DOI: 10.5281/zenodo.17213706
title: Spatiotemporal scenarios of socioeconomic futures in Germany

description: This dataset contains spatially explicit, annual socioeconomic indicator projections for Germany at the district (NUTS-3; "Landkreise") level from 2020 to 2100. It provides multidimensional trajectories covering human, social, financial, and manufactured capital, including demographic dynamics, education, income, employment, inequality, and social cohesion. Developed through a mixed-methods framework integrating historical trend analysis, participatory scenario building, and quantitative projection, the dataset supports integrated climate-land system modelling, with a focus on informing land use, climate mitigation, and adaptation strategies, particularly carbon dioxide removal.

The dataset contains the following 10 socioeconomic indicators (short indicator name used in file names and data columns): 





Population density (pop)




Life expectancy (life_exp)




Secondary education (sec_edu)




Household income (income)




Employment rate (employment)




Crimes per person (crime)




Social cohesion (cohesion)




Income inequality (inequality)




Share of urban and traffic area (built_up)




Gross value added (manufacturing) (gva_manu)



The indicator projections are provided for six national scenarios that area based on the Shared Socioeconomic Scenarios (SSPs) and tailored to a Germany-specific land use focus: SSP1a (Green Growth), SSP1b (Degrowth), SSP2 (Middle of the Road), SSP3 (Regional Rivalry), SSP4 (Inequality), and SSP5 (Fossil-fuelled Development). Here some short descriptions of the narratives (see Gulde et al., in review, for more detail): 



SSP1a (Green Growth): With strong government backing and sustainability standards, Germany becomes a leader in green economics. Traditional industries such as automotive and steel decarbonise successfully, while new markets thrive through innovation, research, and an equitable education system. Society values sustainability highly, with trust in democracy, strong welfare structures, and active civic participation. Consumption remains high but shifts towards environmentally friendly goods, while agriculture and forestry adapt early to sustainable practices.

SSP1b (Degrowth): This path reflects a deliberate move away from growth, with well-being, ecological restoration, and social justice at its core. Bottom-up initiatives face resistance at first but eventually reshape society through equity-oriented policies, redistribution, and support for unpaid care work. Sufficiency-focused lifestyles and strict regulation drastically reduce consumption and strengthen the common good while prioritising opportunities for the Global South. Local and circular economies expand, traditional industries rapidly decarbonise, and unsustainable sectors are phased out, reducing dependence on global trade.

SSP2 (Middle of the Road): Germany largely continues on its current trajectory, facing mounting demographic challenges, labour shortages, and rising inequalities. Policy decisions favour maintaining established structures, and technological advances concentrate on traditional industries, while education and digitalisation lag. Social cohesion weakens under growing polarisation, hampering effective reforms. Sustainability awareness grows but remains limited by resource-intensive lifestyles, bureaucratic inefficiencies, and slow progress in the energy transition.

SSP3 (Regional Rivalry): Rising insecurity and inadequate political responses fuel distrust in democracy and growing nationalist sentiment. Protectionist policies restrict trade, leading to economic stagnation, declining prosperity, and worsening inequalities. Industry is re-shored to Germany, fossil fuels are reactivated, and investment priorities shift to defence and security. Consumption, services, and migration decline, while employment increasingly shifts towards agriculture, forestry, and industry in a fragmented, inward-looking society.

SSP4 (Inequality): Rapid technological progress and automation create new markets, boosting Germany’s global competitiveness in sectors like robotics, renewables, and IT. However, economic elites and lobby groups increasingly dominate politics, weakening democracy and curbing public investment in education and infrastructure. Structural change brings job losses in traditional industries, eroding the middle class, widening inequalities, and driving rural depopulation. Advanced technologies reshape agriculture, meat becomes a luxury item, and Germany strengthens its position in globalised markets at the expense of the Global South.

SSP5 (Fossil-fuelled Development): Initially hindered by energy and demographic pressures, Germany restores growth by abandoning environmental standards and investing heavily in fossil fuels. Subsidies, alongside a strong STEM focus in education, drive industrial innovation, while environmental awareness fades. Traditional industries benefit from deregulation, lifestyles remain resource-intensive, and consumption rises sharply, including demand for meat and luxury goods. Despite persisting inequalities, growing prosperity, robust institutions, and social spending sustain social stability and trust in democracy.


By capturing regional diversity and interdependencies among socioeconomic dimensions, these projections enable more nuanced assessments of equity, resilience, and sustainability under alternative Shared Socioeconomic Pathway (SSP)-aligned futures. The dataset advances beyond conventional aggregate GDP and population indicators by providing high-resolution, policy-relevant insights into persistent regional disparities and scenario-specific developmental pathways. It is intended for researchers, policymakers, and modelers working on climate action, land-use planning, and socioeconomic impacts of climate change.

The dataset is openly available under a CC-BY 4.0 license to facilitate reuse, validation, and integration into diverse climate and land system modelling frameworks. Accompanying documentation includes methodological details, indicator definitions, and scenario narratives to support proper application and interpretation.

 

Dataset is linked to a publication (currently in review): Winkler, K., Witting, M., Gulde, F., Garschagen, M., Pongratz, P., Rounsevell, M. (in review). Spatiotemporal scenarios of socioeconomic futures in Germany. Frontiers in Climate.
description: Dataset structure

CSV tables

The CSV files show the projected socioeconomic indicator for a specific scenario with annual values for each NUTS3 region (Landkreis) in Germany from 2020 to 2100.



Files are named as follows: [short indicator name]_projection_[scenario name]_2020-2100.csv

Tables contain the following columns: year, nuts3_code, [short indicator name], ssp


NUTS3 shape file

A shape file with the NUTS3 regions in Germany is provided as ZIP archive: NUTS3_shape.zip. The shape file uses EPSG:25832 projection (ETRS89 / UTM zone 32N) and contains the following attributes: NUTS_LEVEL, NUTS_CODE, NUTS_NAME, and can be linked via NUTS_CODE to the nuts3_code column of the CSV tables. 

Geotiffs

The ZIP archive geotiffs.zip contains multi-band geotiffs (named [short indicator name]_projection_[scenario name]_2020-2100.tif). They have a spatial resolution of 1x1km and are in EPSG:3035 projection (ETRS89-extended / LAEA Europe). Years from 2020 to 2100 are band numbers from 1 (2020) to 81 (2100).