Initiative to foster broad SAR adoption and accelerate machine learning applications
SAN FRANCISCO, August 21, 2019 — Capella Space, an information services company that provides on-demand Earth observation imagery, today announced its partnership with SpaceNet®, a nonprofit organization dedicated to accelerating open source, artificial intelligence (AI) applied research for geospatial applications. Capella joins the collaborative SpaceNet partnership alongside In-Q-Tel’s (IQT) CosmiQ Works, Maxar Technologies, Intel AI and Amazon Web Services (AWS). Capella’s addition to the partnership presents an exciting opportunity to expand SpaceNet’s existing geospatial open source research to a new data type, Synthetic Aperture Radar (SAR). Opening access to this data will help broaden the use of high-quality SAR in a variety of geospatial analytic applications.
“SAR promises substantial value for a wide variety of geospatial applications because, unlike satellite imagery, it is not limited by weather or lighting conditions. Furthermore, SAR phase data can offer additional insights into a particular location such as land subsidence,” said Ryan Lewis, Senior Vice President at IQT and General Manager of SpaceNet. “Capella’s contribution of an open-source, high-resolution SAR data set is an important next step for SpaceNet, and we are excited to see how participants use this data for machine learning models in an upcoming challenge.”
There is tremendous potential in applying machine learning to SAR data for a range of applications, from natural disaster response to monitoring global supply chain activity, but the industry still faces significant barriers to adoption. Developers and data scientists lack open data and software tools. Capella seeks to help overcome these obstacles through its partnership with SpaceNet and the development of a new SAR user community.
“Traditionally, this type of high-resolution SAR data has only been used by governments for defense applications and has not been easy to access. By opening access to this type of data and lowering barriers to adoption, we aim to foster broad and rapid advances in commerce, conservation and well-being across many industries,” said Andrew Ulmer, Vice President of Business Development at Capella Space. “We encourage industry leaders, academics and NGOs to experiment with the data, as it’s our collective imagination that will unlock the most value and transform how we live.”
The Capella User Community will broaden the adoption of high-resolution SAR data to solve a range of global issues. Data scientists and software engineers will have access to free and open Capella data along with tools and techniques to work more easily with SAR data. The company invites academics, non-government organizations (NGOs), governments, and companies to join Capella’s User Community at capellaspace.com/community.
About Capella Space
Capella Space is an information services company that provides on-demand Earth observation imagery. Through a constellation of small satellites, Capella is providing easy access to frequent, timely and flexible information affecting dozens of industries worldwide. Capella’s high-resolution synthetic aperture radar (SAR) satellites are matched with unparalleled infrastructure to deliver reliable global insights that sharpen our understanding of the changing world – improving decisions about commerce, conservation and well-being on Earth. Learn more at capellaspace.com.
SpaceNet is a nonprofit organization dedicated to accelerating applied research in geospatial machine learning by developing and providing publicly available commercial satellite imagery and labeled training data, as well as open sourcing computer vision algorithms and tools. Designed to lower the barrier to entry for developers, researchers and startups to access high-quality geospatial data, SpaceNet focuses on four key open source pillars: data, tools, challenge, and algorithms. SpaceNet is a collaborative initiative between CosmiQ Works, Maxar, Intel AI, Amazon Web Services, and Capella Space. Learn more at spacenet.ai.