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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...

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Qiusheng Wu

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52,855 просмотров • 6 месяцев назад •via X (Twitter)

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This Free Tool Unlocks Access to Nationwide US LiDAR Data in Seconds! Discover how this powerful web app lets you search, visualize, and download LiDAR point clouds across the entire United States, in just seconds. Built with the maplibre-gl-lidar plugin, this tool makes nationwide USGS LiDAR data more accessible than ever. Try the Web App: GitHub Repository: Full video tutorial: #lidar #opendata #opensource #usgs
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This Free Tool Unlocks Access to Nationwide US LiDAR Data in Seconds! Discover how this powerful web app lets you search, visualize, and download LiDAR point clouds across the entire United States, in just seconds. Built with the maplibre-gl-lidar plugin, this tool makes nationwide USGS LiDAR data more accessible than ever. Try the Web App: GitHub Repository: Full video tutorial: #lidar #opendata #opensource #usgs

Qiusheng Wu

70,023 просмотров • 5 месяцев назад

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
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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

13,005 просмотров • 5 месяцев назад

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
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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

56,169 просмотров • 5 месяцев назад

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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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

102,240 просмотров • 4 месяцев назад

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
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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

34,475 просмотров • 1 месяц назад

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
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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

18,930 просмотров • 1 месяц назад

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
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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

39,148 просмотров • 1 месяц назад

Free Maxar/Vantor Satellite Imagery for Disaster Response - QGIS and MapLibre Plugins Demo Want to download free high-resolution satellite imagery in QGIS? In this tutorial, I’ll show you how to access and visualize imagery from the Vantor (formerly Maxar) Open Data Program using two powerful plugins, no programming required. The Vantor Open Data Program provides free satellite imagery to support global disaster response and recovery efforts. These plugins make it easy to search, filter, preview, and download imagery directly inside QGIS or in web applications built with MapLibre GL. MapLibre GL Plugin GitHub: Live Demo: QGIS Plugin: GitHub: Plugin Page: Vantor Open Data Program: #QGIS #Maxar #SatelliteImagery #DisasterResponse #OpenSource
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Free Maxar/Vantor Satellite Imagery for Disaster Response - QGIS and MapLibre Plugins Demo Want to download free high-resolution satellite imagery in QGIS? In this tutorial, I’ll show you how to access and visualize imagery from the Vantor (formerly Maxar) Open Data Program using two powerful plugins, no programming required. The Vantor Open Data Program provides free satellite imagery to support global disaster response and recovery efforts. These plugins make it easy to search, filter, preview, and download imagery directly inside QGIS or in web applications built with MapLibre GL. MapLibre GL Plugin GitHub: Live Demo: QGIS Plugin: GitHub: Plugin Page: Vantor Open Data Program: #QGIS #Maxar #SatelliteImagery #DisasterResponse #OpenSource

Qiusheng Wu

11,042 просмотров • 4 месяцев назад

GeoLibre now supports rendering Google Photorealistic 3D Tiles! 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. Try it out with your own Google Maps API key: - Launch GeoLibre web: - GitHub: - Documentation: #GIS #Geospatial #OpenSource #RemoteSensing #MapLibre #GeoLibre
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GeoLibre now supports rendering Google Photorealistic 3D Tiles! 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. Try it out with your own Google Maps API key: - Launch GeoLibre web: - GitHub: - Documentation: #GIS #Geospatial #OpenSource #RemoteSensing #MapLibre #GeoLibre

Qiusheng Wu

18,916 просмотров • 9 дней назад

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
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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

56,713 просмотров • 2 лет назад

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
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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 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

12,678 просмотров • 4 месяцев назад

GeoLibre now supports rendering 3D Tiles! Try it out: GeoLibre is a lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data across desktop, mobile, and web environments. GitHub: Website: #geospaptial #opensource #maplibre #GeoLibre
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GeoLibre now supports rendering 3D Tiles! Try it out: GeoLibre is a lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data across desktop, mobile, and web environments. GitHub: Website: #geospaptial #opensource #maplibre #GeoLibre

