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A collection of Jupyter Notebook examples for visualizing #geospatial data, including raster (COG, STAC), vector (GeoParquet, PMTiles, GeoJSON, Shapefile, GeoPackage, etc.), and LiDAR data. Raster: Vector: LiDAR: #dataviz #lidar #cog #geopython

Qiusheng Wu

53,173 subscribers

56,730 次观看 • 2 年前 •via X (Twitter)

科学技术教育艺术 #geospatial

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Private livecam show

3 条评论

Col Collins 的头像

Col Collins2 年前

This is amazing!

Mario Luna 的头像

Mario Luna2 年前

😮😮😮👍🏽👍🏽👍🏽 thanks for sharing

mambri86🪂🔻 🧯💨🕎 的头像

mambri86🪂🔻 🧯💨🕎2 年前

Hi @giswqs amazing works, can you give tutorial on how to access and download overture maps global data

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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

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

Qiusheng Wu

102,491 次观看 • 7 个月前

🚀 Visualize Geospatial Data Instantly from the Command Line! You can now interactively explore raster and vector datasets without opening a desktop GIS or Jupyter Notebook. Simply run: pip install "leafmap[viewer]" Then visualize your data with one line: view-raster /path/to/raster.tif view-vector /path/to/vector.geojson Customize your visualization easily: view-raster /path/to/raster.tif --band 1 --colormap coolwarm view-vector /path/to/vector.geojson --style liberty These CLI tools are powered by Leafmap, MapLibre, and LocalTileserver, supporting all geospatial formats compatible with rasterio and geopandas. 👉 Check it out: #geospatial #datascience #mapping #python

🚀 Visualize Geospatial Data Instantly from the Command Line! You can now interactively explore raster and vector datasets without opening a desktop GIS or Jupyter Notebook. Simply run: pip install "leafmap[viewer]" Then visualize your data with one line: view-raster /path/to/raster.tif view-vector /path/to/vector.geojson Customize your visualization easily: view-raster /path/to/raster.tif --band 1 --colormap coolwarm view-vector /path/to/vector.geojson --style liberty These CLI tools are powered by Leafmap, MapLibre, and LocalTileserver, supporting all geospatial formats compatible with rasterio and geopandas. 👉 Check it out: #geospatial #datascience #mapping #python

Qiusheng Wu

13,495 次观看 • 11 个月前

🚀 Visualize Big Vector Data in Python—FAST! Tired of slow and clunky tools for visualizing big vector dataset in Python? Discover this one-line Python trick using Leafmap + DuckDB to instantly render huge vector datasets—even gigabytes in size—right in your Jupyter notebook. In this video, you'll learn how to: ✅ Visualize millions of vector features with ease ✅ Use Leafmap + DuckDB to serve vector tiles dynamically ✅ Handle GeoParquet, GeoPackage, cloud-hosted data & more ✅ Create fully interactive maps—without crashing your browser! 📌 Watch the full video tutorial on YouTube: 👉 Notebook example: #Visualization #Leafmap #BigData #DuckDB #GeoPython #GIS #OpenSource

🚀 Visualize Big Vector Data in Python—FAST! Tired of slow and clunky tools for visualizing big vector dataset in Python? Discover this one-line Python trick using Leafmap + DuckDB to instantly render huge vector datasets—even gigabytes in size—right in your Jupyter notebook. In this video, you'll learn how to: ✅ Visualize millions of vector features with ease ✅ Use Leafmap + DuckDB to serve vector tiles dynamically ✅ Handle GeoParquet, GeoPackage, cloud-hosted data & more ✅ Create fully interactive maps—without crashing your browser! 📌 Watch the full video tutorial on YouTube: 👉 Notebook example: #Visualization #Leafmap #BigData #DuckDB #GeoPython #GIS #OpenSource

Qiusheng Wu

13,147 次观看 • 10 个月前

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 and vector data layers, and visualize datasets directly in your browser or in a Jupyter Notebook environment. Web-based demo: Jupyter notebook demo: Video tutorial: #geospatial #opensource #python #jupyter #maplibre

