SilviaTerra is using aerial imagery and AI to survey forests at a national scale, transforming how conservationists and landowners measure and monitor forests.Learn about SilviaTerra
Conservationists and landowners need to inventory forests to understand and make decisions supporting their management goals. This data can help determine the effects climate change has on sustainable land practices, support or improve species habitat, and provide a more sustainable timber harvest. But taking forest inventories is labor-intensive. Foresters must manually count trees across thousands of acres—a slow, costly, and occasionally unreliable process.
SilviaTerra is revolutionizing how we inventory forests by combining satellite imagery with machine learning to reduce manual fieldwork while improving data precision and quality. Running on Microsoft Azure, SilviaTerra collects high-resolution satellite images and combines it with pre-existing field data to create detailed maps of forests at a 15-meter resolution. Conservationists, governments, and landowners can use these maps to assess their forests and develop sustainable management plans for a fraction of the time and cost of traditional forest surveys.
Mapping the future of our forests
Forest managers depend on detailed forest inventories to better understand the effects of climate change and protect habitats. SilviaTerra uses Microsoft Azure, high-satellite and aerial imagery, and US Forest Service field data to train machine-learning models that monitor forests.
How SilviaTerra works
High-resolution satellite imagery is stored on Azure and paired with field data from the US Forest Service to train machine-learning models for predicting the sizes and species of trees. Azure HDInsight applies these models to terabytes of images. The result is a high-resolution, tree-level map with unprecedented information about forests.