Field Data Check

This workflow should be used by sensor operators in the field to ensure that all necessary data has been acquired. Some steps do not apply to all systems.

  1. Download data from the lidar system. Then, run SpatialExplorer and File->Open the PLP file.

  2. Navigation system data check:

    1. Pay close attention to the messages window. Look for warnings in yellow regarding missing IMU samples and/or missing GNSS data.

    2. If you have NavLab Embedded/InertialExplorer and a standalone reference station (as opposed to a public or virtual reference station), quickly process the trajectory via NavLab Embedded to ensure the trajectory quality meets your expected standards.

  3. Lidar data check:

    1. Build a pointcloud using the real-time trajectory.

      1. For RIEGL users: Fuse a down-sampled pointcloud. MTA ambiguities can create an excessive amount of noise. Depending on the number of MTA zones you encountered, it may be necessary to run MTA disambiguation prior to fusing a field check cloud.

      2. For RECON or Multi-laser users: Use the auto-downsampling slider, located in the lidar processing settings tab, to lower the density significantly (place the slider to fuse only 1/2 of the data).

    2. Check that the cloud fully covers your AOI. You can import a KML geometry of your AOI using File->Open.

    3. Visualize the cloud by interval index to ensure you achieved sufficient flightline overlap. Typically, all parts of the AOI should have at least two intervals present.

  4. Imagery QA/QC (if imagery was co-acquired).

    1. For cameras with internal storage (A7R4, A7R4-lite, A7R2, IXM-50, IXM-100), check that the number of camera trigger events in the camera session(s), visible under Camera->Acquisition, matches the number of images recorded on the storage medium (SD or XQD memory card) .

    2. Check that the imagery is suitable for processing.

      1. Imagery generally matches the expected content.

      2. Imagery is not over-exposed, under-exposed, blurry, or particularly grainy.

Some issues are not identifiable via a cursory field check. This workflow should be used just to identify the most common and obvious issues with acquired data.

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