While Google Maps is a useful enough tool for directing you up and down Manhattan’s urban grid of avenues of streets on a daily basis, what about industries who want to examine the world on a larger scale, from multiple angles, and in real-time?
Enter Descartes Labs, a venture-based start-up that is gaining traction as one of the most exciting platforms to come out of the geospatial industry. Harnessing the power of cloud computing, machine learning, and global sensors, Descartes Labs is modelling daily environmental, commercial, and economic processes on a global scale, in real time. Their composite maps don’t just show you highways and streets: they can track vegetation health across countries, predict crop yields, forecast which locations that are at risk of famine, and more.
At present, Descartes Labs have compiled three composite global atlas platforms available in Landsat 8, Sentinel-1, and Sentinel-2.
The three names refer to three different satellites that capture and archive earth imagery. Landsat 8, launched in 2013, was developed by NASA and the U.S. Geological Survey. Containing two instruments called the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Landsat 8 captures seasonal coverage of global landmass at a resolution of 30 meters per pixel. As Landsat 8 holds the record for capturing data about the Earth’s surface for the longest amount of time, it has the largest and, therefore, most useful archive of information out of the three satellites.
Sentinel-1 and Sentinel 2, however, were both launched by the European Space Agency (ESA) as part of the Copernicus initiative in 2014 and 2017 respectively. While Sentinel-1 and Sentinel-2 are both younger than Landsat 8, they use Synthetic Aperture Radar (SAR) to capture images at a higher resolution of 10 meters per pixel, and they also have a higher revisit frequency (how frequently images are recorded at a given location).
Taking the data provided by the three satellites, Descartes’ global atlases organizes this vital information for a wide audience that comprises not only of the agricultural industry, but also international supply chain companies, hedge funds that require new quantitative multi-modal sources of business intelligence, and researchers in academia.
Descartes Labs is hoping to attract CDS students who are interested in machine learning, image capture, and geo-spatial research to join their team.
by Cherrie Kwok