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🚀 GeoAI Tutorial 12: Wetland Mapping with Deep Learning and GeoAI! 🌍 Unlock the power of your geospatial data! Learn to train an wetland detection model and run inference on large datasets—all with just a few lines of code. 🎥 Watch the full tutorial here: 📓 Explore the notebook:...

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Qiusheng Wu

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16,614 views • 1 year ago •via X (Twitter)

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Learn how to access market data using Polygon's Stock API and the Python programming language.

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🚀 GeoAI Tutorial 19: Train a Semantic Segmentation Model for Objection Detection from Remote Sensing Imagery 🌍 Leverage any PyTorch segmentation model from — with hundreds of image encoders & pretrained weights available. 🎥 Watch the full tutorial here: 📓 Explore the notebook: 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

Qiusheng Wu

20,082 views • 1 year ago

🚀 GeoAI Tutorial 6: Building Footprint Regularization Using Deep Learning and GeoAI! 🌍 Learn how to regularize building footprints detected from aerial imagery with three different regularization techniques. Transform building footprints with rugged edges into smooth and rectangular shapes. 🎥 Watch the full tutorial here: 📓 Access the notebook: 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python
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🚀 GeoAI Tutorial 6: Building Footprint Regularization Using Deep Learning and GeoAI! 🌍 Learn how to regularize building footprints detected from aerial imagery with three different regularization techniques. Transform building footprints with rugged edges into smooth and rectangular shapes. 🎥 Watch the full tutorial here: 📓 Access the notebook: 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python

Qiusheng Wu

16,568 views • 1 year ago

🚀 GeoAI Tutorial 23: Building Detection from Aerial Imagery and LiDAR Data 🏙️🛰️ In this tutorial, I demonstrate how to train a deep learning segmentation model for building detection by combining aerial/satellite imagery with LiDAR data. You'll learn how to fuse multi-source remote sensing data to improve model accuracy and robustness. 🔗 Tutorial video: 📓 Notebook example: 💻 GitHub repo: 📚 Documentation: 🎥 Full playlist: #GeoAI #geospatial #AI #Python #DeepLearning
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🚀 GeoAI Tutorial 23: Building Detection from Aerial Imagery and LiDAR Data 🏙️🛰️ In this tutorial, I demonstrate how to train a deep learning segmentation model for building detection by combining aerial/satellite imagery with LiDAR data. You'll learn how to fuse multi-source remote sensing data to improve model accuracy and robustness. 🔗 Tutorial video: 📓 Notebook example: 💻 GitHub repo: 📚 Documentation: 🎥 Full playlist: #GeoAI #geospatial #AI #Python #DeepLearning

Qiusheng Wu

12,194 views • 11 months ago

🚀 The GeoAI QGIS Plugin is here 🔥 You can run Moondream vision-language models, object detection, image segmentation (SAM 3), and even train your own geospatial segmentation model end-to-end. Website: GitHub: Short demo: Full video tutorial: #QGIS #GeoAI #SAM3 #Geospatial #DeepLearning #ComputerVision #OpenSource #Python
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🚀 The GeoAI QGIS Plugin is here 🔥 You can run Moondream vision-language models, object detection, image segmentation (SAM 3), and even train your own geospatial segmentation model end-to-end. Website: GitHub: Short demo: Full video tutorial: #QGIS #GeoAI #SAM3 #Geospatial #DeepLearning #ComputerVision #OpenSource #Python

Qiusheng Wu

11,682 views • 6 months ago

🚀 Leafmap now supports visualizing geospatial data on a stunning 3D globe with MapLibre 🌍. Create stunning 3D maps with just a few lines of Python code! 🎥 Check out the full tutorial: 📓 Dive into the notebook: 🌐 Try the demo: #Geospatial #3DMapping #Python
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🚀 Leafmap now supports visualizing geospatial data on a stunning 3D globe with MapLibre 🌍. Create stunning 3D maps with just a few lines of Python code! 🎥 Check out the full tutorial: 📓 Dive into the notebook: 🌐 Try the demo: #Geospatial #3DMapping #Python

