of geospatial big data, historical data of those buildings and facilities are not available, which served as a limiting factor for the study. When collecting and managing geospatial big data, related agencies in Korea thus need to enhance their data infrastructures to increase spatial resolution and include historical changes.
In terms of data sources, the Japanese research team obtained the data of buildings and future population from private sectors, which the Korean team acquired a similar set of data from public sectors such as Seumtu, etc. Japan with a high level of dependency on private data seems to strengthen its efforts to develop new types of big data from its administrative businesses. Contrastingly, Korea need to foster private markets of geospatial big data so as to facilitate integrated uses of public and private data.
With respect to diagnosing regional problems due to depopulation, geospatial big data would be used to support ① early detection and management of life-vulnerable areas in the future, ② selection of candidate spots for facility relocation, ③ derivation and pre-evaluation of spatial reorganization strategies, and ④ construction of inventories of essential data such as empty houses, idle spaces, and life-vulnerable population. To facilitate the use of geospatial big data to deal with depopulation issues, continuous research is required to develop application models of geospatial big data as well as to formulate analytical methods and technical infrastructures for the construction of value-added new
geospatial big data. In addition, governments need to create institutional environments where the use of big data is recommended or mandated when the practitioners of regional policies work on the issue of depopulation.