TL;DR: Utility asset management using aerial imagery and data provided from a program like Eagleview reveals infrastructure conditions across entire service territories without needing to dispatch crews to each location. Utilities can build accurate inventories and prioritize capital replacement based on actual risk rather than age alone.
Utility asset management using systematic aerial capture replaces reactive field inspection with comprehensive condition documentation across distribution and transmission networks. Utilities operating under consent decrees or facing accelerated failure rates can inventory millions of components and identify defects like corroded hardware, overloaded poles, and oil-stained transformers without the labor cost and safety exposure of bucket truck assessments at every location.
In this post, we'll discuss how modern utility asset management combines high-resolution aerial imagery, oblique capture technology, and GIS integration to create the authoritative asset data utilities need for predictive maintenance and grid modernization planning to prevent failures of any kind.
Why Utility Asset Management Drives Grid Reliability
The U.S. electric grid faces a dual challenge in aging infrastructure and surging demand. Most components were built in the 1960s and 70s. According to the Department of Energy, 70% of power transformers are 25 years or older, 60% of circuit breakers are 30 years or older, and 70% of transmission lines are 25 years or older. The National Renewable Energy Laboratory found that 55% of distribution transformers are at least 33 years old.
These assets are approaching the end of life simultaneously. Failure rates will accelerate after 2030, exactly when electrification and data center expansion will increase electricity demand by 27 to 39% compared to 2021 levels.
Capital spending on distribution infrastructure increased 160% from 2003 to 2023, reaching $17.4 billion for overhead systems alone in 2023. Yet this investment surge hasn't translated to proportional reliability gains. Most utilities still operate on age-based replacement cycles that write off transformers at 35 years regardless of actual condition and leave degraded poles in service because they haven't reached the predetermined retirement threshold. Utilities end up overinvesting in functional assets while deferring maintenance on equipment approaching failure. Without condition data to differentiate between a 40-year-old pole with sound wood and a 20-year-old pole compromised by decay, utilities allocate capital based on install dates rather than failure probability.
The cost of getting this wrong adds up. Power outages cost the U.S. economy $18 to $33 billion annually. Reactive maintenance costs three to five times more than preventive approaches. When a pole snaps during a storm or a transformer causes a fire, regulatory and legal exposure can dwarf the replacement cost.
The data gap behind utility asset management failures
Most utilities know they have data problems. Many still track assets using spreadsheets, tribal knowledge, and decades-old GIS data that has high potential to be incorrect.
Pole locations might be off by meters, and transformer ratings might be wrong. When the majority of asset records contain errors, any analysis built on that foundation produces unreliable conclusions.
Most asset records break down here:
| Asset Record | Typical GIS Entry | What Aerial Imagery Shows |
| Pole | Location, class, install year | Lean angle, crossarm condition, guy wire issues, overloaded attachments |
| Transformer | kVA rating, install year | Oil staining, corrosion, mounting condition, and access constraints |
| Crossarm | Material, age | Splits, rot, missing hardware |
| Insulators | Count | Cracks, chips, missing units |
| Attachments | Communications present | Full attachment stack, unauthorized installs, loading risks |
| Vegetation | Cleared last cycle | Trees within fall distance, brush blocking access |
| Transmission structure | Tower ID | Bent members, footing issues, loose hardware |
Limited capital budgets force asset managers into prioritization decisions without the data to justify them. A transformer bank serving commercial load may be 40 years old, but if the oil tests clean and cooling systems function properly, replacement might wait. Meanwhile, poles rated for 30 years can fail at 15 if foundation conditions accelerate decay or if ice loading exceeds design assumptions. Without measured condition data distinguishing between chronological age and structural integrity, utilities default to worst-case planning or respond to the most visible complaints.
Capital gets allocated to the substation that attracts board attention or the feeder where a council member lives, not necessarily where failure probability times consequence produces the highest risk score. This explains why utilities can simultaneously over-invest in redundant capacity while experiencing preventable outages from assets that looked fine in outdated records but had degraded past safe operation.