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 and vector data layers, and visualize datasets directly in your browser or in a Jupyter Notebook environment. Web-based demo: Jupyter notebook demo: Video tutorial: #geospatial #opensource #python #jupyter #maplibre

Qiusheng Wu

12,745 次观看 • 6 个月前

GeoLibre v0.5.0 is out! This update significantly expands data format support, making it easier to work with a wide range of geospatial datasets in a lightweight, modern GIS environment. Newly supported formats and services include: GeoJSON, Shapefile, GeoPackage, GeoParquet, KML/KMZ, FlatGeobuf, PMTiles MBTiles, GeoTIFF, Zarr, LiDAR point clouds, Gaussian Splatting, and ArcGIS services. GeoLibre is a lightweight, cloud-native GIS built with MapLibre and Tauri. It runs directly in the browser and is also available as a standalone cross-platform desktop application at only ~30 MB. GitHub: Website: Live demo: Feedback, ideas, and contributions are welcome. #geospatial #opensource #maplibre

GeoLibre v0.5.0 is out! This update significantly expands data format support, making it easier to work with a wide range of geospatial datasets in a lightweight, modern GIS environment. Newly supported formats and services include: GeoJSON, Shapefile, GeoPackage, GeoParquet, KML/KMZ, FlatGeobuf, PMTiles MBTiles, GeoTIFF, Zarr, LiDAR point clouds, Gaussian Splatting, and ArcGIS services. GeoLibre is a lightweight, cloud-native GIS built with MapLibre and Tauri. It runs directly in the browser and is also available as a standalone cross-platform desktop application at only ~30 MB. GitHub: Website: Live demo: Feedback, ideas, and contributions are welcome. #geospatial #opensource #maplibre

Qiusheng Wu

19,198 次观看 • 3 个月前

GeoLibre v0.9.0 is out. GeoLibre is a lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data across desktop and web environments, with a responsive layout for mobile screens. This release turns GeoLibre into a far more complete analysis environment. Highlights: - New cloud data panels for Microsoft Planetary Computer and Google Earth Engine, plus an Overture Maps plugin and federal Web Services plugins, including NASA Earthdata, USGS National Map, EPA EnviroAtlas, FEMA NFHL - Accessing 1000+ NASA Earthdata layers with a few simple clicks - Time Slider plugin for animating time series raster and vector data - SQL Workspace: run DuckDB Spatial SQL directly against loaded layers, local files, and remote URLs, with query history and one-click "add results to map" - Conversion tools: Vector to GeoParquet, CSV to GeoParquet, and Raster to COG, running in the browser with DuckDB-WASM - Controls menu with Measure, Bookmark, Minimap, View State, and Print Everything is open source. Try it in your browser, install the desktop app, or self-host it. Live demo: GitHub: Feedback and contributions are welcome. #GIS #Geospatial #OpenSource #MapLibre #DuckDB #WebGIS #GeoLibre

GeoLibre v0.9.0 is out. GeoLibre is a lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data across desktop and web environments, with a responsive layout for mobile screens. This release turns GeoLibre into a far more complete analysis environment. Highlights: - New cloud data panels for Microsoft Planetary Computer and Google Earth Engine, plus an Overture Maps plugin and federal Web Services plugins, including NASA Earthdata, USGS National Map, EPA EnviroAtlas, FEMA NFHL - Accessing 1000+ NASA Earthdata layers with a few simple clicks - Time Slider plugin for animating time series raster and vector data - SQL Workspace: run DuckDB Spatial SQL directly against loaded layers, local files, and remote URLs, with query history and one-click "add results to map" - Conversion tools: Vector to GeoParquet, CSV to GeoParquet, and Raster to COG, running in the browser with DuckDB-WASM - Controls menu with Measure, Bookmark, Minimap, View State, and Print Everything is open source. Try it in your browser, install the desktop app, or self-host it. Live demo: GitHub: Feedback and contributions are welcome. #GIS #Geospatial #OpenSource #MapLibre #DuckDB #WebGIS #GeoLibre

