Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

How to Create a Spinning Globe 🌍 with Your Own Data Layers (No Coding Required) Learn how to create a spinning 3D globe map without writing any code using a simple web-based tool. In this step-by-step geospatial tutorial, you'll see how to build an interactive spinning globe, overlay raster...

giswqs's profile picture

Qiusheng Wu

53,795 subscribers

12,745 görüntüleme • 7 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

5 Yorum

🅅🄸🄽🄰🅈🄰🄺 profil fotoğrafı
🅅🄸🄽🄰🅈🄰🄺7 ay önce

yah, i’m gonna try this on the homepage -

Rajant profil fotoğrafı
Rajant7 ay önce

This is so cool. Thanks for sharing this so openly.

Aditya Narayan Nayak ☁️🚢☸️ profil fotoğrafı
Aditya Narayan Nayak ☁️🚢☸️7 ay önce

Ur so cool Professor. Every time there is a solution to a problem

Haris Firdaus profil fotoğrafı
Haris Firdaus7 ay önce

Very cool.

MOHAMED ALKAMEL profil fotoğrafı
MOHAMED ALKAMEL7 ay önce

How I add chart By AOI

Benzer Videolar

🚀 Exciting news! The GeoAI Python package just got a major upgrade. It now supports interactive geospatial data visualization powered by AI Agents. 🌍✨ GitHub: Full tutorial: 🌍 In this tutorial, you’ll learn how to build interactive maps powered by AI agents that respond to natural language queries. Watch how you can fly to any city, add raster or vector layers, visualize 3D buildings, and explore geospatial data—all without writing code. Perfect for developers, researchers, and anyone curious about AI, GIS, and interactive mapping. #geospatial #mapping #python #GeoAI #AI
1:16

🚀 Exciting news! The GeoAI Python package just got a major upgrade. It now supports interactive geospatial data visualization powered by AI Agents. 🌍✨ GitHub: Full tutorial: 🌍 In this tutorial, you’ll learn how to build interactive maps powered by AI agents that respond to natural language queries. Watch how you can fly to any city, add raster or vector layers, visualize 3D buildings, and explore geospatial data—all without writing code. Perfect for developers, researchers, and anyone curious about AI, GIS, and interactive mapping. #geospatial #mapping #python #GeoAI #AI

Qiusheng Wu

12,908 görüntüleme • 1 yıl önce

🚀 Leafmap now supports visualizing geospatial data on a stunning 3D globe with MapLibre 🌍. Create stunning 3D maps with just a few lines of Python code! 🎥 Check out the full tutorial: 📓 Dive into the notebook: 🌐 Try the demo: #Geospatial #3DMapping #Python
0:58

🚀 Leafmap now supports visualizing geospatial data on a stunning 3D globe with MapLibre 🌍. Create stunning 3D maps with just a few lines of Python code! 🎥 Check out the full tutorial: 📓 Dive into the notebook: 🌐 Try the demo: #Geospatial #3DMapping #Python

Qiusheng Wu

10,980 görüntüleme • 1 yıl önce

📢 Exciting news! Leafmap now supports creating 3D 🌎 maps with Mapbox! This demo showcases how to visualize the ESA global land cover from #EarthEngine on a 3D globe. Explore the 100 PB+ Earth Engine Data Catalog and display any geospatial datasets in 3D 🚀 Notebook: #leafmap #geospatial #opensource #python
0:26

📢 Exciting news! Leafmap now supports creating 3D 🌎 maps with Mapbox! This demo showcases how to visualize the ESA global land cover from #EarthEngine on a 3D globe. Explore the 100 PB+ Earth Engine Data Catalog and display any geospatial datasets in 3D 🚀 Notebook: #leafmap #geospatial #opensource #python

Qiusheng Wu

18,749 görüntüleme • 2 yıl önce

🚀 New Tutorial Alert! I just published a step-by-step guide on building an interactive dashboard with Python and Leafmap. 🌍📊 Explore the Jupyter Notebook: Watch the full video tutorial: #leafmap #geospatial #python #dataviz
0:31

🚀 New Tutorial Alert! I just published a step-by-step guide on building an interactive dashboard with Python and Leafmap. 🌍📊 Explore the Jupyter Notebook: Watch the full video tutorial: #leafmap #geospatial #python #dataviz

