AI's Role In Tracking Climate Change Indicators

Forest carbon monitoring gets an AI boost, reports Abhishyant Kidangoor. Forests have long been surveyed from above. Satellite data reveal where they stand and how they shrink or grow, while lidar—laser-based radar—has allowed scientists to map them in 3D, uncovering details that lie beyond human sight. Now, artificial intelligence is adding a new layer of insight. Earth-imaging company Planet has unveiled a Forest Carbon Monitoring tool that fuses its satellite imagery with lidar data. The tool can estimate carbon storage, tree height, and canopy cover in remote forests at a granular resolution of three meters. “It will help us understand aspects of the forest that might not be initially accessible to the naked eye,” says Andrew Zolli, Planet’s chief impact officer. Satellites track forest cover but not the carbon stored in biomass. Measuring this requires lidar, which calculates tree dimensions by measuring the time laser beams take to bounce off foliage. NASA’s GEDI mission, mounted on the International Space Station, has mapped swathes of forests, but coverage gaps persist. Planet’s tool aims to bridge these voids, training machine-learning models to infer carbon data in areas without lidar coverage. Initial findings from the tool have been striking. While deforestation ravages the Amazon, the northern reaches harbor untouched carbon reserves. “What really resonated with me is the understanding of where we have extant forest carbon stocks which we must absolutely protect,” says Zolli. The data also underpin Project Centinela, which supports conservation efforts in biodiversity hotspots like Tanzania’s Gombe Stream National Park. Meanwhile, carbon markets—often criticized for opacity—may gain credibility through applications of the tool argues Zolli: “The data gives a shared, common picture of what’s actually happening on the ground.” Planet’s innovation rests on decades of data, cutting-edge AI, and cloud computing. “We are the first generation that has had all three in place,” Zolli says, enabling swift, confident assessments of carbon across the globe. 📰 story: https://lnkd.in/gwRWf5Qf 📷: A view of carbon storage in forest and an area of fishbone deforestation in the Brazilian Amazon. Image courtesy of Planet.

Earth Observation is no longer just about capturing images from orbit. It’s rapidly becoming one of the most important tools we have to understand what’s happening on the ground—and act on it. Recent developments in EO are showing a clear trend: using satellite data to support real-time, local decisions in areas that impact lives, environments, and economies. Here are four examples that stand out: 1. Detecting Wildfires Before They Spread Google and Muon Space are building Fire Sat, a constellation of over 50 satellites that will scan fire-prone areas every 15 minutes. With real-time thermal imaging and cloud-based AI, it’s designed to catch wildfires early—before they become disasters. 2. Mapping Carbon Storage from Orbit The European Space Agency’s Biomass satellite uses a powerful radar system to measure how much carbon Earth’s forests are actually storing—by looking through the canopy itself. This gives scientists a more accurate understanding of climate-related forest change and carbon sinks. 3. Monitoring Land Use with Consistent Imaging EarthDaily Analytics launched the first satellite in a new constellation purpose-built for high-frequency, high-accuracy landscape monitoring. It’s especially relevant in agriculture, forestry, and environmental policy—where visibility over time matters more than snapshots. 4. Enabling Localized Impact Forecasting Xoople has developed a cloud-native Earth Observation platform that blends EO data with local models to forecast regional environmental risks—like floods, soil degradation, or vegetation stress. It’s EO made practical for governments and agencies on the front lines of climate and resource planning. These aren’t just satellites in orbit. They’re part of a growing EO ecosystem that’s focused on enabling faster, more confident action—where and when it’s needed most. From archive to alert. From static to streaming. From observation to intervention.

In this week's column, I look at NVIDIA's new generative foundation model that it says enables simulations of Earth’s global climate with an unprecedented level of resolution. As is so often the case with powerful new technology, however, the question is what else humans will do with it. The company expects that climate researchers will build on top of its new AI-powered model to make climate predictions that focus on five-kilometer areas. Previous leading-edge global climate models typically don’t drill below 25 to 100 kilometers. Researchers using the new model may be able to predict conditions decades into the future with a new level of precision, providing information that could help efforts to mitigate climate change or its effects. A 5-kilometer resolution may help capture vertical movements of air in the lower atmosphere that can lead to certain kinds of thunderstorms, for example, and that might be missed with other models. And to the extent that high-resolution near-term forecasts are more accurate, the accuracy of longer-term climate forecasts will improve in turn, because the accuracy of such predictions compounds over time. The model, branded by Nvidia as cBottle for “Climate in a Bottle,” compresses the scale of Earth observation data 3,000 times and transforms it into ultra-high-resolution, queryable and interactive climate simulations, according to Dion Harris, senior director of high-performance computing and AI factory solutions at Nvidia. It was trained on high-resolution physical climate simulations and estimates of observed atmospheric states over the past 50 years. It will take years, of course, to know just how accurate the model’s long-term predictions turn out to be. The The Alan Turing Institute of AI and the Max Planck Institute of Meteorology, are actively exploring the new model, Nvidia said Tuesday at the ISC 2025 computing conference in Hamburg. Bjorn Stevens, director of the Planck Institute, said it “represents a transformative leap in our ability to understand, predict and adapt to the world around us.” The Earth-2 platform is in various states of deployment at weather agencies from NOAA: National Oceanic & Atmospheric Administration in the U.S. to G42, an Abu Dhabi-based holding company focused on AI, and the National Science and Technology Center for Disaster Reduction in Taiwan. Spire Global, a provider of data analytics in areas such as climate and global security, has used Earth-2 to help improve its weather forecasts by three orders of magnitude with regards to speed and cost over the last three or four years, according to Peter Platzer, co-founder and executive chairman.