This project is supported by Norwegian Public Roads Administration (NPRA).

Aiming to address the issue of varying positioning errors in produced point clouds, this project put forward two potential solutions that integrate the techniques and knowledges from the fields of geographic information science and computer science, namely, (1) feature level and (2) point level.
The former suggests improving the positioning accuracy of extracted features rather than all points, while the latter focuses on improving that accuracy for the produced point cloud data.

These potential solutions are expected to effectively and efficiently improve the accuracy of registered LiDAR point clouds, and are applicable to various scenarios involving point cloud data. 

FKB data
Within the test area, the most recently updated FKB data sets + the nearest data sets 10-12 years back in time are desired, possibly only every two years. Aerotriangulation reports or other reports that describe the accuracy of the data are also relevant.

Data from a complete remapping (not just maintenance) would be most interesting.
Delivery is desired in a format that can easily be converted to NTM10, e.g. SOSI format.

Laser data
If laser data with a density of 25 or more points per square meter is available in this area, these are desirable.

Orthophoto
Orthophoto will be downloaded from www.norgeibilder.no. Orthophotos with GSD (Ground Sampling Distance) 10 cm or lower that are not on www.norgeibilder.no are wanted.

Oblique images
According to Gudmund.Melland@Trondheim.kommune.no, there are also oblique images, among other things. from 2021 and 2022.

Control points
In the spring/summer of 2024, the Norwegian Road Administration (NPRA) consider to establish and measure an accurate network of permanent control points for the area.

Passage points
NPRA also considered to signal checkpoints before flights in spring 2024.