Building authoritative asset inventories
High-resolution aerial imagery captures utility infrastructure across entire service territories in days. One gas utility serving the western United States built a complete foundational dataset across 7,000 miles of corridor within 90 days. The timeline would have been impossible using their existing imagery and field inspections.
Eagleview's oblique aerial imagery provides 40-to-50-degree angle views from all cardinal directions, revealing details that top-down imagery cannot show.
This multi-angle capture matters because utility assets are three-dimensional. A top-down view shows pole locations but obscures attachments.
Eagleview imagery does this by delivering more than 70 times the resolution of standard satellite data. Analysts can identify individual equipment types, measure attachment heights, count insulators, and assess visible damage from their desks.
This imagery creates a visual baseline for comparison against existing GIS records.
Condition assessment and defect identification
Aerial imagery reveals structural defects that age-based inspection schedules miss. Analysts spot poles leaning beyond manufacturer tolerance. They catch crossarms with stress cracks propagating from bolt holes. Insulators show porcelain fractures that precede flashover. Corrosion patterns on steel hardware signal imminent mechanical failure. Vegetation encroachment violates minimum clearance distances. Compromised guy wire anchors appear in the same capture. These conditions don't correlate with asset age, which is exactly why condition-based assessment catches failures that calendar-driven programs overlook until equipment is already de-energized or on the ground.
First-pass review identifies obvious problems across entire service territories at a fraction of field inspection costs. The approach provides predictive asset management. Utilities work from prioritized lists where imagery has identified issues, rather than waiting for failures or driving every circuit looking for problems.
Identifying overloaded poles before they snap
Each pole has a structural capacity determined by class, material, age, and condition. Every attachment adds load: transformers, switching equipment, communication cables, guy wires, and service drops. When the total load exceeds capacity, the failure risk increases dramatically.
Overloaded poles break more easily, sustain greater storm damage, and can fail without warning, causing outages, injuries, property damage, and regulatory scrutiny.
Traditional pole loading analysis sends field crews to inventory attachments one pole at a time. Aerial imagery assesses entire networks systematically.
Oblique views capture attachment configurations from multiple angles. Analysts count transformer banks, communication equipment, and service drops without dispatching trucks. They flag poles carrying equipment beyond class rating. Visible deflection in crossarms indicates loading past design limits. Guy wires under excessive tension show stress patterns before anchor failure. This screening identifies which poles need structural calculations and which can wait, concentrating engineering resources where loading actually exceeds capacity rather than inspecting everything sequentially.
Detecting corroded equipment before failure
Corrosion degrades equipment predictably but invisibly from the inside. High-resolution imagery catches the external signs before internal failure. Rust staining on steel hardware indicates moisture penetration and loss of galvanization.
Oil staining below the transformer points to gasket failure and contamination risk. Discoloration on aluminum connectors suggests oxidation, increasing resistance at termination points. Surface pitting on tank walls precedes through-wall corrosion. These visual indicators don't confirm how far degradation has progressed internally, but they identify which assets need dielectric testing, oil sampling, or thermal imaging rather than waiting for catastrophic failure during peak load.
While imagery can't detect internal corrosion, it provides systematic screening that identifies equipment warranting detailed inspection.
Asset-Specific Applications for Utility Asset Management
Pole condition and remaining useful life
Wood poles remain dominant in American distribution systems. They're vulnerable to decay, insect damage, and mechanical failure that’s difficult to detect until collapse becomes imminent.
Aerial imagery contributes multiple data points for assessing remaining useful life.
By combining imagery-based assessment with age data and maintenance history, utilities estimate remaining useful life more accurately than age alone permits.
Distribution transformers step down voltage for customer use. Utilities manage millions across residential, commercial, and industrial applications. Failures cause outages and can result in fires.
High-resolution oblique views reveal transformer nameplates and tank configurations. Analysts verify inventory records against actual installations. Equipment styles indicate the manufacturing era when install dates are missing. Oil staining flags seal degradation requiring follow-up. Pad conditions show whether maintenance trucks can reach the unit or if vegetation needs clearing first.