Qiusheng Wu

42,457 次观看 • 3 个月前

Beautiful new raster data layers are now available on Google Earth’s intuitive, no-code canvas. 🗺️👉 With the analytical power of Google Earth Engine directly integrated into Google Earth, geospatial analysis is as easy as point and click. Rolling out over the coming days, you will have access to ten new raster layers from Earth Engine's iconic data catalog, including: • Slope • Aspect • Land cover • and more It's never been easier to quickly combine raster data, vector data, imagery, and your own data to save time and make better decisions. Explore these new data layers, now.

Beautiful new raster data layers are now available on Google Earth’s intuitive, no-code canvas. 🗺️👉 With the analytical power of Google Earth Engine directly integrated into Google Earth, geospatial analysis is as easy as point and click. Rolling out over the coming days, you will have access to ten new raster layers from Earth Engine's iconic data catalog, including: • Slope • Aspect • Land cover • and more It's never been easier to quickly combine raster data, vector data, imagery, and your own data to save time and make better decisions. Explore these new data layers, now.

Google Earth

15,693 次观看 • 5 个月前

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

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

Qiusheng Wu

52,988 次观看 • 8 个月前

Excited to share that maplibre-gl-lidar v0.6.0 is now available! This release adds support for the Entwine Point Tile (EPT) format ( making it possible to stream and visualize billions of LiDAR points directly in the browser with ease and performance. The demo below showcases the visualization of an incredible 184 billion LiDAR points! Live Demo Viewer: GitHub Repository: Full Video Tutorial: Huge thanks to U.S. Geological Survey (USGS) and the 3DEP Program ( for acquiring nationwide LiDAR data, Hobu, Inc. for processing the point clouds into Entwine format ( and the Amazon Web Services (AWS) Open Data Program ( for hosting this massive and continually growing collection of over 350 TB of EPT data with over 75 trillion points. #lidar #opensource #opendata #geospatial #maplibre #deckgl

Excited to share that maplibre-gl-lidar v0.6.0 is now available! This release adds support for the Entwine Point Tile (EPT) format ( making it possible to stream and visualize billions of LiDAR points directly in the browser with ease and performance. The demo below showcases the visualization of an incredible 184 billion LiDAR points! Live Demo Viewer: GitHub Repository: Full Video Tutorial: Huge thanks to U.S. Geological Survey (USGS) and the 3DEP Program ( for acquiring nationwide LiDAR data, Hobu, Inc. for processing the point clouds into Entwine format ( and the Amazon Web Services (AWS) Open Data Program ( for hosting this massive and continually growing collection of over 350 TB of EPT data with over 75 trillion points. #lidar #opensource #opendata #geospatial #maplibre #deckgl

Qiusheng Wu

13,095 次观看 • 8 个月前

I am very excited to release GeoLibre v1.0 🌍 GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. In this video, I walk through GeoLibre 1.0 step by step: how to install and run it, load vector and raster data, stream gigabyte-scale cloud-native datasets without downloading them, edit attributes and geometry, work with PMTiles, 3D tiles, LiDAR point clouds, and DuckDB, and share your projects as static links. GeoLibre is built on MapLibre GL JS, React + TypeScript, Tauri (Rust), DuckDB, and Try it: GitHub: Full video tutorial: If you have feature requests or run into bugs, leave a comment or open an issue on GitHub. And if you find GeoLibre useful, please give it a star. #GIS #OpenSource #Geospatial #MapLibre #Python #DataVisualization #GeoLibre

I am very excited to release GeoLibre v1.0 🌍 GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. In this video, I walk through GeoLibre 1.0 step by step: how to install and run it, load vector and raster data, stream gigabyte-scale cloud-native datasets without downloading them, edit attributes and geometry, work with PMTiles, 3D tiles, LiDAR point clouds, and DuckDB, and share your projects as static links. GeoLibre is built on MapLibre GL JS, React + TypeScript, Tauri (Rust), DuckDB, and Try it: GitHub: Full video tutorial: If you have feature requests or run into bugs, leave a comment or open an issue on GitHub. And if you find GeoLibre useful, please give it a star. #GIS #OpenSource #Geospatial #MapLibre #Python #DataVisualization #GeoLibre

