Gennadii Donchyts

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.

This hands-on session will empower you to share your geospatial research and insights with the world. We will explore the full spectrum of app and dashboard development for Google Earth Engine, from rapid prototyping with Earth Engine Apps or Python UI libraries to robust full-stack applications leveraging Google Cloud services (Cloud Run, BigQuery).

In this session, we'll introduce you to Open Foris Ground, an open-source platform developed by Google and FAO. A thoughtfully designed web app make it easy to create field surveys which combine geospatial and structured data with data collectors.

Numerous publicly available Earth Observation maps provide data on forests, land use, and tree cover. However, these maps often differ because they use various definitions and classification systems.

This hands-on session will empower you to share your geospatial research and insights with the world. We will explore the full spectrum of app and dashboard development for Google Earth Engine, from rapid prototyping with Earth Engine Apps or Python UI libraries to robust full-stack applications leveraging Google Cloud services (Cloud Run, BigQuery).

Join us for an hour-long session where you’ll have the opportunity to connect directly with the Earth Engine team and other Cloud Partners. Get insights on the product, network with your peers, and share your invaluable feedback on our latest features.

In this session, we'll introduce you to Open Foris Ground, an open-source platform developed by Google and FAO. A thoughtfully designed web app make it easy to create field surveys which combine geospatial and structured data with data collectors.

Numerous publicly available Earth Observation maps provide data on forests, land use, and tree cover. However, these maps often differ because they use various definitions and classification systems.

Learn how to develop and train basic neural networks in TensorFlow, for use with Earth Engine. This session will cover vector inputs, suitable for tabular or per-pixel image models.

Building on NN1, this session will demonstrate how to use Apache Beam to build large training datasets, training a convolutional model of land cover on Vertex AI, deploying the model and visualizing predictions in Earth Engine.

This session provides an overview of multiple datasets and applications for water detection from EO data with EE, including surface water occurrence and change mapping, coastal changes and bathymetry, moisture. Then the session provides a hands-on experience focusing on the waterbody dynamics and flood detection with optical multispectral and SAR satellite imagery.

Combining the powers of Earth Engine and Google Earth allows us create exciting visualizations, showng the results of data science and analytics in an immersive 3D environment, helping us better understand and explore our world and the science that concerns it. This session will feature a panel of presenters who will demonstrate how they combined Earth Engine and Google Earth, plus a little bit of scripting with HTML, JavaScript, and KML, to create engaging stories and visualization.