Rapidly Processing Planning Data with FME

For most Local Planning Authorities (LPAs), processing development proposals requires manual planning data processing at almost every step. The tasks involved are time-consuming, arduous, and represent a burden on tight budgets. We used FME to remove the need for so much human intervention in the process. This cut the time needed to prepare vital reference data used for cross-checking each proposal.

The SSSI and Impact Risk Zones (IRZ) Dataset

 

When making the call on proposals, LPAs refer to the SSSI Impact Risk Zones dataset, published and updated bi-monthly by Natural England. If a planned development falls within a zone where risk has been identified for that type (e.g. residential), Natural England must be consulted.
The dataset contains information on Sites of Special Scientific Interest and their surrounding Impact Risk Zones (IRZs) across England and Wales. The dataset aims to highlight where sensitivities to different types of development exist. It’s structured as below:

Screenshot showing the SSSI and Impact Risk Zones dataset in FME Data Inspector

If an entry appears in the column, a constraint exists within that zone for that particular type of development. For example, if an LPA received an application for a solar farm within the zone indicated by the first record, they would need to approach Natural England. No entry in the column for what’s been proposed? The LPA can proceed with the decision-making process themselves.

Current Process

The process of preparing and cross-checking the SSSI dataset is difficult. Many use GIS tools like MapInfo Pro to inspect and analyse the raw dataset before splitting it out to separate files for each constraint. The files are then loaded into a central planning system.

As the dataset consists of over 90,000 records, any GIS charged with handling it all often struggles. The slow process is caused largely by the clipping and creation of multiple maps being prepared for the planning system. Natural England updates their dataset every 2 months, so LPAs run the process semi-regularly.

When a proposal is submitted the LPA will refer to the dataset to determine if any relevant constraints are in-effect at that location. They will then either continue to make a decision or consult Natural England.

Speeding-up Planning Data Processing

Following a recent FME training session with a local council, a delegate approached our trainer and told him about their problem. In around 20 minutes, he had created a time-saving workflow to take the pain out of the process.

Screenshot of FME Workflow created to process planning data

Here’s what it does:

  1. Reads-in the SSSI and IRZ dataset, along with the council’s boundary polygon.
  2. Reprojects the data to ensure the user is working with consistent and compatible formats.
  3. Clips the SSSI and IRZ dataset to the boundary polygon – discarding everything outside of this area.
  4. Creates a MapInfo .tab file, including all the constraints present within the area.
  5. Creates a separate .tab file for each possible constraining theme (e.g. wind & solar farms/airports/waste disposal sites).

At the end of the workflow, there’s also scope for adding a transformer to load each of the outputs into a planning system.

We’ve put this article together to show how simple creating time-saving workflows in FME can be. The workflow, created in a lunch-break made a 180MB (in GeoDatabase format) dataset significantly easier to manage. We hope that this inspires you to get the most out of your data and create something that makes your job a little bit easier!

What processes do you think FME could help you to streamline? You can always let our team know by getting in touch!