Preparing for Winter: How Geospatial Data Helps Utilities Build More Resilient Networks
Winter presents a predictable but significant operational challenge for electricity networks. Storm activity, heavy snow, ice loading and wind-blown vegetation all increase the likelihood of faults and outages. As utilities enter the most demanding period of the year, a detailed, data-driven understanding of network condition and surrounding hazards becomes essential for maintaining reliability and reducing customer impact.
Across the sector, high-accuracy geospatial data and digital network models are becoming key tools for identifying winter risks, prioritising maintenance, and supporting operational decision-making before severe weather arrives.
Using LiDAR and 3D Network Models to Identify Winter Risks
Aerial LiDAR surveys remain one of the most effective ways for utilities to understand their overhead line environment. With centimetre-level accuracy, this data provides a comprehensive, engineered view of each span, including:
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Precise vegetation clearances
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Trees with potential to contact conductors during storms
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Condition and position of structures
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Span geometry, sag and ground clearances
From this dataset, NM Group develops 3D digital network models that highlight where winter conditions are most likely to introduce risk – whether from wind-driven tree movement, snow-laden branches or tall leaning trees.
This level of insight enables utilities to prioritise and complete targeted, preventative maintenance, reducing the likelihood of weather-related outages and improving overall winter resilience.
Understanding Snow Loading and Trees That Bend Into Lines
In colder climates, snow and ice accumulation can cause trees to deflect significantly, bringing branches or stems into contact with conductors. Crucially, many of these trees may sit well outside traditional clearance limits under normal conditions.
By segmenting LiDAR point clouds into individual tree objects, NM Group creates a detailed virtual forest inventory. This enables analysis of:
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Likely bending behaviour under snow load
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Crown width-to-height ratios
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Centre of gravity
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Required bend angle before contact
This engineering-led approach isolates the small proportion of trees that present a realistic snow-loading risk. As a result, utilities can focus resources on high-risk locations ahead of winter, rather than managing thousands of lower-priority trees.
Combining Multiple Data Sources for Better Winter Planning
Most utilities now collect data from a wide range of sources: LiDAR, drone imagery, satellite monitoring, fixed sensors, weather records and historic fault information. Integrating these datasets provides a far more complete view of network conditions than any single source alone.
NM Group supports winter planning by combining these inputs into a clear, accessible picture of emerging risks. This helps operators answer key questions such as:
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Which spans or corridors are most exposed to storm activity?
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Which areas require pre-storm vegetation checks?
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Where should operational crews be positioned ahead of severe weather?
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How is the network environment changing year on year?
This multi-source approach gives utilities the operational intelligence needed to make confident decisions under winter conditions.
Preparing for Winter Operations
As winter progresses, utilities must manage a combination of challenges: severe weather, limited inspection windows and increased vegetation movement. High-quality geospatial intelligence provides a practical way to reduce preventable outages and target maintenance where it delivers the greatest benefit.
By combining high-accuracy LiDAR, engineering analysis and multi-source geospatial modelling, NM Group supports operators in strengthening winter resilience, improving safety and maintaining reliable supply during the most demanding months of the year.