Qiusheng Wu

16,828 görüntüleme • 1 yıl önce

🚀 Visualize Big Vector Data in Python—FAST! Tired of slow and clunky tools for visualizing big vector dataset in Python? Discover this one-line Python trick using Leafmap + DuckDB to instantly render huge vector datasets—even gigabytes in size—right in your Jupyter notebook. In this video, you'll learn how to: ✅ Visualize millions of vector features with ease ✅ Use Leafmap + DuckDB to serve vector tiles dynamically ✅ Handle GeoParquet, GeoPackage, cloud-hosted data & more ✅ Create fully interactive maps—without crashing your browser! 📌 Watch the full video tutorial on YouTube: 👉 Notebook example: #Visualization #Leafmap #BigData #DuckDB #GeoPython #GIS #OpenSource
0:43

🚀 Visualize Big Vector Data in Python—FAST! Tired of slow and clunky tools for visualizing big vector dataset in Python? Discover this one-line Python trick using Leafmap + DuckDB to instantly render huge vector datasets—even gigabytes in size—right in your Jupyter notebook. In this video, you'll learn how to: ✅ Visualize millions of vector features with ease ✅ Use Leafmap + DuckDB to serve vector tiles dynamically ✅ Handle GeoParquet, GeoPackage, cloud-hosted data & more ✅ Create fully interactive maps—without crashing your browser! 📌 Watch the full video tutorial on YouTube: 👉 Notebook example: #Visualization #Leafmap #BigData #DuckDB #GeoPython #GIS #OpenSource

Qiusheng Wu

13,147 görüntüleme • 1 yıl önce

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
1:48

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

Qiusheng Wu

102,582 görüntüleme • 8 ay önce

Regularize Building Footprints in the Browser with GeoLibre! Learn how to regularize building footprints directly in your web browser using GeoLibre, with no installation required. In this tutorial, you'll see how GeoLibre uses the high performance Rust-based engine to clean up irregular building polygons generated from AI models or manual digitizing. The video demonstrates how to load data, configure regularization parameters, compare before and after results, export the processed data, and access hundreds of additional geospatial analysis tools powered by the GeoLibre-Rust project. Try it out - Video tutorial: - Live demo: - Launch GeoLibre Web: - GeoLibre: - GeoLibre-Rust: - Sample building dataset: #geospatial #opensource #MapLibre #GeoLibre
1:04

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

Qiusheng Wu

17,934 görüntüleme • 3 ay önce

🚀 Visualize Geospatial Data Instantly from the Command Line! You can now interactively explore raster and vector datasets without opening a desktop GIS or Jupyter Notebook. Simply run: pip install "leafmap[viewer]" Then visualize your data with one line: view-raster /path/to/raster.tif view-vector /path/to/vector.geojson Customize your visualization easily: view-raster /path/to/raster.tif --band 1 --colormap coolwarm view-vector /path/to/vector.geojson --style liberty These CLI tools are powered by Leafmap, MapLibre, and LocalTileserver, supporting all geospatial formats compatible with rasterio and geopandas. 👉 Check it out: #geospatial #datascience #mapping #python
0:41

🚀 Visualize Geospatial Data Instantly from the Command Line! You can now interactively explore raster and vector datasets without opening a desktop GIS or Jupyter Notebook. Simply run: pip install "leafmap[viewer]" Then visualize your data with one line: view-raster /path/to/raster.tif view-vector /path/to/vector.geojson Customize your visualization easily: view-raster /path/to/raster.tif --band 1 --colormap coolwarm view-vector /path/to/vector.geojson --style liberty These CLI tools are powered by Leafmap, MapLibre, and LocalTileserver, supporting all geospatial formats compatible with rasterio and geopandas. 👉 Check it out: #geospatial #datascience #mapping #python

Qiusheng Wu

13,504 görüntüleme • 1 yıl önce

🎯 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
1:12

🎯 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

10,380 görüntüleme • 1 yıl önce

📢Exciting new feature in #Leafmap! 🌟 You can now visualize #EarthEngine data on a stunning 3D terrain with #MapLibre 🗺️ Browse the massive 100+ PB Earth Engine Data Catalog and overlay any dataset on an interactive 3D map. 🌍 This demo showcases the ESA global land cover dataset with 3D buildings on top 🌳 GitHub: Notebook: #geospatial #opensource #dataviz #python
0:38

