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Hello

Here’s my challenge:
I have two datasets that I need to compare after several transformations.

- Dataset 1: This contains georeferenced points with distances associated with a linear reference system (LRS).
- Dataset 2: This has no geometry, but contains distances from the same LRS.

My aim is to associate each value km_start in dataset 2 with the closest value _measures in dataset 1, even if they don't match exactly (I’d like to be able to assigne a tolerance, for ex. max difference of 0.01m). Thanks to this matching, I will be able to assign a geometry to the data in the second set.

 

Below are a few screenshots to illustrate my question:

 

Dataset1 with georeferenced points, _measures are distances in the LRS
Dataset2 with non geometry features I want to get the closest match from Dataset1

 

We're talking about fairly important datasets but it shouldn't be too much of a problem if the process takes time.

Thank you in advance for your help and ideas.

Hello 

 

I found a much simpler and more direct way of achieving the desired result thanks to a video by Dave Campanas. For those interested, here's the link: 

 

Have a great day

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