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title: "V3.0 Vegetation Connect - Overview"
canonical: "https://support.cordel.ai/space/CSD/2840758648/V3.0%20Vegetation%20Connect%20-%20Overview"
format: markdown
---
Cordel Connect's Vegetation Management module offers a comprehensive solution for monitoring and managing vegetation along the railway corridor. This solution provides precise, up-to-date insights into vegetation encroachment and growth patterns - with regard to both overhead line equipment and the [kinematic envelop](https://corridor1.atlassian.net/wiki/spaces/CSD/pages/2840758648/V3.0+Vegetation+Connect+-+Overview#The-Corridor-Vegetation-Report)e. Users benefit from customisable profiles and risk thresholds, allowing them to tailor analysis to their requirements and standards.

Cordel’s unattended capture systems enable frequent analysis of vegetation - detecting changes in vegetation proactively. Combined with powerful visual tools, rail networks can conduct detailed assessments before prioritising and scheduling maintenance.

### Corridor Vegetation Management (Kinematic envelope)

This solution affixes a digital version of the client defined vehicle profile to the rail heads detected in the LiDAR point cloud. The profile is aligned to the plane of rail and the point cloud is then segmented into 1 metre cross-sections. Each cross-section is analysed using Cordel’s sophisticated machine learning algorithms, which detects the volume of vegetation found within the profile (K), as well as within other configurable encroachment zones - which by default are set to K +1500 mm and K +3000 mm of the profile. 

Where vegetation is detected within these zones, the volume is measured and this data is provided as a .CSV, as well as being available for review using Cordel Connects suite of visual and analytic tools. 

![image-20250728-054808.png](media://e6a90521-5472-4f60-8ea1-b1a644421098)


### OLE Vegetation Management

This is a vegetation-specific solution, utilising AI algorithms to solve complex vegetation management challenges. Using the overhead wire as the datum point, a digital profile is applied to the detected overhead line equipment; Cordel’s machine learning algorithms then measure the volume of vegetation found within and around the profile (typically K, K +1500+, K +3000).

![ole veg man.png](media://2146b4f5-ff9e-476d-b532-232b235a2163)