Cloud-Native Geospatial Forum (CNG)

✨ The CNG Conference 2025 website just got an upgrade! A huge thank you to OGC for helping us design an easy-to-navigate site - making it simpler to explore #CNG2025: ✅ Discover the full speaker lineup--featuring experts from NASA - National Aeronautics and Space Administration, Esri, Google, Amazon Web Services (AWS), The New York Times, Wherobots, Earthmover, Element 84, Tilebox Inc., and more! ✅ Find sessions & workshops that match your skill level—whether you're new to cloud-native geospatial or a seasoned expert ✅ Register now for Apr 30 – May 2 at Snowbird, Utah before it's too late! We’re just weeks away—who’s joining us? Drop a comment below! 👇🏾

Are you a scientific programmer or full stack data wrangler or technical solutions builder who loves ocean data and enjoys building tools, applications, and systems to make data more accessible? Passionate about open science and supporting the science community? Do you enjoy learning about new technologies, machine learning techniques, and cloud computing? Come join the team at Schmidt Ocean Institute as our new Data Solutions Engineer! You'll help make data accessible to the world by developing smart systems for scientific data and video. Check out the full position announcement https://lnkd.in/g4jXM4CX

Heading to the Cloud-Native Geospatial Forum (CNG) Conference next week? Learn how to leverage ML to extract deeper insights from satellite imagery — you won’t want to miss this session led by Damian Wylie. Day 2 | 11:45am-1:15pm 📍 Wasatch A | Getting Started with Cloud-Native Geospatial Workflows 1: Solutions 🔍 Session: Extract insights from satellite imagery at scale with WherobotsAI Inferring objects and detecting change in satellite imagery was once reserved for companies with the talent, money, and time to build, manage, and run sophisticated, self-managed ML inference solutions against satellite data.

Lots happening in the cloud-native geospatial space these days. Let's keep the momentum going. Adoption is crucial to ensuring that decisions about the Earth and society are made with the best available data. Access to that data lies with cloud-native data & tools and YOUR ability to use that data to solve - not just study - our greatest challenges. Here's a few resources to explore: - Optimizing Geospatial Data for the Cloud Zine comic (https://lnkd.in/gAPeWun6) Development Seed - Introduction to Geospatial Raster and Vector Data with Python (https://lnkd.in/gjWzfvr9) The Carpentries - Cloud-Optimized Geospatial Formats Guide (https://lnkd.in/gD3TgnU2) by Cloud-Native Geospatial Forum (CNG) - Cloud computing tutorial (https://lnkd.in/gtk-pye3) University of Washington eScience Institute - Introduction to Cloud Native & Analysis Ready Data Formats (https://lnkd.in/gHvNCM45) Tyson Swetnam - NextGen Geospatial: AI & Cloud Tools for Geographic Analysis (https://lnkd.in/gEpgS-FY) Jeffrey Kent Gillan - Fundamentals: What is Cloud-Optimized Scientific Data? (https://lnkd.in/g_quuxu5) by Earthmover - Cloud-Native Geospatial 101 (https://lnkd.in/gMRerBNx) thriveGEO, sign up to be notified the next time they offer this course

With today's Zarr Python release, switch to the new obstore-based backend for **3x faster** reading from S3, Google Cloud Storage, and Azure than the default fsspec backend. https://lnkd.in/eAnk4Jzy https://lnkd.in/dJsuPKFa Thanks Max Jones for doing this benchmarking! See https://lnkd.in/e84y2wia

At #GoogleCloudNext last week, we announced the launch of Earth Engine in BigQuery. This is an extension of BigQuery's geospatial capabilities that will broaden access to pixel-based (raster) analytics, making it easier than ever before to process and analyze satellite imagery for sustainability use cases. Check out the breakout session and 5 min recap I led with Jeremy Malczyk and Jeff Sternberg on how to leverage this new feature for climate resilience, specifically wildfire risk prediction and recovery. 5 minute recap of session: https://lnkd.in/eB3bfPxj Full breakout session (Climate Resilience): https://lnkd.in/ezfyKFdV Full breakout session (Sustainable Sourcing): https://lnkd.in/e5tzEEv9 Special thanks to Alicia S. Sean Wohltman Hugh Lynch Kel Markert Gennadii Donchyts for featuring sustainable sourcing, agriculture, and weather use cases at Cloud Next!

Pacific Spatial Solutions 株式会社 も参加します！日本からどなたか参加される方がいれば、ぜひお声がけください！

Join us! Two postdoc roles available in our team. Looking forward to working with you. #biodiversity https://lnkd.in/gtjW4Cgp https://lnkd.in/gmwNJUtY

You can query the data in the Overture Maps Foundation buildings dataset (2.6 billion rows) a lot faster when it’s in GeoParquet instead of GeoJSON. It takes over 47 minutes to fetch the number of buildings in a small portion of Florida when you store the data in GeoJSON. When you store the same data in GeoParquet, the query can run in under a minute.

"Fundamentals: What is Cloud-Optimized Scientific Data? Why naively lifting scientific data to the cloud falls flat." https://lnkd.in/gGnX9EJr Thank you Tom Nicholas