Leica Pegasus:Two processing
Turn Pegasus:Two panoramas, point cloud and trajectory into one measurable dataset in GEORIZON automatically, typically ready for viewer, API and download within 24 hours.
A Pegasus:Two mission produces three streams that have to stay tightly linked: the scanner profiles, the camera frames with their capture timestamps, and the raw GNSS, IMU and distance measurement observations. GEORIZON starts with the last of those: we solve the trajectory using base station data or a correction service and assess the result against the estimated accuracy per section, so it is clear where the solution is weak, under viaducts or between tall buildings for instance. Profiles are then converted into a point cloud along that trajectory, thinned on point density, cleared of noise and passing traffic, colourised from the panoramic imagery and structured into tiles. The individual camera frames are stitched into measurable panoramas that remain available as capture stations along the driven line. The whole is placed in the reference frame your organisation works in and tied to surveyed control points.
Many organisations hold years of Pegasus:Two missions on disk that were never fully exploited, simply because processing each project costs time and a specialised workstation. Now that successor platforms are in service, maintaining that processing environment is also harder to justify. GEORIZON processes such archives in bulk and publishes them as a time series: the same route from different years side by side, in the same frame and the same viewer, so change along a road or a railway becomes visible. New missions from a Pegasus:Two, a Pegasus TRK or a system from another manufacturer join them in the same environment, without a separate way of working for each sensor.
Once processing is complete, the Pegasus:Two dataset is waiting in your own GEORIZON tenant. Colleagues and partners open the panoramas and the point cloud in the browser without an installation or a licence per user, measure distances and heights, and share a location through a direct link. To use the data in your own environment, connect to the open API, add a WMTS layer in QGIS or ArcGIS, or download the point cloud in common formats such as LAZ or E57. Faces and number plates are automatically blurred in line with the GDPR, which is almost always required for capture along public roads. Single sign-on and an on-premises deployment are supported, and AI detection and vectorisation can optionally be applied to extract objects from the dataset. Organisations including ProRail (SpoorInBeeld), the municipality of Nijmegen and Kempkes Landmeten work with their geodata this way.