Qiusheng Wu

39,593 次观看 • 3 个月前

🚀 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

🚀 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

12,258 次观看 • 1 年前

GeoLibre + GeoLens: A Modern GIS Stack for Self-Hosting Geospatial Data In this tutorial, I introduce a modern, fully open-source GIS stack for self-hosting, managing, visualizing, editing, and analyzing geospatial data using GeoLens and GeoLibre. GeoLens provides an easy-to-deploy platform for hosting vector and raster datasets, while GeoLibre connects directly to GeoLens for interactive visualization and geospatial analysis. Together, they provide a powerful open-source workflow for organizations, researchers, and individuals who want to manage their own geospatial infrastructure. Everything is built around open-source software and open geospatial standards. GeoLibre: GeoLibre Web: GeoLibre GitHub: GeoLens: #geospatial #opensource #MapLibre #GeoLibre #GeoLens

GeoLibre + GeoLens: A Modern GIS Stack for Self-Hosting Geospatial Data In this tutorial, I introduce a modern, fully open-source GIS stack for self-hosting, managing, visualizing, editing, and analyzing geospatial data using GeoLens and GeoLibre. GeoLens provides an easy-to-deploy platform for hosting vector and raster datasets, while GeoLibre connects directly to GeoLens for interactive visualization and geospatial analysis. Together, they provide a powerful open-source workflow for organizations, researchers, and individuals who want to manage their own geospatial infrastructure. Everything is built around open-source software and open geospatial standards. GeoLibre: GeoLibre Web: GeoLibre GitHub: GeoLens: #geospatial #opensource #MapLibre #GeoLibre #GeoLens

Qiusheng Wu

20,236 次观看 • 1 个月前

Introducing DJI Zenmuse L2, an integrated LiDAR system designed for precise and accurate 3D data collection. The Zenmuse L2 integrates a 4/3 CMOS RGB mapping camera, a Livox LiDAR module, and an IMU, all on a 3-axis stabilized gimbal. Learn more 👉

Introducing DJI Zenmuse L2, an integrated LiDAR system designed for precise and accurate 3D data collection. The Zenmuse L2 integrates a 4/3 CMOS RGB mapping camera, a Livox LiDAR module, and an IMU, all on a 3-axis stabilized gimbal. Learn more 👉

DJI Enterprise

25,163 次观看 • 2 年前

GeoLibre v2.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release is about reaching more data and moving through it: new browsers for STAC, NASA Earthdata, and Hugging Face, a flight simulator, a Time Slider that animates tiled data and data cubes, and a live API for pages that embed the map. What's new in v2.4.0 - STAC catalogs browser: discover public catalogs from STAC Index, connect to static catalogs and STAC APIs, search a collection's items, and add any visualizable asset to the map. No more copying COG URLs by hand. - Earthdata GIS browser: search NASA's Earthdata GIS portal and add its imagery, map, and feature services, and its published web maps, as first-class layers. - Hugging Face on the map: search the Hub, walk a dataset repo's folders, and add its vector and raster files. You can create a dataset repo and upload layers to it too. - Flight Simulator: steer a continuous free-flight camera over terrain and 3D layers from the keyboard, instead of declaring a destination and watching a scripted flight. - Time Slider for tiled data and data cubes: bind vector tiles, PMTiles, and MBTiles to the timeline and animate them over their full extent, and let a Zarr store's own time dimension join the shared timeline. - Zarr gets a real Add Data path: open a remote store or a folder on disk, and pick variables and dimensions by their actual coordinate values rather than raw indices. - Live embed API: a versioned postMessage protocol so a host page can load a project, move the camera, highlight features, and open a tool at runtime, with events coming back out. - OGC API - Features: add collections as vector layers from whatever URL you have in hand, whether that is a landing page, /collections, or a full items URL. - H3 everywhere: a new hexagonal grid plugin that renders and inspects H3 cells and exports them as GeoJSON or CSV, plus typing an H3 index into the search box to fly straight to that cell. - Jupyter from outside the app: attach VS Code's Jupyter extension or jupyter console to the desktop app's server and your notebook cells drive the map. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #GeoLibre

