Heritage Spatial Computing

Advanced volumetric digitisation, neural rendering, and AI-driven analysis for the permanent preservation of Europe's cultural heritage. Building digital twins at scale for research, conservation, and public access.

View Capabilities

Core Capabilities

State-of-the-art spatial computing applied to cultural preservation challenges.

Volumetric 3D Reconstruction

Sub-centimetre photogrammetric capture combined with Neural Radiance Fields (NeRF) to produce photorealistic, metrically accurate digital twins of heritage structures, artefacts, and landscapes.

NeRF & Gaussian Splatting

AI-Driven Heritage Analysis

Machine learning classification of architectural elements, decay patterns, and stratigraphic features. Automated condition assessment designed to significantly reduce specialist survey time.

Computer Vision & ML

Airborne LiDAR & Remote Sensing

Aerial and terrestrial LiDAR survey for landscape-scale heritage mapping. Integration with multispectral and hyperspectral data for subsurface feature detection and vegetation analysis.

LiDAR & Multispectral

Digitisation Pipeline

Designed end-to-end workflow from field acquisition to research-grade digital archive

01

Field Acquisition

Multi-sensor spatial capture using UAV photogrammetry, terrestrial LiDAR, and structured-light scanning

02

Point Cloud Processing

Automated registration, classification, and noise filtering of dense point clouds at billion-point scale

03

Neural Reconstruction

NeRF and Gaussian Splatting to generate photorealistic volumetric models with full metric accuracy

04

Archive & Dissemination

FAIR-compliant data packaging, open-access repository deposit, and interactive web-based 3D viewers

Research Outputs

Deliverables designed for academic rigour and institutional interoperability

Digital Twin Archives

Permanent, high-fidelity 3D records of heritage structures deposited in institutional repositories. Ensuring long-term preservation independent of physical site conditions.

  • Metrically accurate point clouds (E57/LAZ)
  • Textured mesh models (OBJ/glTF)
  • Neural radiance field datasets
  • Dublin Core & CIDOC-CRM metadata

Condition & Risk Assessment

AI-generated condition reports identifying structural degradation, material weathering, and environmental risk factors. Supporting conservation planning and funding applications.

  • Automated decay classification maps
  • Temporal change detection (multi-epoch)
  • Risk-priority matrices for conservation
  • Integration with national heritage databases

Funding & Consortium Context

Active engagement with European and national heritage funding frameworks

EU Horizon Europe

Cluster 2

Culture, Creativity & Inclusive Society. Digital heritage preservation, AI for cultural analysis, and citizen science platforms.

EuroHPC JU

AI Compute

High-performance computing allocation for large-scale neural rendering and volumetric processing of heritage datasets.

National Heritage

UK & EU

Historic England, Heritage Fund, and member-state cultural preservation programmes. Statutory compliance and public benefit delivery.

Consortium & Partnership Enquiries

We are seeking consortium partners for upcoming Horizon Europe Cluster 2 and EuroHPC calls in digital heritage and AI-driven cultural preservation.

Contact Heritage Division