Qiusheng Wu

10,980 views • 1 year ago

🚀 Exciting news! The GeoAI Python package just got a major upgrade. It now supports interactive geospatial data visualization powered by AI Agents. 🌍✨ GitHub: Full tutorial: 🌍 In this tutorial, you’ll learn how to build interactive maps powered by AI agents that respond to natural language queries. Watch how you can fly to any city, add raster or vector layers, visualize 3D buildings, and explore geospatial data—all without writing code. Perfect for developers, researchers, and anyone curious about AI, GIS, and interactive mapping. #geospatial #mapping #python #GeoAI #AI
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🚀 Exciting news! The GeoAI Python package just got a major upgrade. It now supports interactive geospatial data visualization powered by AI Agents. 🌍✨ GitHub: Full tutorial: 🌍 In this tutorial, you’ll learn how to build interactive maps powered by AI agents that respond to natural language queries. Watch how you can fly to any city, add raster or vector layers, visualize 3D buildings, and explore geospatial data—all without writing code. Perfect for developers, researchers, and anyone curious about AI, GIS, and interactive mapping. #geospatial #mapping #python #GeoAI #AI

Qiusheng Wu

12,831 views • 9 months ago

🚀 Exciting update! The GeoAI Python package is getting even smarter — soon it will support AI agents. That means you’ll be able to use natural language to effortlessly download, analyze, and visualize geospatial data without coding 🌍🤖 Stay tuned for the upcoming release! 🔗 GitHub: #geospatial #GeoAI #Python #AI
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🚀 Exciting update! The GeoAI Python package is getting even smarter — soon it will support AI agents. That means you’ll be able to use natural language to effortlessly download, analyze, and visualize geospatial data without coding 🌍🤖 Stay tuned for the upcoming release! 🔗 GitHub: #geospatial #GeoAI #Python #AI

Qiusheng Wu

17,073 views • 9 months ago

The GeoAI Python package now supports interactive segmentation of remote sensing imagery with the Moondream AI Vision Language Models (VLMs), which provides powerful and efficient visual reasoning. A great alternative to Meta's SAM 3. GitHub: Notebook example: #GeoAI #geospatial #AI #opensource
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The GeoAI Python package now supports interactive segmentation of remote sensing imagery with the Moondream AI Vision Language Models (VLMs), which provides powerful and efficient visual reasoning. A great alternative to Meta's SAM 3. GitHub: Notebook example: #GeoAI #geospatial #AI #opensource

Qiusheng Wu

11,655 views • 6 months ago

🎯 AI Agents for Microsoft Planetary Computer: Explore Satellite Data with Zero Code Unlock satellite data without writing a single line of code! 🌍 In this step-by-step tutorial, you’ll discover how to harness the power of AI agents to search, filter, and visualize geospatial datasets from the Microsoft Planetary Computer — all using natural language. Perfect for researchers, developers, and environmental professionals who want fast, intuitive, code-free access to massive Earth observation datasets like Sentinel-2, Landsat, NAIP, and DEM. Learn how to: ✅ Use zero-code AI agents in Jupyter Notebooks ✅ Search satellite imagery by date, location, or cloud cover ✅ Visualize data instantly using Leafmap ✅ Integrate STAC data catalogs into your GeoAI workflow Full video tutorial available on YouTube: #geospatial #GeoAI #opensource #PlanetaryComputer
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🎯 AI Agents for Microsoft Planetary Computer: Explore Satellite Data with Zero Code Unlock satellite data without writing a single line of code! 🌍 In this step-by-step tutorial, you’ll discover how to harness the power of AI agents to search, filter, and visualize geospatial datasets from the Microsoft Planetary Computer — all using natural language. Perfect for researchers, developers, and environmental professionals who want fast, intuitive, code-free access to massive Earth observation datasets like Sentinel-2, Landsat, NAIP, and DEM. Learn how to: ✅ Use zero-code AI agents in Jupyter Notebooks ✅ Search satellite imagery by date, location, or cloud cover ✅ Visualize data instantly using Leafmap ✅ Integrate STAC data catalogs into your GeoAI workflow Full video tutorial available on YouTube: #geospatial #GeoAI #opensource #PlanetaryComputer

