Raster Vision Archives | Page 2 of 3

Azavea team team leading GIS training in Guyana.

Ethical Machine Learning for Disaster Relief: Rage for Machine Learning

By Niki LaGrone on December 10th, 2019

ML's predictive powers are driving a rage for deep learning in the crisis management and disaster relief industries. How can these powers be harnessed for ethical machine learning?

Software Engineering

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?

Software Engineering

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.

Screenshot of labeled satellite imagery in Raster Vision.

Company

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.

Satellite imagery displaying machine learning labels.

Software Engineering

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.

Software Engineering

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.