Message: Terra Bella (Google Company) formerly Skybox Imaging
Terra Bella (Google Company) formerly Skybox
On June 10, 2014, Skybox Imaging announced that it had entered into an agreement to be acquired by Google for US$500 million.[18][19]The acquisition was completed on August 1, 2014.[19][20]
https://terrabella.google.com/
https://en.wikipedia.org/wiki/Terra_Bella
Our satellites
We are building an entirely new class of imaging satellites. We’ve developed a high-resolution, small satellite platform capable of rapid response, high-resolution imagery at a fraction of the cost of traditional imaging satellites.
One of the key enablers of this breakthrough is our ability to capture high-resolution color and near-infrared imagery (90 cm resolution) in a small <100 kilogram package. It’s like taking a picture of San Diego from San Francisco and being able to see objects up to the size of a car while moving at 5 miles per second.
We also use a two-dimensional sensor array with a proprietary image filter to capture a higher quality image by taking multiple frames per second and stitching them on the ground. This also gives us the ability to capture the first-ever commercial high-resolution video of Earth from a satellite.
We’ve launched the first seven satellites of our constellation which are continuing to capture beautiful imagery and video across the globe. Our second generations satellites (SkySat-3-7) include a propulsion module to support orbit-stationing and enable improvements in resolution. As we continue to grow our constellation, we will be able to construct a living, breathing snapshot of any location in the world within hours, and tackle more problems around the globe.
- Small size, big performance
- <100 kg: 60cm x 60cm x 80cm
- Precision attitude control (star trackers, reaction wheels, gyros, gps)
- Proprietary Imaging Chain
- Custom-designed, cutting-edge Silicon Carbide telescope
- High-frame rate CMOS image sensors
- <90 cm imagery resolution (Pan, RGB, NIR)
- 1.1 meter video resolution at 30 frames per second
from 600 kilometers
- High-Speed Radios
- >480 Mbit/s X-band
- downlink rate
- S-band uplink
Our history
2009The Sky is Not The Limit
2010Rethinking Aerospace
2011Designing for Scale
2012Agile Ground and Space Dev
2013Go for Launch
2014Onwards and Upwards
2015Preparing for scale
Founders (Dan Berkenstock, Julian Mann, John Fenwick, and Ching-Yu Hu) wrote the first business plan as part of a Stanford graduate entrepreneurship course.
Spent 6 months working out of John’s living room.
Secured Series A financing of $3M from Khosla Ventures.
Moved into a windowless 3,000 sqft office in Palo Alto.
Began to attract, court, and hire the smartest people they knew to join the vision.
Began designing the data platform and high-resolution imaging satellites.
Began expanding our network of customers, partners, and suppliers.
Moved to Mountain View and began building out our testing and manufacturing facility.
Completed Series B financing of $18M from Khosla Ventures, Bessemer Venture Partners.
Designed scalable data infrastructure.
Completed satellite Critical Design Review for SkySat-1 and SkySat-2.
Began building out mission control team.
Completed Series C financing of $70M from Canaan Partners, Norwest Ventures, Bessemer Ventures, and Khosla Ventures.
Completed proprietary image processing toolbox and tasking and scheduling algorithms.
Completed design and fabrication of SkySat-1; began SkySat-2.
Partnered with ECAPS on propulsion module for SkySat-3 and beyond.
Completed design, manufacture, and test of first two spacecraft SkySat-1 and SkySat-2 and Terra Bella HQ.
Completed mission operations and production infrastructure to fly our constellation via Chrome.
Acquired by Google.
Successfully launched SkySat-2 aboard a Soyuz-2/Fregat rocket.
Bought an Orbital Sciences Minotaur-C rocket to launch 6 additional SkySats out of Vandenberg Airforce Base in 2016.
Bought an Arianespace rocket to launch 4 additional SkySats out of French Guiana in 2016.
Began integrating Terra Bella infrastructure into Google from data processing, archiving, scheduling and optimization, to machine learning technologies.
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