Geo for Good 2023: Geospatial Machine Learning: An Introduction
1The slide deck for this talk → https://docs.google.com/presentation/d/1aZA8Q7nI-lCWHh709U2xRr2tSaGL6WRbfWMZfDecuSw/edit?usp=sharing&resourcekey=0-L4QfUh2AXGnMoLgmrnTHxw
More about the 2023 Geo for Good Summit → https://g.co/earth/geoforgood23
Remote Sensing data is teeming with valuable insights for tackling the most important problems vexing the world today. Machine Learning (ML) can help you extract these insights from the flood of data that's available. But how do you get started?
If you've ever felt overwhelmed by various ML options or confused by an alphabet soup of acronyms, this session is for you. We will start with an introduction to Machine Learning and its common applications within Remote Sensing. We will talk about the various geospatial ML options for handling both image (raster) and feature (vector) data. We'll cover Earth Engine's Machine Learning APIs and then move onto an explanation of when to take advantage of integrations with Google Cloud Platform. This session sets the stage for the remaining Machine Learning talks at the conference.
Speakers: Steve Greenberg, Daniel Coelho; Google