Geospatial analysis made easy with PostGIS and Geoalchemy
summary
Shows how PostGIS stores shapefiles and OpenStreetMap extracts, how PostGIS spatial index and bounding boxes cut million‑polygon queries down to milliseconds, and how GeoAlchemy integration wires those queries into Python. Describes a live Flask valuation platform using regression and gradient‑boosted trees plus comparable‑transaction radius (~500 m), serving results in about one second, running on AWS and Docker. Data scale: a few hundred thousand properties and ~1M polygons, and the pipeline actually works end to end.
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chapters (7)
- 0:00Cassava and valuation intro
- 5:32Geospatial tools and PostGIS
- 10:45Storing geospatial data
- 16:33Querying spatial data
- 20:02Geoalchemy for Python
- 21:04Performance insights
- 27:37Q&A
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