Reflections from the UN World Data Forum
By Ross Bernet on November 9th, 2018
Azavea attended the UN World Data Forum in Dubai last week and learned how Earth Imagery can be applied to Sustainable Development Goals (SDGs).
Raster Vision: A New Open Source Framework for Deep Learning on Satellite and Aerial Imagery
By Rob Emanuele on October 18th, 2018
Azavea is pleased to announce the release of Raster Vision, a new open source framework for deep learning on satellite and aerial imagery.
Predicting Land Use in the Amazon using Deep Learning
By Lewis Fishgold and Annie Zhao on January 3rd, 2018
Learn about our methods and results leveraging our RasterVision deep learning project to predict land use in satellite images of the Amazon.
Serving Tiles with GeoTrellis, Lambda, and API Gateway
By James Santucci on October 30th, 2017
Have this open source serverless tile server built with the Serverless framework, AWS Lambda, AWS API Gateway, and GeoTrellis up and running in minutes.
Video: Using Convolutional Neural Networks to Automatically Analyze Aerial and Satellite Imagery
By Lewis Fishgold on September 6th, 2017
In this recording of our most recent Technical Staff Meeting, we walk through our team’s work on Raster Vision, a...
Deep Learning for Semantic Segmentation of Aerial and Satellite Imagery
By Lewis Fishgold and Rob Emanuele on May 30th, 2017
This post describes how to use deep learning to do semantic segmentation on aerial and satellite imagery, experiments on the ISPRS Potsdam dataset, and how to visualize model predictions on a map.