We are a British based Limited company founded by PhDs combining expertise in Machine Learning, Deep Learning, Data Science, Remote Sensing, Planetary Science and Space Engineering. We are backed by the world's leading talent investor and have been developing our deep technology since 2016. Our flagship product is the innovative Predictive Crop Yield Index Insurance (PYII) based on predicting crop yields using machine learning analysis of satellite, soil and weather data. Currently available in Ukraine, this is area crop yield index insurance which covers the entire country with insurance coverage for eight crops (including sunflower, winter wheat and maize) at rayon level (also offered at oblast level) in Ukraine. Request a two-part report for more information including insurance pricing and payout accuracy information using the form below.
Dr Steven R Tsitas
Dr Steven R Tsitas has a PhD in Planetary Science from the California Institute of Technology (Caltech), a Masters in Astronautics and Space Engineering from Cranfield University (where he was awarded the Vega Space Systems Engineering Prize for Excellent Performance in Dynamics Related Subjects), a Master of Science in Planetary Science, a Master of Science with Distinction in Physics and a Bachelor of Science (Honours) in Physics. He was the first to publish a peer reviewed journal paper on the system design of a 6U CubeSat capable of pushbroom imaging to a similar standard as an existing commercial satellite. His innovative 6U CubeSat work is referenced in Wikipedia and has received extensive media coverage, including :
Ring In The New, Special Report Innovation, Qantas The Australian Way Inflight Magazine
From little things big things grow, Neos Kosmos
Nano-satellite offers best hope for Australia's future in space, Space Daily
Shoebox-size craft could put Australia in space, ABC Science
Small space has a big future, The Drum Opinion
Dr Phong D Vo
Dr Vo has a PhD in Signal and Images from Télécom ParisTech, plus two other degrees in Computer Science. His thesis, funded by the French Space Agency, proposed a new class of machine learning algorithms requiring little annotation efforts, and has potential applications for satellite images. He further explored this work using deep learning technology during a Postdoctoral Fellowship at the French Alternative Energies & Atomic Energy Commission. With expertise ranging from machine learning to computer vision, he is also a reviewer for several remote sensing journals.
At Kubesee, Dr Vo has been leading in research and development an end-to-end framework of predictive crop yield, bringing raw satellite image data of arable crop fields to insights for insurance payouts, for multiple crops and national wide.
Earth Observation Technologies
Kubesee uses long-term high quality Earth observation data publicly available from NASA, NOAA and ESA. Some of the satellites we use are listed below. More information about our data sources is given in a two-part report which can be requested using the form below.
The flagship of the Earth Observation System, Terra is a multi-national NASA scientific research satellite. Terra is almost 7 m long and 3.5 m wide and weighs 5,190 kg. Terra carries five instruments capable of simultaneous observations of the Earth’s surface and atmosphere. Terra was launched by NASA into a sun synchronous orbit on 18 December 1999. The MODIS instrument carried by Terra is known for its long time series of high temporal resolution images of land, ocean and clouds with a spatial resolution as good as 250 meters, daily revisit rate and 36 spectral bands. Applications of the MODIS instrument include the monitoring of vegetation (including crop) health, deforestation, changes in the water levels of major lakes, forest fires and global snow cover changes.
Smaller than Terra but still a large satellite at 2,934 kg, the NASA Aqua scientific research satellite was launched 2.5 years after Terra in May 2002, with on-board instruments collecting information about the Earth’s water cycle including precipitation, evaporation, clouds and precipitation. Aqua is also equipped with a MODIS instrument, which provides high temporal resolution images of land, oceans and clouds with a daily revisit rate and spatial resolutions as good as 250 meters.
The latest generation of environmental satellites, NOAA-20, together with previous generations have maintained a long term time-series of Earth observation data going back to the 1980s. NOAA-20 was launched into a sun synchronous orbit on November 18 2017 and has a mass of 2,294 kg. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on NOAA-20 is a moderate resolution imaging instrument that observes the Earth’s land, oceans and atmosphere in visible and infrared light with 22 bands (colours) at high temporal resolution. VIIRS data is compatible with MODIS data from the Terra and Aqua satellites.
This 464 kg polar orbiting weather satellite, operated by NOAA, was launched in 2011. Soumi NPP carries a VIIRS instrument which is a 22-band radiometer designed to collect infrared and visible light observations of land, the oceans and atmosphere.