Data · dataset · 2026
Assessment of the potential-allocation downscaling methodology for constructing spatial population projections
Listed in National Center for Atmospheric Research
The IIASA gridded population downscaling methodology is one of only a few existing models for constructing spatially explicit global population scenarios.
Description
Furthermore, this methodology is unique in that it does not employ proportional scaling techniques or extrapolated rates of change. Instead, the IIASA methodology applies a gravity-type spatial allocation model to distribute projected national-level change.
In this technical note we present and analyze the IIASA methodology within the context of a hypothetical population situated in one-dimensional space. Our results indicate that border effects exert significant influence over spatial population outcomes. Furthermore, over a reasonable time horizon (100-150 years), we find that in most cases the IIASA methodology will have a smoothing effect on existing population distributions.
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This paper is the first in a series related to the construction of spatial population scenarios organized around the IIASA methodology, and the results presented within not only help to explain the IIASA scenarios, but inform feature research and refinements to the methodology.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7fx78xj ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/assessment-of-the-potential-allocation-downscaling-met… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=624ea5ae-eeb8-4ffc-86a5-197c3180f… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Life Sciences · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Agriculture, land and farm management 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 624ea5ae-eeb8-4ffc-86a5-197c3180fade | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3002 | enrichment · data ucar edu | taxonomy-embedding@1.1.0 | title+keywords+description (75%) |
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:social-science | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |