> For the complete documentation index, see [llms.txt](https://knowledge.flyability.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://knowledge.flyability.com/third-party-software/faro-connect/how-to..-step-by-step-guides/how-to-use-the-reflective-target-georeferencing-workflow.md).
# How to use the Reflective Target Georeferencing workflow
With the appropriate reflective targets, and their X, Y, Z coordinate measurements, it is possible to georeference (Rigid transformation) a point cloud using FARO connect.
The *rigid transformation* applies a single transform to every point in the point cloud, so that the XYZ position of every point is altered. However, the relative position to other points in the point cloud will remain the same. Comparing the shape of the point cloud before and after the rigid transformation should show identical results.
### Data capture:
The following is required for this process:
* A minimum of 4 retroreflective targets, of the following specs:
* **Material:** Survey grade or 3M Diamond grade retroreflective targets.
* **Size:** 300mm x 300mm (recommended), 200x200mm (minimum)
* **Shape:** Circular or square.
* **Crosshairs:** Required for surveying the target
* **Number of targets:** Six targets recommended, minimum four targets required. Using more targets provides a higher level of redundancy if/when control point/s cannot be matched to the target/s.
* A properly formatted, tab delimited coordinate file.
* Measurements should be X, Y, Z, and in Meters. Follow example:
When capturing data, standard mapping best practices should be employed. Start and finish the scan in the same location/orientation, thus ‘Closing the Loop’ to achieve the best results. When scanning reflective targets, keep the sensor 1 to 3 meters from the target/s and ensure that the LiDAR is facing the target and capturing the target for at least 3 seconds. Add a little more time when using the REV 6 LiDAR scanner. For more information: [GeoSLAM for Elios 3 Online Training (light version)](https://docs.google.com/presentation/d/1HmrH64uUpKfAcbXEHASSGJtkCaiPnqIBg7Q0tyvgk5s/edit?usp=sharing)
### Processing data:
With the data exported, and coordinate file formatted, there are two ways to georeference the project.
One way is to process using the *Flyability Reflective Target Georeferencing* workflow. A problem with this workflow is if any aspect of the data (targets, measurements, scanned environment, etc) fails, the entire process fails with no results regardless where failure occurs.
An alternative approach is to process the project using the *Flyability SLAM Processing* workflow ([How to process a point cloud](/third-party-software/faro-connect/how-to..-step-by-step-guides/how-to-process-a-point-cloud.md)) and then follow up with the georeferencing. In this way, there is the ability to view the point cloud, targets, and employ any filtration as needed before georeferencing, and/or if georeferencing fails. Setting the Color Mode to Intensity will provide the best vision for viewing the targets.
{% hint style="info" %}
This is the better workflow when georeferencing data collected with a standard REV 6 LiDAR scanner.
{% endhint %}
### How to georeference the processed project:
Once the project has finished processing you can georeference it using the Registration tab:
1. Click the *Registration* tab.
2. Select the *Reflective Target Georeferencing (Cloud)* workflow.
3. Click *Pick from Project* and select the processed .laz. If the point cloud was filtered before, ensure to select the filtered point cloud.
4. Click the dropdown arrow and select *Browse System*. Navigate to, and select the coordinate .txt file. After this selection, subsequent processes can use Pick from Project for selection.
5. Click the dropdown arrow and select *Elios 3*.
6. Click *Pick from Project* and select the trajectory.
7. Click *Run*.
On completion of processing the selected point cloud will be georeferenced with the following files:
* \\_registered.laz: Registered output point cloud file.
* \\_registered.gs-traj: Registered output trajectory file.
* alignment\_dashboard.gs-chart: Alignment dashboard displaying the accuracy of the registration.
* Survey\_error.gs-accuracy: Accuracy table of each control point and overall RMSE.
* .gs-control: Name of the imported surveyed control point file.
For more information: [GeoSLAM for Elios 3 Online Training (light version)](https://docs.google.com/presentation/d/1HmrH64uUpKfAcbXEHASSGJtkCaiPnqIBg7Q0tyvgk5s/edit?usp=sharing)
If aspects are failing please see our [FARO / FAQ Troubleshooting](/third-party-software/faro-connect/faro-faq-troubleshooting.md) article for more information.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://knowledge.flyability.com/third-party-software/faro-connect/how-to..-step-by-step-guides/how-to-use-the-reflective-target-georeferencing-workflow.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.