Researchers develop machine learning model to improve Amazon carbon storage estimates

A collaboration led by an Oregon State University College of Forestry researcher has used very-high-resolution satellite imagery to develop a machine learning model that aims to improve climate scientists' ability to estimate aboveground carbon stocks in the Amazon. Findings of the study were published in the journal Carbon Balance and Management. Covering more than 2.5 million square miles in South America, the Amazon is the largest of the world's tropical forests, which play huge ecological roles for the planet despite covering less than 10% of the Earth's land area. More than half of all carbon stored in aboveground biomass is sequestered in tropical rain forests, which are also home to greater than 60% of all terrestrial species. Second growth and degraded forests now cover more area than intact forests, but scientists say the full extent of tropical forest degradation is not completely known.