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Qiusheng Wu

@giswqs • 50,684 subscribers

Associate Professor @UTKGeography | @Amazon Scholar | Talk about #opensource #geospatial #dataviz #GeoAI

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The GeoAI Python package now supports object detection using pre-trained models from the GeoDeep libarary ( The supported object types include cars, trees, birds, planes, aerovision, utilities, buildings, and roads. Try it out: GitHub: Notebook example: #geospatial #geoai #opensource #python

The GeoAI Python package now supports object detection using pre-trained models from the GeoDeep libarary ( The supported object types include cars, trees, birds, planes, aerovision, utilities, buildings, and roads. Try it out: GitHub: Notebook example: #geospatial #geoai #opensource #python

86,786 次观看

Introducing segment-geospatial, A Python package for segmenting geospatial data with the Segment Anything Model (SAM) GitHub: Docs: Notebook: #segmentanything #deeplearning #geopython

Introducing segment-geospatial, A Python package for segmenting geospatial data with the Segment Anything Model (SAM) GitHub: Docs: Notebook: #segmentanything #deeplearning #geopython

312,324 次观看

segment-geospatial v0.3.0 is out - segmenting satellite imagery with the Segment Anything Model (SAM). GitHub: Docs: Notebook: #segmentanything #deeplearning #geopython #geospatial

segment-geospatial v0.3.0 is out - segmenting satellite imagery with the Segment Anything Model (SAM). GitHub: Docs: Notebook: #segmentanything #deeplearning #geopython #geospatial

207,094 次观看

Google just released the AlphaEarth Foundations with 64 dimensions of satellite embeddings at 10-m resolution at the global scale! It is very interesting! Check it out Blog post: Dataset: Paper: #AI #geospatial #remotesensing #geoai

Google just released the AlphaEarth Foundations with 64 dimensions of satellite embeddings at 10-m resolution at the global scale! It is very interesting! Check it out Blog post: Dataset: Paper: #AI #geospatial #remotesensing #geoai

46,968 次观看

Removing clouds from satellite images with a few clicks using That's fun. Try it out: Image source: #AI #deeplearning #geospatial

Removing clouds from satellite images with a few clicks using That's fun. Try it out: Image source: #AI #deeplearning #geospatial

103,400 次观看

A sneak peek of a new feature in the #GeoAI Python package! 🎉 Now you can detect cars from georeferenced aerial imagery using deep learning—all with just a few lines of code. Stay tuned for an in-depth video tutorial coming soon! 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist:

A sneak peek of a new feature in the #GeoAI Python package! 🎉 Now you can detect cars from georeferenced aerial imagery using deep learning—all with just a few lines of code. Stay tuned for an in-depth video tutorial coming soon! 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist:

45,610 次观看

Cloud and Cloud Shadow Detection From Satellite Imagery with GeoAI and OmniCloudMask In this tutorial, you’ll detect clouds and cloud shadows, compute cloud statistics, clean segmentation outputs, convert raster masks to vectors, smooth boundaries, and generate a cloud-free mask for downstream remote sensing analysis. This workflow works with imagery that includes Red, Green, and NIR bands (e.g., Landsat, Sentinel-2, NAIP, and other commercial data). Notebook: Video tutorial: #geospatial #remotesensing #geoai

Cloud and Cloud Shadow Detection From Satellite Imagery with GeoAI and OmniCloudMask In this tutorial, you’ll detect clouds and cloud shadows, compute cloud statistics, clean segmentation outputs, convert raster masks to vectors, smooth boundaries, and generate a cloud-free mask for downstream remote sensing analysis. This workflow works with imagery that includes Red, Green, and NIR bands (e.g., Landsat, Sentinel-2, NAIP, and other commercial data). Notebook: Video tutorial: #geospatial #remotesensing #geoai

11,389 次观看

Create Stunning Time-Series Satellite Images in Seconds! The GEE Data Catalogs Plugin v0.5 for QGIS is now available and it's a powerful upgrade. You can now create time-series satellite imagery with just a few clicks using a simple interface. The new version also supports direct downloads to your computer, making the workflow faster and more efficient. Key Features: - Access over 80 petabytes of satellite and geospatial datasets from Google Earth Engine - Generate animated time-series imagery effortlessly - Export results directly from QGIS to your local machine Useful Links: QGIS Plugin Page: GitHub Repository: Video Tutorial: #QGIS #geospatial #EarthEngine #Python #datascience #satellite

