GridSight® VGM · Vegetation Management.

Vegetation encroachment is one of the leading causes of outages and wildfires on overhead lines. Risk comes from direct contact (vegetation inside the right-of-way growing close enough to touch or arc to a conductor) and tree-fall exposure (tall trees outside the RoW whose fall radius reaches the line). Traditional periodic field inspections are reactive, labour-intensive, and blind between inspection cycles. GridSight® VGM replaces that snapshot-in-time approach with continuous, predictive monitoring.

GridSight® VGM combines LiDAR-derived terrain/surface models with multi-channel orthophotography in a multi-stage AI pipeline: vegetation is segmented and classified into vegetation classes - species-level where the local taxonomy supports it - with a target accuracy of ≥90% (precision, recall and F1); a species-calibrated growth model projects height trajectories over configurable horizons; distance from each grid point to the nearest conductor (from the true 3-D catenary geometry) drives High/Medium/Low risk classification with client-customisable thresholds; and an integrated pruning scheduler manages planning, execution and audit of trimming actions with automatic risk recalculation after each pruning.

Spatially resolved vegetation risk maps with recommended actions; risk-per-tower charts; per-span alert tables with clearance and fall-distance metrics; growth-forecast timelines for time-to-encroachment estimation; a pruning planning scheduler with full audit trail; and GIS export in GeoJSON, WFS and Shapefile formats compatible with Esri ArcGIS and QGIS.

Yes. GridSight® VGM produces audit-ready clearance records and pruning documentation aligned with NERC FAC-003, the North American transmission vegetation management standard, and exports in industry-standard geospatial formats - including OGC-compliant WFS - for interoperability with enterprise GIS platforms.

GridSight® VGM works from LiDAR-derived terrain and surface models (DTM/DSM in LAS, LAZ, TIF or TIFF, pre-classified for cables, structures, vegetation and ground) combined with multichannel orthophotos (TIFF with at least four channels: R, G, B and infrared), plus static asset data such as tower coordinates and geometry. Without a survey, accurate vegetation risk analysis isn't possible - talk to us about options for getting one done.

Growth models start from published parameters per species and region, constrained by WWF ecoregion context for species plausibility. They're then calibrated with periodic re-scans and auto-optimise with each new data acquisition - the more re-scans a corridor accumulates, the more the forecast relies on its own observed growth data rather than literature averages, until it converges on that corridor's actual behaviour.

Yes. Beyond direct-contact risk inside the corridor, GridSight® VGM evaluates the fall radius of tall trees outside the right-of-way against the real 3-D catenary geometry of the conductors, and correlates the result with real-time and forecast weather (wind, precipitation) to generate actionable, weather-aware alerts.