📢Exciting new feature in #Leafmap! 🌟 You can now visualize #EarthEngine data on a stunning 3D terrain with #MapLibre 🗺️ Browse the massive 100+ PB Earth Engine Data Catalog and overlay any dataset on an interactive 3D map. 🌍 This demo showcases the ESA global land cover dataset with 3D buildings on top 🌳 GitHub: Notebook: #geospatial #opensource #dataviz #python

Qiusheng Wu

18,248 görüntüleme • 2 yıl önce

I am very excited to release GeoLibre v1.0 🌍 GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. In this video, I walk through GeoLibre 1.0 step by step: how to install and run it, load vector and raster data, stream gigabyte-scale cloud-native datasets without downloading them, edit attributes and geometry, work with PMTiles, 3D tiles, LiDAR point clouds, and DuckDB, and share your projects as static links. GeoLibre is built on MapLibre GL JS, React + TypeScript, Tauri (Rust), DuckDB, and Try it: GitHub: Full video tutorial: If you have feature requests or run into bugs, leave a comment or open an issue on GitHub. And if you find GeoLibre useful, please give it a star. #GIS #OpenSource #Geospatial #MapLibre #Python #DataVisualization #GeoLibre
1:49

I am very excited to release GeoLibre v1.0 🌍 GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. In this video, I walk through GeoLibre 1.0 step by step: how to install and run it, load vector and raster data, stream gigabyte-scale cloud-native datasets without downloading them, edit attributes and geometry, work with PMTiles, 3D tiles, LiDAR point clouds, and DuckDB, and share your projects as static links. GeoLibre is built on MapLibre GL JS, React + TypeScript, Tauri (Rust), DuckDB, and Try it: GitHub: Full video tutorial: If you have feature requests or run into bugs, leave a comment or open an issue on GitHub. And if you find GeoLibre useful, please give it a star. #GIS #OpenSource #Geospatial #MapLibre #Python #DataVisualization #GeoLibre

Qiusheng Wu

39,768 görüntüleme • 4 ay önce

Image Georeferencing Using GeoLibre in the Browser Learn how to georeference images, scanned maps, and historical maps directly in your web browser using GeoLibre, with no desktop GIS software required. Video tutorial: In this tutorial, I demonstrate how to georeference a campus map by selecting ground control points, choosing a transformation method, evaluating residual errors, and aligning the image with a basemap. You'll also learn how to export the georeferenced result as a GeoTIFF, reload it into GeoLibre, compare it with the basemap, and share the finished map online. GeoLibre is a free and open-source, cloud-native GIS platform that runs in the browser, on desktop and mobile devices, and in Jupyter notebooks. Try it out: - Web App: - GitHub: #opensource #geospatial #GeoLibre
0:22

Image Georeferencing Using GeoLibre in the Browser Learn how to georeference images, scanned maps, and historical maps directly in your web browser using GeoLibre, with no desktop GIS software required. Video tutorial: In this tutorial, I demonstrate how to georeference a campus map by selecting ground control points, choosing a transformation method, evaluating residual errors, and aligning the image with a basemap. You'll also learn how to export the georeferenced result as a GeoTIFF, reload it into GeoLibre, compare it with the basemap, and share the finished map online. GeoLibre is a free and open-source, cloud-native GIS platform that runs in the browser, on desktop and mobile devices, and in Jupyter notebooks. Try it out: - Web App: - GitHub: #opensource #geospatial #GeoLibre

Qiusheng Wu

39,030 görüntüleme • 1 ay önce

Run MATLAB code directly in Jupyter notebooks, JupyterLab, and JupyterHub using the MATLAB kernel. Just open a browser-based MATLAB environment from Jupyter to directly access MATLAB apps and features. Get started with our repo: #Jupyter #Coding
0:30

Run MATLAB code directly in Jupyter notebooks, JupyterLab, and JupyterHub using the MATLAB kernel. Just open a browser-based MATLAB environment from Jupyter to directly access MATLAB apps and features. Get started with our repo: #Jupyter #Coding

