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Videos of the lectures taught in Fall 2023 at the University of Tennesseeare now available as a YouTube playlist. They provide a complete overview of the concepts of GeoSpatial science usingGoogle Earth Engine, PostgresSQL GIS , DuckDB, Python and SQL.

Taught on campus, but recorded for the rest of us to enjoy for free, by Dr. Qiusheng Wu, an Associate Professor in the Department of Geography & Sustainability at the University of Tennessee. Dr. Qiusheng is also an Amazon Visiting Academic and a Google Developer Expert (GDE) for Earth Engine.

The target groups addressed by the course are GIScientists and geographers who want to learn about Data Science, and the other way around, data scientists who want to work with geographical data; and of course students in that area.

Geographical data nowdays are everywhere. At its simplest form you'll be familiar with Google Maps, Mobile applications and social media metadata, while at the more advanced, there's the need to model objects that exist in the real world and are location aware. The software industry aside, lately there's many traditional business that started working with that kind of data.

In this course then you'll learn how to manage geospatial and bigdata using Google Earth Engine, PostgresSQL GIS , DuckDB, Python and SQL which you will use to query, analyze, and manipulate spatial databases effectively. Take note that PostGIS, a geospatial extension to Postgres is the the most popular Postgres extension. Under that perspective, the course's value which explores various techniques for efficiently retrieving and managing spatial data, explodes multifold.

As such, students who successful complete the course should be able to:

The tech stack used throughout the course is impressive too. Tools that are going to be used include:

The course is making use of that stack beginning very early on, as seen by the curriculum spanning 13 weeks:

Week 1: Course IntroductionWeek 1: Spatial Data ModelsWeek 2: Installing Miniconda and geemapWeek 2: Introducing Visual Studio CodeWeek 2: Setting Up Powershell for VS CodeWeek 2: Introducing Git and GitHubWeek 3: Python BasicsWeek 3: Getting Started with GeemapWeek 4: Using Earth Engine ImageWeek 4: Filtering Image CollectionWeek 4: Filtering Feature CollectionWeek 5: Styling Feature CollectionWeek 5: Earth Engine Data CatalogWeek 5: Visualizing Cloud Optimized GeoTIFF (COG)Week 6: Visualizing STAC and Vector DataWeek 6: Downloading OpenStreetMap DataWeek 6: Visualizing Earth Engine DataWeek 7: Timeseries visualization and zonal statisticsWeek 7: Parallel processing with the map functionWeek 7: Earth Engine data reductionWeek 8: Creating Cloud-free Imagery with Earth EngineWeek 9: Downloading Earth Engine ImagesWeek 9: Downloading Earth Engine Image CollectionsWeek 9: Earth Engine ApplicationsWeek 10: DuckDB for GeospatialWeek 10: Introduction to DuckDB (CLI, Python API, VS Code, DBeaver)Week 10: DuckDB CLI and SQL BasicsWeek 10: Introducing SQL Basics with DuckDBWeek 11: Intro to the DuckDB Python APIWeek 11: Importing Spatial Data Into DuckDBWeek 11: Exporting Spatial Data From DuckDBWeek 12: Working with Geometries in DuckDBWeek 13: Analyzing Spatial Relationships with DuckDBWeek 13: Visualizing Geospatial Data in DuckDB with leafmap and lonboard

Of course 13 weeks was the duration on campus. The rest we can enjoy at a self pace. The videos are alsoaccompanied by an online reference book in HTML format.

Quality wise, Dr. Qiusheng Wu clearly explains the concepts and showcases the whole process of working with the tools that handle geodata. Which means that even if you are not familiar with Geo-science, the course is well worth attending regardless due to the tech stack employed, especially the PostgreSQL part. If on the other hand you already are a data scientist, then this is a must do.

Youtube playlist

Course

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Hydra Turns PostgreSQL Into A Column Store

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Spatial Data Management For GIS and Data Scientists - iProgrammer