Create Stunning Time-Series Satellite Images in Seconds! The GEE Data Catalogs Plugin v0.5 for QGIS is now available and it's a powerful upgrade. You can now create time-series satellite imagery with just a few clicks using a simple interface. The new version also supports direct downloads to your computer, making the workflow faster and more efficient. Key Features: - Access over 80 petabytes of satellite and geospatial datasets from Google Earth Engine - Generate animated time-series imagery effortlessly - Export results directly from QGIS to your local machine Useful Links: QGIS Plugin Page: GitHub Repository: Video Tutorial: #QGIS #geospatial #EarthEngine #Python #datascience #satellite

14,019 次观看

Check out this 📹 step-by-step tutorial on how to visualize and download 🛰️ satellite images of the #Morocco earthquake using the Maxar Open Data on #AWS. Video: Web App: GitHub: Notebook: #moroccoearthquake #geospatial #dataviz #python

Check out this 📹 step-by-step tutorial on how to visualize and download 🛰️ satellite images of the #Morocco earthquake using the Maxar Open Data on #AWS. Video: Web App: GitHub: Notebook: #moroccoearthquake #geospatial #dataviz #python

56,004 次观看

Display a video on an interactive map 🗺️ with #MapLibre and #Leafmap. Check it out: Map: GitHub: Notebook: #geospatial #opensource #dataviz #python

Display a video on an interactive map 🗺️ with #MapLibre and #Leafmap. Check it out: Map: GitHub: Notebook: #geospatial #opensource #dataviz #python

34,823 次观看

Tree extraction from satellite imagery using segment-geospatial v0.5 and the Segment Anything Model (SAM) - by Lucas Prado Osco LinkedIn post: Notebook: #geospatial #segmentanything

Tree extraction from satellite imagery using segment-geospatial v0.5 and the Segment Anything Model (SAM) - by Lucas Prado Osco LinkedIn post: Notebook: #geospatial #segmentanything

40,463 次观看

A sneak peak of segment-geospatial v0.4.0 - Automatically generating object masks for satellite imagery GitHub: Notebook: #geospatial #deeplearning #segmentanything

A sneak peak of segment-geospatial v0.4.0 - Automatically generating object masks for satellite imagery GitHub: Notebook: #geospatial #deeplearning #segmentanything

39,553 次观看

🚀 Exciting news! The #GeoAI Python package now lets you train land cover classification models with just one line of code. Leverage any PyTorch segmentation model from — with hundreds of image encoders & pretrained weights available. 📍 GitHub: 📓 Notebook: #GeoAI #Geospatial #DeepLearning

🚀 Exciting news! The #GeoAI Python package now lets you train land cover classification models with just one line of code. Leverage any PyTorch segmentation model from — with hundreds of image encoders & pretrained weights available. 📍 GitHub: 📓 Notebook: #GeoAI #Geospatial #DeepLearning

15,301 次观看

🚀 MapLibre Tutorial 15: Create stunning 3D maps using OpenFreeMap vector tiles—all with just a few lines of code! Best of all, it’s completely FREE and requires no API key! 🎥 Watch the video: 📚 Explore the playlist: 📝 Check out the notebook: 🌐 Try the demo: To learn more about OpenFreeMap, visit #geospatial #opensource #leafmap #maplibre

🚀 MapLibre Tutorial 15: Create stunning 3D maps using OpenFreeMap vector tiles—all with just a few lines of code! Best of all, it’s completely FREE and requires no API key! 🎥 Watch the video: 📚 Explore the playlist: 📝 Check out the notebook: 🌐 Try the demo: To learn more about OpenFreeMap, visit #geospatial #opensource #leafmap #maplibre

20,690 次观看

🚀 I spent the entire day training image segmentation models from scratch! I've created several pretrained models to detect features like buildings, cars, ships, solar panels, and wetlands. Video tutorials are coming soon! 🤗 Check out the pretrained models on Hugging Face: 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

🚀 I spent the entire day training image segmentation models from scratch! I've created several pretrained models to detect features like buildings, cars, ships, solar panels, and wetlands. Video tutorials are coming soon! 🤗 Check out the pretrained models on Hugging Face: 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

