Keynote Lectures

Abstract
The last two decades have been marked by a substantial increase in the amplitude and frequency of a wide range of climate extremes on the global scale. Such an increment presents a significant challenge with far-reaching implications for the environment, economy, and society. In particular, the European continent has been struck with more frequent extreme weather events such as heatwaves, droughts, heavy rainfall, and storms, pressing the need to understand and address the impacts of these changes. Here I provide an overview of how these extreme weather events, namely heatwaves, droughts and fires have become more frequent and to what extent we can attribute human-induced climate change to their increasing frequency (or amplitude). Addressing the growing climate extremes in Europe requires a multi-faceted approach that includes mitigation efforts to reduce greenhouse gas emissions, adaptation strategies to build resilience to changing conditions, and international cooperation to tackle this global issue. Finally, I will present a few examples where the use of high-resolution geographical information systems can be useful in informing civil protection and other authorities in developing useful adapting strategies.

Abstract
The increasing interest in the interpretability and explainability of artificial intelligence (AI) decisions requires innovative model diagnostic tools that account for the unique challenges of geospatial and environmental data, notably spatial dependence and high dimensionality. Leveraging the geostatistical paradigm rooted in distance-based metrics, spatial prediction error profiles (SPEPs) and spatial variable importance profiles (SVIPs) as well as derived summary statistics based on spatial cross-validation are novel, model-agnostic tools for assessing and interpreting models across various prediction horizons. Additionally, to tackle the complexities of deciphering joint effects in environments abundant with strongly correlated or high-dimensional features, interpretation tools that distill aggregated relationships from complex models are required. The efficacy of these techniques is demonstrated in two case studies: the regionalization of environmental pollution based on point measurements of concentrations, and a classification task from multitemporal remote sensing of land use. In these case studies, SPEPs and SVIPs effectively highlight differences and unexpected similarities of geostatistical methods, linear models, random forest, and blended algorithms. With 64 correlated features in the remote-sensing case study, the transformation-based interpretation approach successfully summarizes high-dimensional relationships in a small number of diagrams for effective science communication. These innovative diagnostic tools enrich the toolkit of geospatial data science, offering potential enhancements to the interpretation, selection, and design of geospatial machine-learning models.

Abstract
In every country, there exists many collections of iconographic contents that depict the territory at different time periods and different scales, such as aerial views belonging to mapping agency surveys or terrestrial photographs taken by a photograph for illustrating a place or an event. They are usually hosted by GLAMs (Galleries, Libraries, Archives, Museums) or mapping agencies, making them scattered in silo and documented or indexed with various standards depending on the hosting institution. Yet they represent a rich heritage touching many sectors of society, e.g. environmental cartography, urban planning, historians and geographers modeling the evolution of the territory, sustainable tourism, sociologists investigating public spaces, media for investigation and engagement, etc. With the acceleration of open data policies aimed at promoting the circulation and valorization of public data, it becomes easier to find out about this content. To exploit and valorize them, the main challenges remain in organizing them optimally, across an institution and even between institutions, in order to access them, discover them and visualize them in ways that are relevant to the various users. In this talk, we will revisit the paradigms and solutions that exist with the objective of structuring and exploring this growing and rich digital(ized) source of documentation of our territories, from their spatialization, their indexing with metadata and content analysis, their automatic linking up to their exploration and visualization. We will present the last advances in research from computer science, computer vision, artificial intelligence and digital humanities, and will illustrate these concepts in several domains: territory understanding from historians and sociologists point of views, collection interlinking for archives and documentation of heritage objects for restoration sites.