The advantages of geospatial data for distribution network operators


Where it was once considered the preserve of transmission utilities, the use of LiDAR and remote sensing technology has evolved. Lower-cost data capture and smarter processing mean that geospatial projects now make sense for distribution network operators too.

Technology-led services provide an effective way to reduce vegetation management costs, optimize asset maintenance and improve network intelligence. This is helping operators visualize their assets from the office to make better decisions and reducing the need to go to site. In this blog I wanted to explore why more distribution utilities are adopting a geospatial approach.

Vegetation management

Vegetation managers need accurate network data to ensure they can mitigate the risk of fall-in and grow-in tree infringements. For most utilities the traditional ‘patrol and cut’ approach is time consuming and a major operational expense. Using remote sensing data utilities can target cutting objectively. Accurate data can prioritize the worst vegetation encroachments and identify where no vegetation exists on the network. Reducing unnecessary time patrolling vegetation risk free areas of the network and simultaneously improving service reliability.

Geospatial DNO2

Asset integrity

Distribution networks consist of hundreds of thousands of poles and associated assets. Ensuring a complete up-to-date record of this is always going to be a substantial challenge for any operator. Remote sensing techniques, like LiDAR, deliver a cost effective method to update the asset inventory, which can be further supplemented with additional information.

Geospatial data displays the true location and quantity of assets, as well as pole type and phase configuration. This has many advantages, from maintenance optimization, disaster and financial planning.

Geospatial DNO3

Condition based asset maintenance

Knowing when and where a defect will occur is often difficult to foresee. Standard maintenance cycles usually apply probabilistic methods for predicting asset life. But by collecting more data through remote sensing technology it is possible to achieve a more comprehensive idea of an assets condition. This can be high resolution imagery or video, but often uses infrared or ultra violet sensors to ‘see’ non visible defects, like hotspots or electromechanical weakness. These asset records also allow an operator to make more informed investment decisions on whether to maintain or replace. It also provides an asset image library to better understand the assets before sending teams to the field.

3D asset management

An increasing number of all-of-network distribution projects have requested a system to be able better use the LiDAR and associated spatial data. This has led to the creation of 3D visualization or 3D asset management systems in the marketplace. The advantage of taking the asset data into this environment is you have a populated 'virtual twin' of the network.

Bringing the network into the office provides a powerful, holistic. way to see the network. This can reduce the number of field trips, provide key information such as OHL clearances or the access requirements at a given location. It can also give information on the environmental context of the site, (e.g. land use, safety risks, quantity of vegetation in area etc.)

Geospatial DNO

In summary

LiDAR and geospatial data for network operators isn’t a new phenomenon. What has changed though is that through more cost effective workflows and increased understanding of the applications, more and more distribution utilities are realizing the benefits of a geospatial approach.


Find out how we put these principles into practice here