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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... AWS Open Data Program. Despite its tremendous value, searching, visualizing, and downloading this data has often been challenging. That is exactly what this new QGIS plugin is designed to solve. With the Maxar Open Data plugin, you can search, filter, preview, and download imagery directly inside QGIS, with no programming required. It is built for analysts, researchers, and practitioners who want fast, seamless access to high-resolution satellite data within their existing GIS workflows. Plugin page: GitHub: Video tutorial: #QGIS #Maxar #SatelliteImagery #DisasterResponse #OpenSource #OpenDatashow more

Qiusheng Wu

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24,695 views • 6 months ago •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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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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Qiusheng Wu

43,285 views • 6 months ago

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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Qiusheng Wu

11,802 views • 1 month ago

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Qiusheng Wu

84,918 views • 6 months ago

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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Qiusheng Wu

62,096 views • 2 months ago

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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Qiusheng Wu

17,352 views • 2 months ago

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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Qiusheng Wu

70,023 views • 6 months ago

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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DeepLearning.AI

20,833 views • 1 year ago

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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Qiusheng Wu

13,071 views • 6 months ago

⚡️ 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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Simon Grimm

16,351 views • 1 year ago

🎯 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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Qiusheng Wu

10,346 views • 9 months ago

We just launched a major new Data Engineering Professional Certificate on Coursera! Data underlies all modern AI systems, and engineers who know how to build systems to store and serve it are in high demand. If you're interested in learning this skill, please check out this 4-course sequence, which is designed to make you job-ready to be a Data Engineer. This is a new specialization taught by Joe Reis, the co-author of the best-selling book “Fundamentals of Data Engineering," in collaboration with AWS. (Disclosure, I serve on Amazon's board.) For many AI systems, data engineering is 80% of the work, and modeling is 20%. But people’s attention on these two topics is often flipped. This makes the job of the data engineer particularly important. In this professional certificate, you'll learn foundational data engineering skills while implementing modern data architectures using open-source tools: - Learn the key steps of the data lifecycle, to generate, ingest, store, transform, and serve data. - Learn to align with organizational goals to design the data pipeline right for your business' needs. - Understand how to make necessary trade-offs between speed, scalability, security, and cost. Joe has distilled into this specialization decades of experience helping startups and large companies with data infrastructure. He is also joined by 17 other industry leaders in the data field, who will help you learn in-demand skills for the growing field of data engineering. Please sign up here:

We just launched a major new Data Engineering Professional Certificate on Coursera! Data underlies all modern AI systems, and engineers who know how to build systems to store and serve it are in high demand. If you're interested in learning this skill, please check out this 4-course sequence, which is designed to make you job-ready to be a Data Engineer. This is a new specialization taught by Joe Reis, the co-author of the best-selling book “Fundamentals of Data Engineering," in collaboration with AWS. (Disclosure, I serve on Amazon's board.) For many AI systems, data engineering is 80% of the work, and modeling is 20%. But people’s attention on these two topics is often flipped. This makes the job of the data engineer particularly important. In this professional certificate, you'll learn foundational data engineering skills while implementing modern data architectures using open-source tools: - Learn the key steps of the data lifecycle, to generate, ingest, store, transform, and serve data. - Learn to align with organizational goals to design the data pipeline right for your business' needs. - Understand how to make necessary trade-offs between speed, scalability, security, and cost. Joe has distilled into this specialization decades of experience helping startups and large companies with data infrastructure. He is also joined by 17 other industry leaders in the data field, who will help you learn in-demand skills for the growing field of data engineering. Please sign up here:

Andrew Ng

118,937 views • 1 year ago

We can only trust X 🚨 META/ Facebook planning to build data centers in China, store their data in China, and then GIVE THE CHINESE GOVERNMENT ACCESS to the data “In this document, Facebook is talking about making Chinese user data available to the Chinese government because they're going to store that data in China. Is that correct?” “Correct” “When you store that data in China, Americans who exchange messages or other information with Chinese Facebook users, that would mean the Chinese government could get access to the American data as well, is that correct? “Through the POP servers? Potentially.” “And Facebook was willing to take that risk?” “Yes. There was a lot of discussion about this and ultimately yes.” “I mean, this is, this is extraordinary. This is exactly contrary to what Facebook has represented for years here. They're willing to build data centers, store data in China. They are willing explicitly to give the Chinese government access to it”

We can only trust X 🚨 META/ Facebook planning to build data centers in China, store their data in China, and then GIVE THE CHINESE GOVERNMENT ACCESS to the data “In this document, Facebook is talking about making Chinese user data available to the Chinese government because they're going to store that data in China. Is that correct?” “Correct” “When you store that data in China, Americans who exchange messages or other information with Chinese Facebook users, that would mean the Chinese government could get access to the American data as well, is that correct? “Through the POP servers? Potentially.” “And Facebook was willing to take that risk?” “Yes. There was a lot of discussion about this and ultimately yes.” “I mean, this is, this is extraordinary. This is exactly contrary to what Facebook has represented for years here. They're willing to build data centers, store data in China. They are willing explicitly to give the Chinese government access to it”

Wall Street Apes

80,854 views • 1 year ago

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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Andrew Ng

84,686 views • 1 year ago

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

42,356 views • 1 month ago

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!

