Royal Institute for Cultural Heritage

Heritage buildings pose persistent challenges for documentation and conservation due to their geometric complexity, material heterogeneity, and the fragmentation of spatial and semantic datasets. To address these limitations, this study proposes a geospatially enabled HBIM–GIS framework that integrates hybrid photogrammetric survey data with semantic modeling and spatial analysis to support evidence-based conservation planning. A multi-source acquisition strategy combining terrestrial digital photogrammetry (TDP), Unmanned aerial vehicle digital photogrammetry (UAVDP), and spherical photogrammetry (SP) was employed to capture accurate geometric and semantic information across multiple spatial scales. Staged point-cloud fusion (UAVDP → TDP via ICP; SP → UAV–TDP via SICP) generated a high-density, georeferenced composite, achieving RMS residuals below 0.013 m and resulting in an integrated dataset exceeding 360 million points. From this composite, authoritative 2D drawings and a reality-based 3D HBIM model were developed, while GIS thematic mapping translated heterogeneous observations into structured, queryable layers representing materials, cracks, detachments, deformations, and construction phases. The proposed framework enabled the spatial diagnosis of deterioration mechanisms, revealing moisture-driven decay from plinth to mid-wall and concentrated cracking at openings and architectural transitions; side-to-side cracks accounted for approximately 55% and 65% of mapped fissures on the most affected façades. By embedding these diagnostics as element-level attributes within the HBIM environment, the framework supports precise localization, quantification, and prioritization of conservation interventions, ensuring material-compatible and location-specific decision making. The applicability of the framework is demonstrated through its implementation on a complex historic mosque in Yemen, validating its robustness under constrained access and resource-limited conditions. Overall, the study demonstrates that geospatially integrated HBIM–GIS workflows provide a reproducible, scalable, and transferable solution for the sustainable documentation and conservation of heritage buildings, supporting long-term monitoring and informed management of cultural heritage assets worldwide.

Subspace clustering has become widely adopted for the unsupervised analysis of hyperspectral images (HSIs). Recent model-aware deep subspace clustering methods often use a two-stage framework, involving the calculation of a self-representation matrix with complexity of O(n2), followed by spectral clustering. However, these methods are computationally intensive, generally incorporating only local or non-local structure constraints, and their structural constraints fall short of effectively supervising the entire clustering process. We propose a scalable, context-preserving deep clustering method based on basis representation, which jointly captures local and non-local structures for efficient HSI clustering. To preserve local structure—i.e., spatial continuity within subspaces—we introduce a spatial smoothness constraint that aligns clustering predictions with their spatially filtered versions. For non-local structure—i.e., spectral continuity—we employ a mini-cluster-based scheme that refines predictions at the group level, encouraging spectrally similar pixels to belong to the same subspace. These two constraints are jointly optimized to reinforce each other. Specifically, our model is designed as a one-stage approach, in which the structural constraints are applied to the entire clustering process. The time and space complexity of our method are O(n), making it applicable to large-scale HSI data. Experiments on real-world datasets show that our method outperforms state-of-the-art techniques.

Abstract Ongoing dendrochronological studies on construction wood from the Brussels region (Belgium), a collaborative effort between the Brussels Capital Region (urban.brussels), the laboratories of the University of Liege, and the Royal Institute of Cultural Heritage, have resulted in a substantial corpus of 443 oak samples with waney edges or partially preserved sapwood. The examined wooden elements date back to the 13th to the 18th centuries, with 85% of them accurately dendrodated. This corpus enables the development of a novel regional framework for estimating the number of missing sapwood rings and consequently refines felling date estimates for timber constructions made of oak in the Brussels region. A key feature of this dataset is the diversity of timber sources, reflecting the complex supply networks of a large and expanding urban centre. The sapwood model presented herein was designed to encompass this diversity in timber provenance, offering a comprehensive tool for dendrochronologists, building historians, and archaeologists to derive and report reliable estimates of felling date ranges. Here, we present a newly developed sapwood model tailored for the Brussels region that estimates the expected number of sapwood rings to be between seven and 27 (95.7% confidence interval). This range was narrower than that of previously used estimates and published datasets, offering improved precision. Furthermore, the new sapwood model enables a standardised workflow for reporting felling date ranges for individual oak timbers.

