Researchers demonstrated that <\/strong>data<\/strong><\/a> from the International Space Station\u2019s ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) instrument played a significant role in the ability of machine learning algorithms to predict wildfire susceptibility. This result could help support development of effective strategies for predicting, preventing, monitoring, and managing wildfires.<\/strong><\/p>\n<\/p>\n As the frequency and severity of wildfires increases worldwide, experts need reliable models of fire susceptibility to protect public safety and support natural resource planning and risk management. ECOSTRESS<\/a> measures evapotranspiration, water use efficiency, and other plant-water dynamics on Earth. Researchers report that its water use efficiency data consistently emerged as the leading factor in predicting wildfires, with evaporative stress and topographic slope data also significant.<\/p>\n Combining instruments provides better emissions data<\/strong><\/p>\n<\/p>\n Scientists <\/strong>found<\/strong><\/a> that averaging data from the International Space Station\u2019s OCO\u20103 and EMIT external instruments can accurately measure the rate of carbon dioxide emissions from power plants. This work could improve emissions monitoring and help communities respond to climate change.<\/strong><\/p>\n<\/p>\n Carbon dioxide emissions from fossil fuel combustion make up nearly a third of human-caused emissions and are a major contributor to climate change. In many places, though, scientists do not know exactly how much carbon dioxide these sources emit. The Orbiting Carbon Observatory-3 or OCO-3<\/a> can quantify emissions over large areas and Earth Surface Mineral Dust Source Investigation<\/a> data can help determine emissions from individual facilities. The researchers suggest future work continue to investigate the effect of wind conditions on measurements.<\/p>\n![\"\"](\"https:\/\/www.nasa.gov\/wp-content\/uploads\/2025\/01\/pia25488orig.jpg?w=2048\")
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