AUSTROMODELS - Modelling Styrian Land Use, 1820-1910 CE: Studying the Past Human-Earth System Dynamics of Industrialization

Project Overview: This interdisciplinary research project develops innovative methods for reconstructing historical land use in the Austrian province of Styria between 1820 and 1870. For the first time, Circle Diagram Models (CDMs), originally developed for tropical Southeast Asian regions, are transferred to a Central European context using cutting-edge Digital Humanities techniques.

Research Objectives: The project pursues three main goals: (1) adapting and applying CDMs to Styrian land use patterns, (2) integrating machine learning methods for systematic analysis of archival materials and cadastral maps, and (3) detailed analysis of proto-industrial transitions in the region. Three time points are examined: 1820 (completion of first cadastral maps), 1848 (end of serfdom), and 1870 (completion of cadastral map readjustments).

Methodology: The project combines traditional historical archival research with innovative digital analysis methods. Extensive datasets from the Austrian State Archive, Styrian Provincial Archive, and digital repositories are analyzed using machine learning algorithms. Collaboration with the University of Graz's Digital Humanities Department enables automated segmentation of cadastral maps and extraction of structured data from historical documents.

Scientific Relevance: The project addresses a central challenge in Earth System research: the lack of reliable data on historical human-environment interactions. While global land use models often fail due to assumptions of cultural homogeneity, CDMs offer a regionalized approach that considers local conditions. Styria serves as an ideal study area because industrial developments occurred unevenly - from subsistence-oriented agriculture to early industrialization.

Innovation: For the first time, Digital Humanities methods are systematically integrated into CDM development. Automated analysis of historical cadastral maps and statistical tables using machine learning significantly accelerates the labor-intensive data collection process. Simultaneously, the transferability of CDM methodology, originally developed for the Global South, is tested in data-rich European contexts.

Expected Results: The project will generate detailed land use models for various "Lifestyles" (time- and location-specific land use patterns) in Styria. These will be visualized as Circle Diagrams, enabling quantitative comparisons between different time periods and regions. Results contribute to understanding proto-industrial transformation processes and demonstrate CDM methodology scalability.

Broader Impact: Beyond scientific contribution, the project will inform local communities about their region's environmental and land use history. Public presentations and a dedicated website will make research results accessible. The developed methods could also be of interest to agronomists and land use planners.
Training Objectives: The project provides comprehensive training in Digital Humanities techniques, expands research expertise to Central Europe, and enhances employability in European academic contexts. The researcher will acquire advanced skills in text mining, machine learning, and image analysis while building professional networks and improving German language proficiency.

Host Institution: The University of Graz provides ideal conditions with its renowned Digital Humanities Department, location in Styria's capital, and strength in Climate Change and Environmental Systems Studies. Collaboration with Prof. Georg Vogeler and Dr. Wolfgang Göderle ensures access to cutting-edge techniques and local expertise in Austro-Hungarian cadastral analysis.