Professional · anonymized
Large-scale geographic data management
Handling large volumes of geospatial information with Python, QGIS and PostGIS.
Context
The organization worked with large volumes of geographic information.
Problem
Keeping geographic information organized and documented took a lot of time and was error-prone.
My role
Processing, loading and maintenance of the geographic data.
Solution
Processing of geographic layers with Python (GeoPandas and PyQGIS) and QGIS, with storage and spatial queries in PostGIS.
Technical decisions
- GeoPandas to process large volumes of data in batches and PyQGIS to integrate with the existing QGIS workflows.
- PostGIS to store and query spatial data directly in the database.
Outcome
Geographic information centralized in PostGIS, easier to query and maintain, with less manual work.