Geolabe

𝐏𝐫𝐞𝐬𝐞𝐧𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐟𝐮𝐥𝐥𝐲 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐠𝐥𝐨𝐛𝐚𝐥 𝐦𝐞𝐭𝐡𝐚𝐧𝐞 𝐝𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦 𝐝𝐨𝐰𝐧 𝐭𝐨 𝐭𝐡𝐞 𝐩𝐨𝐢𝐧𝐭 𝐬𝐨𝐮𝐫𝐜𝐞 𝐥𝐞𝐯𝐞𝐥 💡After years of research, our team of scientists that spun out of the Los Alamos National Laboratory has managed to build the first global and automated high resolution methane emissions detection system. 𝐎𝐮𝐫 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 𝐭𝐨 𝐦𝐞𝐭𝐡𝐚𝐧𝐞 𝐝𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 In a study published today in Nature Communications, our Geolabe research team, out of Los Alamos, New Mexico, has developed the first method to automatically detect methane emissions in satellite imagery at high spatial and temporal resolution and global scale. Our team trained an AI algorithm able to parse through large amounts of data produced by the powerful Sentinel-2 satellite constellation, and autonomously identify methane signatures. In semi-arid areas, the approach can reliably detect methane emissions down to 200-300 kg/h, accounting for more than 85% of methane from the Permian Basin and is precise enough (20m pixel size) to identify the particular sources leaks and emissions come from. 𝐎𝐮𝐫 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 Curbing methane emissions is the focus of many recently introduced regulations and voluntary commitments around the globe. However, the systematic identification of leaks and emissions remains challenging, as sensors suffer from trade-offs with respect to detection thresholds and scalability. Ask for a demo of our cloud implementation of the technology to see how this new automated system can help with methane monitoring for your organization. www.geolabe.com 🗞 The paper "Automatic Detection of Methane Emissions in Multi-Spectral Satellite Imagery Using a Vision Transformer" appeared today in Nature Communications: https://lnkd.in/g74U5ndc We are very grateful for the the support we received to make this research happen, from NASA - National Aeronautics and Space Administration and the U.S. Department of Energy (DOE) We are also immensely grateful for the support we have received in our entrepreneurial journey, from Activate, Creative Destruction Lab and Google for Startups #methane #AI

Geolabe will be at CERAWeek next week! Wednesday morning I'll be talking about Geolabe's pioneering work in AI for methane detection in satellite data. We'll also unveil our platform, making near real-time on-demand methane data a reality! We'll also have a booth so if around come say hi!

We're on the front-page of NASA's website! 🛰 Our work on training AIs to automatically detect methane emissions in satellite data has been featured by NASA today: https://lnkd.in/dWvDihXk We're very grateful for NASA - National Aeronautics and Space Administration's support, and looking forward to bringing new scalable and inexpensive methane detection capabilities to market. Stay tuned for our upcoming methane detection platform, with a launch planned for this October. Our platform will provide on-demand methane detection anywhere, every few days, down to the source level. 💡 Our detection back-end is already operational in Google Cloud and we're happy to look at any number of sites of interest ahead of the launch!

📣 Exciting update: Geolabe has been selected for the Google for Startups AI Academy: American Infrastructure program. We are grateful for Google's continued support as we finalize our methane detection platform, at global scale and down to the asset level!

📣 Exciting update: Geolabe has been selected for the Google for Startups AI Academy: American Infrastructure program. We are grateful for Google's continued support as we finalize our methane detection platform, at global scale and down to the asset level!

I had the pleasure and honor to give a talk yesterday at the META seminar series organized by Stanford University and the Natural Gas Initiative! In this presentation, I talked about the importance of methane detection in the context of global warming, the limitations of existing methods, and how the AI we trained to detect methane in general purpose satellite data from ESA and NASA can overcome some of these limitations, and provide methane detection at global scale 🌎 *and* down to the specific sources 🏭 . It is already on YouTube in case you missed it and want to check it out: https://lnkd.in/gRnJf7u5