Understanding how agriculture and land use affect nutrient flows and concentrations in the vast area of the Great Lakes is an essential step to developing sustainable management strategies.
machine learning & AI
How Big Data is Helping Environmental and Climate Research
A new special collection invites papers focusing on the processing, modeling, and analysis of all types of big datasets in the Earth and space sciences, including the influence of solar forcing on Earth’s climate.
Tree Ring Width Predicted by Machine Learning
When predicting a tree’s annual growth, consider the whole weather system and not just the sum of its parts.
Unleashing the Power of AutoML for Atmospheric Research
Automated Machine Learning liberates domain scientists from selecting learners and hyperparameters and discovers the importance of atmospheric trace gases for improving surface PM2.5 estimates.
“Icefin” Investigates a Glacial Underbelly
An instrument-laden submersible reveals where—and how rapidly—the Antarctic glacier is melting.
The Limits to Tree Planting in the Indian Himalayas
The Indian government has an ambitious forestry goal. New research shows it may be out of sync with environmental and social constraints.
Machine Learning Helps Researchers Track Illegal Fishing
Using machine learning, researchers found that nearly 20% of high seas fishing could be unauthorized.
Prospecting for Copper with Machine Learning and Zircons
Using artificial intelligence, researchers can now identify zircons derived from valuable copper deposits.
Boreal Trees May Grow Faster Due to Climate Change
Enhanced tree growth could significantly offset carbon emissions, but some researchers say it’s not enough to compete with forest disturbances.
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.