C01 - RurbanGeography: Towards a global geography of rurbanity - developing a set of indicators to map and monitor rurban spaces

• Applicants: Professor Dr. Thomas Esch; Dr. Safia Loulad; Professor Dr. Stefan Siebert
• Subject Area: Plant Cultivation, Plant Nutrition, Agricultural Technology ; Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography ; Human Geography ; Physical Geography
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 548312187

Managing urban and rural development requires knowledge about the built environment and its interaction with human activity at the landscape level, which is captured by the concept of rurbanity. Working across and beyond the partner countries, project C01 aims at developing a set of indicators to map and evaluate rurbanity qualitatively and quantitatively using geoinformation on the built environment derived from earth observation, modelling and auxiliary sources of open and free geodata. C01 will combine census- and earth observation data with findings from other FOR5903 projects to derive these indicators and create a rurbanity index. Case studies will demonstrate that the new concept is able to reflect interlinkages between urban and rural areas and that the developed methodology can better describe rurban development than methods using neighbourhood relationships between binary, urban and rural, pixels. The seamless scalability of the index from regional to global will be investigated, with the aim that a generalised form of this method can be employed to upscale the approach to continental or global level. We hypothesise that (i) with this approach (using a set of specific indicators and spatiotemporal measurements) we can arrive at a unified measure of the “degree” of rurbanity of a landscape, independent of its case-specific context. We further hypothesise that (ii) the degree of rurbanity has increased in most regions as a consequence of globalisation, specialisation, increased mobility and information exchange. More specifically, C01 will use free remote sensing technology, modelling results, and results of surveys to generate the empirical evidence and indicators to specify the spatiotemporal pattern of socio-economic properties and trends in the study area (initially Morocco). A spatial network analysis will model the rurbanity index of all settlements within the network. C01 will integrate findings from Clusters A and B in a GIS-based synthesis. Moroccan partners with expertise in remote sensing and access to ground observations and regional data sets will be involved in developing the mapping framework, applying the methodology to obtain more detailed regional rurbanity datasets and validating the large scale rurbanity data set.

• DFG Programme: Research Units
• Subproject of: FOR 5903: Sustainable Rurbanity - Resources, Society, and Regulatory Systems
• International Connection: Morocco
• Co-Investigator: Professor Dr. Christoph Gornott
• Cooperation Partner: Professor Dr. Hassan Rhinane