truestar inc. population statistics irregular
Summary
This dataset is an analytical dataset processed and integrated by truestar based on the National Land Numerical Information’s 250 m mesh future population projections from the Ministry of Land, Infrastructure, Transport and Tourism.
Sample Data
Please select the table you wish to view from the data dictionary in the snowflake marketplace.
Click here for sample data from Japanese Mesh Data
Features/Usages
This dataset provides past population data for 2020 in 5-year age groups, as well as projected population data in 5-year intervals through 2070, organized by 250-meter mesh grids.
Prefecture and municipality names are assigned using the administrative area codes included in the original dataset. Users can easily extract the information they need by filtering based on age group, prefecture, or municipality.
By overlaying this data with POIs—such as your company’s store locations or planned expansion sites—you can analyze potential business impacts through demand forecasting based on the area’s future population estimates.
Please note that this dataset is very large. When performing mapping or visualization, we strongly recommend filtering to a single prefecture first—for example, by using the PREF_NAME field—to ensure smooth processing.
Data Fields
| RESEARCH_YEAR |
| PREF_CODE |
| PREF_NAME |
| PREF_NAME_EN |
| PREF_CODE_NAME |
| MESH_CODE |
| CITY_CODE |
| CITY_NAME |
| CITY_CODE_NAME |
| YEAR |
| INCLUDED_IN_AREA_CODE |
| TOTAL_POPULATION |
| AGE_00_04 |
| AGE_05_09 |
| AGE_10_14 |
| AGE_15_19 |
| AGE_20_24 |
| AGE_25_29 |
| AGE_30_34 |
| AGE_35_39 |
| AGE_40_44 |
| AGE_45_49 |
| AGE_50_54 |
| AGE_55_59 |
| AGE_60_64 |
| AGE_65_69 |
| AGE_70_74 |
| AGE_75_79 |
| AGE_80_84 |
| AGE_85_89 |
| AGE_90_AND_OVER |
| MESH_250M |
References
The data is prepared by Truestar, based on the following data.
National Land Numerical Information: 250 m Mesh Future Population Projections (R6 IPSS Estimates)
https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-mesh250r6.html
Special Notes
Note 1: Duplicate MESH_IDs
In the 2018 edition (Heisei 30) of the mesh-based future population projection data, each MESH_ID was unique.
However, in the 2024 edition (Reiwa 6), a MESH_ID is no longer unique on its own.
Uniqueness is ensured only when the following three fields are combined: MESH_ID / CITY_CODE / YEAR (projection year)
Note 2: Cases Where Multiple SHICODE Values Exist for a Single MESH_ID
In the 2024 edition, there are cases where a single MESH_ID is associated with multiple SHICODE values, separated by underscores (“_”).
As a result, it is not possible to clearly identify which SHICODE corresponds to which value.
To address this, we assign the same value to all SHICODEs linked to the MESH_ID, allowing users to select the appropriate SHICODE based on their specific use case.
Note 3: SHICODE Values Not Matching 2024 Administrative Area Codes
In the 2024 edition, some SHICODE values do not correspond to the latest administrative area codes (2024 version).
Therefore, CITY_CODE cannot be assigned directly for affected mesh cells.
To handle this issue, we calculate the municipality polygon (based on the 2024 municipal boundaries) in which the centroid of each mesh cell falls, and assign the corresponding CITY_CODE based on that result.