SAN FRANCISCO – Descartes Labs unveiled Jan. 22 a cloud-based platform for commercial customers that pairs geospatial datasets with modeling tools and applications.
Many companies don’t employ computational software, remote sensing and machine learning experts. The Descartes Labs Platform offers analysts within those companies the tools necessary to draw relevant information from geospatial datasets, Sam Skillman, Descartes head of engineering, told SpaceNews.
The Descartes Labs Platform could, for example, help customers identify all the areas on Earth with similar geophysical or geological properties.
“It supercharges how you think about visualizing and inspecting data in a high-dimensional space,” Skillman said. “This is not red, green, blue visible wavelengths. This is looking across a multispectral set of characteristics.”
Descartes Labs is not the first company to unveil a cloud-based geospatial data platform. In 2015, DigitalGlobe, now part of Maxar Technologies, rolled out the cloud-based GBDX platform to pair satellite imagery with analytics. What makes the Descartes Labs Platform unique, Skillman said, is the diversity of geospatial datasets included and the platform’s orientation toward commercial customers.
“We’re finding ways to bring remote sensing data and analytics to companies that didn’t know they could utilize that data,” Skillman said.
Sustainability is likely to be a popular application for the Descartes Labs Platform, Skillman said.
“The Descartes Labs Platform was built to model the physical world,” Phil Fraher, Descartes Labs CEO, said in a statement. “Predictive models empower business leaders to save on costs and implement novel strategies to address climate and sustainability challenges.”
The Descartes Labs Platform, powered by a cloud-run supercomputer, is designed to help companies make forecasts related to agriculture, energy, sustainability, mining, shipping, financial services and insurance, according to the Jan. 22 news release.
The Descartes Labs Platform pairs the firm’s “Data Refinery,” petabytes of geospatial data prepared for easy analysis, with applications and a workbench full of models and visualization tools.
Since Santa Fe, New Mexico-based Descartes Labs spun off from the U.S. Energy Department’s Los Alamos National Laboratory in 2014, the firm has focused on applying powerful computers and machine learning to draw insight from remote sensing data.