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

51,650 views • 2 months ago

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.

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

20,744 views • 1 month ago

Dr. John Campbell exposed that the government is HIDING data showing that Covid-19 shots are clearly associated with excess deaths. RUSSELL BRAND: “What … will be the single piece of data that provides a tipping point where the majority of people will say … we were lied to about this?” CAMPBELL: “The obvious one is correlating vaccination status against excess deaths.” “Now, the British government were given the opportunity to release this [data] just last month.” “They actually … said they weren’t going to release it.” “What we don’t know [in the data] is who had the vaccine and did they die?” “The government has REFUSED to release that data.” “We believe that that data has been released to the pharmaceutical industry.” “Bits of data have appeared … in Japan, for example, and also in Italy.” “It doesn’t look good.” “It looks like excess deaths were associated with vaccination.” Russell Brand John Campbell

Children’s Health Defense

25,186 views • 5 months ago

AI is transforming the way businesses operate 🤖. It helps companies work faster, cut costs, and make smarter decisions. From automating repetitive tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI can’t function without data 📊. Massive amounts of high-quality data are required to train models and make them effective. Right now, most of this data is controlled by a few centralized giants 🔒, making it expensive, siloed, and out of reach for smaller businesses and innovators. This is where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By combining decentralized storage with AI infrastructure powered by blockchain, OORT makes data open, secure, and accessible to everyone. It’s building a foundation where businesses of all sizes can tap into AI’s full potential and compete in the AI-driven economy 🚀

AI is transforming the way businesses operate 🤖. It helps companies work faster, cut costs, and make smarter decisions. From automating repetitive tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI can’t function without data 📊. Massive amounts of high-quality data are required to train models and make them effective. Right now, most of this data is controlled by a few centralized giants 🔒, making it expensive, siloed, and out of reach for smaller businesses and innovators. This is where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By combining decentralized storage with AI infrastructure powered by blockchain, OORT makes data open, secure, and accessible to everyone. It’s building a foundation where businesses of all sizes can tap into AI’s full potential and compete in the AI-driven economy 🚀

Sky Wee

58,239 views • 8 months ago

Introducing the Future of AI-Powered Sports Data with $FXI.⚡️ We’re not just talking about innovation, we’re building it. 🚀 From #AI-driven data capture to on-chain validation and data monetization, the FX1 ecosystem is rewriting the rules of the sports and data economy. Our platform empowers leagues, teams, and creators to unlock the full potential of their data with cutting-edge AI solutions. 🧠 Why FX1? ➡️ AI-Powered Precision: Transform raw sports data into actionable insights. ➡️ Data Validation on Chain: Building trust in the data economy through blockchain. ➡️ AI-Powered Revenue Streams: Use sports data to drive predictive analytics, odds modeling, and other high-value solutions that unlock new ways to monetize. FX1 is leading the charge in AI innovation, creating a seamless bridge between sports, blockchain, and the data economy. This isn’t just evolution - it’s a revolution. 💡 The future of sports is here. And it’s powered by AI. 🤖 Watch the full video and see how we’re turning vision into reality. 👇

Introducing the Future of AI-Powered Sports Data with $FXI.⚡️ We’re not just talking about innovation, we’re building it. 🚀 From #AI-driven data capture to on-chain validation and data monetization, the FX1 ecosystem is rewriting the rules of the sports and data economy. Our platform empowers leagues, teams, and creators to unlock the full potential of their data with cutting-edge AI solutions. 🧠 Why FX1? ➡️ AI-Powered Precision: Transform raw sports data into actionable insights. ➡️ Data Validation on Chain: Building trust in the data economy through blockchain. ➡️ AI-Powered Revenue Streams: Use sports data to drive predictive analytics, odds modeling, and other high-value solutions that unlock new ways to monetize. FX1 is leading the charge in AI innovation, creating a seamless bridge between sports, blockchain, and the data economy. This isn’t just evolution - it’s a revolution. 💡 The future of sports is here. And it’s powered by AI. 🤖 Watch the full video and see how we’re turning vision into reality. 👇

FX1

23,913 views • 1 year ago