GeoLibre v2.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release is about reaching more data and moving through it: new browsers for STAC, NASA Earthdata, and Hugging Face, a flight simulator, a Time Slider that animates tiled data and data cubes, and a live API for pages that embed the map. What's new in v2.4.0 - STAC catalogs browser: discover public catalogs from STAC Index, connect to static catalogs and STAC APIs, search a collection's items, and add any visualizable asset to the map. No more copying COG URLs by hand. - Earthdata GIS browser: search NASA's Earthdata GIS portal and add its imagery, map, and feature services, and its published web maps, as first-class layers. - Hugging Face on the map: search the Hub, walk a dataset repo's folders, and add its vector and raster files. You can create a dataset repo and upload layers to it too. - Flight Simulator: steer a continuous free-flight camera over terrain and 3D layers from the keyboard, instead of declaring a destination and watching a scripted flight. - Time Slider for tiled data and data cubes: bind vector tiles, PMTiles, and MBTiles to the timeline and animate them over their full extent, and let a Zarr store's own time dimension join the shared timeline. - Zarr gets a real Add Data path: open a remote store or a folder on disk, and pick variables and dimensions by their actual coordinate values rather than raw indices. - Live embed API: a versioned postMessage protocol so a host page can load a project, move the camera, highlight features, and open a tool at runtime, with events coming back out. - OGC API - Features: add collections as vector layers from whatever URL you have in hand, whether that is a landing page, /collections, or a full items URL. - H3 everywhere: a new hexagonal grid plugin that renders and inspects H3 cells and exports them as GeoJSON or CSV, plus typing an H3 index into the search box to fly straight to that cell. - Jupyter from outside the app: attach VS Code's Jupyter extension or jupyter console to the desktop app's server and your notebook cells drive the map. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #GeoLibre

Qiusheng Wu

14,268 次观看 • 1 个月前

🚀 GeoLibre just passed 5,000 stars on GitHub, in only two months! GeoLibre went public on May 27, and the community has already pushed it past 5,100 stars and 500+ forks. Thank you to everyone who starred, forked, filed issues, opened pull requests, and shared the project. For those just discovering it: GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. Key features of GeoLibre: - Runs anywhere: the same app ships as a native desktop app, a browser web app, a native Android app, and a Jupyter widget. - Local and private by default: load and analyze GeoJSON, GeoParquet, GeoPackage, Shapefile, COG, LiDAR, 3D Tiles, and more, right in the browser. - Powered by open source: built on MapLibre GL JS, DuckDB-WASM Spatial, Tauri, React, and TypeScript. - Spatial SQL in the browser: query your data with DuckDB Spatial, PostGIS via PGlite, and Apache Sedona. - Extensible: a growing plugin system for cloud data, federal web services, and custom tools. - Supports 12 planetary basemaps: Earth, Mars, the Moon, Mercury, Venus, and more. Two months in, we have already shipped 25 releases, the latest being v2.4.0. There is a lot more to come, and the best way to shape it is to jump in. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: If GeoLibre is useful to you, a star on GitHub and a share here go a long way. Thank you for an incredible first two months. #geospatial #opensource #MapLibre #GeoLibre

