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Qiusheng Wu

@giswqs53,625 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

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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

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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

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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

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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

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Downloading Google Open Building dataset for #Morocco. It contains 12.3M buildings. Great for assessing building damage by the earthquake 🫨 Notebook: GeoPackage: (3.11 GB) #geospatial #opendata #MoroccoEarthquake

Downloading Google Open Building dataset for #Morocco. It contains 12.3M buildings. Great for assessing building damage by the earthquake 🫨 Notebook: GeoPackage: (3.11 GB) #geospatial #opendata #MoroccoEarthquake

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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:

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Segment-geospatial v0.4.0 is out. Segmenting satellite imagery and saving results as GeoTIFF and vector formats 👇 GitHub: Notebook: Video: #geospatial #segmentanything #leafmap

Segment-geospatial v0.4.0 is out. Segmenting satellite imagery and saving results as GeoTIFF and vector formats 👇 GitHub: Notebook: Video: #geospatial #segmentanything #leafmap

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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

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Visualizing @Maxar Open Data for the 2023 #Morocco Earthquake GitHub: Web App: #moroccoearthquake #geospatial #opendata #aws

Visualizing @Maxar Open Data for the 2023 #Morocco Earthquake GitHub: Web App: #moroccoearthquake #geospatial #opendata #aws

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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

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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

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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

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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

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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

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🚀 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

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🚀 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

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🚀 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

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🚀 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

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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

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Videos

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GeoLibre v2.3.0 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 a legend that writes itself from your symbology, a new GeoLens catalog browser, and 200+ GeoLibre Rust geoprocessing tools running entirely in the browser. What's new in v2.3.0 - Automatic on-map Legend: the legend builds itself from your visible layers, with class rows for graduated, categorized, rule-based, and expression styling, gradient bars for heatmaps and raster colormaps, and land-cover labels from a Raster Attribute Table. Rename, hide, reorder, or add your own entries, and it saves with the project. - Symbology swatches in the Layers panel: every row shows a dot, line, square, or image glyph in the layer's own color, so a tall layer stack reads at a glance. - GeoLens catalog browser: connect to a self-hosted GeoLens server, search its catalog, and add datasets as vector tiles, GeoJSON, or rendered raster tiles. - Emerging Hot Spot Analysis: build a space-time cube from timestamped points and classify every cell as a new, intensifying, persistent, diminishing, sporadic, oscillating, or historical hot or cold spot, all client side. - Mosaic time series: the Time Slider now steps through MosaicJSON and STAC collections of many COGs per date, on either a GPU or a WASM rendering engine. - Copy and paste layer styles: give a whole set of layers one consistent look without restyling each in turn. - Shareable tool links: deep-link any Whitebox tool with a ?tool= URL that opens the dialog preselected and pre-fills the form, with a Copy link button to build it for you. - Smarter data loading: pick which layers to load from a multi-layer GeoPackage, import CSVs whose coordinates are in any projected CRS, and read a raster's real CRS, pixel size, and extent from the metadata dialog. - Multiple AI profiles: define several provider, model, and credential setups, pick a default, and switch between them from the assistant panel. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #MapLibre #GeoLibre

Qiusheng Wu

293,227 görüntüleme • 1 ay önce

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🚀 GeoLibre just passed 5,000 stars on GitHub, in only two months! GeoLibre went public on May 27, and the community has already pushed it past 5,100 stars and 500+ forks. Thank you to everyone who starred, forked, filed issues, opened pull requests, and shared the project. For those just discovering it: GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. Key features of GeoLibre: - Runs anywhere: the same app ships as a native desktop app, a browser web app, a native Android app, and a Jupyter widget. - Local and private by default: load and analyze GeoJSON, GeoParquet, GeoPackage, Shapefile, COG, LiDAR, 3D Tiles, and more, right in the browser. - Powered by open source: built on MapLibre GL JS, DuckDB-WASM Spatial, Tauri, React, and TypeScript. - Spatial SQL in the browser: query your data with DuckDB Spatial, PostGIS via PGlite, and Apache Sedona. - Extensible: a growing plugin system for cloud data, federal web services, and custom tools. - Supports 12 planetary basemaps: Earth, Mars, the Moon, Mercury, Venus, and more. Two months in, we have already shipped 25 releases, the latest being v2.4.0. There is a lot more to come, and the best way to shape it is to jump in. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: If GeoLibre is useful to you, a star on GitHub and a share here go a long way. Thank you for an incredible first two months. #geospatial #opensource #MapLibre #GeoLibre

