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👉 The slide deck for this talk → https://docs.google.com/presentation/... 🛰️ More about the 2023 Geo for Good Summit → https://g.co/earth/geoforgood23 ❤️🌍 DESCRIPTION: Geospatial AI is an application of AI, particularly machine learning to geospatial big data. Geospatial AI can be used for tasks such as change detection, image classification, and object detection. However, training these models requires large amounts of data, variety, and veracity. Discover how Collect Earth Online (an open source platform) enables users to visualize and organize geospatial data, and can be used to collect reference data for training GeoAI models. We'll also discuss the process of creating a sampling design, gathering samples, and using those samples in Earth Engine to train a classifier. #remotesensing #EarthEngine #cloudcomputing #GeographicInformationSystem #GIS #ClimateAnalysis #EarthObservation #climatechange #sustainability #ai #machinelearning 💻 TIMESTAMPS: 0:00 - Introduction to Geospatial AI 1:21 - Geospatial AI Overview 5:23 - Introduction to Collect Earth Online 11:28 - Tutorial: Using Collect Earth Online 13:10 - Project Creation in Collect Earth 19:14 - Data Analysis Techniques 22:35 - Data Export to Google Earth Engine 23:20 - Earth Engine Classifier Tutorial 25:20 - Future of Earth Observation Data 28:15 - Audience Q&A Session 29:45 - Handling Large Geospatial Datasets 33:10 - EO Data Interpretation Standards 35:32 - Using Reference Data in Projects 37:52 - Crowdsourcing in Earth Observation 41:10 - Grading Standards in EO Analysis 43:28 - Applying Machine Learning to EO Data 45:40 - Ground Data Integration Methods 47:02 - Next Steps in Geospatial Analysis 47:20 - Final Questions and Wrap-up 🎙️ SPEAKERS -Gino Miceli, Google -David Saah, Spatial Informatics Group