Qiusheng Wu

10,346 views • 8 months ago

Agricultural Field Boundary Delineation (Instance Segmentation) with GeoAI Learn an end-to-end GeoAI workflow for agricultural field boundary delineation using instance segmentation and the Fields of the World dataset ( This workflow can be adapted to detect other object types (not just field boundaries) as long as training data is available. Video tutorial: Notebook: Web app: #geoai #geospatial #deeplearing
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🚀 New Tutorial Alert! I just published a step-by-step guide on building an interactive dashboard with Python and Leafmap. 🌍📊 Explore the Jupyter Notebook: Watch the full video tutorial: #leafmap #geospatial #python #dataviz
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16,755 views • 10 months ago

🌍 New Tutorial Alert: Visualizing Google's AlphaEarth Satellite Embeddings in 3D! 🛰️🏙️ Google DeepMind has released AlphaEarth, a groundbreaking satellite embedding dataset on Google Earth Engine. It includes annual global embeddings from 2017 to 2024, where each pixel covers a 10×10 meter area. In this tutorial, you'll learn how to: ✅ Access and visualize AlphaEarth embeddings in 3D ✅ Leverage them for machine learning and change detection 🎥 Watch the tutorial: 📘 Try the notebook: #GeoAI #geospatial #AI #Python #DeepLearning
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🌍 New Tutorial Alert: Visualizing Google's AlphaEarth Satellite Embeddings in 3D! 🛰️🏙️ Google DeepMind has released AlphaEarth, a groundbreaking satellite embedding dataset on Google Earth Engine. It includes annual global embeddings from 2017 to 2024, where each pixel covers a 10×10 meter area. In this tutorial, you'll learn how to: ✅ Access and visualize AlphaEarth embeddings in 3D ✅ Leverage them for machine learning and change detection 🎥 Watch the tutorial: 📘 Try the notebook: #GeoAI #geospatial #AI #Python #DeepLearning

Qiusheng Wu

25,950 views • 10 months ago

🚀 Excited to share a new tutorial on how to detect buildings 🏘️using the Segment Anything Model 2 (SAM 2) with Segment-Geospatial! You can choose interactive segmentation or utilize a GeoJSON file with building centroids or bounding boxes to do automated building detection. 📹 Check out the video tutorial: 📓 Explore the notebook: #Geospatial #OpenSource #AI #MachineLearning
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🚀 Excited to share a new tutorial on how to detect buildings 🏘️using the Segment Anything Model 2 (SAM 2) with Segment-Geospatial! You can choose interactive segmentation or utilize a GeoJSON file with building centroids or bounding boxes to do automated building detection. 📹 Check out the video tutorial: 📓 Explore the notebook: #Geospatial #OpenSource #AI #MachineLearning

Qiusheng Wu

71,967 views • 1 year ago

🚀 A brand-new feature is coming to the SAMGeo Python package: interactive remote-sensing image segmentation with text prompts powered by SAM3. This update makes geospatial segmentation even more intuitive: just describe what you want to detect, and let GeoAI do the rest. ✨ GitHub PR: #GeoAI #SAM3 #OpenSource #Python
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🚀 A brand-new feature is coming to the SAMGeo Python package: interactive remote-sensing image segmentation with text prompts powered by SAM3. This update makes geospatial segmentation even more intuitive: just describe what you want to detect, and let GeoAI do the rest. ✨ GitHub PR: #GeoAI #SAM3 #OpenSource #Python