Qiusheng Wu

94,422 görüntüleme • 29 gün önce

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GeoLibre v2.2 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. What's new in v2.2.0 - Terrain-aware 3D measurement: the Measure tool now follows the terrain surface for true slope distances and volumes. - Timelapse plugin: animate an image or map series and export it as a shareable GIF or video. - Styled offline basemaps: export PMTiles basemaps that keep their styling, with the offline menus consolidated into one place. - Advanced symbology: a rule-based renderer with per-rule symbol properties, scale-dependent visibility, and nested rules, plus a Style Manager that saves reusable symbol, ramp, and label presets to a personal library. - Diagrams and a symbology pack: draw pie, donut, and bar charts on features, and reach for inverted-polygon masks, arrow and marker lines, geometry generators, and data-driven proportional marker sizing. - Expression everywhere: a shared Expression Builder with a function reference, field list, live preview, and variables. - Print Atlas: generate a map series in the Print Layout, one page per feature or a uniform run of pages along a river or trail, with attribute-table and chart blocks on the page. - Browser-native conversions: COG, FlatGeobuf, Shapefile, and GeoPackage conversions now run in the browser, and Vector to PMTiles. - More formats: VRT raster support, and Esri File Geodatabase (.gdb) layers on the desktop app. - Better recordings: Record Video now captures on-map panels (HTML, legend, colorbar) in the output. - Processing History: a panel that lists every tool you have run, with one-click re-run and Copy as Python to turn a session into a reproducible script. - Live GPS tracking: a moving position marker, a recorded track log, and digitizing new features straight from the GPS feed. - Data quality tools: check validity, fix geometries, and check topology rules to catch and repair bad geometries before they bite. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

Qiusheng Wu

57,034 görüntüleme • 1 ay önce

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GeoLibre v2.7.0 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 is about building analysis instead of typing it: a visual Model Builder for processing workflows, a STAC browser that can add every asset type the app can draw, and a Chrome extension that opens the data on any web page in one click. 97 pull requests merged in 9 days, from 11 contributors besides me, 9 of whom sent their first contribution to GeoLibre in this cycle. Thank you all. What's new in v2.7.0 - Model Builder, a visual canvas for processing: drop tools as nodes, wire one tool's output into the next tool's input, and save the graph as a model that re-runs as a single job. The whole graph is validated before anything executes. - Your AI assistant can build one for you: describe a workflow in plain English, and it authors a validated model and opens it for review before it runs. Any model copies out as a runnable Python script. - Open data in GeoLibre, a Chrome extension now on the Chrome Web Store: it finds the dataset links and map services on the page you are viewing, including services inside embedded maps, and opens the ones you pick together on one map. - The STAC browser adds everything: PMTiles, GeoParquet, and Zarr with a variable picker join the COGs it already loaded, Icechunk repositories are read through their own manifest, and private Planetary Computer assets are signed for you. A static catalog can now be walked as a tree, not only searched. - Select features by drawing on the map: click, rectangle, polygon, freehand, and radius gestures, with Shift and Alt combining into the selection you already have. No more describing features in an expression to pick a handful of them. - Apache Iceberg tables load as vector layers, read in the browser through DuckDB, from a metadata location or a REST catalog, with the row count reported before anything is scanned. - Encoded polylines are a first-class format, with a codec, an interactive preview, processing tools, layer export, and Python support. - New vector tools: merge layers, extract vertices, and generate points along lines and polygon boundaries, all running client-side. - An activity log for shared projects and collaboration sessions, so a project owner can see who opened and edited their work. - Plugins and processing tools are now translatable too, closing the last gap where a non-English interface still read half in English. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #MapLibre #GeoLibre

Qiusheng Wu

14,793 görüntüleme • 10 gün önce

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GeoLibre v2.5.0 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 is about meeting you where your work already lives: open your QGIS and ArcGIS Pro projects directly, talk to your team on the map itself, explore hyperspectral imagery as a 3D cube, work in discrete global grids, and host sharing and live collaboration on your own server. It is also the most community-driven release so far: 121 pull requests and 52 issues closed in 8 days, from 14 contributors, 12 of whom sent their first contribution to GeoLibre in this cycle. Thank you all. What's new in v2.5.0 - Comments on the map: pin a comment to any location or feature, reply in a thread, resolve it when it is handled. - Live collaboration, on your own server: several people can open the same session and see each other's edits, cursors, and comments in real time. - QGIS and ArcGIS Pro project import: open a .qgs, .qgz, .aprx, or .mapx and get the layers. - Discrete global grids: three new DGGS plugins (A5, DGGRID, and DGGAL) render and identify cells over the current view, plus DGGS Generator, Binning, and Compact processing tools. - Hyperspectral data you can actually read: local NetCDF and HDF grids are colormapped in the browser, a cube gets an RGB band combination picked by wavelength. - Spectral profiles from a click: identify a pixel to chart its spectrum against wavelength. - Smart styling on add: every new layer arrives with its own color and geometry-appropriate sizing, and a Style suggestions strip offers one-click renderers. - Autosave, crash recovery, and project history, plus an Elements panel for managing every annotation from a list, a Layer Library for saving a fully configured layer and re-adding it to any later project, and project duplication and templates. - GeoLibre Desktop is on the Mac App Store, and Thai brings the shipped locales to 16 languages besides English, all at 100% coverage. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

