Michael DeWitt

In this session, we'll give an early look at how we're evolving Google Earth Engine to meet the current moment. In a world where Remote Sensing is more important than ever, where datasets are larger than ever and where diverse users (human and agentic) come from a wide variety of places, Earth Engine is evolving with open cloud standards, modular pipelines, and scalable compute to help support a new era of impact.

We'll demystify the rapidly evolving landscape of AI in this survey tailored for the Earth Engine Partner. We'll survey Google’s AI tools for geospatial and Earth AI—including Earth Engine & AlphaEarth Foundations (AEF), Geospatial Reasoning, Gemini, Spark, and Co-Scientist.

An in-depth look at serverless automation for Earth Engine workflows that take advantage of service accounts and Cloud tools like Run functions, Scheduler, Pub/Sub, and Compute Engine for production data processing.

Believe it or not, you may occasionally encounter errors when using Earth Engine. This course will walk through a set of best practices for handling many of the different types of errors in Earth Engine, as well as techniques for avoiding them to begin with.

Believe it or not, you may occasionally encounter errors when using Earth Engine. This course will walk through a set of best practices for handling many of the different types of errors in Earth Engine, as well as techniques for avoiding them to begin with.

An overview of importing and exporting data, then a deeper dive into architectures and sharing. We'll cover a number of topics related to getting data in and out; manifest upload; GDAL VRT for tiled exports; BigQuery; XArray, High Volume API, REST API; best practices for building.

This is Part 2 of the Intro to Earth Engine & JavaScript class. We'll continue where Part 1 left off, focusing on computing statistics on imagery, creating charts, exporting the results of your analyses.

Learn to operationalize your Earth Engine workflows! We'll cover scheduling and automation with Cloud Functions, best practices for using EE with other Google Cloud tools, and reference architectures for a few important operational use-cases.