MATLAB

13,875 görüntüleme • 2 yıl önce

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
1:21

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

63,819 görüntüleme • 5 ay önce

Want to easily explore and visualize LiDAR point clouds from NOAA Digital Coast? In this step-by-step tutorial, you'll learn how to search, load, and interact with massive coastal LiDAR datasets using a powerful web app built with the maplibre-gl-lidar plugin. No complex setup required. ust open the browser and start exploring. Try the Web App: GitHub Repository: Full video tutorial: NOAA Digital Coast: #lidar #opensource #geosptial #mapping #noaa #opendata
1:05

Want to easily explore and visualize LiDAR point clouds from NOAA Digital Coast? In this step-by-step tutorial, you'll learn how to search, load, and interact with massive coastal LiDAR datasets using a powerful web app built with the maplibre-gl-lidar plugin. No complex setup required. ust open the browser and start exploring. Try the Web App: GitHub Repository: Full video tutorial: NOAA Digital Coast: #lidar #opensource #geosptial #mapping #noaa #opendata

Qiusheng Wu

10,096 görüntüleme • 8 ay önce

🚨 New Tutorial Alert 🚨 Rendering Google Earth Engine & Cloud-Optimized GeoTIFF Tiles in 3D with Google Earth In this tutorial, I demonstrate how to visualize Google Earth Engine tile layers and Cloud Optimized GeoTIFFs (COGs) directly in Google Earth’s 3D environment. This approach lets you bring together high-resolution historical imagery and Street View data into one powerful platform. It’s a simple but effective way to make your geospatial data more accessible—just like sharing a Google Doc link. 🔗 Notebook: ▶️ Video: #geospatial #googleearth #dataviz #earthengine
0:55

🚨 New Tutorial Alert 🚨 Rendering Google Earth Engine & Cloud-Optimized GeoTIFF Tiles in 3D with Google Earth In this tutorial, I demonstrate how to visualize Google Earth Engine tile layers and Cloud Optimized GeoTIFFs (COGs) directly in Google Earth’s 3D environment. This approach lets you bring together high-resolution historical imagery and Street View data into one powerful platform. It’s a simple but effective way to make your geospatial data more accessible—just like sharing a Google Doc link. 🔗 Notebook: ▶️ Video: #geospatial #googleearth #dataviz #earthengine

Qiusheng Wu

16,502 görüntüleme • 1 yıl önce

RustGIS is now on PyPI: pip install rustgis RustGIS is a fast, free and open-source GIS in pure Rust for mapping, analyzing and sharing geospatial data. It runs natively on Windows, macOS and Linux, and in your web browser. Your data stays on your machine unless you send it to an AI model you choose, and every action is a command you can script. The new rustgis Python package brings the RustGIS engine into Python and the full RustGIS app into your Jupyter notebook, with no server to run and nothing else to install. What you can do - The engine in-process: open the same data the app opens, run any of RustGIS's commands and geoprocessing tools, style layers and render maps, all from Python. - GeoPandas in and out: turn any layer into a GeoDataFrame, or add a GeoDataFrame as a layer. - The whole app in a notebook cell: shows the ribbon, panes and map right below your code. - Two-way sync: what Python adds or styles appears in the app, and what you pan, edit or add in the app comes back to Python. - Projects that travel: save a .rgis project from Python and open it as it is in the desktop app or the web app. - Runs where you work: JupyterLab, Jupyter Notebook, VS Code and Google Colab, with prebuilt wheels for Windows, macOS and Linux. Get started in three lines: import rustgis m = m Try it out - Open the getting-started notebook in Colab: - PyPI: - Python guide: - Launch the web app: - GitHub: #GIS #Rust #Python #Jupyter #OpenSource #Geospatial
0:38

RustGIS is now on PyPI: pip install rustgis RustGIS is a fast, free and open-source GIS in pure Rust for mapping, analyzing and sharing geospatial data. It runs natively on Windows, macOS and Linux, and in your web browser. Your data stays on your machine unless you send it to an AI model you choose, and every action is a command you can script. The new rustgis Python package brings the RustGIS engine into Python and the full RustGIS app into your Jupyter notebook, with no server to run and nothing else to install. What you can do - The engine in-process: open the same data the app opens, run any of RustGIS's commands and geoprocessing tools, style layers and render maps, all from Python. - GeoPandas in and out: turn any layer into a GeoDataFrame, or add a GeoDataFrame as a layer. - The whole app in a notebook cell: shows the ribbon, panes and map right below your code. - Two-way sync: what Python adds or styles appears in the app, and what you pan, edit or add in the app comes back to Python. - Projects that travel: save a .rgis project from Python and open it as it is in the desktop app or the web app. - Runs where you work: JupyterLab, Jupyter Notebook, VS Code and Google Colab, with prebuilt wheels for Windows, macOS and Linux. Get started in three lines: import rustgis m = m Try it out - Open the getting-started notebook in Colab: - PyPI: - Python guide: - Launch the web app: - GitHub: #GIS #Rust #Python #Jupyter #OpenSource #Geospatial

