Orthophoto reconstruction with accurate pose (from INS) and lidar point cloud but limited side lap

Does anyone know a workflow using ContextCapture to generate an orthophoto reconstruction by skipping the AT, using accurate pose from an INS and a lidar derived mesh/DSM rather than an internally generated DSM from matched points? 

Basically, I have a lidar/imagery dataset in which the side lap of the images is pretty low (25%) but where the images have accurate position and rotation from an AP50 INS, and a dense lidar point cloud from which I can derived a quality DSM for the final rectification.  The standard workflow requires me to solve the AT, which results in a substandard set of tie points, and a poor DSM the reconstruction.  It would be great if you could skip the AT, and proceed directly to the reconstruction, loading an indepent mesh from my lidar survey.  

Any thoughts gratefully received!

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  • You can generate 3SM terrain directly from LIDAR by using Descartes/CC Editor. Also it allows to generate orthophotos by using Merge raster tool but rasters need to be georeferenced first. Not possible to skip AT in Contextcapture so best option would be to generate orthophoto in some 3rd party software and then overlay it on DSM.

    I have also noticed that combining LIDAR with AT results in more artifacts as if LIDAR is not dense enough then in some parts AT points are still used and deep pits appear. Have not tried but it is now possible to delete tie points after aerotriangulation maybe that would allow to use only lidar points.

  • Many thanks for the quick and helpful feedback Oto.  I had guessed as much and I'll revert to my old workflows using PCI or ERDAS.  

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