Corridor-wide envelope context
Review fitted conductors and envelope overlays directly on the hosted corridor point cloud to see where clearance risk concentrates along the span.
Powerline LiDAR analytics for spans, clearance envelopes, encroachment, and fuel
SmartData is expanding powerline workflows from hosted point clouds into corridor intelligence: classified networks, pole and span foundations, catenary fits, worst-case clearance envelope screening, encroachment, pole lean, fuel metrics, contours, and evidence reports.
Status
Active buildout
Best-fit audience
Utilities and network operators
A product page for utilities and corridor managers who need more than a survey-day point cloud: they need a defensible screening layer that shows where clearances can tighten under thermal sag and wind conditions.
Turn a drone LiDAR survey into a worst-case clearance screening report.
Show the difference between where the conductor was on flight day and where it can be under load and wind.
Prioritise spans for trimming, field review, or certified engineering follow-up.
See the workflow in SmartData
Product screenshots show how hosted spatial context connects with linked inspection evidence inside the SmartData workspace.
Structure-to-structure span review
Inspect how conductor geometry, span fit, and envelope lines behave through a section of corridor rather than relying on a single survey-day clearance snapshot.
Long-span clearance screening
Use the point cloud view to compare corridor vegetation and ground context against fitted spans and screening overlays before prioritising review or follow-up work.
What this unlocks
Connect source data, SmartData processing, hosted views, and review outputs so operational teams can move from capture to decisions with less file handling.
Ground, vegetation, conductor, and structure classification
Pole clustering and span ordering
Exact catenary fit per span from classified LiDAR points
Thermal sag and wind blowout envelope screening from a single survey
Vegetation and ground clearance against the swept conductor envelope
Monte Carlo uncertainty bands with P50 and conservative P05 outputs
Self-consistency gates that exclude weak spans instead of silently guessing
Voxel fuel metrics, hotspot segments, contours, HTML reports, and JSON sidecars
Workflow story
1
Load a corridor point cloud with usable LAS/LAZ classes or run SmartData classification.
2
Build the network foundation: poles, spans, and corridor ordering.
3
Fit conductors with exact catenary mechanics and infer the observed conductor state.
4
Re-solve clearance scenarios for elevated operating temperatures and wind blowout.
5
Compare survey-day clearance with envelope clearance for vegetation and ground points.
6
Report P50/P05 clearance bands, uncertainty drivers, excluded spans, assumptions, and exports.
Commercial use cases
- Turn a drone LiDAR survey into a worst-case clearance screening report.
- Show the difference between where the conductor was on flight day and where it can be under load and wind.
- Prioritise spans for trimming, field review, or certified engineering follow-up.
Delivery notes
- Current analytics cover classification, network foundation, catenary fitting, clearance, encroachment, pole lean, and fuel.
- The worst-case clearance envelope engine produces screening reports with HTML and JSON outputs.
- Envelope outputs are for screening and prioritisation, not certified engineering assessment or PLS-CADD replacement.
- Fuel mass is indicative and should carry QA/assumption language.
- Outputs can include point cloud overlays, clearance/envelope reports, and analytics side panels.
Utilities and network operators
SmartData gives this team a hosted workflow for turning complex capture outputs into reviewable evidence.
Vegetation management teams
SmartData gives this team a hosted workflow for turning complex capture outputs into reviewable evidence.
Drone LiDAR providers working on corridor programs
SmartData gives this team a hosted workflow for turning complex capture outputs into reviewable evidence.
Common questions
Straight answers about inputs, availability, outputs, and where human review still matters.
Does SmartData need classified LAS input?
It can prefer existing classes where available or run built-in classification heuristics, with network type and data quality affecting confidence.
What is the first practical engagement?
A scoped clearance-screening pilot on representative corridor data, with clear QA notes around classifier confidence, excluded spans, uncertainty drivers, fuel assumptions, and corridor complexity.
Where do contour and terrain outputs fit?
They sit alongside the LiDAR corridor view as terrain, clearance, and surface context rather than replacing the network analytics stages.
Is this a certified engineering assessment?
No. The clearance envelope workflow is positioned as a screening and prioritisation layer. It helps teams find spans that deserve trimming, field review, or certified engineering follow-up.
Why not just use survey-day LiDAR clearances?
A drone survey shows the conductor state at capture time. The envelope workflow screens how clearance can change under higher operating temperature and wind assumptions, then reports the uncertainty instead of hiding it behind one number.