Martin Eglin¹, Philip Midgley¹, David Tarrant² and Simon James²

¹JBA Consulting
²Natural Resources Wales (NRW)

NRW maintain a suite of flood risk datasets that support decision-making, investment planning and resilience across Wales. Two important datasets are flood defence lines, which denote the location and key attributes of assets on the ground, and defended areas, representing the geographical areas protected by those assets. Although closely related, these datasets are maintained independently, creating spatial inconsistencies that can affect downstream analysis.

Issues became apparent when calculating the costs associated with defences within national investment planning tools. Maintenance and operational costs are reported at the defended area level and individual defence lines frequently span multiple defended areas. Cost allocation therefore relies on spatial intersection analysis and unit-cost calculations. Where defended area boundaries are not correctly aligned with defence lines, costs can be under-reported, affecting economic assessments and future investment decisions.

To address this challenge, NRW developed an automated GIS workflow using Python and ArcGIS Pro. The workflow identifies defence lines that are not correctly connected to defended area polygons using near-table analysis and distance-based calculations. Polygon vertices requiring adjustment are identified automatically, and translation vectors are generated between those vertices and their nearest defence line. These vectors are then used to reshape defended area boundaries, improving alignment while maintaining user control through configurable tolerances and filtering options.

The workflow is executed from the command line and has significantly reduced the manual effort required to review and correct defended area boundaries. Quality assurance is supported through the creation of intermediary outputs that visualise every vertex translation, allowing analysts to review and validate automated changes before acceptance.

This presentation will describe the challenge, spatial analysis techniques used and lessons learned. It will also explore the balance between automation and manual intervention when maintaining large, interconnected geospatial datasets. Whilst some complex line-polygon interactions still require manual editing, the approach has substantially improved the data quality and reporting accuracy that underpins key investment decisions.