FOSS4G 2023 workshops

Scaling Spatial Temporal Data Analysis with Postgres, PostGIS, TimescaleDB, and H3 Indexing: A Hands-On Workshop
06-27, 16:00–18:00 (Europe/Tirane), UBT D / N113 - Second Floor

Join this workshop to discover the powerful combination of Postgres, PostGIS, TimescaleDB, and H3 indexing for managing spatial temporal data at scale. With open source tools, you can create a scalable database solution for even the most complex data sets.

Working with spatial-temporal data using Postgres + Postgis + timescaleDB + h3
- Setup a local environment using docker
- Installing an extension or using an image from the docker hub
- Checking versions of extensions
- Connecting to your environment using psql
- Connecting to your environment using QGIS
- Connecting to your environment using pgAdmin4
- Loading a set of sample data points, polygons for analysis (use some backups and restore)
- Doing some spatial queries (point in polygon, polygon in polygon) with postgis
- Doing temporal queries with and without timescaleDB
- Optimizing spatial joins using h3

Explore further possibilities of combing and optimizing spatial temporal data, introduction of pg_raster.

I have been honing my skills in the geospatial domain, gaining diverse experience in Climate tech startups, Agritech solutions, and Public urban transport planning. Throughout these experiences, I have heavily relied on Postgres + PostGIS, Python, and cloud technologies to drive my work.

My experience extends to working with satellite data (including Sentinel and Landsat), geospatial data modeling, and handling large datasets at scale in the cloud using Docker, Python, S3, etc

I am most interested in building a generic spatial-temporal database that can handle a wide variety of data and use cases (building digital earth in postgres)