Airborne Lidar Processing
Last updated
Last updated
This workflow is for customers who intend on processing raw, airborne lidar data from a native-Phoenix system to produce a calibrated, colorized point cloud, as well as other deliverables.
If using a RECON system, open one of the DATA files. SpatialExplorer will detect the other associated DATA files, and then will proceed to extract lidar, imagery, and navigation data. Once decoding is complete, a PLP (project) file will be created.
Open PLP file (s). If imagery was acquired, ensure images are present in the Cam0 folders. After opening the PLP file, for the project. If multiple PLP files were opened, File->Save As the collective project (e.g. "Combined_Project.plp"), so that the multi-flight project can easily be re-opened.
If working with data from a Riegl lidar scanner, .
Import or create a processed trajectory (CTS, CLS, SBET, POF). users can load in a CTS, CLS, or SBET file. Trajectories can also be processed using and .
When processing data acquired via an aerial platform (helicopter, UAV, fixed-wing aircraft), it is recommended to use the Airborne or UAV dynamics profiles in NavLab or InertialExplorer.
Configure for the lidar. Consider a 90 degree field of view, and a minimum range of 5 meters.
(these intervals will also apply to imagery).
.
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. Typically up and yaw are the only parameters that need to be optimized in an aerial data set.
Run and optimize for necessary parameters. Typically the LiDARSnap Aerial Trajectory Optimization preset works well.
Classify and . It's usually recommended to have an accurate ground classification prior to adjusting to control (step 12). Noise should always be classified BEFORE ground.
(if available).
If ground control points are available, from point cloud to control points to determine what rigid adjustment, if any, is needed to match lidar elevations to ground control elevations.
along processing intervals.
Calibrate the camera using . If necessary, enable per-pose orientation corrections to compute attitude corrections specific to each image.
Colorize the point cloud using.
Perform any additional classification necessary. Users can make use of the window, as well as some routines.
Generate .
Generate deliverables such as (RGB raster, DTM, DEM) and (contours and meshes).