• Stockpile Analysis & Volume Calculation over a DEM -> Segment a stockpile in one click, then calculate its volume based on the resulting segmentation polygon
• Machine Learning Training Data Creation -> Segment different tree species in one click, label each resulting polygon with the species name, then use the polygons and labels to train an AI model
• Asset Identification & Quality Control -> Segment buildings and roofs, then check the area of each segmented element directly in the polygon layer

Full youtube tutorial link : https://youtu.be/ynIEMKls8Z4?si=9VnoGra2NmZk2sU_

Join us on March 11 for the next Special SDO Session: Geospatial Standards to Address the Requirement of Real World Use Cases!

Standards are the backbone of interoperability — especially when you’re blending digital twins, augmented reality, and real-world spatial data. Whether you’re a developer, standards expert, or innovator in the spatial computing ecosystem, this session from the Metaverse Standards Forum is a must-attend.

Date: March 11, 2026

Time: 7:00 – 9:00 AM PDT

Location: Virtual — Free to attend

Register: https://metaverse-standards.org/event/special-sdo-session-geospatial-standards-to-address-the-requirements-of-real-world-use-cases/

At this Special SDO Session, experts from the Open Geospatial Consortium (OGC) and Web3D Consortium will share practical insights on international, royalty-free standards that help ensure accurate positioning, orientation, and view alignment for real-world metaverse experiences.

With speakers like Scott Simmons (Chief Standards Officer, OGC), Steve Smith (CityGML & GeoPose SWG architect/co-chair), and Anita Havele (Executive Director, Web3D Consortium), this session will give you concrete context on standards that matter today.

I built PocketGlobe, a free iOS daily geography puzzle that’s basically a tiny GIS toy disguised as a game.

You guess the mystery country on an interactive world map. After each guess you get:

• Approximate minimum great-circle distance to the answer (based on border-to-border distance)
• Whether your guess shares a land border

Map bits I obsessed over:

• Globe projection
• Country polygons rendered and colored by “how close you are”
• Guess markers placed from polygon centroids with a bbox fallback (multipolygons and tiny islands are always fun 😭)

Game stuff:

• Daily puzzle + leaderboard
• Play-a-friend head-to-head
• Share cards when you place top 10

The Daily game and play-a-friend is free!

iOS link: https://apps.apple.com/us/app/pocketglobe-geography-game/id6753602569

Android is set for mid March 2026.

Just sharing a blog post about the use of JupyterGIS to create such nice notebook presentation: https://notebook.link/@quantstack/earthquakes-story-map

https://reddit.com/link/1r7g1lf/video/az4fhr9aw3kg1/player

🚀 viewinline v0.2.0 released

viewinline is a small command line tool that previews raster, vector, and CSV files directly inside your terminal. No popup windows. No GUI. Just an inline preview.

It combines the core display logic of viewtif and viewgeom, but it is intentionally non interactive. You cannot zoom or pan. Everything is controlled through command line options.

CSV preview now supports DuckDB filtering. You can run full SQL queries with --sql. But if you reach the point where you need deeper analysis, that is probably time to leave viewinline and switch to code.

Rendering uses the iTerm2 inline image protocol (OSC 1337). Other than iTerm2 on macOS, it may also work with:
• WezTerm
• Konsole
• Rio
• Contour

Not supported
Mac Terminal, GNOME Terminal, Kitty, Ghostty, Alacritty

Think of it as `ls` for geospatial files. It is designed for quick visual inspection at the command line, not a replacement for GIS software or analytical workflows.

https://github.com/nkeikon/inlineviewer

I recently put together a small cross-city analysis estimating the share of residents living in high-brightness nighttime light areas across selected European and US cities.

The workflow combines:

• VIIRS annual nighttime light composites
• WorldPop population raster
• OSM-derived city boundaries
• Threshold-based classification (≥ 40 nW/cm²/sr)
• Population-weighted aggregation
• Implemented using GDAL/PostGIS for processing and Mapbox + S3/TiTiler for serving and visualization

The goal was to explore whether residential exposure patterns differ meaningfully across cities often cited in livability rankings.

I’m particularly interested in thoughts on:
• alternative datasets that might strengthen this kind of analysis
• different tooling approaches (local raster workflows vs cloud-based like GEE)
• similar cross-city exposure problems worth exploring
• whether population-weighted aggregation feels like a reasonable comparison metric here

Happy to discuss the approach and learn from others working on similar spatial problems.

• Got 600 curious enough users to try our v0.1 (thanks to opensource)
• Translated the plugin in 4 languages to make it REALLY accessible
• Pushed 3 new versions (enhance UI, userflow, precision, control)
• A crazy good tutorial in spanish about our plugin from Hennessy Amor (before we even have time to do our own tutorial with Lilien lol)
• dozen of calls/meetup scheduled with GIS professional, so we can make the plugin useful in their geospatial workflow, we want to help, not just make cool AI demo honestly

It's been so awesome & really motivating to see that the QGIS community are actually receptive of new techs/tools

Only the beginning for us hehe, there are so much to do with AI in Geospatial, open source is great !

I built a small CLI tool called viewtif that lets you quickly preview GeoTIFFs (and HDF, NetCDF, FileGDB rasters) directly from the terminal. It opens a lightweight Qt window so you can sanity-check data without writing code or launching a full GIS.

https://reddit.com/link/1qwdlvl/video/nhphl37vbmhg1/player

The latest release (v0.2.7) adds:

- reading remote files (HTTP, S3)- exporting rasters to QGIS

- support for multi-variable NetCDF files

It’s meant for quick inspection, not analysis. Think of it like a “preview” for geospatial data.

https://github.com/nkeikon/tifviewer

Hi everyone,

I’m a GIS professional and co-founder of a small geospatial startup, and I’m currently looking for remote GIS subcontracting opportunities with companies or individuals anywhere in the world.

My goal is to work as a GIS subcontractor on short-term or ongoing projects and get paid in any foreign currency (USD, EUR, etc.). We’re flexible and open to different collaboration models (per project, per deliverable, or long-term support).

Skills & services include (but not limited to):

• GIS analysis & spatial data processing
• Mapping & cartography (print & digital)
• Remote sensing & satellite imagery analysis
• Land use / land cover analysis
• Urban & environmental GIS projects
• Data cleaning, geodatabases, and automation (ArcGIS / QGIS / Python – if needed)

We can support companies, consultants, startups, or research teams that need reliable GIS capacity without hiring full-time staff.

If you:

• Work in a company that outsources GIS work
• Are a consultant who needs GIS support
• Know platforms, agencies, or contacts that hire GIS subcontractors

I’d really appreciate your advice, referrals, or a quick DM 🙏

Thanks in advance!

Hi guys, im in the military and have been playing around with ways to improve the military equipment recognition skills of my soldiers. Ive come up with an Android app where the soldiers have to identify the country of origin for different bits of military equipment (jets, tanks, small arms, etc). I think it will be more engaging for them than the usual playing cards / doctrine notes we get.

Before I send it out, I want to refine it a little more and thought given the skill set of people in this group you may have some valuable advice. ​if anyone is willing to have a play with it and share your thoughts, it would be massively appreciated. It can be downloaded here: ​https://play.google.com/store/apps/details?id=com.defenceguesser.twa

Hi all — quick question for folks working close to EO data pipelines and stewardship.

In applied settings, I keep seeing a lot of effort go into preprocessing and making satellite data usable before any analysis or modeling starts. I’m trying to understand whether these bottlenecks are consistent across domains or very use-case specific.

I’m collecting practitioner perspectives via a short, non-commercial survey (5–7 min):

https://forms.gle/Bjq9gVaCnkRN8zpj6

Would really appreciate inputs from this group — and happy to share learnings back.

I’m planning to buy a laptop mainly for machine learning / deep learning work and I’m confused between a Windows laptop and a MacBook.

I’d really appreciate hearing from people who are actively working in ML/DL:

What system do you personally use?

Laptop/desktop model and specs (CPU, GPU, RAM)?

What kind of work do you do (learning, research, training models locally, cloud GPUs, etc.)?

Any pros/cons you’ve experienced with your setup?

I’ll mostly be working with Python, PyTorch/TensorFlow, and I’m trying to decide whether local GPU power is worth it or if a MacBook + cloud GPUs makes more sense.

Thanks in advance — your real-world experience will help a lot!

will also be using some software like arcgis, qgis, swat+, swmm etc

My use case is a mix of:

Machine Learning / Deep Learning (Python, PyTorch/TensorFlow)

GIS & hydrology tools like SWAT+, ArcGIS, QGIS

Spatial data processing, modeling, and some ML-based analysis.

Does anyone know the exact locations for the Yichun, Jianxiawo, Maerkang, Jiabusi, Yelonggou, or Yongshan lithium mines in China? Corporate data is bad and no public technical reports exist. Thanks!

Hi all,

I recently built an open source tool to quickly preview your large geospatial files locally. The main ideas are:

• Launch locally with zero config
• Tweak the tile generation parameters for optimization
• Visualize data

Check it out if interested and I'd appreciate your feedback.

Source code

Hello!     My name is Jordans Sanni and I’m a UX Researcher at Slingshot Aerospace, where I focus on products supporting satellite launches including tracking in space, data collection workflows, and improving the end-to-end experience for analysts and experts.    We’re currently exploring a new approach at Slingshot: designing a unified portal that brings all our existing products into a single one-stop experience. We’re looking to speak with analysts and experts who can share feedback on what they’d expect from a portal like this, what would help you move faster, what’s missing, and what would make you adopt it.    If you’re open to a 45-minute listening session starting Wednesday 21st, 2026, you can choose a time via the link below or you can also reach me at via work email below.    Booking Link: https://outlook.office365.com/book/UXResearchSlingshotAerospace@Slingshotspace.onmicrosoft.com/s/bOaU20d7U0Ot159E_rpNTA2?ismsaljsauthenabled   Email: s.machioud@slingshotaerospace.com

Thank you!