Hi everyone, Hope you’re doing very well! Have you ever wondered how those colorful land cover maps showing forests, cities, water bodies, and farmland are created? In this post, we’ll walk through how we can use machine learning to automatically identify and map different land cover types from satellite imagery. I have used satellite images from Google Earth Engine’s data catalog (Landsat 8 to be specific) - https://developers.google.com/earth-engine/datasets/catalog and Kubeflow notebooks for the tutorial with the help of GEE’s python API.
Here’s links to the recording and documentation: https://drive.google.com/file/d/1qa_PGy3kee98IeNtlS1luhXpnlTt4Qep/view?usp=drive_link https://docs.google.com/document/d/1zZMAvcKrRj-UK8Ok_Pc888d1i-RX4UbgVbwTG-rpd9Y/edit?usp=sharing
Thank you, Shrishti Karkera