15,071 次观看

🚀 The #GeoAI Python package now supports feature segmentation from high-resolution satellite and aerial imagery using text prompts, such as trees, buildings, etc. It efficiently processes large datasets with automatic tiling and can save results as a single image. Stay tuned for more features coming soon! 📓 Access the notebook: 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

🚀 The #GeoAI Python package now supports feature segmentation from high-resolution satellite and aerial imagery using text prompts, such as trees, buildings, etc. It efficiently processes large datasets with automatic tiling and can save results as a single image. Stay tuned for more features coming soon! 📓 Access the notebook: 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

13,738 次观看

🚀 A sneak peek of a new feature in the #GeoAI Python package! Now you can train an image segmentation model for extracting features (e.g., buildings) from satellite or aerial imagery—all with just a few lines of code. 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

🚀 A sneak peek of a new feature in the #GeoAI Python package! Now you can train an image segmentation model for extracting features (e.g., buildings) from satellite or aerial imagery—all with just a few lines of code. 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearning

11,284 次观看

🌎Visualizing the Agricultural Field Boundary dataset - Fields of The World (FTW, - using #leafmap on PyCafe ☕️ Check it out: Chris Holmes

🌎Visualizing the Agricultural Field Boundary dataset - Fields of The World (FTW, - using #leafmap on PyCafe ☕️ Check it out: Chris Holmes

13,104 次观看

A comprehensive list of 9,043 #NASA Earth science data products available in TSV and JSON formats. Integration into #leafmap for interactive search and visualization is coming soon 🗺️🌎 ➡️ NASAEarthdata #opendata #geospatial #earthobservation

A comprehensive list of 9,043 #NASA Earth science data products available in TSV and JSON formats. Integration into #leafmap for interactive search and visualization is coming soon 🗺️🌎 ➡️ NASAEarthdata #opendata #geospatial #earthobservation

17,392 次观看

📢Visualize hyperspectral data in 3D 🌍 with just a few lines of code using the HyperCoast #Python package . It supports popular datasets like AVIRIS, DESIS, EMIT, PACE, and NEON AOP. GitHub: Notebook: bingqing liu #geospaptial #hyperspectral #nasa #dataviz

📢Visualize hyperspectral data in 3D 🌍 with just a few lines of code using the HyperCoast #Python package . It supports popular datasets like AVIRIS, DESIS, EMIT, PACE, and NEON AOP. GitHub: Notebook: bingqing liu #geospaptial #hyperspectral #nasa #dataviz

13,498 次观看

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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

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

33,192 次观看 • 5 天前

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

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

18,028 次观看 • 4 天前

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

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

60,670 次观看 • 1 个月前

Introducing anymap-ts: a new Python package that makes geospatial visualization easy! Built on MapLibre + TypeScript, anymap-ts brings the same rich mapping experience to both the web and Jupyter Notebook. It supports many popular geospatial formats, including GeoJSON, GeoParquet, FlatGeobuf, PMTiles, COG, Zarr, COPC LiDAR, and Gaussian Splat. It also includes powerful built-in UI components such as a minimap, bookmarks, print tool, view state manager, STAC search, street view, and geometry editor. Try it out: Web demo: Jupyter demo: GitHub: Documentation: Video tutorial: #mapping #maplibre #typescript #jupyter #python

Introducing anymap-ts: a new Python package that makes geospatial visualization easy! Built on MapLibre + TypeScript, anymap-ts brings the same rich mapping experience to both the web and Jupyter Notebook. It supports many popular geospatial formats, including GeoJSON, GeoParquet, FlatGeobuf, PMTiles, COG, Zarr, COPC LiDAR, and Gaussian Splat. It also includes powerful built-in UI components such as a minimap, bookmarks, print tool, view state manager, STAC search, street view, and geometry editor. Try it out: Web demo: Jupyter demo: GitHub: Documentation: Video tutorial: #mapping #maplibre #typescript #jupyter #python

102,022 次观看 • 3 个月前

A sneak peek at the upcoming QGIS OpenGeoAgent plugin! Run geospatial analysis and visualization using natural language, powered by over 480 geoprocessing tools from WhiteboxTools. This brings a new level of accessibility to advanced spatial workflows directly inside QGIS, making it easier to explore, analyze, and visualize data without writing code. Explore the projects: • GeoAgent: • whitebox-python: • WhiteboxTools: Huge credit to Dr. John Lindsay Whitebox Geospatial for developing WhiteboxTools! #QGIS #geospatial #opensource

