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Improve town, forest and river tags #614

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Intended as a basis for discussion on the further development of the pseudo tags:

  • Increase the size threshold for ponds to 10000
  • Decrease the lower population threshold to 1000
  • Subtract meadow and farmland from the town area
  • Only subtract ways which are truely inside of a green area
  • Limit the estimated_forest_tag to forests and only forests
Before After

Example: https://brouter.de/brouter-web/#map=12/50.1407/8.7074/...profile=fastbike (with consider_town enabled)

- Increase the size threshold for ponds to 10000
- Decrease the lower population threshold to 1000
- Subtract meadow and farmland from the town area
- Only subtract ways which are truely inside of a green area
- Limit the `estimated_forest_tag` to forests and only forests
@quaelnix quaelnix temporarily deployed to BRouter August 16, 2023 16:37 — with GitHub Actions Inactive
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I couldn't test the fine tuning at the moment. May be @EssBee59 could test more.
But I see the st_area is fixed. And it's running error free against the database.

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quaelnix commented Aug 20, 2023

I couldn't test the fine tuning at the moment.

This draft is not about fine-tuning. It is about fixing some of the most frustrating flaws in the current logic, and beyond that, untangling the city, forest, and river tags to give profile creators the freedom to nest them together as needed.


The current situation in three pictures:

Example 1 Example 2 Example 3
estimated_town_class=3 estimated_town_class= estimated_forest_class=2

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quaelnix commented Sep 4, 2023

@EssBee59, this PR fixes the problem shown in Example 1 by subtracting meadow and farmland landuse polygons from the town polygon, the one shown in Example 2 by greatly decreasing the lower population limit (I would prefer 1k as lower limit) and the one shown in Example 3 by only subtracting ways which are inside of green areas (this might need some more fine-tuning).

The performance overhead is definitely manageable and should not be the reason to not fix these problems.

If you have other ideas on how to fix them, please let me know.

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2 participants