> For the complete documentation index, see [llms.txt](https://docs.phoenixlidar.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.phoenixlidar.com/lidarmill-cloud/workflow/processing-tools/pointcloud-optimization-pipeline.md).

# Pointcloud Optimization Pipeline

The **Pointcloud Optimization** pipeline is designed for processing LAZ/LAS files. This pipeline takes in an input LAS/LAZ, performs classification routines (noise and ground), and then generates deliverables, such as surfaces and raster products. This pipeline can also calibrate point clouds, using either sensor calibration and/or trajectory optimization ("strip alignment") routines if an input trajectory is provided. 

{% hint style="info" %}
Many of the options for starting a Pointcloud Optimization pipeline are very similar to the SpatialFuser options.
{% endhint %}

## Pointcloud Optimization Pipeline

Navigate to the pipelines tab of LiDARMill and select a **Pointcloud Processing** pipeline:

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2FDLzAkdljnvZumFJHk9ya%2Fimage.png?alt=media&amp;token=b4c5dcf8-3cf0-419b-b760-f2c3570142ac" alt=""><figcaption></figcaption></figure>

First, you will need to specify the **Sensor Model**:

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2Frr7I777JKb982FLj71sX%2Fimage.png?alt=media&amp;token=5c44517e-bed9-4b78-a54f-c4f337979d53" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
Specifying the correct sensor model is necessary if you wish to calibrate the sensor, otherwise you can leave it set to **Generic**.&#x20;
{% endhint %}

You should specify an IMU orientation. If you do not know the IMU orientation, you can leave the values set to 0, as shown below.:

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2Fmda5Uk3f47M25FH8CRMC%2Fimage.png?alt=media&amp;token=ed5eb384-5eff-4d2b-8327-9f2a0e4b96c0" alt=""><figcaption></figcaption></figure>

Flightlines can be defined similarly to the [SpatialFuser workflow](/lidarmill-cloud/workflow/processing-tools/spatial-fuser-pipeline.md#flightlines):

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2FSvlwsWqQTzZX1IpYExXO%2Fimage.png?alt=media&amp;token=4171b30f-d287-42ca-ba92-648d4cbd56c6" alt=""><figcaption></figcaption></figure>

Define what optimization you would like to perform. Refer to the SpatialFuser documentation for a [description of optimization parameters](/lidarmill-cloud/workflow/processing-tools/spatial-fuser-pipeline.md#optimization).

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2F1NtMPoUw1WnThYB7KjLx%2Fimage.png?alt=media&amp;token=64dfb27d-4dd0-4ff8-8edf-e546bdc0df8c" alt=""><figcaption></figcaption></figure>

Specify an output coordinate system:

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2FQclUJjt7BPOZ6OCuoRlQ%2Fimage.png?alt=media&amp;token=41808e24-aa66-4c7e-a136-d7f67a32bf3b" alt=""><figcaption></figcaption></figure>

Lastly, specify the output products to generate:

<figure><img src="https://2222094320-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FdEevfLZRIk38LUPwDa4V%2Fuploads%2FW67Hxoz9tcfwq9rGMoyi%2Fimage.png?alt=media&amp;token=f5d8f378-029d-42f8-8f83-c94e581db518" alt=""><figcaption></figcaption></figure>

Note that LiDARMill will always generate project and processing reports, which contains metrics on accuracy and other processing results.