🚀 GeoLibre just passed 5,000 stars on GitHub, in only two months! GeoLibre went public on May 27, and the community has already pushed it past 5,100 stars and 500+ forks. Thank you to everyone who starred, forked, filed issues, opened pull requests, and shared the project. For those just discovering it: GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. Key features of GeoLibre: - Runs anywhere: the same app ships as a native desktop app, a browser web app, a native Android app, and a Jupyter widget. - Local and private by default: load and analyze GeoJSON, GeoParquet, GeoPackage, Shapefile, COG, LiDAR, 3D Tiles, and more, right in the browser. - Powered by open source: built on MapLibre GL JS, DuckDB-WASM Spatial, Tauri, React, and TypeScript. - Spatial SQL in the browser: query your data with DuckDB Spatial, PostGIS via PGlite, and Apache Sedona. - Extensible: a growing plugin system for cloud data, federal web services, and custom tools. - Supports 12 planetary basemaps: Earth, Mars, the Moon, Mercury, Venus, and more. Two months in, we have already shipped 25 releases, the latest being v2.4.0. There is a lot more to come, and the best way to shape it is to jump in. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: If GeoLibre is useful to you, a star on GitHub and a share here go a long way. Thank you for an incredible first two months. #geospatial #opensource #MapLibre #GeoLibre

Qiusheng Wu

94,705 次观看 • 1 个月前

🚀 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

🚀 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 次观看 • 11 个月前

Visualize 350TB of LiDAR Point Clouds (75 Trillion Points in Your Browser!) Learn how to access and visualize massive USGS LiDAR datasets, including over 350TB and 75 trillion points, directly in your browser using two powerful open-source formats: - COPC (Cloud Optimized Point Cloud) - Entwine Point Tiles (EPT) for large-area streaming No downloads needed. Stream and explore massive point cloud datasets instantly using cloud-native datasets from AWS Open Data Program and Microsoft Planetary Computer. Try it now: LiDAR Viewer: GitHub: Full video tutorial: #lidar #COPC #USGS #opensource #opendata

Visualize 350TB of LiDAR Point Clouds (75 Trillion Points in Your Browser!) Learn how to access and visualize massive USGS LiDAR datasets, including over 350TB and 75 trillion points, directly in your browser using two powerful open-source formats: - COPC (Cloud Optimized Point Cloud) - Entwine Point Tiles (EPT) for large-area streaming No downloads needed. Stream and explore massive point cloud datasets instantly using cloud-native datasets from AWS Open Data Program and Microsoft Planetary Computer. Try it now: LiDAR Viewer: GitHub: Full video tutorial: #lidar #COPC #USGS #opensource #opendata

Qiusheng Wu

56,243 次观看 • 7 个月前

Why Elon rejected LiDAR for cars while personally spearheading LiDAR development at SpaceX “LiDAR is lame. They’re all going to dump LiDAR. Mark my words” And years later, the industry is starting to realize just how massive that mistake that was Automakers spent years piling expensive sensors onto cars while Elon took the opposite path: Solve vision People acted like Elon hated LiDAR He literally spearheaded the development of SpaceX’s own LiDAR system from scratch Dragon uses LiDAR to navigate and dock with the International Space Station Because in space, LiDAR actually solves a real problem But for cars, once vision is solved, LiDAR becomes expensive, redundant hardware That became Tesla’s entire autonomy architecture: Cameras, Neural networks, Massive real-world training data........AI doing the driving And Cybercab is the purest version of that philosophy. It comes with no LiDAR or giant rooftop sensor array or a hardware circus Just cameras, onboard AI and FSD Elon chose this path more than a decade ago while almost everyone else was throwing more sensors at the problem Now Cybercab is being built with pure vision from day one Solve vision well enough...and autonomy becomes dramatically simpler, cheaper and infinitely easier to scale The industry kept building autonomy around more hardware. Elon built Tesla around better intelligence

