Cloud to cloud matching
Search cloud-to-cloud command is designed for straightforward tie line search finding observations suitable to correct XY(Z) shift. It can find observations comparing the active point cloud to a reference point cloud, or internal observations comparing the active data to other passes in the active data. The observations against the reference help improving the positioning towards the more accurate reference point cloud, while the internal observations help improving the relative positioning in the active data. These observations are good for solving corrections for data suffering from dominating XY(Z) drift, that could be caused by poor positioning satellite visibility in MLS data, or positioning satellite jamming, for example.
Search cloud-to-cloud extracts a time slice of the active data, and compares the slice to comparison data. The comparison data may be a reference point cloud, or another moment in time in the active data. Using reference point cloud the cloud-to-cloud observations become useful for improving the absolute accuracy of the data. Searching for internal observations within the active data, the tie lines are useful from mitigating mismatches that originate from system positioning drift.
This approach has three different methods for finding the optimal shift minimizing the mismatches in the data. The tool can search for shift minimizing the average point mismatch in the data, compare the intensity footprint of the datasets, or compare the height footprint of the datasets. The different methods enable matching in all axis directions (xyz), or only horizontally (xy) depending on the method capabilities. The different methods suit for different data densities, and surrounding environments.
1. (Optional, if searching internal observations) Set the TerraScan project for the ALS point cloud as the reference project for the MLS project. See Reference project exists option in the Project information dialog of TerraScan. If loaded points are used, the reference points can be loaded into TerraScan with the Read reference points command. If a project block is loaded, the Load reference points option must be switched on.
2. Compute normal vector and dimension attributes for the MLS data set by using either the macro step or the menu command for loaded points in TerraScan.
3. Start Define tie lines. In the Tie line settings dialog, set the class numbers of matching point classes as Cloud classes.
4. Start the cloud-to-cloud tie line search in TerraMatch.
5. Validate the tie lines. Validate the pull vectors visually. Delete low reliability observations by criteria. Check worst tie point positions and delete, if bad. Filter bad tie lines, if necessary.
6. Solve fluctuating corrections using a smooth curve.
7. Apply correction to point cloud data.
You may write a new copy of the data set.
This matching method can be extended by introducing Known Xy tie points for a better horizontal match, especially if there are not enough building walls that can be used. The additional tie points for horizontal matching may be produced as described in the Using orthophotos and ground points section.
