Introducing Granite-Geospatial-Ocean: A new AI model for ocean monitoring

Revolutionizing Satellite Imagery: Discover Planet's Owl Fleet - A Leap Forward in Space Technology Discover the groundbreaking capabilities of Planet's Owl satellites set to reshape satellite imagery with unprecedented detail by late 2026. Planet's upcoming Owl satellite fleet represents an ambitious leap in earth observation, designed to provide highly detailed imagery at a 1-meter resolution. This groundbreaking technology will cater to a wide range of applications, from agriculture and urban planning to environmental monitoring and disaster response. Slated for a technical demonstration in late 2026, these satellites will not only advance scientific research but also contribute significantly to sustainable development goals worldwide. The introduction of Owl satellites is poised to greatly enhance the capabilities of various sectors. Agriculture will benefit through precise crop monitoring, while city planners can employ detailed imagery to optimize urban growth and infrastructure. Environmental scientists will have access to critical data for tracking changes in global ecosystems, and humanitarian efforts during natural disasters will become more effective with rapid, detailed imaging support. "The Owl satellite series marks a turning point in global observation technology, offering insights that were previously unimaginable," noted space technology expert Jane Doe. Powered by state-of-the-art satellite design and cutting-edge optical devices, the Owl series incorporates revolutionary technologies such as AI-driven data analysis and cloud-based processing systems. These innovations are set to redefine the boundaries of what is possible in remote sensing and data utilization, solidifying Planet's position as a pioneer in the space technology industry. #CurrentTrendsInTechnology Source : Next Big Future

Embedding space systems development within the realm of AI is becoming an everyday reality for engineers and designers. Among the many AI tools, knowledge graphs (KG) stand out as a powerful approach — and I’m very proud to share that our latest paper on their application to space systems has just been published in Acta Astronautica (https://lnkd.in/dYeFUN5H). Most of the credit goes to #LucaPatrignani, who laid the foundations of this study during his Master’s thesis in Astronautical and Space Engineering at La Sapienza. This paper is the result of a true team effort across multiple institutions and researchers. I’m especially grateful to #EleonoraLaurenza, whose creativity in structuring the author network and deep expertise in knowledge graph techniques made this work possible, and who strongly believed in their application to space systems. I hope many colleagues in the space field will find this paper both interesting and inspiring for future developments. Keywords: #ConsolatoGenraledItaliaaBoston, #KnowledgeGraphs #ArtificialIntelligence #MachineLearning #SystemsEngineering #SpaceSystems #DigitalEngineering #ModelBasedEngineering #SpaceMissions #Ontology #ComplexSystems

🚀 New Preprint Published! My latest research — “Round-Trip Mars Missions in the 2031 Window: Feasible and Extreme Scenarios Derived from CA21-Anchored Trajectories” — is now available on Preprints.org no link: https://lnkd.in/dixGyhPS This study presents two dynamically consistent Earth–Mars–Earth mission designs based on the orbital geometry of asteroid 2001 CA21, revealing how asteroid-anchored trajectories can reduce plane-change penalties and enable sub-year round trips. 🛰️ Highlights: Rapid mission (153 days): 33 + 30 + 90 days configuration Feasible mission (226 days): 56 + 35 + 135 days configuration Uses Lambert-based modeling validated with JPL Horizons ephemerides Demonstrates realistic energetic symmetry for round-trip Mars transfers This work bridges astrodynamics, mission architecture, and orbital geometry, showing how early asteroid data can guide future high-energy interplanetary missions.

💥💥 New Publication! Hot off the press!💥💥 Excited to share a new open-access article titled 'Prediction and mapping of boreal forest fire fuel loads using high-resolution satellite stereo imagery' by Lauri Korhonen, Matti Maltamo, Syed Adnan & Petteri Packalen. Just published in International Journal of Remote Sensing. 🛰️🛰️ Conventional satellite imagery is great for forest resources monitoring, but it is hard to infer forest vegetation height and structure from these "flat" 2D images. A new breed of satellites have additional 3D (stereo) vision capability - they can also sense vertical vegetation structure. Example satellites are the WorldView series, Pléiades series and Planet's SkySat constellation. We used data from such a satellite and showed that one can infer vegetation height and several other important forest parameters from it (see fig. 2 in the paper). We also demonstrated a new method ("DTM independent metrics") which makes our prediction methods applicable across the globe 🌍🌍. The paper is here: https://lnkd.in/dvng4pJZ. 😊🛰️🌲🌳💚📊🌎😊

Australia has officially joined the Inter-Agency Space Debris Coordination Committee (IADC) as an Associate Member, and Deakin research is helping lead the way! At the heart of this achievement is Deakin’s cutting-edge research into hypervelocity impacts, led by Assoc Prof Shannon Ryan from the Deakin Applied Artificial Intelligence Initiative and School of Engineering. Shannon’s team is pioneering the use of physics-informed AI to model and predict the effects of hypervelocity impacts, the kind caused by space debris and micrometeoroids. Learn more about Shannon’s research and how it's contributing to global space sustainability efforts 🔗 https://lnkd.in/g5HyKKbr

Australia has officially joined the Inter-Agency Space Debris Coordination Committee (IADC) as an Associate Member, and Deakin is contributing to this global effort. Assoc Prof Shannon Ryan and the team at Deakin’s Deakin Applied Artificial Intelligence Initiative and School of Engineering are leading innovative research into hypervelocity impacts, using physics-informed AI to better understand and mitigate space debris.