A sneak peek at the upcoming QGIS OpenGeoAgent plugin! Run geospatial analysis and visualization using natural language, powered by over 480 geoprocessing tools from WhiteboxTools. This brings a new level of accessibility to advanced spatial workflows directly inside QGIS, making it easier to explore, analyze, and visualize data without writing code. Explore the projects: • GeoAgent: • whitebox-python: • WhiteboxTools: Huge credit to Dr. John Lindsay Whitebox Geospatial for developing WhiteboxTools! #QGIS #geospatial #opensource

27,514 次观看 • 1 个月前

🎁 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

84,791 次观看 • 5 个月前

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

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

69,985 次观看 • 4 个月前

Just received a proof copy of my new GeoAI book from Amazon! The printing quality is very good. It is now the #1 best-seller in GIS, Remote Sensing, and Computer Programming Languages. Grab your packpaer copy here: PDF edition available in English, Spanish, Chinese, French, and German: #geospatial #geoai #opensource

Just received a proof copy of my new GeoAI book from Amazon! The printing quality is very good. It is now the #1 best-seller in GIS, Remote Sensing, and Computer Programming Languages. Grab your packpaer copy here: PDF edition available in English, Spanish, Chinese, French, and German: #geospatial #geoai #opensource

35,731 次观看 • 2 个月前

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

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

56,057 次观看 • 4 个月前

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

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

17,122 次观看 • 1 个月前

Excited to share a new open-source project for the web-mapping and LiDAR community: maplibre-gl-lidar 🚀 With maplibre-gl-lidar, you can visualize large-scale LiDAR point clouds (LAS/LAZ, including COPC) directly in the browser using MapLibre GL JS. It supports point-cloud data stored locally or hosted on the web, and comes with an interactive GUI featuring customizable color schemes, classification legends, and point picking. It even works seamlessly inside Jupyter Notebooks. Visualizing tens of millions of LiDAR points has never been this simple or fast, making it easy to build modern, lightweight, and fully interactive web-based LiDAR viewers. Try it out: Live Demo Viewer: GitHub Repository: Full Video Tutorial: #MapLibre #LiDAR #WebGIS #OpenSource #PointCloud #3DMapping

Excited to share a new open-source project for the web-mapping and LiDAR community: maplibre-gl-lidar 🚀 With maplibre-gl-lidar, you can visualize large-scale LiDAR point clouds (LAS/LAZ, including COPC) directly in the browser using MapLibre GL JS. It supports point-cloud data stored locally or hosted on the web, and comes with an interactive GUI featuring customizable color schemes, classification legends, and point picking. It even works seamlessly inside Jupyter Notebooks. Visualizing tens of millions of LiDAR points has never been this simple or fast, making it easy to build modern, lightweight, and fully interactive web-based LiDAR viewers. Try it out: Live Demo Viewer: GitHub Repository: Full Video Tutorial: #MapLibre #LiDAR #WebGIS #OpenSource #PointCloud #3DMapping

52,651 次观看 • 4 个月前

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

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

43,111 次观看 • 4 个月前

Agricultural Field Boundary Delineation (Instance Segmentation) with GeoAI Learn an end-to-end GeoAI workflow for agricultural field boundary delineation using instance segmentation and the Fields of the World dataset ( This workflow can be adapted to detect other object types (not just field boundaries) as long as training data is available. Video tutorial: Notebook: Web app: #geoai #geospatial #deeplearing

Agricultural Field Boundary Delineation (Instance Segmentation) with GeoAI Learn an end-to-end GeoAI workflow for agricultural field boundary delineation using instance segmentation and the Fields of the World dataset ( This workflow can be adapted to detect other object types (not just field boundaries) as long as training data is available. Video tutorial: Notebook: Web app: #geoai #geospatial #deeplearing

19,898 次观看 • 2 个月前

Introducing a new #Python package called mapwidget - creating interactive 3D maps in a Jupyter environment using popular JavaScript libraries, such as #CesiumJS, #Mapbox, #MapLibre, #Leaflet, and #OpenLayers GitHub: #geospatial #gischat #anywidget

