Hello,

I have to calculate the height differences outside jag3d, then consider them as leveling observations and solve the network as 1D. In a analogous manner, solve the network as 2D, using calculated horizontal distances and directions.

That is the usual procedure, yes.

So, the network cannot be solved in one step as 3D.

It is also possible to process the network in 3D with additional pseudo-observations. In this case, you don't have to divide the spatial observations into corresponding planar and height components. To perform such a network adjustment, import all points as unknown 3D points - including your reference points. Import the height reference as 1D reference point and the 2D reference points point BUT with different names (e.g. add a suffix or prefix). Define GNSS baselines between the 3D "reference" points and the true reference points to constrain the adjustment.

Example: Let H be the reference height. Import the point H as 3D point. Thus, spatial observations from and to H are defined. Define a 1D reference point say H_REF having the known height. Import this reference point. Moreover, define a 1D-GNSS baseline. To constrain the height component, the height difference must be zero having a small uncertainty (last column 1 µm), i.e.

H  H_REF   0.000     0.000001

In almost the same manner, the XY components of the planar reference points can be fixed using 2D baselines.

/Micha