We develop advanced geospatial analysis, remote sensing, and computational modelling frameworks to solve critical challenges across heritage preservation, ecological monitoring, and resilient infrastructure.
Explore Our ResearchInterdisciplinary spatial analysis applied to society's most pressing structural challenges.
High-fidelity 3D reconstruction and digital twin creation for at-risk cultural heritage sites. Combining photogrammetry, NeRF-based neural rendering, and LiDAR to produce permanent, research-grade digital archives.
Digital HeritageUAV-based spatial data acquisition for biodiversity assessment, habitat mapping, and agricultural monitoring. Multi-spectral analysis pipelines delivering actionable environmental intelligence at landscape scale.
Environmental MonitoringGeospatial modelling for distributed energy systems, micro-hydro site identification, and rural asset revitalisation. Combining terrain analysis with structural informatics for off-grid deployment planning.
Infrastructure & EnergyEnterprise-grade infrastructure engineered for large-scale spatial data programmes
Technical infrastructure designed for institutional-grade spatial data programmes
Purpose-built data pipelines engineered for institutional-grade spatial data processing. Designed for continuous operation with automated quality assurance, built to Tier-1 High-Performance Computing (HPC) standards for volumetric dataset management.
Multi-stage orchestration frameworks for complex spatial data workflows. Fault-tolerant pipeline architecture with automated checkpointing, state management, and resource-aware scheduling across heterogeneous HPC environments.
Self-hosted, air-gappable compute and storage architecture for sensitive geospatial datasets. Designed for institutional data sovereignty requirements where cloud dependency is unacceptable.
Custom machine learning pipelines for spatial feature extraction, object classification, and neural 3D reconstruction. From LiDAR point cloud segmentation to photorealistic NeRF/Gaussian Splatting volumetric models.
Peer-reviewed research and technical whitepapers from the Applied Spatial team
This paper presents a formal framework for maintaining institutional sovereignty over high-resolution volumetric spatial datasets. We address the growing tension between cloud-hosted compute infrastructure and the data residency requirements of national heritage bodies, proposing a hybrid architecture that preserves sub-centimetre fidelity while guaranteeing jurisdictional compliance under GDPR and the EU Data Governance Act.
We describe a production-validated architecture for large-scale ingestion and classification of multi-source spatial telemetry data. Drawing on proven patterns from High-Performance Computing batch processing systems, we demonstrate how event-driven pipeline design achieves efficient throughput at petabyte scale while maintaining data integrity guarantees critical for regulatory environmental monitoring and statutory biodiversity compliance.
Specialised units with dedicated methodologies, each contributing to the institute's cross-cutting spatial framework.
Volumetric rendering, digital twins, and AI-driven analysis for European cultural preservation. Seeking partnerships with national heritage bodies and EU-funded consortiums.
Visit Division →Aerial telemetry, biodiversity net gain assessment, and rural monitoring using UAV platforms and multi-spectral imaging. Supporting statutory environmental compliance.
Visit Division →Geospatial analysis for resilient grids, micro-hydro feasibility, and rural asset revitalisation. Terrain modelling, watershed analysis, and structural condition assessment.
Visit Division →Institutional-grade project management and regulatory compliance
Structured processes for managing complex multi-stakeholder technical programmes with rigorous reporting standards. Aligned with EU Horizon, Innovate UK, and national heritage funding frameworks. Designed for government compliance environments and institutional delivery requirements.
All data pipelines are version-controlled, documented to institutional standards, and built for independent audit. Outputs conform to FAIR data principles and are compatible with major research data repositories. Full data lineage tracking from raw acquisition through to published outputs.
Data processing and analysis infrastructure engineered for production deployment, handling large-scale datasets with automated quality assurance. Architecture designed for long-running batch reliability with automated monitoring, alerting, and fault recovery.
GDPR-compliant data handling architecture with full residency controls. Designed to ensure sensitive heritage and environmental datasets are processed within EU-resident infrastructure. Encryption at rest and in transit with hardware-backed key management.
Multidisciplinary expertise spanning spatial computing, environmental science, and systems engineering

25-year veteran of full-stack software engineering and enterprise systems architecture. Specialising in bridging the gap between High-Performance Computing and domain-specific academic research. Designing production-grade, sovereign data pipelines capable of handling massive spatial telemetry and volumetric rendering workloads. Oxford, UK.
Applied Spatial operates a federated research model, integrating our core computational infrastructure with domain-specific Principal Investigators, post-doctoral researchers, and field specialists on a project-by-project consortium basis.
This model enables rapid assembly of world-class interdisciplinary teams tailored to each funding call, while maintaining a permanent, production-grade technical backbone. Our federated partners include university research groups, national heritage survey teams, licensed UAV operators, and environmental consultancies across the UK and EU.
We are actively seeking consortium partners for EU Horizon, Innovate UK, and national heritage and environmental funding calls. Technical annex and SME capacity available at short notice.
Contact the Director