Ethical Machine Learning for Disaster Relief: Avoiding the Second Disaster
By Niki LaGrone on November 25th, 2019
Machine learning on satellite imagery is revolutionizing disaster relief. What does ethical machine learning mean in this field?
STAC: Creating an Ecosystem of SpatioTemporal Assets
By Niki LaGrone, James Santucci and Aaron Su on October 1st, 2019
STAC is creating an ecosystem of interoperable spatiotemporal assets. Learn how Azavea has contibuted and about future steps for the specification.
Is This a Crosswalk?: 5 Takeaways from Training a Data Labeling Team
By Niki LaGrone on September 13th, 2019
We trained remote computer vision workers to provide data labeling for machine learning projects. Here's what we learned.
Introducing WMS and WCS Support for GeoTrellis and Raster Foundry
By Nathan Zimmerman on July 3rd, 2019
Raster Foundry and GeoTrellis now support WMS and WCS standards, enabling streamlined workflows that utilize multiple data sources.
Lessons in Functional API Development from Haskell’s Servant and Http4s
By James Santucci on May 20th, 2019
As a 10% time project, we replicated a small piece of the Raster Foundry backend code in Haskell, using servant for the REST interface and postgresql-simple for database interaction.
Aster Vision – A New Open Source Framework for Deep Learning on Astrospatial Imagery and Space Exploration
By James Santucci on April 1st, 2019
Aster Vision is an open source machine learning library for analyzing huge troves of astrospatial data and finding habitable planets around nearby stars.