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?
Betting Big on the Spatiotemporal Asset Catalog (STAC) Standard
By Joe Morrison on November 22nd, 2019
We're investing heavily in the STAC specification - including building a STAC-compatible Python library and server as well contributing to the Label Extension. We're hoping this work will help accelerate adoption across the geospatial engineering community more broadly.
An Introduction to Satellite Imagery and Machine Learning
By Joe Morrison on November 5th, 2019
Today, the availability of satellite imagery still far outpaces our capacity to analyze it, but machine learning and tools like Raster Vision are helping.
Azavea and CloudFactory: Partners on Quality Training Data and Social Impact
By Joe Morrison on October 8th, 2019
Read about our journey to hiring an outsourced data labeling firm and how we’ve found a partner in CloudFactory.
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.