Julio Gontor 🌎

PostGIS, QGIS, Developer, Cadastre, Maps and Data . Bitcoin, blockchain, VR/AR lover 🌈

[Arturo Gleason E @arturogleasone]

Desde hace más de 30 años que inicié mi carrera en el estudio del agua en Guadalajara, he visto su deterioro. Aquí dejo parte de mi trabajo de investigación como sustento. Problemas y propuestas.

Artículo científico: https://t.co/CXeF3Q9Ec9

Mi libro: https://t.co/CrGXboqFIX

[José Luis @iChocko]

Le pedí a Claude que scrapeara Datos Viales 2025 (SICT/IMT) y lo publicara como dataset abierto: 32 estados, 4,791 segmentos con geometría, TDPA 2009–2024, GeoJSON y GeoPackage listos para QGIS, Kepler gl y más 🗺️ 🇲🇽🫡

https://t.co/A5YdSkv3II

[Lenin Alevski @Alevsk]

Pude ingestar estos datos en mi plataforma con tan solo apuntar a los archivos CSV del repositorio de GitHub, y ahora tenemos otra forma de consumirlos 😀

Necesitamos más fuentes de datos abiertos. Excelente proyecto

https://t.co/mhzZ85u7ie

#OpenData #OSINT #Cybersecurity

[Qiusheng Wu @giswqs]

GeoLibre v1.6.0 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 multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip.

What's new in v1.6.0

- Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side.
- Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library.
- Label engine: Label vector features by any attribute, with full placement and styling control.
- Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web.
- New vector analysis: Movement, space-time, and cell-coverage tools under Processing.
- Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel.
- Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel.

Try it out

- Live demo: https://t.co/hOVekblXMc
- GitHub: https://t.co/VXq8c1o2Nd
- Documentation: https://t.co/7VA2AQoCUc
- Release notes: https://t.co/e39LunOEWW

#GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography

[Yohan @yohaniddawela]

It now takes Alibaba's Mapping Lab just 10 minutes to generate a square kilometre of photorealistic 3D city from a 2D satellite image.

The problem they're chasing is the gap between simulation and reality. If you want to train a delivery drone or a disaster-response aircraft to navigate a city, you need a realistic virtual version to practise in, because crashing real machines to gather data is expensive and dangerous. Building those virtual cities by hand, or by stitching thousands of overlapping photos into a textured model, is so slow that you can only ever cover a handful of places. Most of the world has no 3D twin to practise against.

ABot-Earth 0.5 takes a different route.

Instead of reconstructing one specific place from many photographs, it learns what cities and terrain generally look like in three dimensions, then generates a plausible 3D scene to match whatever satellite image you hand it.

Give it a top-down view of a neighbourhood it has never seen and it invents the building heights, the facades, the texture of the ground, all consistent with the photo.

The underlying method involves Gaussian Splatting. Rather than modelling hard surfaces, it scatters millions of soft, coloured blobs through space, each a little smudge of light, and tunes their size and position until the cloud as a whole looks solid from any angle. It renders fast and looks photographic, which is why it has taken over 3D graphics research in the last two years. ABot-Earth's contribution is to make those blobs generative, conditioned on satellite imagery, so the system produces new geometry rather than replaying a scanned scene. It also builds the output in layers of detail, coarse from far away and fine up close, so a whole region can stream into a web browser.

The headline number is the speed: under ten minutes per square kilometre, against the days or weeks that photo-based reconstruction needs for the same area. That difference is what turns 3D city modelling from a bespoke project into something you could run across a continent. The paper carries 28 authors, the kind of team size that signals a company building infrastructure rather than a one-off demo.

Interestingly, they've launched this as version 0.5, so I'm guessing further updates are coming soon.

Obviously, a generated facade is an educated guess rather than a survey, so you wouldn't use it to measure a real building to the centimetre. But for teaching a drone to find its way, or giving a planner a fast rough model of a district that doesn't exist yet, a convincing guess at continental scale beats a perfect model of ten city blocks.

link to full article: https://t.co/jGThvOAGJb

[Qiusheng Wu @giswqs]

Introducing geolibre-rust: 700+ geospatial tools running entirely in your browser, no server, no Python, no install.

I am excited to share geolibre-rust, a pure-Rust geospatial toolkit for GeoLibre that compiles to WebAssembly. It builds on opengeos/whitebox-wasm (the WASM-ready fork of whitebox_next_gen) and ships as a superset: everything that package offers, plus new GeoLibre-authored tools.

