2.5D Tool for Lidar data integration


The aim of this tutorial is to show how to integrate your LiDAR point clouds with Dense Image Matching (DIM) point clouds produced with SURE. Please visit 2.5D Tool for a detailed description on how to use the 2.5D tool.

Fusing both data sources can be advantageous for the following reasons:

  • DIM limitations:
    • Occluded areas, such as narrow alleys, are often not visible in at least two images, therefore object points cannot be triangulated here. As a consequence, large holes appear in products such as DSM, True Ortho or Meshes.
    • Regions in the images with bad radiometry (i.e. too dark, too bright) can lead to these pixels not being matched, or being matched erroneously - hence producing noisy results.
  • LiDAR limitations:
    • larger GSD - lower resolution
    • surface details not captured

Using the 2.5 Tool can be an optimal solution to complement the two data sources with each other.

  • Step. 1:

Edit your cloudlist.txt located in the root folder of your project and add the Lidar Point Cloud

  • Step 2:

On the 2.5D Tool, open this cloudlist.txt as the Input Cloud file

  • Step3:

Start Processing by choosing the photogrammetric products you wish to produce.



To obtain the best results, disable the spleckle filter in the advanced configurations by turning Speckle filter size (pix) to 0

With speckle filterWithout speckle filter


Results comparison


Without Lidar point CloudWith Lidar Point Cloud