> For the complete documentation index, see [llms.txt](https://docs-7.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-7.phoenixlidar.com/lidarmill-desktop/workflow-kk/lidarsnap-v4/optimizing-data-from-multiple-scans.md).

# Optimizing Data from Multiple Scans

LiDARSnap trajectory optimization can be used to merge multiple scans, from multiple trajectories, into one CLOUD file. A single CLOUD file can be built from multiple sets of raw data (multiple PLP files, each with associated lidar and trajectory data), however relative accuracy between the individual scans may be poor, due to vertical drift or other trajectory errors, so running LiDARSnap trajectory optimization is recommended. An example below illustrates this process with two aerial data sets:

With the first mission open, open the second mission's PLP file:

![](/files/zFYbfuD9Yvo0wIsHCuVa)

Create[ Intervals](/lidarmill-desktop/workflow-kk/create-a-cloud/automatic-intervals.md). Intervals will be created from both mission's trajectories:

![](/files/OAe9m7DTqu1CVimNekQ9)

Create a point cloud using the flightline intervals from both missions:

![](/files/Opo4xfNYgArdWWMNVx0I)

![](/files/5CnXbgsuqjJcK3DzU2gK)

Then, run LiDARSnap using the intervals for both missions. In this example, we will use the Aerial Trajectory Optimization preset:

<figure><img src="/files/G56PaK6OBNa6JHAGQtg0" alt=""><figcaption></figcaption></figure>

&#x20;Upon completion of LiDARSnap, a new optimized trajectory for each mission is created and loaded into the project window under **Trajectories**:

![](/files/mdaVibnVBcPsRAxkbXIT)

The point cloud will be automatically recomputed in respect to these new, optimized trajectories, however it is advised to save the point cloud before continuing with further processing.&#x20;