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The asset management capabilities of GIS rely on data integrated from a variety of sources. Discrepancies can often occur between different datasets, or between older and updated spatial data. For critical utility infrastructure applications, a simplistic fix to reconcile these differences will not pass muster. Achieving the most accurate dataset requires a strategic and rigorous approach to conflation by utilising advanced realignment techniques, excellent project management and extensive industry expertise.

As the GIS plays increasingly crucial roles in managing complex modern utility infrastructure networks, the need for quality and integrity of asset location data becomes ever more vital for efficient, cost-effective, and safe asset management. Accurate location data can also be key to unlocking the full capabilities of a digital twin and smart technologies to optimise performance.

However, as additional sources of data are integrated into a GIS and old data is updated, duplication and discrepancies between datasets can occur. Overlapping or adjacent sections of different maps may not match perfectly.

Meanwhile, utilising newer, more precise location data frequently requires existing GIS data to be spatially adjusted to align with updated asset locations. To position assets accurately, preserve data integrity and merge overlapping datasets without conflicts, a composite combining the best elements of each map must be created. The process of combining and layering geographical information is known as conflation.

Digital cadastre modernisation is underway across much of Australia to better delineate land parcel boundaries. Superseding older map data with more precise location data enables boundaries to better align with GPS, high-resolution imagery, LiDAR, and other high-precision data collection methods. As utility assets are recorded in relation to land boundaries, any change to cadastre mapping requires a corresponding adjustment to infrastructure locations.

The importance of accurate spatial data

Successful conflation is essential to ensure a utility’s GIS uses the most precise, up-to-date location data for more effective asset management, outage management, field services management, project planning, performance analysis, emergency response and other uses.

The quality and integrity of utility infrastructure location data is critical for an array of reasons, and its importance continues to increase as old assets reach end of life and require replacement, and networks are expanded and upgraded, resulting in smarter and more complex networks required to meet changing consumer needs.

Damage to underground utility infrastructure due to inaccurate positional data is an ongoing concern for the industry. Utility strikes result in significant financial costs and service interruptions and pose serious and potentially life-threatening safety hazards to workers and members of the public.

Higher-precision location data vastly expands the potential applications of GIS in the utility sector. As digital transformation gains momentum, the ability to accurately visualise infrastructure locations underpins a growing range of smart technologies to make utilities’ networks, operations and services safer and more efficient, and to unlock additional capabilities and value streams.

Some of the additional benefits of higher-precision location data include:

• The ability to integrate with aerial imagery and new-generation mapping systems
• Reduced costs associated with checking and accessing locations when maintaining, upgrading or replacing network assets
• Improved billing accuracy
• More accurate reporting leading to improved
regulatory compliance

Successful conflation for higher-precision mapping

To achieve a suitable level of data accuracy in the GIS, conflation must be undertaken using mathematically rigorous best-practice methods and optimised workflows. A simplistic ‘rubber-sheeting’ solution, shifting all vertices from one dataset to another, will not suffice.

A successful conflation project calls for expertise and a strategic, scalable approach using advanced and robust mathematical models to realign and reconcile conflicting datasets, supported by a high-performance adjustment engine. The conflation procedures need to allow for the application of business rules and constraints to preserve network topology and connectivity, as well as maintain straight lines, angles, and other important attributes.

Quality assurance processes should ensure outliers are excluded and any other issues that could reduce accuracy are rectified before the updated dataset is applied to a GIS. Data security and the ability to rollback changes are essential. Most importantly, a utility’s business must not be interrupted, allowing work to continue while conflation is underway.

Expert conflation for utility assets

we-do-IT has extensive experience delivering utility industry conflation projects on time and on budget. Utilising proprietary quality-assurance and project-management processes, robust technology and advanced mathematical modelling, we-do-IT helps utilities achieve the highest levels of GIS location accuracy, all without interrupting business as usual.

This sponsored editorial is brought to you by we-do-IT. To find out more contact we-do-IT on (03) 9098 8617 or email [email protected].

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