Introducing a new #Python package called mapwidget - creating interactive 3D maps in a Jupyter environment using popular JavaScript libraries, such as #CesiumJS, #Mapbox, #MapLibre, #Leaflet, and #OpenLayers GitHub: #geospatial #gischat #anywidget

154,809 次观看 • 3 年前

🚀 SamGeo v0.14.0 is here! This release brings interactive segmentation for remote sensing imagery powered by Meta’s SAM3. 🟦 Draw a bounding box to automatically detect all similar objects across the image. 📝 Or just type a text prompt to segment objects instantly. No complex setup. No manual labeling. Just intuitive, AI-driven geospatial analysis. 🔗 GitHub: 🧪 Notebook: #SAM3 #GeoAI #Geospatial #OpenSource #Python #DataScience

🚀 SamGeo v0.14.0 is here! This release brings interactive segmentation for remote sensing imagery powered by Meta’s SAM3. 🟦 Draw a bounding box to automatically detect all similar objects across the image. 📝 Or just type a text prompt to segment objects instantly. No complex setup. No manual labeling. Just intuitive, AI-driven geospatial analysis. 🔗 GitHub: 🧪 Notebook: #SAM3 #GeoAI #Geospatial #OpenSource #Python #DataScience

33,366 次观看 • 6 个月前

🚀 A brand-new feature is coming to the SAMGeo Python package: interactive remote-sensing image segmentation with text prompts powered by SAM3. This update makes geospatial segmentation even more intuitive: just describe what you want to detect, and let GeoAI do the rest. ✨ GitHub PR: #GeoAI #SAM3 #OpenSource #Python

32,867 次观看 • 6 个月前

🚀 I am very excited to release the SamGeo QGIS plugin for geospatial image segmentation, powered by Meta’s Segment Anything Model (SAM 3) In this full tutorial, I’ll walk you through how to install, configure, and start segmenting satellite imagery in QGIS without writing a single line of code! 👉 Download the plugin here: 💻 Full video tutorial: #QGIS #SegmentAnything #SAM #GeoAI #RemoteSensing

🚀 I am very excited to release the SamGeo QGIS plugin for geospatial image segmentation, powered by Meta’s Segment Anything Model (SAM 3) In this full tutorial, I’ll walk you through how to install, configure, and start segmenting satellite imagery in QGIS without writing a single line of code! 👉 Download the plugin here: 💻 Full video tutorial: #QGIS #SegmentAnything #SAM #GeoAI #RemoteSensing

28,652 次观看 • 5 个月前

🚀 Excited to share a new tutorial on how to detect buildings 🏘️using the Segment Anything Model 2 (SAM 2) with Segment-Geospatial! You can choose interactive segmentation or utilize a GeoJSON file with building centroids or bounding boxes to do automated building detection. 📹 Check out the video tutorial: 📓 Explore the notebook: #Geospatial #OpenSource #AI #MachineLearning

🚀 Excited to share a new tutorial on how to detect buildings 🏘️using the Segment Anything Model 2 (SAM 2) with Segment-Geospatial! You can choose interactive segmentation or utilize a GeoJSON file with building centroids or bounding boxes to do automated building detection. 📹 Check out the video tutorial: 📓 Explore the notebook: #Geospatial #OpenSource #AI #MachineLearning

71,967 次观看 • 1 年前

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 #OpenData

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 #OpenData

24,434 次观看 • 4 个月前

QGIS GeoAI Plugin v0.5.0 is out! I just released v0.5.0 of the QGIS GeoAI Plugin, bringing interactive image segmentation powered by DeepForest ( to your desktop GIS workflow. With this update, you can load pretrained DeepForest models to segment real-world objects such as trees, birds, livestock, dead trees, and more, directly inside QGIS. Try it out: Documentation: GitHub: #deepforest #geoai #QGIS #geospatial #OpenSource

QGIS GeoAI Plugin v0.5.0 is out! I just released v0.5.0 of the QGIS GeoAI Plugin, bringing interactive image segmentation powered by DeepForest ( to your desktop GIS workflow. With this update, you can load pretrained DeepForest models to segment real-world objects such as trees, birds, livestock, dead trees, and more, directly inside QGIS. Try it out: Documentation: GitHub: #deepforest #geoai #QGIS #geospatial #OpenSource

21,308 次观看 • 4 个月前