Qiusheng Wu

32,888 views • 7 months ago

🚀 Introducing the Earth Engine Dataset Explorer, powered by Google #Gemini! 🌍✨ Struggling to find the right #geospatial datasets for your research? Our Dataset Explorer recommends tailored datasets and offers an interactive exploration experience. 📹 Check out the video tutorial: 📒 Explore the notebook: #geemap #OpenSource #AI #EarthEngine
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🚀 Introducing the Earth Engine Dataset Explorer, powered by Google #Gemini! 🌍✨ Struggling to find the right #geospatial datasets for your research? Our Dataset Explorer recommends tailored datasets and offers an interactive exploration experience. 📹 Check out the video tutorial: 📒 Explore the notebook: #geemap #OpenSource #AI #EarthEngine

Qiusheng Wu

23,929 views • 1 year ago

QGIS GeoAI Plugin v0.5.0 is out! I just released v0.5.0 of the QGIS GeoAI Plugin, bringing interactive image segmentation powered by DeepForest ( to your desktop GIS workflow. With this update, you can load pretrained DeepForest models to segment real-world objects such as trees, birds, livestock, dead trees, and more, directly inside QGIS. Try it out: Documentation: GitHub: #deepforest #geoai #QGIS #geospatial #OpenSource
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QGIS GeoAI Plugin v0.5.0 is out! I just released v0.5.0 of the QGIS GeoAI Plugin, bringing interactive image segmentation powered by DeepForest ( to your desktop GIS workflow. With this update, you can load pretrained DeepForest models to segment real-world objects such as trees, birds, livestock, dead trees, and more, directly inside QGIS. Try it out: Documentation: GitHub: #deepforest #geoai #QGIS #geospatial #OpenSource

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21,385 views • 5 months ago

Automatic code generation and data visualization for #EarthEngine and #geemap using #Gemini 🚀 Explore the power of cloud computing and #geospatial big data with minimal coding 🌎. Gemini can interpret the data on the map and iteratively improve the visualization. Check out the notebook:
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Automatic code generation and data visualization for #EarthEngine and #geemap using #Gemini 🚀 Explore the power of cloud computing and #geospatial big data with minimal coding 🌎. Gemini can interpret the data on the map and iteratively improve the visualization. Check out the notebook:

Qiusheng Wu

22,322 views • 1 year ago

Mapping swimming pools 🏊‍♀️ interactively with text prompts and the Segment Anything Model 🤩 Notebook: GitHub: #geospatial #segmentanything #deeplearning
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Mapping swimming pools 🏊‍♀️ interactively with text prompts and the Segment Anything Model 🤩 Notebook: GitHub: #geospatial #segmentanything #deeplearning

Qiusheng Wu

30,498 views • 3 years ago

An AI assistant for Google Earth Engine is now available in QGIS! You can explore and visualize any dataset from the 80+ PB Earth Engine Data Catalog using natural language, and run scalable geospatial analysis on demand without writing code. Every interaction automatically generates reusable code, making it easy to reproduce results, customize workflows, and transition from no-code to full scripting when needed. Upgrade the plugin to get started and bring AI-powered geospatial analytics directly into your QGIS workflow. GitHub: QGIS plugin: GeoAgent: #EarthEngine #QGIS #OpenSource #GeoAI #Geospatial
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An AI assistant for Google Earth Engine is now available in QGIS! You can explore and visualize any dataset from the 80+ PB Earth Engine Data Catalog using natural language, and run scalable geospatial analysis on demand without writing code. Every interaction automatically generates reusable code, making it easy to reproduce results, customize workflows, and transition from no-code to full scripting when needed. Upgrade the plugin to get started and bring AI-powered geospatial analytics directly into your QGIS workflow. GitHub: QGIS plugin: GeoAgent: #EarthEngine #QGIS #OpenSource #GeoAI #Geospatial

Qiusheng Wu

17,245 views • 2 months ago