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Introducing the Maxar Open Data Plugin for QGIS 🚀 The Maxar Open Data Program, now called the Vantor Open Data Program, provides free high-resolution satellite imagery to support global disaster response and recovery. To date, it has released around 150,000 images totaling ~14 TB, all freely accessible through the...

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Qiusheng Wu

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25,009 просмотров • 7 месяцев назад •via X (Twitter)

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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
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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

11,194 просмотров • 6 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

Qiusheng Wu

43,391 просмотров • 8 месяцев назад

Working with Planet Tanager Hyperspectral Data (426 Bands) in QGIS with HyperCoast Learn how to access, visualize, and analyze Planet’s Tanager hyperspectral imagery in QGIS using the HyperCoast plugin. In this tutorial, you will explore freely available Planet Tanager open data with over 426 spectral bands and learn how to stream imagery, download HDF5 datasets, inspect spectral signatures, and perform hyperspectral visualization directly inside QGIS. Video Tutorial: HyperCoast: QGIS Plugin: Tanager STAC Repo: Tanager STAC Browser: #opendata #geospatial #hypercoast #QGIS #Tanager #hyperspectral
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Working with Planet Tanager Hyperspectral Data (426 Bands) in QGIS with HyperCoast Learn how to access, visualize, and analyze Planet’s Tanager hyperspectral imagery in QGIS using the HyperCoast plugin. In this tutorial, you will explore freely available Planet Tanager open data with over 426 spectral bands and learn how to stream imagery, download HDF5 datasets, inspect spectral signatures, and perform hyperspectral visualization directly inside QGIS. Video Tutorial: HyperCoast: QGIS Plugin: Tanager STAC Repo: Tanager STAC Browser: #opendata #geospatial #hypercoast #QGIS #Tanager #hyperspectral

Qiusheng Wu

12,238 просмотров • 3 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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🎁 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

Qiusheng Wu

85,182 просмотров • 8 месяцев назад

I am excited to introduce OpenGeoAgent, a powerful open-source multimodal AI agent for automated geospatial analysis and visualization! It supports QGIS, Jupyter notebook, and Python scripting. In this tutorial, you’ll learn how to automate GIS workflows using natural language, generate maps, analyze satellite data, and even run complex hydrological models. You can even interact with the agent using voice commands (no typing needed). Video: GitHub: QGIS Plugin: #geospatial #GeoAgent #OpenSource #AI
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I am excited to introduce OpenGeoAgent, a powerful open-source multimodal AI agent for automated geospatial analysis and visualization! It supports QGIS, Jupyter notebook, and Python scripting. In this tutorial, you’ll learn how to automate GIS workflows using natural language, generate maps, analyze satellite data, and even run complex hydrological models. You can even interact with the agent using voice commands (no typing needed). Video: GitHub: QGIS Plugin: #geospatial #GeoAgent #OpenSource #AI

Qiusheng Wu

62,928 просмотров • 4 месяцев назад

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

17,523 просмотров • 4 месяцев назад

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

70,193 просмотров • 7 месяцев назад

GeoLibre v2.1 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 adds a QGIS-style Browser panel for exploring data from one place, animated route playback with video export, Wikipedia knowledge cards, and Mapillary street-level images. What's new in v2.1.0 - Browser panel (Data Source Manager): explore and add data from one place. Browse map services, connect to PostGIS databases and drill into their schemas and tables, open local files, and save Favorites, all with full keyboard navigation. - Route animation: send a marker along any line layer, follow the track in 3D with camera controls, and export the whole animation as an MP4 video. - In-browser object detection: run ONNX/YOLO models directly in the webview, with no server or Python required. - Map recording: capture the map canvas, or a drawn bounding box, straight to a video file from the browser. - Native-resolution photo viewer: view geotagged photos at full detail right on the map. - Wikipedia knowledge cards: click any place to pull up its Wikipedia summary and info card. - More planetary basemaps: USGS imagery for nine more celestial bodies, plus a new OpenAerialMap imagery search plugin. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre
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GeoLibre v2.1 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 adds a QGIS-style Browser panel for exploring data from one place, animated route playback with video export, Wikipedia knowledge cards, and Mapillary street-level images. What's new in v2.1.0 - Browser panel (Data Source Manager): explore and add data from one place. Browse map services, connect to PostGIS databases and drill into their schemas and tables, open local files, and save Favorites, all with full keyboard navigation. - Route animation: send a marker along any line layer, follow the track in 3D with camera controls, and export the whole animation as an MP4 video. - In-browser object detection: run ONNX/YOLO models directly in the webview, with no server or Python required. - Map recording: capture the map canvas, or a drawn bounding box, straight to a video file from the browser. - Native-resolution photo viewer: view geotagged photos at full detail right on the map. - Wikipedia knowledge cards: click any place to pull up its Wikipedia summary and info card. - More planetary basemaps: USGS imagery for nine more celestial bodies, plus a new OpenAerialMap imagery search plugin. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

Qiusheng Wu

12,139 просмотров • 1 месяц 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

