I was reading through the SQL used to generalise the landcover layer ([`layers/landcover/generalized.sql`](596f44aa26/layers/landcover/generalized.sql)) and I noticed that when creating the generalised landcover tables for zooms 9-13, the SQL was doing something like this:
```sql
SELECT * FROM simplify_vw_z13 WHERE ST_NPoints(geometry) < 50
UNION ALL
SELECT * FROM simplify_vw_z13 WHERE ST_NPoints(geometry) >= 50 AND ST_NPoints(geometry) < 300
```
As in, the simplification/clustering of landcover generalisations was being done in two steps: once for polygons with fewer than fifty points, and once for polygons with 50+ points.
As far as I can see, there's no benefit to doing this — it's probably just an artefact of the dev work done for the [original pull request](https://github.com/openmaptiles/openmaptiles/pull/1035). Of course, I might be completely missing the reason for clustering polygons into two groups (<50 points and 50+ points). But assuming I haven't, I've created this pull request to simplify the SQL used in the generalisation, merging the two steps into something like this:
```sql
SELECT * FROM simplify_vw_z13 WHERE ST_NPoints(geometry) < 300
```
The effect is to slightly reduce the number of landcover features (polygons with <50 points can now be clustered/unioned with those 50+), and to reduce the time taken to generalise the landcover tables (in a small test using OSM's Iceland data I saw a 7% reduction in the time spent). It doesn't alter the features that are shown on the map.
Builds upon work from commits 4a1b0afa26 and da689f9e42.
While reviewing #1255, it became apparent that the ETL documentation for the landcover layer was incomplete. This PR updates the ETL documentation in `generalized.sql` so that each table has a node in the ETL diagram.
Add missing `NOT` in WHERE condition.
It causes there are duplicated features of subclass `wood` and `forest` and features of other subclasses are missing.
This PR brings few modification which make it possible to generalize landcover on larger areas. Tested on Europe.
- Use ST_SnapToGrid to avoid ERROR: GEOSUnaryUnion: TopologyException: found non-noded intersection between LINESTRING.
- Cluster only landcover subclasses: wood and forest.
- Use less generalized tables as a starting point for next step generalization.
Instead of using [Douglas-Peucker algorithm](https://postgis.net/docs/ST_SimplifyPreserveTopology.html) which is using for generalized tables [imposm](https://imposm.org/docs/imposm3/latest/mapping.html#generalized-tables) it is used [Visvalingam-Whyatt algorithm](https://postgis.net/docs/ST_SimplifyVW.html).
Solution:
remove imposm generalized tables (during `import-osm`) and create generalization in `import-sql` step for zooms 7-14. Zooms 0-6 are from Natural Earth data.
Upper zoom levels (7 and 8) are ok to merge with no big impact on creation speed. In Canada from z9 it took too long. Between zoom levels 10 - 13 there can be union polygons with less than 300 edge points (empirical number based on a test on Canada forest, can be discussed). Polygons with more than 300 edge points are just simplified. Zoom 14 is from the original dataset `osm_landcover_polygon`.
There is also removed `osm_id` which is never used and not passed into vector tiles.
Tomas Pohanka