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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...

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Qiusheng Wu

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70,193 просмотров • 7 месяцев назад •via X (Twitter)

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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
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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

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13,071 просмотров • 7 месяцев назад

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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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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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

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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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12,704 просмотров • 5 месяцев назад

🎁 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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85,182 просмотров • 8 месяцев назад

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🚀 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

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12,238 просмотров • 3 месяцев назад

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Regularize Building Footprints in the Browser with GeoLibre! Learn how to regularize building footprints directly in your web browser using GeoLibre, with no installation required. In this tutorial, you'll see how GeoLibre uses the high performance Rust-based engine to clean up irregular building polygons generated from AI models or manual digitizing. The video demonstrates how to load data, configure regularization parameters, compare before and after results, export the processed data, and access hundreds of additional geospatial analysis tools powered by the GeoLibre-Rust project. Try it out - Video tutorial: - Live demo: - Launch GeoLibre Web: - GeoLibre: - GeoLibre-Rust: - Sample building dataset: #geospatial #opensource #MapLibre #GeoLibre

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206,884 просмотров • 5 месяцев назад

Introducing the NASA Earthdata Plugin for QGIS! NASA’s Earthdata archive hosts over 120 petabytes of satellite imagery and geospatial datasets, but accessing it has often required navigating complex web portals or writing code. This new QGIS plugin changes that. With the NASA Earthdata plugin, you can search, filter, preview, and download NASA datasets directly inside QGIS, no programming needed. It’s designed for anyone who wants fast, seamless access to NASA data within their existing GIS workflow. Plugin page: GitHub: Step-by-step video tutorial: #QGIS #NASA #satelliteimagery #opensource
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Introducing the NASA Earthdata Plugin for QGIS! NASA’s Earthdata archive hosts over 120 petabytes of satellite imagery and geospatial datasets, but accessing it has often required navigating complex web portals or writing code. This new QGIS plugin changes that. With the NASA Earthdata plugin, you can search, filter, preview, and download NASA datasets directly inside QGIS, no programming needed. It’s designed for anyone who wants fast, seamless access to NASA data within their existing GIS workflow. Plugin page: GitHub: Step-by-step video tutorial: #QGIS #NASA #satelliteimagery #opensource

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43,391 просмотров • 7 месяцев назад

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Fly along with NOAA Twin Otter #NOAA48 during a coastal mapping mission over Puerto Rico! Equipped with bathymetric LiDAR technology, NOAA's Twin Otter aircraft can capture aerial imagery of the coastal waters of the United States and its territories. NOAA's Ocean Service uses this data to identify navigational hazards and update the shorelines and coastal features of nautical charts. #FlyNOAA Video Credit: Lt.j.g. Davis Benningfield, NOAA Corps

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