Qiusheng Wu

14,460 просмотров • 1 месяц назад

Elon Musk in 2019 on LiDAR: “They’re all going to dump LIDAR; that’s my prediction. I should point out that I don’t actually super hate LIDAR as much as it may sound. But at SpaceX, SpaceX Dragon uses LIDAR to navigate to the space station and dock. Not only that, SpaceX developed its own LIDAR from scratch to do that, and I spearheaded that effort personally. Because in that scenario, LIDAR makes sense. In cars, it’s freaking stupid. Once you solve Vision, it’s worthless.”
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Elon Musk in 2019 on LiDAR: “They’re all going to dump LIDAR; that’s my prediction. I should point out that I don’t actually super hate LIDAR as much as it may sound. But at SpaceX, SpaceX Dragon uses LIDAR to navigate to the space station and dock. Not only that, SpaceX developed its own LIDAR from scratch to do that, and I spearheaded that effort personally. Because in that scenario, LIDAR makes sense. In cars, it’s freaking stupid. Once you solve Vision, it’s worthless.”

Nic Cruz Patane

1,070,115 просмотров • 6 месяцев назад

ELON: ONCE YOU SOLVE VISION, LiDAR IS WORTHLESS “They're all going to dump LiDAR. That's my prediction. Mark my words. I should point out that I don't actually super hate LiDAR as much as it may sound. SpaceX Dragon uses LiDAR to navigate to the space station and dock. Not only that, SpaceX developed its own LiDAR from scratch to do that, and I spearheaded that effort personally because in that scenario LiDAR makes sense. And in cars, it's friggin' stupid. It's expensive and unnecessary. Once you solve vision, it's worthless.” Source: Elon Musk Tesla Autonomy Day, April 2019
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ELON: ONCE YOU SOLVE VISION, LiDAR IS WORTHLESS “They're all going to dump LiDAR. That's my prediction. Mark my words. I should point out that I don't actually super hate LiDAR as much as it may sound. SpaceX Dragon uses LiDAR to navigate to the space station and dock. Not only that, SpaceX developed its own LiDAR from scratch to do that, and I spearheaded that effort personally because in that scenario LiDAR makes sense. And in cars, it's friggin' stupid. It's expensive and unnecessary. Once you solve vision, it's worthless.” Source: Elon Musk Tesla Autonomy Day, April 2019

Mario Nawfal

1,031,011 просмотров • 7 месяцев назад

Elon Musk: LiDAR in cars is friggin stupid. “They're all going to dump LiDAR. That's my prediction. Mark my words. I should point out that I don't actually super hate LiDAR as much as it may sound. SpaceX Dragon uses LiDAR to navigate to the Space Station and dock. SpaceX developed its own LiDAR from scratch to do that and I spearheaded that effort personally. Because in that scenario, LiDAR makes sense! In cars, it's friggin stupid. It's expensive and unnecessary. And as Andrej was saying, once you solve vision, it's worthless. So you have expensive hardware that's worthless on the car.” Autonomy Day, April 22, 2019
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Elon Musk: LiDAR in cars is friggin stupid. “They're all going to dump LiDAR. That's my prediction. Mark my words. I should point out that I don't actually super hate LiDAR as much as it may sound. SpaceX Dragon uses LiDAR to navigate to the Space Station and dock. SpaceX developed its own LiDAR from scratch to do that and I spearheaded that effort personally. Because in that scenario, LiDAR makes sense! In cars, it's friggin stupid. It's expensive and unnecessary. And as Andrej was saying, once you solve vision, it's worthless. So you have expensive hardware that's worthless on the car.” Autonomy Day, April 22, 2019

