There are many ways in which machine learning and artificial intelligence can be used to improve environmental sustainability. In the context of climate change, a landmark report outlines several relevant areas, including applications in energy systems, transportation, buildings and cities, industry, farms and forests, carbon removal, climate adaptation, individual actions, and climate science. Within the comic, we have selected some exemplary use cases.
The first panel starts with one of the most important areas where artificial intelligence is already indispensable: the distilling of diverse remote sensing data from satellites, drones, sensors and cameras into meaningful insights. For example, computer vision models can learn from a few examples labeled by humans and then potentially scale to new places where data is missing. This has many applications, from feeding climate and weather models to assessing the impact of climate change, tracking actions such as tree planting, precision agriculture, estimating CO2 emissions, finding methane leaks, census animal and species populations, and planning disaster recovery efforts.