13,071 просмотров • 7 месяцев назад

Enrollment is now open for the Data Engineering Professional Certificate! Data engineers are the architects of modern organizations, ensuring data is reliable, accessible, and ready for analytics and machine learning. This professional certificate is tailored to equip you with the critical skills, through frameworks and hands-on practice, to excel in this role. Taught by industry expert Joe Reis, co-author of the best-selling book "Fundamentals of Data Engineering," along with 17 guest instructors from the data field, you will gain expertise to start and further your career in the high-demand field of data engineering. Key focus areas: 🗂️ Data Engineering Lifecycle: Learn the important stages of building an efficient data pipeline that creates business value. 📥 Data Ingestion: Learn how to efficiently gather data from various sources. 💾 Data Storage: Master the techniques for storing data securely and cost-effectively. 🔄 Data Transformation: Understand how to clean, organize, and prepare data for analysis and machine learning. 🏗️ Data Architecture Design: Build robust architectures that support scalable, efficient data workflows. 📊 Serving Data: Ensure that data is available to stakeholders when and where they need it to drive business decisions. Enroll now!
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Enrollment is now open for the Data Engineering Professional Certificate! Data engineers are the architects of modern organizations, ensuring data is reliable, accessible, and ready for analytics and machine learning. This professional certificate is tailored to equip you with the critical skills, through frameworks and hands-on practice, to excel in this role. Taught by industry expert Joe Reis, co-author of the best-selling book "Fundamentals of Data Engineering," along with 17 guest instructors from the data field, you will gain expertise to start and further your career in the high-demand field of data engineering. Key focus areas: 🗂️ Data Engineering Lifecycle: Learn the important stages of building an efficient data pipeline that creates business value. 📥 Data Ingestion: Learn how to efficiently gather data from various sources. 💾 Data Storage: Master the techniques for storing data securely and cost-effectively. 🔄 Data Transformation: Understand how to clean, organize, and prepare data for analysis and machine learning. 🏗️ Data Architecture Design: Build robust architectures that support scalable, efficient data workflows. 📊 Serving Data: Ensure that data is available to stakeholders when and where they need it to drive business decisions. Enroll now!

DeepLearning.AI

20,833 просмотров • 1 год назад

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
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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 просмотров • 23 дней назад

Mapping the 2026 Nepal Floods with Free High-Resolution Satellite Imagery In this tutorial, I demonstrate how to use GeoLibre to find, visualize, compare, and download open disaster imagery from Vantor, Planet Labs, and OpenAerialMap. You’ll learn how to create an interactive layer-swipe map, explore the terrain in 3D, and examine affected buildings and infrastructure. Video tutorial: Try it out: - Web app: - GitHub: #Nepal #NepalFloods #geospatial #opensource #GeoLibre
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Mapping the 2026 Nepal Floods with Free High-Resolution Satellite Imagery In this tutorial, I demonstrate how to use GeoLibre to find, visualize, compare, and download open disaster imagery from Vantor, Planet Labs, and OpenAerialMap. You’ll learn how to create an interactive layer-swipe map, explore the terrain in 3D, and examine affected buildings and infrastructure. Video tutorial: Try it out: - Web app: - GitHub: #Nepal #NepalFloods #geospatial #opensource #GeoLibre

Qiusheng Wu

63,215 просмотров • 4 дней назад

⚡️ Open SQLite Databases in React Native Debugging SQLite was always challenging until I found out about this library: Drizzle Studio for Expo SQLite 🎉 This is a dev tool plugin you can easily install in your app and open by pressing shift + m in your terminal. The result is the easiest way to see and edit your SQLite data right inside your browser 😍 Did you know about this plugin??
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⚡️ Open SQLite Databases in React Native Debugging SQLite was always challenging until I found out about this library: Drizzle Studio for Expo SQLite 🎉 This is a dev tool plugin you can easily install in your app and open by pressing shift + m in your terminal. The result is the easiest way to see and edit your SQLite data right inside your browser 😍 Did you know about this plugin??

Simon Grimm

16,351 просмотров • 1 год назад

🎯 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 просмотров • 10 месяцев назад

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!
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Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

85,107 просмотров • 1 год назад

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
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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 просмотров • 2 месяцев назад

I'm excited to share the Geo Register Plugin for LichtFeld Studio from the LichtFeld community! This plugin helps bring Gaussian splat scenes into real-world geographic space. It registers a scene to WGS-84 and ECEF coordinates, so you can click any point on the model and get its latitude, longitude and altitude. It supports multiple georeferencing sources, including EXIF GPS data, image position CSVs, RealityScan camera parameters and saved similarity transforms. Once the scene is registered, you can export geo-referenced splat models as LAS, LAZ or 3D Tiles datasets for use in GIS and 3D mapping workflows. Built for anyone working with drone data, photogrammetry, Gaussian splatting, GIS, ArcGIS or CesiumJS. Link in the comment below!
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I'm excited to share the Geo Register Plugin for LichtFeld Studio from the LichtFeld community! This plugin helps bring Gaussian splat scenes into real-world geographic space. It registers a scene to WGS-84 and ECEF coordinates, so you can click any point on the model and get its latitude, longitude and altitude. It supports multiple georeferencing sources, including EXIF GPS data, image position CSVs, RealityScan camera parameters and saved similarity transforms. Once the scene is registered, you can export geo-referenced splat models as LAS, LAZ or 3D Tiles datasets for use in GIS and 3D mapping workflows. Built for anyone working with drone data, photogrammetry, Gaussian splatting, GIS, ArcGIS or CesiumJS. Link in the comment below!

MrNeRF

51,983 просмотров • 3 месяцев назад

Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.
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Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.

Santiago

20,877 просмотров • 3 месяцев назад