ELON CLIPS

40,407 просмотров • 1 год назад

GeoLibre v1.4.0 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 brings field data collection, image georeferencing, and a full Jupyter notebook experience right next to the map. What's new in v1.4.0 - Jupyter beside the map: Run notebooks alongside your map (JupyterLite in the browser, JupyterLab on the desktop). - Field data collection: Capture point observations in the field with custom, configurable forms. - Georeferencer: Pin a scanned map or image to the map using ground control points. - Spectral Index toolbox: Compute NDVI, NDWI, EVI, and more directly from your rasters. - Better internationalization: Correct rendering of right-to-left basemap labels (Arabic, Hebrew). - More reliable data handling: Render GeoPackages without GDAL's WASM thread crash. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python
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GeoLibre v1.4.0 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 brings field data collection, image georeferencing, and a full Jupyter notebook experience right next to the map. What's new in v1.4.0 - Jupyter beside the map: Run notebooks alongside your map (JupyterLite in the browser, JupyterLab on the desktop). - Field data collection: Capture point observations in the field with custom, configurable forms. - Georeferencer: Pin a scanned map or image to the map using ground control points. - Spectral Index toolbox: Compute NDVI, NDWI, EVI, and more directly from your rasters. - Better internationalization: Correct rendering of right-to-left basemap labels (Arabic, Hebrew). - More reliable data handling: Render GeoPackages without GDAL's WASM thread crash. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python

Qiusheng Wu

29,300 просмотров • 25 дней назад

Uber CEO on Tesla using Camera Vision over LiDAR: “I think in the near-term it’s going to be very difficult, and Elon Musk would tell me I’m wrong, and never bet against him, but it’s my instinct — in the near-term it’s going to be very difficult to build a camera only product that has superhuman level of safety. Will it be possible? Quite possibly yes. If you can have instrumentations that include cameras and LiDAR ; the cost of Solid State LiDAR is only $400-$500— WHY NOT include LiDAR as well in order to achieve superhuman safety. So, possible? Yeah it will be — I don’t know when, but is possible the better product? I’m not sure. All of your partners right now are using a combination of camera, Radar and LiDAR, and I personally think that’s the right solution— but I could be proven wrong.”
1:30

Uber CEO on Tesla using Camera Vision over LiDAR: “I think in the near-term it’s going to be very difficult, and Elon Musk would tell me I’m wrong, and never bet against him, but it’s my instinct — in the near-term it’s going to be very difficult to build a camera only product that has superhuman level of safety. Will it be possible? Quite possibly yes. If you can have instrumentations that include cameras and LiDAR ; the cost of Solid State LiDAR is only $400-$500— WHY NOT include LiDAR as well in order to achieve superhuman safety. So, possible? Yeah it will be — I don’t know when, but is possible the better product? I’m not sure. All of your partners right now are using a combination of camera, Radar and LiDAR, and I personally think that’s the right solution— but I could be proven wrong.”

Nic Cruz Patane

937,385 просмотров • 10 месяцев назад

Uber CEO in new interview on which approach to autonomy will win: Tesla’s camera-only or Waymo’s multi-sensor. "In the near term, I think it's going to be very difficult—and Elon would tell me I'm wrong—to build a camera-only product that has superhuman levels of safety. At some point will it be possible? Quite possible yes; Solid state LiDAR is $500. Why not include LiDAR as well in order to achieve super human safety. All of our partners are using a combination of camera, radar and LiDAR, and I personally think that's the right solution, but I could be proven wrong."
1:30

Uber CEO in new interview on which approach to autonomy will win: Tesla’s camera-only or Waymo’s multi-sensor. "In the near term, I think it's going to be very difficult—and Elon would tell me I'm wrong—to build a camera-only product that has superhuman levels of safety. At some point will it be possible? Quite possible yes; Solid state LiDAR is $500. Why not include LiDAR as well in order to achieve super human safety. All of our partners are using a combination of camera, radar and LiDAR, and I personally think that's the right solution, but I could be proven wrong."

Sawyer Merritt

459,933 просмотров • 10 месяцев назад

🚀 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

12,238 просмотров • 1 год назад