LiDAR integration in SURE


Since version 3.0, SURE offers the possibility to use LiDAR data to improve the results both in the 2.5D workflow (DSM, True Ortho, DSM Mesh), as well as in the 3D workflow (3D Mesh). The use of LiDAR data is optional and the Dense Image Matching is completely independent from their provision. The LiDAR point clouds are meant as a complement to the Image data and prove to be particularly useful in situations where the geometry of the surface is difficult to reconstruct from images only, due to photogrammetric constraints (i.e. a Photogrammetry 3D point requires at least 2 lines of sight with no redundancy, while a LiDAR 3D point only requires 1 line of sight).

SURE remains a Surface Reconstruction software based on Dense Image Matching (DIM), making use of the advantages of this data source. Furthermore, there is the possibility of improving the results by adding LiDAR data.


From a workflow perspective, LiDAR data can be introduced during the DSM and the 3D Mesh processing steps. The table below describes the integration of LiDAR into the SURE workflow (only applicable if LiDAR data is provided and its usage is enabled). 

Processing stepNecessary LiDAR dataAffected results
  • LiDAR point clouds
  • DSM
  • True Ortho
  • DSM Mesh
3D Mesh
  • LiDAR point clouds
  • LiDAR trajectory file

  • 3D Mesh

LiDAR data preparation

In a scenario where input LiDAR data have been specified, SURE will proof test the LiDAR data, whether they are valid for later use in the workflow. This step will happen at the beginning of the processing. In case the tests are not passed, the user will be notified about the inconsistencies.

Input / Formats / Requirements

Currently supported formats:

DataSupported FormatsIf LiDAR enabled, data is required in the processing steps
LiDAR point cloud filesup to LAS version 1.3 (LAZ supported as well)

DSM and 3D Mesh

LiDAR trajectory file
  • SBET (.out)
  • SOL (.sol)
3D Mesh

LiDAR point clouds

SURE will use the first return points (first echo) of the LiDAR point clouds, in the idea that it stays consistent with an Image-based Surface Reconstruction product.

If the LiDAR point clouds have the noise points classified as such, then SURE will ignore those points. Otherwise, it is not necessary that the LiDAR input clouds are classified into other classes such as Ground, Vegetation, etc.

LiDAR Trajectory Files

The SBET (Smoothed Best Estimation of Trajectory, from Applanix ) and SOL (Solution, from HxMap) are binary formats storing information about the trajectory of the LiDAR data acquisition platforms. Relevant for the SURE workflow are the positional information in the form Latitude, Longitude, Altitude (typically in the WGS84 reference frame) and the Time information (week seconds).


RequirementExplanation / Additional remarksRequired for the processing steps
The same coordinate system for LiDAR point clouds and DIM data
  • No adjustment or transformation operation is performed on the two data sources
  • Surface described by the LiDAR point clouds should "fit" well with the surface reconstructed from DIM
  • Inconsistencies of the surface features between LiDAR and DIM (e.g. like a building being represented only in one of the two sources) could lead to unwanted effects in those areas in the results.
  • DSM
  • 3D Mesh
Time information and Meta Time information contained in the LiDAR point clouds
  • Time Information: when the observation was taken for each of the points
  • Meta Time Information: bit field for GPS time set correctly according to the LAS format specification:
    • 0 for GPS Week Seconds
    • 1 for Adjusted Standard GPS Time
  • 3D Mesh
Specification of the correct Coordinate System of the DIM data
  • Necessary to bring the data from the LiDAR trajectory file into the same reference frame as the LiDAR point clouds
  • Can be provided indirectly through the orientation file (*.prj / *.gori), or directly by supplying the coordinate system *.wkt file during project setup
  • More info at Coordinate System article
  • 3D Mesh

Influence of LiDAR data

Data based only on DIMData based on DIM and LiDAR

Source: Leica - Bordeaux Oblique dataset (DSM)

Source: IGI - Betzdorf Nadir dataset (3D Mesh)

Source: Melk Nadir dataset (3D Mesh)