RECRUITERS Post your GeoJob Ad Today
Lightning Talk, Training Workshop Planned
LOS ALAMOS, N.M., May 25, 2017 – Descartes Labs Inc., a pioneer in cloud-based geospatial analytics, will unveil its global-scale machine learning Platform to the Defense/Intelligence Community at the 2017 GEOINT Symposium in San Antonio. The Platform powers geographic and temporal analysis of remote sensing data to identify objects, forecast change and deliver high-performance intelligence solutions.
GEOINT attendees can learn more about Descartes Labs at booth #1325 in the GEOINT Exhibit Hall, which is open June 5-7. Descartes will also present a Lightning Talk at GEOINT Forward on Sunday, June 4, and conduct a Training Workshop on Tuesday, June 6.
Established in 2014 as a spin-off from Los Alamos National Laboratory, Descartes Labs developed the secure cloud-based Platform to leverage machine learning and proprietary forecasting models to deliver business intelligence products for government, industry, and academia. The Platform taps into a massive archive of historical Earth imagery that is updated daily from multiple satellites including Landsat 8, MODIS, and Sentinel 1/2/3 for local, regional and global analysis.
“The Descartes Labs Platform quickly analyzes petabytes of real-time and archived imagery to assess subtle changes on the ground – such as a failing harvest – that could impact national security or regional stability,” said Mark Johnson, Co-founder and CEO of Descartes Labs. “Accurately identifying change and predicting results enable organizations to put vital resources in place to avert potential crises.”
Complex searches of the imagery archive in the cloud can be performed based on acquisition date, cloud cover, sensor types, bands and other parameters. Raster functionality allows retrieval of selected imagery, performance of on-the-fly band calculations and time stacks for temporal analysis.
Also at GEOINT 2017, Descartes Labs will showcase GeoVisual Search (GVS) powered by the geospatial analytics Platform. By clicking on any map-based object through any browser, such as a wind turbine or airport, GVS instantly processes satellite and aerial imagery in the cloud to find visually similar features around the world or within specific geographic or temporal confines. The results are presented instantly on a map with thumbnail images.
“The Platform will provide GEOINT professionals with the capabilities to do their jobs, based on their needs, through the best commercial imagery resource with faster and greater accuracy,” said Johnson. “These extremely sophisticated tools are designed to accelerate science at all levels of Defense/Intelligence, Homeland Security, civilian public safety along with other government and commercial interests.”
Descartes Labs will be featured in two additional events at GEOINT:
Lightning Talk at GEOINT Forward, 2:40 pm on June 4 – Descartes Co-founder & Chief Science Advisor Steve Brumby will discuss specific GEOINT applications of Platform technology. (Please note there is an extra fee to attend GEOINT Forward events.)
Descartes Labs Workshop Training Session, 7-9 am on June 6, River Level 006C – Dr. Daniela Moody presents “Fast Prototyping of Satellite Imagery Analysis Algorithms Using Open Source Software and Cloud Computing Infrastructures.” (Training sessions can be added on to your registration and are not included in the Symposium Pass registration. Each training session is $25 for USGIF Members and $30 for USGIF Non-Members.)
About Descartes Labs
Descartes Labs is a technology company advancing the science of forecasting by creating the first breathing atlas of the world. The team has developed a platform that applies machine learning to massive data sources like satellite imagery, resulting in better forecasting, monitoring, and historical analysis. Descartes Labs’ mission is to ask the hard questions and solve the most challenging forecasting problems today, so we can better understand the happenings of planet Earth and prepare for the future. Descartes Labs was founded in 2014 and is based in Santa Fe, New Mexico.