A neural network could size up trees from satellite images, according to new research.
From environmental scientists to civil engineers and wood industry workers, there are many people who require accurate estimates of forest tree size. This information is vital for understanding how much atmospheric carbon dioxide the trees are capturing, whether there’s risk of them damaging power lines, and how much timber is available for logging.
Currently, these estimates are obtained from satellite images as well as multiple cameras spanning several bands of infrared radiation, as drone technology is ineffective in large and hard to reach regions. However, this multispectral data is scarce and expensive to acquire.
Researchers from Moscow-based research institute Skoltech may have found the perfect alternative, as they have been able to train a neural model to determine tree height in a reliable and cost-effective manner.
Unlike prior solutions, the model presented...