# Jupyter Notebook intersecting OSM Graph and LBSM points (user frequentation)

## Intersecting OSM Graph with LBSM user-post locations

for measuring user frequentation (routing, meingruen)

- Final Map (Heidelberg)
- Final Map (Dresden)
- Jupyter HTML
- Jupyter Notebook (Download)

Weighted OSM Graph for Heidelberg:

For Dresden:

A post is counted for lines based on proximity, e.g. in the example below, the shown use-post-location is counted for both line segments:

Default distance is 25m:

With smaller distances, more accurate assignment is possible:

However, many other points will also fail to be assigned to a line segment. A possible solution could be to use IDW-Measure based on distance: the line nearest to the post will be updated most significantly, others will be updated less.

Theres are two other examples where it is obvious that accurate assignment to a single line-segment is not always possible:

Also, to reduce the impact of small line-segments on average user/ segment-length calculation, a minimum length can be specified.

Minimum length 50m (default):

Minimum length 25m: