Christoph Rieke

@chrieke.bsky.social

geo. space. tech. geopolitics.

I’m excited to introduce OpenGeoPub (opengeopub.com), a new platform designed for geospatial learning and publishing. The goal is simple: bring books, video courses, and hands-on lab assignments together in one place, with flexible pricing and lifetime access.

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Introducing 𝐀𝐬𝐲𝐧𝐜-𝐆𝐞𝐨𝐓𝐈𝐅𝐅, a new library for reading GeoTIFFs and COGs. developmentseed.org/async-geotif... - Fast, with a Rust core - Uses a non-blocking thread pool for image decoding - Integrates with NumPy, PyProj, Affine & Morecantile - Remote data support with Obstore - No GDAL dependency

Introducing Async-GeoTIFF - async-geotiff

A fast, async GeoTIFF and Cloud-Optimized GeoTIFF (COG) reader for Python.

developmentseed.org

Announcing deck.gl-raster: 𝐟𝐮𝐥𝐥𝐲 𝐜𝐥𝐢𝐞𝐧𝐭-𝐬𝐢𝐝𝐞 𝐂𝐎𝐆 𝐫𝐞𝐧𝐝𝐞𝐫𝐢𝐧𝐠. No server required. 1.3 𝐠𝐢𝐠𝐚𝐛𝐲𝐭𝐞 COG, streamed directly into the browser: developmentseed.org/deck.gl-rast... - GPU-accelerated raster reprojection - GPU image processing for colormaps, nodata values - Efficient use of COG overviews

i think the 2005-2015 era open source boom was built on a nice job environment where people had a little free time and employers believed in creativity the free time dried up, everyone burned out, 2015-2025 open source has been explicitly targeted toward getting funding & making money. what's next?

Still time to register for the hybrid workshop on satellite #EO data in agriculture! Keynote: Prof. Dr. Patrick Hostert from @humboldteolab.bsky.social -Novel Opportunities in Optical Remote Sensing for Agricultural Monitoring Towards 2030. 🛠Hands-on with Sentinel-1, Sentinel-2, PlanetScope & EnMAP

Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF)@zalf.bsky.social · 12mo ago

📡🌍 🌱 Analyzing fields with #satellite data & #AI: On September 10, 2025, ZALF in Müncheberg is hosting a hybrid KiKompAg workshop. 👩‍💻 Learn more about #remote sensing, artificial intelligence and modern analysis methods for #agriculture! 👉 Registration & more Info: www.zalf.de/en/aktue...

Workshop on Advanced Earth Observation, Machine Learning and Artificial Intelligence
for Agricultural Applications
MULTI-SOURCE REMOTE SENSING FOR AGRICULTURE
Date: September 10th, 2025
Location: Hybrid – Online & In-Person (at ZALF)

The uv build backend is now stable, and considered ready for production use. An alternative to setuptools, hatchling, etc. for pure Python projects, with a focus on good defaults, user-friendly error messages, and performance. When used with uv, it's 10-35x faster.

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So now there is the 2day AI4EO symposium in Renne in Sep 25 (previously 3 times in Munich organized by TU Munich), and new 1.5 day ML4Earth in Bonn also in Sep 25, directly organized by TU Munich. What's up with that.

At Living Planet Symposium next week. Looking forward to lots of ML&forest sessions, but also the random "I have 0 clue about this but it's awesome" volcano, ice etc session. That makes #LPS25 so great. Would love to meet some new people for coffe chat and learn new things! Just ping!

I'm looking for any info about how & why it was decided to use the Space Shuttle do create SRTM in 2000 A few questions I have: - How of the world had we mapped in 3D before 2000? - Why the Space Shuttle over a dedicate satellite (or pair of satellites) - How the data was processed

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If you're attending the Living Planet Symposium in Vienna, join us for happy hour on Wed, June 25 at 5pm #LPS25 This free event is hosted in partnership with thriveGEO, @developmentseed.org & our local host, EOX. Space is limited, so please register to attend lu.ma/56jksm3l

Cloud-Native Geospatial Community Social · Luma

Join us for a lively social gathering with connection and conversation on Wednesday, after the Living Planet Symposium wraps for the day. We're celebrating the…

lu.ma

Timbervision: a YOLO-based approach to identifying and measuring timber based on RGB imagery (Steininger et al. on arXiv). This is very cool and has loads of potential applications in forestry and forest management. 🧪

Figure 8: Representative fusion results on test images. The left side shows detected and derived OBBs. The right side shows ISEG results along with center points of cut surfaces and middle axes estimated by our fusion algorithm. Colors identify individual trunk instances, with lighter and darker shades of the same hue corresponding to associated Side and Cut components, respectively.