What makes it different:

- 738 tools in the browser. Slope, aspect, hydrology, terrain analysis, LiDAR, vector, raster math, and more, all running client-side over an in-memory filesystem.
- No backend required. No server, no Python sidecar, no GDAL, no native install. Inputs and outputs are passed as byte arrays, and raster results come back as Cloud Optimized GeoTIFFs.
- Two layers in one npm package (geolibre-wasm): a typed browser library for GeoTIFF/COG read and write, projections, vector, and LiDAR, plus a WASI tool runner that executes the full tool suite.
- New pure-Rust tools. We ported the DEM depression and mount delineation algorithms from opengeos/lidar to pure Rust, so they run in WASM with no RichDEM, SciPy, or scikit-image dependency.

There is also an interactive demo page: pick any of the 700+ tools, fill in an auto-generated parameter form, and run it on a sample DEM or your own GeoTIFF, right in the browser.

This is part of the broader GeoLibre effort to build a fast, open, and dependency-light geospatial stack that works anywhere the web does.

GitHub: https://t.co/fWfT5ZsF8S
Live demo: https://t.co/lrgNPv9b3x

Feedback and contributions are welcome.

#OpenSource #Geospatial #Rust #WebAssembly #GIS #RemoteSensing #GeoLibre #WhiteboxTools

[Ujaval Gandhi @spatialthoughts]

Took a long time, but finally glad to launch our first workshop on Git. Learn Git, GitHub, and Web Development from the very basics and build your online portfolio website. The full workshop with videos is now available on Spatial Thoughts OpenCourseWare https://t.co/piWHfSsLbh

[Qiusheng Wu @giswqs]

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 https://t.co/Iu3zs18eJk 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: https://t.co/hOVekblXMc
Star it on GitHub: https://t.co/VXq8c1o2Nd
Docs and roadmap: https://t.co/7VA2AQoCUc
Release notes: https://t.co/G7VorFZxIy

#GIS #OpenSource #Geospatial #MapLibre #WebGIS #DuckDB #GeoLibre

[Tom Krikorian ᯅ @tom_krikorian]

Reality Composer Pro 3 is like a completely new experience! This is just impressive the difference between version 2 & 3. #WWDC26 is amazing for visionOS developers and the Vision Pro.

[J P @JPMS79]

Vaya actos circenses de nuestro gobernador @PabloLemusN

Tenemos un ex gobernador que ahora es auxiliar técnico de futbol, quizás Lemus, cuando salga de gobernador, puede ir a trabajar al Cirque du Soleil.

Y también habla inglés, en una de esas hasta habla francés.

[@andresdlp.bsky.social @andres_dlap]

Airbnb tiene casi 300 mil alojamientos en México.

En este reportaje de @quintoelab, gracias a datos inéditos de @InsideAirbnb, podemos explicar dónde están y quiénes son los grandes propietarios (con hasta 840 alojamientos).

REPORTAJE: https://t.co/a2qTl36Y2i

Abro un hilo 🧵

[Bert Temme @berttemme]

Data sources in GeoLibre v0.7.0

[Bert Temme @berttemme]

CesiumJS 1.142 release with vector tiles https://t.co/nH5VmM1srQ

[Datos Aeronáuticos ◽ @CapLaloVargas]

✈️🌥️ Así se disfruta entrar a la nube… ¡desde la cabina y de frente!
Una vista que nunca cansa.
¿Cuál ha sido tu mejor vista desde la cabina?
¿Te gustaría vivir esto alguna vez?

[Robin @robinhodl69]

Gente vibe codera de Guadalajara 🇲🇽

Nos vemos el viernes 12 de junio a las 4:00 PM en @hackergarage.

Trae tu laptop para compartir flujos de trabajo y conectar con quienes están construyendo el futuro, todo con un buen café ☕️

Registro: https://t.co/bVdL8mVf9A

[huangserva @servasyy_ai]

真的没有套路
SAM3 是开源的，而且效果非常强

它特别擅长的一点是目标跟踪，即使是在这种非常复杂的场景中也表现很好。

[MoundLore @MoundLore]

Mexico LiDAR

[Google Earth @googleearth]

Urban planners spend hours wrangling GIS data for stakeholder presentation, analysis, and reviews. Unify your city planning data in Google Earth with new SHP imports. https://t.co/DS7TvwDR1P

Securely combine zoning data, environmental constraints, and property boundaries as performant, cloud-native data layers to create a single source of truth for your entire team.
Upload your SHP files to Google Earth today.

[Teleport @TeleportByVarjo]

Drone in. 3D out.📍
Up to 10,000 images, 5K resolution, 100M splats.

Entire neighborhoods, terrains & infrastructure -- reconstructed in full 3D automatically via the cloud.
https://t.co/HXaCuHpQfw

[Kyle Walker @kyle_e_walker]

Zoom to an area.

Lasso-select wells.

Summarize the data with AI.

Then download the data you need.

Energy intelligence in seconds, no enterprise contract required.

https://t.co/ZSUs4ERLSn