> 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/post-processing/mobile-lidar-workflow.md).

# Mobile Lidar Workflow

1. If using a RECON system, [decode the DATA files](/lidarmill-desktop/workflow-kk/uploading-files/decoding-recon-data.md). 
2. Open the PLP file. After opening the PLP file, [select a CRS](/lidarmill-desktop/workflow-kk/project-setup.md) for the project. 
3. If using a Ladybug camera,[ import the Ladybug PGR streams](/lidarmill-desktop/workflow-kk/uploading-files/imagery/importing-ladybug5+-data.md). 
   1. [Create receptor masks](/lidarmill-desktop/workflow-kk/colorization-of-point-clouds/mobile-colorization-using-ladybug-imagery.md) for each of the 6 Ladybug receptors.
4. [Import a processed trajectory](/lidarmill-desktop/workflow-kk/uploading-files/trajectory.md) (CTS, CLS, SBET, POF). If you do not yet have a processed trajectory, produce one using either InertialExplorer, [NavLab embedded](/lidarmill-desktop/workflow-kk/trajectory-processing/inertial-explorer-trajectory-upload.md), or [NavLab via LiDARMill](/lidarmill-cloud/workflow/processing-tools/navlab-pipeline.md). 
5. [Import ground control points ](/lidarmill-desktop/workflow-kk/ground-control/ground-control-points-gcps.md)(if available).
6. Configure [processing settings](/lidarmill-desktop/workflow-kk/create-a-cloud/configure-lidar-processing-parameters.md) for the lidar.
7. [Create processing intervals](/lidarmill-desktop/workflow-kk/create-a-cloud/manually-split-intervals.md) for point cloud creation - typically for mobile data sets a single large interval covering the entire data set is used for point cloud creation.  
8. [Create a point cloud](/lidarmill-desktop/workflow-kk/create-a-cloud/create-cloud.md).
9. Visually check lidar relative accuracy and determine what degree and type of optimization needs to be performed. Consider reviewing trajectory accuracy reports to determine what trajectory parameters (X,Y,Z,yaw, pitch, roll) require optimization. 
10. Run [LiDARSnap](/lidarmill-desktop/workflow-kk/lidarsnap-v4.md) and optimize for necessary parameters. Typically the LiDARSnap Mobile Trajectory Optimization preset works well. 
11. If ground control is available, [compute residuals](/lidarmill-desktop/workflow-kk/ground-control/adjusting-automatically-to-gcps-vertical-only.md) from point cloud to control points to determine what adjustment, if any, is needed to match lidar elevations to ground control elevations.
12. If using a Ladybug, calibrate the camera and colorize the point cloud:
    1. [Create processing intervals](/lidarmill-desktop/workflow-kk/camera-snap/camera-calibration-with-mobile-data-sets.md) specifically for camera calibration.
    2. [Activate images](/lidarmill-desktop/workflow-kk/colorization-of-point-clouds/enabling-and-disabling-images.md) along processing the intervals made in step 12.1.
    3. Calibrate the camera using [CameraSnap](/lidarmill-desktop/workflow-kk/camera-snap/camera-calibration-with-mobile-data-sets.md). Because the Ladybug is not permanently coupled to the lidar system's IMU, it's always necessary to calibrate the ladybug. 
    4. Colorize the point cloud using [CloudColorizer](/lidarmill-desktop/workflow-kk/colorization-of-point-clouds/mobile-colorization-using-ladybug-imagery.md).
13. Generate accuracy [reports](/lidarmill-desktop/workflow-kk/export-cloud/reports.md).
14. Generate deliverables such as [rasters](/lidarmill-desktop/workflow-kk/data-products/create-maps.md) (RGB raster, DTM, DEM) and [vector deliverables](/lidarmill-desktop/workflow-kk/data-products/create-contours.md) (contours and meshes).