2023-08-17 –, Aula
Have you ever wondered what type of data you can get about a certain location on the globe? What if I told you that you can access an enormous amount of information while sitting right there at your laptop? In this talk, I'll show you how to use Google Earth Engine to enrich your dataset. Either your exploring, or planning your next ML project, Geospatial data can provide you with a lot of information you did not know you had access to. Let me show you how!
This talk is aimed at Machine Learning Engineers, Data Scientists, and researchers that have good experience with Python. The goal is to teach these professsionals how they can leverage Google Earth Engine (GEE) to enrich and explore their datasets. By the end of this talk, I expect that the audience has a good grasp of what GEE is, and how they can use it in their next project!
We'll go through a small introduction of Geospatial data, and the different types of providers out there. I'll introduce Google Earth Engine and the Python API that has been recently in the works. Finally, I'll go over some use cases that users might explore, as well as some examples from the trenches.
Here's the outline:
- Geospatial data: What is it?
- A miriad of providers: From LandSat, to Modius, to Sentinel
- Bringing it all together: Google Earth Engine
- An intro to Google Earth Engine
- The Python API, how to use it?
- Example: Enriching a dataset for carbon stock measurements in Farms
- Tips and tricks
- Where to go from here
Want to learn of to extract data from Satelites to enrich your dataset? Learn how to use Google Earth Engine with Python!
Category [Scientific Applications]:Geo Science
Expected audience expertise: Domain:some
Expected audience expertise: Python:some
I'm a technologist, born and raised in sunny Portugal, now based in Copenhagen. My work lies in the intersection of Machine Learning, Data, Software Engineering, and People. I'm in love with Technology, and how it can improve people's lives.
In the past, I've worked in Consumer Electronics, Public Institutions, Big Three Management Consulting, and Startups. The common thread? Solving problems end-to-end.
Now, I run my own ML consulting shop, where I focus on solving tough problems end-to-end.