Transformer density mapping identifies neighborhoods approaching capacity limits before customer complaints start. This beats driving circuits to photograph each unit or trusting decades-old GIS records that list wrong kVA ratings or show transformers that were removed years ago.
Transmission structure assessment
Transmission infrastructure carries higher voltages over longer distances. Tower failures can cascade into regional outages affecting millions.
Eagleview imagery provides tower assessment without dispatching helicopters or climbing crews. The imagery creates documentation supporting regulatory compliance, which can be inspection coverage and remediation tracking tied to specific assets and dates.
Vegetation encroachment on assets
Vegetation threatens assets beyond conductor contact. Trees growing into guy wires compromise pole stability, while brush accumulating around pad-mounted transformers creates fire risk and blocks maintenance access.
Aerial imagery captures vegetation conditions across all asset types, from trees within fall distance of structures to brush blocking equipment access.
Digital Twins and Grid Modernization in Utility Asset Management
Grid modernization requires accurate models of existing infrastructure. Digital twins, or virtual replicas of physical assets, help utilities to simulate and optimize operations.
Eagleview's georeferenced imagery provides the foundation for digital twin creation. Combined with 3D point cloud data, it captures asset locations, configurations, and spatial relationships in measurable detail.
These models support capacity planning and upgrade sequencing. They feed interconnection studies with accurate as-built conditions. Resilience analysis runs on actual infrastructure geometry rather than approximate GIS records. Construction planning identifies conflicts before crews mobilize.
The imagery becomes a single authoritative source. Planning, engineering, and operations reference the same dataset. No more reconciling conflicting records between departments.
Smart grid deployments require knowing what's actually installed. Aerial imagery updates GIS with verified asset positions. It confirms equipment types and ratings before deploying sensors or controls. Targeted planning works when you're not guessing about pole classes or conductor sizes based on records from 1987.
Integrating Aerial Imagery Into Utility Asset Management Programs
Imagery integration determines whether utilities actually use the data. Esri users overlay high-resolution views directly on network maps. Click any asset, and oblique angles load without switching applications. Measurement tools calculate span lengths, attachment heights, and clearance distances in the same viewer. No separate software required.
This matters because adoption drops when workflows require three different logins. Analysts stick with tools that fit existing processes. If viewing imagery means exporting to another platform, most won't bother. Direct integration keeps the data where planners and engineers already work.
Field verification workflows
Aerial imagery makes field work more productive by directing crews to identified problems with context before arrival.
Imagery review identifies potential issues, which are ranked by severity and turned into work orders with a visual reference attached. Field crews arrive knowing what they're looking for and can compare current conditions against the remote assessment before documenting their findings back into GIS.
Change detection
Utility networks change constantly. Regular imagery capture creates temporal records supporting change detection. That can mean new attachments, advancing vegetation encroachment, or accumulating damage.
Utilities can track condition evolution and verify completed work. The visual record supports regulatory compliance and dispute resolution. By tracking visible deterioration over time, utilities better predict remaining useful life, providing more sophisticated replacement planning than age-based schedules.
Utility Asset Management: ROI and Implementation
Transitioning from reactive to predictive maintenance
The shift from reactive to predictive asset management requires accurate condition data. Utilities can't predict failures and respond to them instead.
Aerial imagery identifies degradation patterns before failures, prioritizing maintenance based on actual risk.
The approach also supports reliability and safety standards. Utilities can document asset conditions systematically, catching hazards before they cause outages or injuries.
Focus on two things: measuring ROI and getting implementation right.
Measuring ROI
After the first imagery review, count how many GIS records need correction. That number quantifies your data quality problem. It's also the baseline for measuring improvement.
Compare inspection economics next. Field crews assess a few hundred poles per day. Desktop analysts reviewing imagery cover several thousand. Calculate cost per asset under both methods. Include vehicle expenses, labor hours, and safety costs. Keeping crews off ladders and out of traffic has real value even if safety managers don't put a dollar figure on avoided incidents.
