Macro tiles

  • Use existing infrastructure (both hardware and software) in our lab. Our stack runs on Postgres and Node.js on consumer grade Mac Pros. This rules out using subscription services.
  • Allow access to zoom levels 0 to 12. Any larger and we’d be misrepresenting the data.
  • Fast access on any device.
  • Fast, scriptable tile generation. As datasets are added, it is essential to be be able to quickly update the map.
  • Keep dynamic tile generation to a minimum. Because of how detailed geologic maps can be, a prototype showed that generating a tile for the medium scale at zoom level 5 could take anywhere from 10–50 seconds.
Example of tile-cover via https://github.com/mapbox/tile-cover
Geological Map of the Arctic with Natural Earth Data’s 1:50m land
SELECT 
ST_AsGeoJSON(
(ST_Dump(
ST_MakeValid(geometry)
)).geom
, 4) geometry
FROM (
SELECT ST_Simplify(((ST_Dump(geom)).geom), 1) AS geometry FROM (
SELECT
ST_Intersection(
ST_GeomFromText(‘POLYGON ((-179 -85, -179 85, 179 85, 179 -85, -179 -85))’, 4326),
ST_Difference(
(
SELECT ST_Buffer(ST_Collect(ref_geom),0)
FROM maps.sources
WHERE sources.source_id = 2
), (
SELECT ST_Buffer(ST_Collect(geom),0)
FROM public.land
)
)
) geom
) sub
) main WHERE geometry IS NOT NULL
et voilà

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Mapper | web developer/designer. Lover of all things open source and geo. Has cooked risotto in three countries.

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John J Czaplewski

John J Czaplewski

Mapper | web developer/designer. Lover of all things open source and geo. Has cooked risotto in three countries.

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