Utility Example 2

High-resolution LiDAR to modernize utility asset tracking

Three decades of data quality improvements enable better visualization and asset management tool to support data-driven decisions
Jan 26, 2018

Utility companies are challenged with managing a wide range of assets across large geographical areas. Until recent years, tracking or cataloging these assets has been accomplished with two-dimensional maps.

Then came digital geographic information systems (GIS) to provide georeferenced data management capabilities and enhance the ability to keep track of assets. GIS data systems pulled in all available mapping data and began to digitally catalog information associated with assets throughout the network.

The difficulty today is that the mapping information doesn’t always line up. Why is this? There are a few factors to consider here:

  • Quality of the base mapping: GIS systems provide the opportunity to “layer” different types of information to build a better overall picture of an area of interest. The layers begin with data collected through various sources, to map or physically represent the physical world. Our first source of misalignment is the inherent deviations made in translating Earth surface points into a digital representation.
  • Estimation of data points: during field survey or aerial data collection, not every single point on the earth can feasibly be collected. To get a continuous set of data points to make a complete map, the surface points in between the collected points must be extrapolated or estimated. The further the distance between the collected data points, the more potential for deviations. 
  • Global positioning sensor (GPS) accuracy: most field and aerial survey data is collected by assigning GPS location information for the data point collected, like a point at the edge of a street or location of a power pole. The GPS points are created by triangulation method: the ground receiver receives communication from at least three satellites in space to calculate location. In the 1990s, the accuracy of GPS systems was within 6 to 12 meters, but as more GPS satellites became available, the accuracy has increased to less than 1 meter in 2017.
  • Keeping up with technology: As GIS tools became available, many utilities rushed to implement digital management tools so base map and asset location mapping information was pulled from several different sources in different formats and were “best fit” to the GIS system. Over time, more distribution lines were added, infrastructure was upgraded or replace or relocated due to urban growth. Even the most diligent tracking teams were unable to record every change in rapid growth periods.

Advances to improve accuracy

In the mid-1990s, the surveying industry began experimenting with new technologies to increase data collection times and improve accuracy. Light detection and ranging (LiDAR) systems became a valuable tool to achieving these goals. It also added a new dimension. From a land-based or airborne unit, the LiDAR sensor sends pulses of light and calculates the distance the reflection travels back to the sensor based on the time it takes. These sensors collect position coordinates on land, but they also offer a third dimension by collecting a vertical location data point.

While this technology offers advances in mapping the earth’s surface, the technology was just beginning to offer enough detail and quality data to identify individual utility assets.

Today, high-resolution LiDAR data is improving to the location accuracy and providing enough feature detail to identify distribution assets such as poles, conductors, and distribution transformers.

High-resolution LiDAR data points map these assets within centimeters of their exact location, giving the utility a much more accurate picture, two-dimensionally as well as three-dimensionally, of their transmission and distribution networks.  The value in having this information in 3D allows for the development of system wide modeling to produce information that supports data-driven decision making.

With a more accurate and complete information, utilities can better visualize and manage assets and produce information to support data-driven decisions:

  • Improve system visualization
  • Develop risk-based strategies that eliminate unplanned asset failures
  • Improve reliability
  • Enhancing asset investment strategies
  • Monitor aging infrastructure
  • Maximize the life of existing and new asset investments