2.5D Tool for LiDAR data integration

The aim of this tutorial is to show how to integrate the 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:

Create a list lidar_cloud_list.txt with the Lidar Point Clouds

  • Step 2:

In the 2.5D Tool, open this lidar_cloud_list.txt as the Input LiDAR Cloud file. Or just point to the location of the LiDAR point clouds.

The user can give as input the path of the LiDAR clouds too and SURE will create the lidar_list.txt file.

In case that the Input cloud is the DSM_Raw cloud, then the Required points per cell should be set to 1.

  • Step3:

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

Results comparison

Without Lidar point CloudWith Lidar Point Cloud