Vegetation Utility Lines

Case study

AiDash: Satellite-powered utility vegetation management

UP42 helped AiDash transform vegetation management for a Fortune 500 power utility company.


AiDash is an AI-first vertical SaaS company enabling satellite-powered operations & maintenance for core industries with distributed assets. AiDash uses high-resolution, multispectral imagery and SAR data from the world’s leading satellite constellations that are fed into its proprietary AI models to make timely predictions for operations and maintenance (O&M) activities. This is coupled with an app that enables prioritized completion and audit of these O&M activities. The company has offices in the San Francisco Bay Area, Washington D.C. Metropolitan Area and Bengaluru.


One of AiDash’s customers, a Fortune 500 power utility company, wanted to manage vegetation effectively along distribution lines spanning over 50,000 miles.

Vegetation management remains the single largest line item in annual operations and maintenance budgets of most power utilities in the USA—exceeding $100 million annually at many larger utilities. Poor vegetation management is one of the major reasons for frequent power outages and wildfires across the country.

Outages cost an average of around $33 billion per year in the United States alone. In addition to this, increasing scrutiny from customers, the media, regulators, and more has led utility companies to better understand the risk of liabilities.

For most power utilities, the vegetation management process is manual, routine, and unoptimized. AiDash’s client faced challenges with this traditional approach. Scheduled trimming cycles spanning 4 - 5 years and manual data collection left the company with minimal predictive capabilities to prevent future outages, damages, and costs.

Managing their distribution lines and assets spread over 50,000 circuit miles across multiple states—proved expensive, difficult and time-consuming.

The lack of visibility with respect to urgent situations and hazards and an inability to identify the exact point of failure resulted in reactive and ad-hoc maintenance that is primarily expensive.

Power Lines

Easy access to satellite data using UP42 formed the backbone of AiDash’s IVMS solution.


Satellite imagery for an AI platform offering end-to-end asset visibility.

AiDash were looking for a solution to transform the way that their customer conducted vegetation management. It had to be reliable, accurate, and easy to use. To solve this, they developed an end-to-end AI proprietary model called the Intelligent Vegetation Management System (IVMS)—using satellite imagery powered by UP42.

UP42 helped AiDash easily access both archive and tasked very high-resolution Airbus Pléiades satellite imagery of utility lines in more than one state in the Southern US. This 50 cm resolution multispectral imagery from the twin satellite constellation provided AiDash with detailed coverage for their customer’s remote asset monitoring needs.

Using these images in combination with a deep neural network model, AiDash’s system was able to learn and then predict the growth rate of the vegetation species in each feeder at a span level — i.e power lines between two consecutive poles.

Knowing these span level predictions then led AiDash to cluster these predictions at section or sub-feeder and feeder level.


More prediction, more reliability, more time, and a reduced budget.

Using UP42, AiDash transformed vegetation management for their customer. Their plug-and-play AI model for vegetation management enabled the utility company to predict the growth rate of different species along power lines—at an individual tree level. They were able to prepare a 3 to 5 year trim plan for the entire network with an accuracy of over 85%

By developing the IVMS solution, AiDash enabled their customer to improve their system reliability by 15% and reduce their annual budget for vegetation management by 20%.

Now, the Fortune 500 utility company can identify risks in real-time and plan vegetation management operations years in advance. They have increased visibility on urgent situations and are better able to save costs and manage contractors through a seamless, app-based approach. Now, post-trim satellite image analysis can be used to audit the compliance of vegetation clearance, without the need for a supervisor on the field.

Working with UP42 helped with the most critical element of AiDash’s AI solution: data. Being able to use archive satellite imagery alongside tasked imagery gave AiDash an edge over other remote sensing companies using airplane or LiDar data to solve similar problems.

AiDash now simplifies the procedure of vegetation management for all stakeholders and continues to use UP42 to deliver tailored solutions.

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