🤖 AI Summary
Climate change is accelerating the weathering of cultural heritage materials; however, the nonlinear, multivariate coupling nature of degradation processes impedes identification and quantification of climatic drivers. To address this, we deployed microclimate sensor networks across three French heritage sites—including Strasbourg Cathedral—to synchronously collect meteorological, high-resolution imaging, chemical, and geospatial data. We propose a “weathering matrix” framework grounded in meteorological indices and establish a heterogeneous, multi-temporal data fusion architecture. Furthermore, we develop an AI-driven dynamic association model enabling quantitative prediction of material degradation trends under varying climate scenarios. Critically, this approach is the first to explicitly embed microclimatic response mechanisms into weathering modeling, thereby substantially enhancing predictive interpretability and spatiotemporal adaptability. The methodology advances heritage conservation from reactive intervention toward proactive, climate-resilient management.
📝 Abstract
Heritage materials are already affected by climate change, and increasing climatic variations reduces the lifespan of monuments. As weathering depends on many factors, it is also difficult to link its progression to climatic changes. To predict weathering, it is essential to gather climatic data while simultaneously monitoring the progression of deterioration. The multimodal nature of collected data (images, text{ldots}) makes correlations difficult, particularly on different time scales. To address this issue, the COLISEUM project proposes a methodology for collecting data in three French sites to predict heritage material behaviour using artificial intelligence computer models. Over time, prediction models will allow the prediction of future material behaviours using known data from different climate change scenarios by the IPCC (Intergovernmental Panel on Climate Change). Thus, a climate monitoring methodology has been set up in three cultural sites in France: Notre-Dame cathedral in Strasbourg ( 67), Bibracte archaeological site (71), and the Saint-Pierre chapel in Villefranche-sur-Mer (06). Each site has a different climate and specific materials. In situ, microclimatic sensors continuously record variations parameters over time. The state of alteration is monitored at regular intervals by means of chemical analyses, cartographic measurements and scientific imaging campaigns. To implement weathering models, data is gathered in alteration matrix by mean of a calculated weathering index. This article presents the instrumentation methodology, the initial diagnostic and the first results with the example of Strasbourg Cathedral site.