National Building Intelligence Platform: 44 Million Polygons

Snapshot

We are building the spatial data foundation for Apexion’s solar development platform, with the broader aim of creating a UK digital twin for property intelligence. The brief is to turn 44 million building polygons into a queryable PostgreSQL/PostGIS database, integrated with environmental and planning constraint layers, that can support solar site assessment and, ultimately, property risk analysis and planning intelligence at scale. The system already handles complex spatial queries across the UK building stock in seconds. Work is ongoing to expand constraint coverage and integrate planning history.

Challenge

Apexion’s immediate focus is a solar development platform that can assess sites across the UK for solar potential, planning viability, and environmental constraints. The longer aim is a comprehensive UK digital twin for property intelligence, covering risk analysis, planning constraint queries, and development assessments across multiple sectors.

The solar platform requires spatial data covering every building polygon in the UK. Forty-four million polygons at national scale means careful attention to data structure, quality, and accessibility. Site assessment needs to evaluate roof characteristics, solar irradiance potential, grid connection proximity, and planning feasibility across the entire building stock.

Our role is gathering, processing, and structuring the spatial data that underpins the platform. This means systematically assembling environmental designations, conservation areas, flood zones, grid infrastructure data, and planning constraints from multiple sources. Each constraint type comes from different providers with varying data quality and formats.

The most substantial challenge is historic planning application data. Gathering planning applications for the entire UK means working with hundreds of individual local planning authorities, each with their own systems, data formats, and levels of digital record-keeping. Data structures vary considerably between authorities. Some have spatial data, some do not. Historical records are patchy. It is a large data gathering and standardisation exercise that will support both immediate solar assessments and the longer-term digital twin.

Our approach

Systematic data gathering and processing: We are working through environmental and planning constraints methodically, identifying authoritative sources, establishing data refresh patterns, and processing each layer into consistent, usable formats. This includes designated sites, conservation areas, flood zones, grid infrastructure, environmental protections, and planning constraints. Each constraint type requires validation, projection handling, and quality assessment.

Planning application data collection: Gathering historic planning applications across the UK requires engagement with hundreds of local planning authorities. We are developing systematic approaches for extracting data from various planning systems, standardising disparate data structures, and handling the considerable variation in digital record quality. Where spatial data exists, we process it into consistent formats. Where it does not, we work with address data and location references.

Building polygon processing: Working with 44 million building polygons from multiple providers means handling inconsistent topology, varied attribution, and different levels of completeness. We process these datasets to ensure spatial validity, consistent projection, and usable attribute structures that support the platform’s analytical requirements.

Data quality and validation: We have developed repeatable processes for handling inconsistent source data. Topology validation and correction routines ensure spatial integrity. Reprojection workflows maintain consistency. Where source quality is variable, we implement validation checks and document known limitations rather than attempting corrections that cannot be sustained.

Documentation and handover: We provide clear documentation of data sources, processing steps, known limitations, and refresh patterns. This ensures Apexion’s team can maintain and extend the datasets as the platform develops.

What we’re delivering

• Processed building polygon datasets covering the UK building stock — 44 million features validated for topology, reprojected to consistent coordinate systems, and structured with usable attribution
• Systematic constraint data covering environmental designations, conservation areas, flood zones, grid infrastructure, and planning limitations — each layer validated, standardised, and documented with refresh patterns and known limitations
• A developing national planning application dataset, gathering historic planning data from local authorities across the UK, standardising varied data structures, and processing both spatial and non-spatial planning records into consistent formats
• Data quality validation and documentation — clear records of source providers, processing steps, topology corrections applied, projection handling, and known data limitations for each dataset
• Ongoing data support as new constraint types are identified or planning authority data becomes available, incorporating new sources using established processing workflows

Impact & next steps

• Solar platform data support: We are providing the processed spatial datasets that underpin Apexion’s solar development platform. Building polygons, constraint overlays, and planning context data at national scale, structured to support site assessment and viability analysis.
• Expanding constraint coverage: Systematically gathering and processing environmental and planning constraint layers relevant to solar development and broader property assessment. Each new dataset extends the platform’s analytical capabilities.
• National planning application data: Gathering historic planning applications from hundreds of local authorities is a substantial undertaking. The variation in systems, data structures, and digital record quality requires patient, systematic work. As this dataset develops, it will provide visibility into UK planning history at scale.
• Data quality and documentation: Systematic processing and validation means Apexion receives datasets with clear provenance, documented limitations, and consistent structure. Known data quality issues are flagged rather than hidden, which supports confident use of the data.

The focus throughout is systematic acquisition, careful processing, and clear documentation. The solar platform provides immediate commercial application while the data foundation supports the longer-term vision of a UK digital twin for property intelligence.