Skoltech researchers have trained a neural model to determine the height of trees to monitor the natural environment, infrastructure, and timber supply.
A neural network has learned to identify tree species from satellite
zmescience.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from zmescience.com Daily Mail and Mail on Sunday newspapers.
Learning aids: Skoltech method helps train computer vision algorithms on limited data
eurekalert.org - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from eurekalert.org Daily Mail and Mail on Sunday newspapers.
Credit: Svetlana Illarionova et al., IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
Skoltech scientists have developed an algorithm that can identify various tree species in satellite images. Their research was published in the
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
Identifying tree species is essential for efficient forest management and monitoring. Satellite imagery is an easier and cheaper way to deal with this task than other approaches that require ground observations of vast and remote areas.
Researchers from the Skoltech Center for Computational and Data-Intensive Science and Engineering (CDISE) and Skoltech Space Center used a neural network to automate dominant tree species identification in high and medium resolution images. A hierarchical classification model and additional data, such as vegetation height, helped further enhance the predictions quality while improving the algorithm s stabi