Qiusheng Wu

13,730 görüntüleme • 10 gün önce

GeoLibre v1.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings field data collection, image georeferencing, and a full Jupyter notebook experience right next to the map. What's new in v1.4.0 - Jupyter beside the map: Run notebooks alongside your map (JupyterLite in the browser, JupyterLab on the desktop). - Field data collection: Capture point observations in the field with custom, configurable forms. - Georeferencer: Pin a scanned map or image to the map using ground control points. - Spectral Index toolbox: Compute NDVI, NDWI, EVI, and more directly from your rasters. - Better internationalization: Correct rendering of right-to-left basemap labels (Arabic, Hebrew). - More reliable data handling: Render GeoPackages without GDAL's WASM thread crash. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python
1:12

GeoLibre v1.4.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings field data collection, image georeferencing, and a full Jupyter notebook experience right next to the map. What's new in v1.4.0 - Jupyter beside the map: Run notebooks alongside your map (JupyterLite in the browser, JupyterLab on the desktop). - Field data collection: Capture point observations in the field with custom, configurable forms. - Georeferencer: Pin a scanned map or image to the map using ground control points. - Spectral Index toolbox: Compute NDVI, NDWI, EVI, and more directly from your rasters. - Better internationalization: Correct rendering of right-to-left basemap labels (Arabic, Hebrew). - More reliable data handling: Render GeoPackages without GDAL's WASM thread crash. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python

Qiusheng Wu

30,143 görüntüleme • 4 ay önce

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
0:51

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

20,799 görüntüleme • 2 ay önce

GeoLibre v1.5.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release lands 90+ merged pull requests and resolves 90+ issues, adding a dashboard of chart widgets, customizable UI profiles, a saved library of web services, and an in-browser Whitebox raster engine. What's new in v1.5.0 - Dashboard panel: Build a collapsible panel of chart widgets (histogram, scatter, bar, line, box) next to the map. - Customizable UI profiles: Tailor the menus and filter the data sources you see, so the workspace matches your workflow. - Saved service library: Save and reuse your favorite web-service layers (XYZ, WMS, WFS) instead of re-entering URLs. - Whitebox in the browser: Run Whitebox raster tools fully client-side through a WASM runtime, no Python sidecar required. - View menu and viewport history: Step backward and forward through your recent map views from a new View menu. - A more beautiful globe: Add a spinning globe, customize the atmosphere halo and deep-space colors, and reset pitch and bearing with a rotation indicator. - More basemaps: New Protomaps basemaps and support for stacking multiple raster basemaps. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python
1:18

GeoLibre v1.5.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release lands 90+ merged pull requests and resolves 90+ issues, adding a dashboard of chart widgets, customizable UI profiles, a saved library of web services, and an in-browser Whitebox raster engine. What's new in v1.5.0 - Dashboard panel: Build a collapsible panel of chart widgets (histogram, scatter, bar, line, box) next to the map. - Customizable UI profiles: Tailor the menus and filter the data sources you see, so the workspace matches your workflow. - Saved service library: Save and reuse your favorite web-service layers (XYZ, WMS, WFS) instead of re-entering URLs. - Whitebox in the browser: Run Whitebox raster tools fully client-side through a WASM runtime, no Python sidecar required. - View menu and viewport history: Step backward and forward through your recent map views from a new View menu. - A more beautiful globe: Add a spinning globe, customize the atmosphere halo and deep-space colors, and reset pitch and bearing with a rotation indicator. - More basemaps: New Protomaps basemaps and support for stacking multiple raster basemaps. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python

Qiusheng Wu

42,011 görüntüleme • 4 ay önce