The ‘PlaFonD’ project examines the emergence of a revolution in mapping literacy in 18th century Europe: How did property maps, previously rare and reserved for judicial purposes or prestige operations, become common tools for the description and appropriation of space? This upheaval was not the result of a simple technical innovation. The inclusion of these new types of documents in pre-existing relationships that societies had with the written word reflects a profound change in social, economic and cognitive practices, even before the advent of geometric cadastres commissioned by modern States.
The study focuses on the pivotal period (1715–1820) and compares the Kingdom of France and the Habsburg Monarchy. Despite their distinct fiscal, legal and cultural structures, both areas experienced a simultaneous spread of property maps. The project seeks to reconstruct the rhythms and spatial dynamics of this rapid transformation of visual cultures and the relationship to the land. It also identifies the actors and factors involved in the widespread adoption of property maps: the circulation of administrative models, the role of local elites, the mobilisation of peasants’ vernacular knowledge, the evolution of land registration, the influence of printed cartography, and the professionalization of surveyors, engineers and geometers. While the technical cultures of administrative and engineering bodies are gradually helping to spread mapping literacy, they are also contributing to the decline of everyday cartography and the disappearance of regional cartographic traditions. Property maps are the product of, and a catalyst for, the spread of literacy. Their study seems to be the best way to break down the silos in the history of professional cultures. Property mapping is the ultimate meeting point for several cartographic traditions, where a great variety of career paths converge.
The project places a strong focus on digital humanities. A database, fed by regional data collection campaigns, will enlighten both in-depth studies of specific documentary corpus and allow for the development of an original typology of historical maps. Given its scale, diversity and, above all, visual nature, the corpus lends itself well to artificial intelligence methods based on deep learning. The initial maps described in the database will make it possible to train AI algorithms capable of classifying new maps, as well as locating and measuring the constituent elements of the cartographic language they contain (captions, patterns, symbols, etc.). These heuristic tools, alongside cross-disciplinary studies, will help to reconstruct the genealogy of property maps.
The project promotes open science policies and the enhancement and protection of digital heritage. The database will eventually be accessible via a map-based interface. It will incorporate the project’s scientific findings and provide guidance on interpreting the maps. It will also be able to accommodate new data entered by users, including heritage professionals, historians, and knowledgeable enthusiasts.