Enhanced tree growth could significantly offset carbon emissions, but some researchers say it’s not enough to compete with forest disturbances.
machine learning & AI
Posted inNews
Mapping Rwanda’s Trees from Above
Researchers used both aerial and satellite imagery, as well as machine learning, to map the carbon stock of every overstory tree in Rwanda—the first such inventory in the world.
Posted inEditors' Highlights
Quantifying the Potential of Forestation for Carbon Storage
Forestation projects in southern China over the past few decades have sequestered large amounts of carbon in tree biomass, but the region is approaching saturation of forest carbon storage capacity.
Posted inEditors' Highlights
Playing Bricks with Neural Networks to Learn Sorption Processes
Designated neural network modules are combined to mimic numerically-discretized diffusion-sorption equations, which allows learning “missing pieces” in system understanding and their uncertainties.
Posted inEditors' Highlights
Interactive Learning for Better AI-Based Subgrid-Scale Modeling
A study shows that interactive learning can significantly enhance the performance of artificial intelligence-based parameterization of small-scale processes, a critical component of climate models.
Posted inNews
Scientists EEAGER-ly Track Beavers Across Western United States
Efficiently tracking nature’s engineers—beavers—at the scale of entire watersheds over time is now possible, thanks to a new artificial intelligence–trained model called EEAGER.
Posted inEditors' Highlights
Using Big Data for Monitoring Network Design and Beyond
Large data sets can be generated using deep learning to improve the design of observation networks for monitoring subsurface flow and transport.
Posted inResearch Spotlights
Enhancing Earthquake Detection from Orbit
A new application of machine learning boosts scientists’ ability to use data from satellite navigation systems to detect and warn of earthquakes.
Posted inFeatures
Are We Entering The Golden Age Of Climate Modeling?
Thanks to the advent of exascale computing, local climate forecasts may soon be a reality. And they’re not just for scientists anymore.