Qiusheng Wu

26,788 görüntüleme • 26 gün önce

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GeoLibre v2.0.0 is here! GeoLibre is a free and open-source geospatial platform that runs everywhere: as a native desktop app, in the browser, on Android, and embedded right inside Jupyter notebooks. It brings modern web mapping, cloud-native data formats, and a full processing toolbox together in one place, all built on MapLibre and with no proprietary lock-in. Our first major release adds a true 3D globe, takes mapping beyond Earth to Mars and the Moon, lets styles round-trip with QGIS, and turns loaded vector layers into editable, save-back-to-source data. What's new in v2.0.0 - Planetary mapping: explore Mars, the Moon, and other bodies with the OpenPlanetaryMap basemaps, a per-project ellipsoid, and a planet switcher right in the Layers panel. - CesiumJS 3D globe: switch any map pane to a photorealistic 3D globe that stays camera-synced with your 2D maps and mirrors the layer stack. - True 3D data: render vector layers with Z coordinates, load TIN/MultiPatch 3D shapefiles, and display KML/KMZ Collada (.dae) 3D models. - Symbology interchange: import and export vector styling as OGC SLD, QGIS QML, and Mapbox GL style JSON, so styles round-trip between GeoLibre, QGIS, and the Mapbox/MapLibre ecosystem. - Editable source layers: edit vector layers and write the changes back to their source, including GeoPackage and GeoJSON files and PostGIS database tables. - Weather and sky: a new Weather menu with live cloud and precipitation radar overlays (RainViewer), plus a Google Earth-style sun position simulation for realistic lighting. - Terrain and lighting: double-click the terrain control to set vertical exaggeration, and view any scene in true 3D relief. - Smarter data import: bring in CSV without coordinates as an attribute table, split GPX track points and route points into separate layers, and load macOS-zipped and projected-CRS shapefiles. - Raster in the browser: build normalized-difference indices for any HTTP COG and extract COG/WMS/XYZ bounding-box subsets client-side. - Field Calculator upgrades: compute geometry length and area directly on your features. - Attribute table: multi-select rows with Ctrl and Shift, plus faster navigation. - Google Earth-style extras: "View in Google Maps / Google Earth" actions, camera-reset keyboard shortcuts, and a UTM easting/northing grid mode for the Gridlines overlay. - New plugins: a Mapillary coverage and street-level image viewer, a Historical Imagery panel, and an Elevation Profile tool. - Fully localized: all 13 language catalogs are complete, so the entire UI is translatable. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

Qiusheng Wu

35,991 görüntüleme • 1 ay önce

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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

41,782 görüntüleme • 2 ay önce

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GeoLibre v1.2.0 is here! 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. This release packs in 35+ pull requests of new capabilities. A few highlights: - Run SQL right in the browser. The SQL Workspace pairs DuckDB Spatial with a new in-browser PostGIS engine (PGlite), so you can query layers, local files, and remote URLs without a server. - A smarter attribute table. Add fields, run a field calculator, and explore your data with a built-in Charts panel (histogram, scatter, bar, line, and box plots). - More ways to add data. OpenStreetMap PBF extracts, Cloud-Optimized NetCDF/HDF via kerchunk, georeferenced video overlays, authenticated 3D Tiles, and a Layer builder for custom overlays. - Better visualization. Heatmap rendering, point clustering, and H3 hexagonal grids for spatial binning. - New analysis and routing. A Directions plugin, plus Spatial Join, Select by Value, and Select by Location vector tools. - Print and share. A print layout composer that exports your map to PNG or PDF. - Work faster. A command palette (Ctrl/Cmd + K), global keyboard shortcuts, and undo/redo for layer and style operations. - Built for everyone. New internationalization framework, an accessibility pass with automated axe checks, an installable offline-capable PWA web build, React error boundaries, and Playwright end-to-end tests. Try the live demo: Star it on GitHub: Docs and roadmap: Release notes: #GIS #OpenSource #Geospatial #MapLibre #WebGIS #DuckDB #GeoLibre

Qiusheng Wu

39,959 görüntüleme • 2 ay önce