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How to Create a Spinning Globe 🌍 with Your Own Data Layers (No Coding Required) Learn how to create a spinning 3D globe map without writing any code using a simple web-based tool. In this step-by-step geospatial tutorial, you'll see how to build an interactive spinning globe, overlay raster...

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Qiusheng Wu

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12,637 просмотров • 3 месяцев назад •via X (Twitter)

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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
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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
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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

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📢 Exciting news! Leafmap now supports creating 3D 🌎 maps with Mapbox! This demo showcases how to visualize the ESA global land cover from #EarthEngine on a 3D globe. Explore the 100 PB+ Earth Engine Data Catalog and display any geospatial datasets in 3D 🚀 Notebook: #leafmap #geospatial #opensource #python
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📢 Exciting news! Leafmap now supports creating 3D 🌎 maps with Mapbox! This demo showcases how to visualize the ESA global land cover from #EarthEngine on a 3D globe. Explore the 100 PB+ Earth Engine Data Catalog and display any geospatial datasets in 3D 🚀 Notebook: #leafmap #geospatial #opensource #python

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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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🚀 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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The anymap-ts Python package now supports creating choropleth maps from vector data with a few simple clicks! Give it a try: Web demo: Jupyter demo: GitHub: Documentation: #geospatial #opensource
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Introducing anymap-ts: a new Python package that makes geospatial visualization easy! Built on MapLibre + TypeScript, anymap-ts brings the same rich mapping experience to both the web and Jupyter Notebook. It supports many popular geospatial formats, including GeoJSON, GeoParquet, FlatGeobuf, PMTiles, COG, Zarr, COPC LiDAR, and Gaussian Splat. It also includes powerful built-in UI components such as a minimap, bookmarks, print tool, view state manager, STAC search, street view, and geometry editor. Try it out: Web demo: Jupyter demo: GitHub: Documentation: Video tutorial: #mapping #maplibre #typescript #jupyter #python
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Run MATLAB code directly in Jupyter notebooks, JupyterLab, and JupyterHub using the MATLAB kernel. Just open a browser-based MATLAB environment from Jupyter to directly access MATLAB apps and features. Get started with our repo: #Jupyter #Coding
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Excited to share a new open-source project for the web-mapping and LiDAR community: maplibre-gl-lidar 🚀 With maplibre-gl-lidar, you can visualize large-scale LiDAR point clouds (LAS/LAZ, including COPC) directly in the browser using MapLibre GL JS. It supports point-cloud data stored locally or hosted on the web, and comes with an interactive GUI featuring customizable color schemes, classification legends, and point picking. It even works seamlessly inside Jupyter Notebooks. Visualizing tens of millions of LiDAR points has never been this simple or fast, making it easy to build modern, lightweight, and fully interactive web-based LiDAR viewers. Try it out: Live Demo Viewer: GitHub Repository: Full Video Tutorial: #MapLibre #LiDAR #WebGIS #OpenSource #PointCloud #3DMapping
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Turning Jupyter notebooks directly into an interactive dashboard with automatic deployment on Hugging Face 👇 GitHub: Web App: #geospatial #dataviz #jupyter
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Jupyter Agents - LLMs running data analysis directly in a notebook! The agent can load data, execute code, plot results and following your guidance and ideas! A very natural way to collaborate with an LLM over data and it's just scratching the surface of what's possible soon!

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🎁 A New Year’s gift to the geospatial community: a brand-new QGIS plugin that unlocks access to 80+ petabytes of satellite imagery and geospatial datasets with zero coding required. In my first video of 2026, I’m excited to share what might be one of the most powerful QGIS plugins I’ve built so far. This plugin makes it incredibly easy to explore the official Earth Engine Data Catalog and the Awesome GEE Community Catalog directly inside QGIS. With just a few clicks, you can browse massive Earth Engine datasets, visualize them on the map, generate time series from ImageCollections, export data for further analysis, and even convert Earth Engine JavaScript workflows to Python, all without writing a single line of code. If you’ve ever wanted the power of Earth Engine inside QGIS without the learning curve, this plugin is for you. 👉 Download the plugin and follow the full step-by-step video tutorial to get started today: QGIS Plugin Page: GitHub Repository: Video Tutorial: Happy New Year, and I hope this tool helps you do more with geospatial data in 2026 🚀 #QGIS #geospatial #EarthEngine #Python #datascience

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