Why Elon rejected LiDAR for cars while personally spearheading LiDAR development at SpaceX “LiDAR is lame. They’re all going to dump LiDAR. Mark my words” And years later, the industry is starting to realize just how massive that mistake that was Automakers spent years piling expensive sensors onto cars while Elon took the opposite path: Solve vision People acted like Elon hated LiDAR He literally spearheaded the development of SpaceX’s own LiDAR system from scratch Dragon uses LiDAR to navigate and dock with the International Space Station Because in space, LiDAR actually solves a real problem But for cars, once vision is solved, LiDAR becomes expensive, redundant hardware That became Tesla’s entire autonomy architecture: Cameras, Neural networks, Massive real-world training data........AI doing the driving And Cybercab is the purest version of that philosophy. It comes with no LiDAR or giant rooftop sensor array or a hardware circus Just cameras, onboard AI and FSD Elon chose this path more than a decade ago while almost everyone else was throwing more sensors at the problem Now Cybercab is being built with pure vision from day one Solve vision well enough...and autonomy becomes dramatically simpler, cheaper and infinitely easier to scale The industry kept building autonomy around more hardware. Elon built Tesla around better intelligence

X Freeze

147,955 次观看 • 5 天前

I'm excited to introduce GeoLibre, a lightweight, cloud-native desktop GIS built with MapLibre GL JS and Tauri. GeoLibre is designed for modern geospatial workflows, combining the flexibility of web technologies with the performance of a native desktop application. The current prototype includes a MapLibre-powered map workspace, local vector data import, project persistence, and built-in plugins for basemaps, layer control, swipe, street view, lidar, GeoAgent, and GeoEditor integrations. GeoLibre can run directly in a web browser or as a standalone cross-platform desktop application (<30 MB). GitHub: Website: Live demo: Feedback, ideas, and contributions are welcome. #GeoLibre #GIS #Geospatial #MapLibre #OpenSource #CloudNative

I'm excited to introduce GeoLibre, a lightweight, cloud-native desktop GIS built with MapLibre GL JS and Tauri. GeoLibre is designed for modern geospatial workflows, combining the flexibility of web technologies with the performance of a native desktop application. The current prototype includes a MapLibre-powered map workspace, local vector data import, project persistence, and built-in plugins for basemaps, layer control, swipe, street view, lidar, GeoAgent, and GeoEditor integrations. GeoLibre can run directly in a web browser or as a standalone cross-platform desktop application (<30 MB). GitHub: Website: Live demo: Feedback, ideas, and contributions are welcome. #GeoLibre #GIS #Geospatial #MapLibre #OpenSource #CloudNative

Qiusheng Wu

34,794 次观看 • 3 个月前

GeoLibre v1.10.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings photorealistic city-scale 3D to the map, adds OGC API vector tiles, and makes vector tiles and live editing easier to work with. What's new in v1.10.0 - Google Photorealistic 3D Tiles: drape entire cities in photorealistic 3D right in the map, streamed and rendered through - ArcGIS I3S scene layers: stream Integrated Mesh and 3D Object scene layers and render them in 3D on the shared instance. - OGC API vector tiles: add standards-based OGC API - Tiles vector tile services as a remote source, right alongside XYZ and ArcGIS vector tiles. - Local HDF5 and NetCDF-4 loading: open scientific HDF5 and NetCDF-4 files straight from disk, no cloud references required. - GeoEditor from the current view: pull the vector features currently visible in the map into the GeoEditor and start editing what you are looking at, without re-importing the source data. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre

GeoLibre v1.10.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings photorealistic city-scale 3D to the map, adds OGC API vector tiles, and makes vector tiles and live editing easier to work with. What's new in v1.10.0 - Google Photorealistic 3D Tiles: drape entire cities in photorealistic 3D right in the map, streamed and rendered through - ArcGIS I3S scene layers: stream Integrated Mesh and 3D Object scene layers and render them in 3D on the shared instance. - OGC API vector tiles: add standards-based OGC API - Tiles vector tile services as a remote source, right alongside XYZ and ArcGIS vector tiles. - Local HDF5 and NetCDF-4 loading: open scientific HDF5 and NetCDF-4 files straight from disk, no cloud references required. - GeoEditor from the current view: pull the vector features currently visible in the map into the GeoEditor and start editing what you are looking at, without re-importing the source data. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre

Qiusheng Wu

24,578 次观看 • 2 个月前