Following the industrial revolution and the modernization of chemistry, purple became one of the most popular colors in the palettes of late 19th- to 20th-century painters. Among them, Robert Delaunay (1885-1941) was one of the key artists of the avant-garde movement in France in the early 20th century. Although widely used in modern and contemporary paintings, inorganic purple pigments of the cobalt phosphate and cobalt arsenate families have been little studied chemically until now. The diversity of emerging chemical syntheses resulted in a wide range of products, characterized by a high diversity of hues, function of their respective composition, and crystal structures. The present work combines structural and optical analyses to probe the purple pigments used by Delaunay. Reference materials synthesized in the laboratory were characterized via synchrotron radiation-based high-angular-resolution X-ray powder diffraction and UV-vis-NIR spectroscopy. Structure-color relationships were established for the first time for several inorganic compounds of the Co-P/As family. Two of Robert Delaunay's earliest masterpieces conserved at the Centre Pompidou in Paris were probed in situ via X-ray powder diffraction in imaging mode and fiber optic UV-vis-NIR reflectance spectroscopy. The results highlight the decisive effect of their structural chemistry on the palettes of modern and contemporary painters.

This study examines Rembrandt’s use of chiaroscuro to depict the costume of Lieutenant Willem Van Ruytenburch, a prominently lit figure in The Night Watch (1642). As part of Operation Night Watch, the painting was analyzed using noninvasive imaging techniques, including reflectance imaging spectroscopy (RIS), macroscopic X-ray powder diffraction (MA-XRPD), and macroscopic X-ray fluorescence (MA-XRF). These methods enabled the mapping of the artist’s pigment palette, which includes lead white, lead-tin yellow, ochres, vermilion, arsenic sulfide pigments, red lakes, smalt, and azurite. Rembrandt applied these pigments in a consistent, systematic way, combining them in groups to achieve pictorial unity. Notably, arsenic-based pigments were used to capture the warm reflections of gold threads, unique to Van Ruytenburch’s costume. MA-XRPD also identified degradation products—mimetite, weddellite, and palmierite—associated with the original pigments. These results provide new insights into Rembrandt’s modus operandi and inform understanding of the current condition and implications for its conservation.

International audience

Textiles are particularly complex and labor-intensive structures, thus their constructive elements, such as fibers and yarns, as well as the final textile products (e.g., threads, cords, fabrics, and applied decoration) reveal a range of important technical, technological, and sociocultural information. In this paper, we discuss the analysis of excavated textiles at two levels: 1) Technical analysis that offers basic information about the qualities of examined textile samples. 2) Technological analysis that provides insights into technology, social relations of production, and the level of craft specialization or production modes. Both analyses offer new evidence for environmental resources, sustainability, trade, and exchange, as well as transfer of technical knowledge, innovations, and expertise. Yet, excavated textiles, being formed of organic materials, survive poorly in archaeological contexts and thus represent environmentally limited remnants of the original pattern of textile consumption. Additionally, excavated textiles are often recovered in minute fragments, altered due to post-depositional processes and, therefore, their analysis is usually challenging. The scope of this paper is to provide an account of the current state of the technological analysis of excavated textiles looking back at its origins, and to offer a concise and clarified synopsis of the main methods and terms used to study and document the technological characteristics of excavated textiles.

Trustworthy metadata about entities related to cultural heritage is important to correctly identify bibliographic meta-data, attribute works, identify works of public domain (based on contributors’ date of death), or to support Named Entity Linking (NEL) for digitised documents. However, in Belgium such data is currently dispersed between numerous institutions, modelled with different ontologies, represented in different formats and curated in different languages. GLAM institutions would profit from data about Belgian entities to correctly annotate their collections.Furthermore, this would facilitate research in Belgium and abroad. The current situation does not only complicate data exchange in a national and international setting, but also leads to duplicate data curation efforts and data quality issues, negatively impacting the users’ experience. This paper introduces the MetaBelgica project, coordinated by KBR - The Royal Library of Belgium with the Royal Museums of Fine Arts, the Royal institute for Cultural Heritage, and the Royal Museum of Art and History, to improve the status quo. The aforementioned Federal Scientific Institutes (FSIs), belonging to the Belgian Science Policy Office (BELSPO), joined forces to develop a shared Linked Data platform for managing shared entities. This platform, based on Wikibase (the technology behind Wikidata), aims to ensure FAIR data about persons, organisations, time/events and locations related to Belgian cultural heritage. We will integrate data about millions of Belgian entities from the four participating FSIs into a Wikibase instance and make it accessible by using Persistent Identifiers. This will not only professionalize our own data management and improve data quality, but according to received project support letters, also impact other regional, national and European institutions.