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UID:pretalx-foss4g-2026-ERGRGW@talks.osgeo.org
DTSTART;TZID=JST:20260902T134500
DTEND;TZID=JST:20260902T135000
DESCRIPTION:verture Maps Places offers 53 million POIs with a clean taxonom
 y — but what can you actually do with them? In 50 lines of Python and Du
 ckDB\, I turn raw Overture places into a visual neighborhood typology. Bef
 ore/after\, pipeline\, and a ready-to-run notebook.
DTSTAMP:20260605T004858Z
LOCATION:Ran1
SUMMARY:50 Lines of Python: Neighborhood DNA from Overture Maps Places - Ma
 rija Ercegovac
URL:https://talks.osgeo.org/foss4g-2026/talk/ERGRGW/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2026-T3DTHT@talks.osgeo.org
DTSTART;TZID=JST:20260903T140000
DTEND;TZID=JST:20260903T143000
DESCRIPTION:Which open mobility dataset should you trust for urban function
  analysis? Using Copernicus Urban Atlas polygons\, we compare Eurostat exp
 erimental MNO statistics\, OpenStreetMap GPS traces\, and census commuting
  flows. You will learn their biases\, and get a fully reproducible Python/
 PostGIS workflow.
DTSTAMP:20260605T004858Z
LOCATION:Conference Management Room2
SUMMARY:Eurostat vs OSM vs Census: Choosing Open Mobility Data for Urban Fu
 nction Maps - Marija Ercegovac
URL:https://talks.osgeo.org/foss4g-2026/talk/T3DTHT/
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