Track unplanned outages from asset failures over 18 to 24 months. Imagery-based inspections should catch degraded equipment before it fails. Outage frequency drops. Emergency callouts decrease. Document the transformer fires that didn't happen and the poles that didn't snap during storms. These avoided costs exceed direct labor savings but require longer measurement windows to capture properly.
Implementation
Pick a pilot area where asset data is demonstrably wrong. Choose circuits where crews routinely arrive at incorrect pole locations or find transformers that don't match the work order. These problem areas prove value faster than well-documented networks.
Run imagery capture across the pilot area. Have analysts review against GIS and document every discrepancy. Missing poles. Wrong transformer types. Unrecorded communication attachments. Correct the records systematically.
Measure work order accuracy over the next three months. Truck rolls to wrong locations should drop. Material orders should match what's actually installed. Crew time wasted searching for equipment decreases.
Expand to adjacent circuits once the pilot demonstrates measurable improvement. Integrate imagery into existing crew applications. Separate logins kill adoption. Field staff won't open another system no matter how good the data is.
Schedule annual or biennial recapture. Data goes stale as attachments change and equipment gets replaced. Regular updates maintain accuracy or you're back to guessing within two years.
Optimize Your Utility Asset Management Program With Eagleview
Aerial imagery provides the foundation for modern asset management. High-resolution oblique imagery reveals details that traditional methods miss while covering entire service territories in a fraction of the time.
Eagleview's imagery integrates directly with existing GIS platforms, so utilities transition to predictive asset management that maximizes infrastructure ROI while meeting reliability and safety standards.
Want to see what a utility asset management integration could look like?
Get in touch with Eagleview to see how aerial imagery can improve your data accuracy and inspection efficiency.
FAQ
What Eagleview products support utility asset management?
Eagleview's oblique aerial imagery captures 40 to 50 degree angle views from all cardinal directions at more than 70 times satellite resolution. CONNECTExplorer provides web-based access to imagery with built-in measurement tools. For utilities running Esri platforms, the Eagleview for ArcGIS integration overlays imagery directly on network maps.
How does Eagleview imagery support digital twin creation?
Eagleview's georeferenced imagery, combined with 3D point cloud data, provides detailed digital representations of utility infrastructure. These models capture asset locations, configurations, and spatial relationships to support capacity planning, upgrade sequencing, and construction planning.
What asset conditions can aerial imagery identify for utility asset management?
Analysts can identify leaning poles, damaged crossarms, missing insulators, corrosion, vegetation contact, unauthorized attachments, and guy wire problems. Rust staining on hardware and oil staining below transformers also becomes visible. Imagery doesn't replace structural inspection for internal defects like wood decay, but it screens entire service territories at a fraction of field inspection costs.
How does utility asset management using aerial imagery help identify overloaded poles?
High-resolution oblique imagery captures attachment configurations from multiple angles. Analysts can inventory transformers, communication cables, service drops, and other equipment on each pole, then compare against pole class capacity. Poles showing excessive loading or structural stress get flagged for engineering analysis before they fail.
Can aerial imagery replace physical pole inspection?
No, but it changes how you allocate inspection resources. Imagery provides first-pass screening that identifies poles requiring detailed assessment. Field crews concentrate on the highest-risk locations rather than inspecting everything sequentially.
How often should utilities capture new imagery for utility asset management programs?
Most utilities schedule annual or biennial capture for distribution networks. Transmission corridors or areas with rapid development may need more frequent updates. Regular capture powers change detection so you can spot new attachments, advancing vegetation, and accumulating damage before they cause problems.
How does utility asset management documentation support regulatory compliance?
Aerial imagery creates timestamped visual records tied to specific assets and dates. Utilities can demonstrate inspection coverage, document defects and remediation, and provide visual evidence of maintenance activities. When regulators ask for proof that assets are maintained properly, georeferenced imagery provides an auditable chain showing what was inspected and when.