By Joe Morrison on October 9th, 2020
We joined with Radiant Earth at the Cloud Native Geospatial Sprint to run a labeling competition for non-technical folks. This resulted in over 2.3 million square kilometers mapped and lots of lessons learned.
By Joe Morrison on August 10th, 2020
Raster Vision is the interface between the fields of earth observation and deep learning, making it easier to apply novel computer vision techniques to geospatial imagery of all types. Joe lays out how it can be implemented in your organization and give you a competitive advantage.
By Joe Morrison on February 2nd, 2020
Cities may not know it, but by nature of collecting and maintaining various datasets, they are sitting on a treasure trove of machine learning-ready training data.
By Joe Morrison on January 2nd, 2020
Every project with satellite imagery begins with a data source. Here's a rundown of the best options, considering cost, usability, and resolution.
By Joe Morrison on December 13th, 2019
How accurate are our supervised machine learning models and what are they really doing? We offer 3 tips to help you better understand these models.