Explore Our Research

Atlas AI develops high-quality and high-resolution data for data sparse environments. We advance research developed at Stanford University centered on the application of cutting edge AI techniques in the fields of Earth Science and Development Economics. Scientific rigor, reliability and transparency are at the center of everything we do.

Yeh, C., Perez, A., Driscoll, A., Azzari, G., Tang, Z., Lobell, D., ... & Burke, M. (2020). Using publicly available satellite imagery and deep learning to understand economic well-being in Africa. Nature communications, 11(1), 1-11.

Jin, Z., Azzari, G., You, C., Di Tommaso, S., Aston, S., Burke, M., & Lobell, D. B. (2019). Smallholder maize area and yield mapping at national scales with Google Earth Engine. Remote Sensing of Environment, 228, 115-128.

Wang, S., Azzari, G., & Lobell, D. B. (2019). Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques. Remote sensing of environment, 222, 303-317.

There's so much more to learn

GISMachine Learning

What are convolutional neural networks?

Convolutional Neural Networks (CNNs) are one important subset of deep learning models that are particularly useful for processing image input data.

Machine Learning

What is machine learning?

Machine learning is a family of techniques that use data and experiences to create an interpretation of patterns in the world and use that interpretation to answer questions about the world.

Machine LearningRemote SensingGIS

Machine learning on remote sensing? What does that even mean?

Machine learning on satellite imagery has a long history, but an understanding of its possible role in the developing world came a little later than it did for other data sources.