High-resolution maps of material stock, population and employment in Austria from 1985 to 2018 - Supplementary Material

Global societal material stocks such as buildings and infrastructure accumulated rapidly within recent decades, along with population growth. Material stocks constitute the physical basis of most socio-economic activities and services, such as mobility, housing, health, or education. The dynamics of stock growth, and its relation to the population that demands those services, is an essential indicator for long-term societal resource use and patterns of emissions. The creation of societal material stock creates path dependencies for future resource use, with an important impact on how the transformation towards sustainable societies can succeed.

This dataset is a supplement to previously generated detailed maps of the distribution of material stocks, population and employment across Austria from 1985 to 2018 (10.5281/zenodo.7195101).

The data are aggregated tabular data used to create illustrations in an accompanying data article.

Data format and units

This dataset features:

• Tabular aggregated data of material stocks, population and employment on a municipality level from 1985 to 2018 (in administrative borders of 2018.
  • Note: Only layers used to create illustrations in the accompanying data article are presented as tabular data!
• Municipalities of Austria as as shape file (from https://www.data.gv.at/katalog/dataset/stat_gliederung-osterreichs-in-gemeinden14f53#resources)
• Annual population and employment numbers on a federal states level, extracted and aggregated from Statistik Austria (see readme.txt)

Further information

For further information, please see the publication or contact Franz Schug (fschug@wisc.edu). Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.

Funding

This research was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).