How do forests look when seen through lasers? A new Nature Communications review article, led by Dr. Eduardo Maeda, shows how terrestrial laser scanning is transforming forest science. Terrestrial laser scanning enables researchers to scan trees and forests in ultra-detailed 3D — not just from above, but from within. This new perspective is opening opportunities to: 🌲 track how trees grow and allocate resources 🔥 study how forests recover from disturbance 🦉 understand how structural complexity supports biodiversity and resilience. Read the article in Nature Communications: https://rdcu.be/eJHnY At our Earth Observation Unit, laser scanning and other geospatial technologies are applied from boreal forests in Finland to the tropics of Amazonia and Southeast Asia. Together with AI and satellite observations, they provide unprecedented insights into how human activity shapes ecosystems, and also how we can manage forests more sustainably. This work also highlights the strength of collaboration. Through the FAME Flagship, funded by the Research Council of Finland | Suomen Akatemia, we work closely with Tampere University, University of Helsinki, Aalto University, and University of Oulu to advance forest-related AI, modelling, and Earth observation. Photo: Adobe Stock. #Research #Forests #EarthObservation #LiDAR #RemoteSensing #ArtificialIntelligence #FAMEFlagship

🔥 Reading the Earth in Color and Beyond What looks like abstract art is actually the Waroona Fire Burn Scar, captured by NASA’s Terra (MODIS) sensor after a 2016 blaze in Western Australia. This image uses a 7-2-1 false-color composite — combining shortwave-infrared, near-infrared, and red bands: SWIR reveals burned soil and ash NIR shows vegetation health Red defines landform detail With just a few wide bands, we can map the full footprint of an event vegetation loss, regrowth, and land-surface change. That’s multispectral imaging: seeing the world through dozens of broad windows. Now imagine scaling that up to hundreds of narrow spectral slices , where each mineral, gas, or plant type has its own optical fingerprint. That’s hyperspectral, and platforms like Pixxel Firefly are making it operational at 5 m resolution. We’re entering a phase where the same physics used to study wildfire scars can power mineral exploration, methane detection, and precision environmental analytics. I’ve been independently developing a system that goes beyond any single sensor fusing multispectral archives, hyper spectral constellations, and other spatial intelligence layers into one adaptive framework I call T.A.R.S. It’s built to translate raw data from orbit to on the ground insight and bridge the gap between space borne observation, terrain modeling, and real-world decision systems. More to come soon. #EarthObservation #Pixxel #Hyperspectral #Multispectral #RemoteSensing #MiningTech #GeoAI #Firefly #EdenX #TARS #SpaceToSurface University of Alaska Fairbanks

SNOW, RAIN, OR IN BETWEEN: Using nearly a decade of high-speed footage, an unsupervised machine learning approach distinguishes nine distinct precipitation types, including varieties of rain, snow and mixed-phases. The results could improve weather forecasting and winter driving safety. “In the short term, better forecasting can help people adjust their daily commute or prepare for big events like floods or an ice storm. On longer time scales, it can help predict how snowpack or runoff timing will change fresh water availability for a region,” said Claire Pettersen, an assistant professor of climate and space sciences and engineering at U-M. The footage used here came from a NASA-developed specialized camera system deployed at seven sites in the United States, Canada and Europe. The instrument uses a high-speed camera system and a bright light to record precipitation falling through the camera’s view while measuring particle sizes, size distribution, density, concentration and fall speeds. Read the full story here: https://bit.ly/3VUNpRe

#SpaceExploration | 𝗥𝗮𝗴𝗶𝗻𝗴 𝗪𝗶𝗻𝗱𝘀 𝗼𝗻 𝗠𝗮𝗿𝘀 | Winds on Mars can reach speeds of up to 160 km/h, far exceeding previous estimates and revealing a new aspect of the Martian atmosphere. This discovery by Dr. Valentin Bickel and his team from the University of Bern and the German Aerospace Center (DLR) shows that dust devils and surrounding winds lift a significant amount of dust into the atmosphere, affecting the climate and future exploration of Mars. The team's use of deep learning to analyze over 50,000 images from Mars cameras has provided insights into atmospheric and surface conditions crucial for planning future missions. Employing advanced imaging and deep learning, the researchers identified and analyzed around 300 dust devils, enabling a comprehensive global analysis of Martian wind dynamics over two decades. This breakthrough improves the modeling of the Martian atmosphere and surface processes, vital for mission risk assessment and technical system adaptation. It also offers new insights into the formation of Martian dunes and slope streaks, crucial for developing weather and climate models on Mars. 👉 Learn more >> https://lnkd.in/gSKfR3vF 👉 Original publication >> https://lnkd.in/gtBd6aJ7 🇨🇭 Follow #ScienceSwitzerland for the latest news and emerging trends on Swiss science, technology, education, and innovation >> swissinnovation.org Follow us >> Science-Switzerland #Science | #Education | #Research | #Innovation