Vegetation Management · Right-of-Way

The Evidence Standard for Vegetation Management

Drones collect the imagery. POLLi turns it into governed, image-linked vegetation evidence, traceable to the source, reviewable by your team, and ready for reporting.

Traceable

Every finding links back to its source imagery and project context.

Verifiable

Outputs are reviewable and validatable by your subject matter experts.

Complete

The record contains imagery, findings, location, and review history.

The Evidence Gap

Most ROW imagery never becomes evidence.

01

Imagery is collected. Evidence is not.

Flights happen. Images land on a hard drive. Without a structured workflow, those images stay disconnected from decisions and from the reviewable record your program depends on.

02

Findings are documented, but not traceable.

Reports exist. But when questions come up, no one can trace a finding back to the source image that supports it. The documentation exists. The evidence does not.

03

Programs change. The work does not travel.

People retire. Contractors change. Analytical methods improve. Each transition is a risk to the institutional knowledge that makes a monitoring program useful over time.

POLLi turns collected imagery into governed, reviewable vegetation evidence: organized, traceable, and built to outlast the people and tools that created it.

The POLLi Workflow

From collected imagery to governed evidence.

  1. 01

    Fly

    Collect imagery at the required resolution using the POLLi® Flight application, which standardizes key mission parameters across crews and monitoring cycles.

  2. 02

    Upload

    Import source imagery directly into the POLLi® platform, where it is organized, preserved, and linked to the project record from the start.

  3. 03

    Standardize

    Apply defined processing and analysis workflows so findings are produced consistently, regardless of which crew, contractor, or monitoring cycle generated them.

  4. 04

    Review

    Review findings while maintaining their direct connection to the source imagery. Subject matter experts stay in control; model-assisted analysis expands review capacity without replacing judgment.

  5. 05

    Report

    Share results or export GIS-ready outputs for operational use. Every deliverable stays connected to the imagery and review history that produced it.

POLLi in action. Vegetation evidence collection and review across real ROW conditions.

The Governed Evidence Standard

Every POLLi finding meets the same quality mark.

T

Traceable

Every finding links back to its source imagery and project context. Nothing disappears into a report or a contractor deliverable. The connection between what was captured and what was concluded is preserved.

V

Verifiable

Outputs can be reviewed and validated by your team or subject matter experts. Model-assisted analysis supports review capacity; expert judgment remains the authority on what findings mean.

C

Complete

The record contains the imagery, findings, location, review history, and outputs needed for review or reuse. A complete record is one that can be understood and acted on without the original team.

Model-Supported Review

The model identifies. The SME decides. The Evidence Pack records both.

Machine learning and computer vision assist analysts in working through large image sets, flagging candidates and supporting consistent classification across a corridor. Expert review remains the authority. Every model-assisted finding is reviewed and validated by a subject matter expert before it enters the evidence record. The model expands review capacity; the SME determines what enters the record.

The Deliverable

The Evidence Pack™

The Evidence Pack is the standardized output of every POLLi workflow: image-linked findings, GIS-ready data, and a reviewable record organized by corridor, site, and monitoring cycle.

Because each Evidence Pack preserves the connection between imagery, analysis, review, and findings, your program does not have to start over when people, contractors, or analytical methods change. Each monitoring cycle adds to what came before.

Who POLLi Serves

Built for right-of-way and land stewardship operations.

Any organization responsible for vegetation along a corridor, around an asset, or across a habitat area faces the same underlying challenge: how to build a consistent, reviewable evidence record over time. POLLi is built around that challenge.

Transportation

Roadside Managers and DOTs

Standardized vegetation evidence for highway ROW management, maintenance documentation, and state or federal reporting requirements.

Electric Utility

Distribution and Transmission

Image-linked evidence for vegetation clearance, cycle-to-cycle comparability, and NERC compliance documentation along distribution and transmission corridors.

Oil and Gas

Midstream Pipeline Operators

Traceable vegetation monitoring records for PHMSA compliance and pipeline corridor management, with consistent evidence across seasons and contractor changes.

Renewable Energy

Solar Operations

Vegetation evidence for panel clearance management, site comparability across installations, and ongoing stewardship documentation.

Conservation

Habitat and Stewardship Programs

Structured monitoring records for pollinator habitat, biodiversity documentation, and programs that require consistent, reviewable evidence over multiple years.

Rail

Railroad Corridor Management

Consistent vegetation evidence for safety clearances and corridor stewardship along rail ROW, with image-linked records across inspection cycles.

CCAA POLLi can support CCAA-aligned monitoring and reporting by providing stronger, image-linked vegetation evidence. The CCAA began accepting remote sensing data in 2025, making structured aerial evidence directly relevant to ROW operators participating in or considering that program.

Innovation Partners

At Davey, we appreciate POLLi®'s focus on conservation and commitment to providing cost-effective solutions. We are excited to become an Innovation Partner to help raise the bar for the management and assessment of ROW habitats.

Adam M. Baker, PhD Research Entomologist, Davey Resource Group
Meet our Innovation Partners →

Peer-Reviewed Research

Comparing Machine Learning Using UAVs to Ground Survey Methods to Quantify Milkweed Stem Density and Habitat Characteristics in ROWs

Baker, A.M., Emerick, G., Bahlai, C., and Eikenbary, S. (2026) Insects, 17(4), 359. MDPI. Impact Factor 2.9  |  Indexed in PubMed
Read the published study →

Get Started

Tell us about your monitoring program.

Whether you manage a highway corridor, a utility ROW, or a habitat program, we start with your evidence workflow. No demo before diagnosis.