Global Marketing Insights at “Small Satellites Big Data Conference”

Cleveland, OH August 3, 2017 – Global Marketing Insights Inc., a pioneer in geospatial business intelligence and geospatial market research, will assist in demonstrating the big data processing capabilities of global-scale machine learning platforms next week at the 2017 Small Satellites Big Data Conference.

Developers of Earth imaging smallsat constellations will be invited to learn more about these capabilities during a presentation when Dr. Shawana Johnson, GISP, of Global Marketing Insights will co-present Platforms Designed for Big Data Provisioning with Small Satellite Constellations on Thursday, August 10, at 8:45 am in a Technical Session.

Come to the session to learn more about secure cloud-based platforms leveraging geospatial analytics, machine learning and forecasting models to deliver business intelligence products for government, industry, and academia tapping into massive archives 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.

“Small satellite constellations can collect petabytes of image data that must be analyzed quickly and accurately for the derived information to have value,” said Dr. Johnson, Chairman of the Board, Global Marketing Insights, Inc. “Machine learning platforms offer the big data compute power that these vigilant surveillance small satellite constellations need to perform the temporal analysis critical to their missions.”

Johnson explained, “Machine learning platforms power geographic and temporal analysis of remote sensing data to identify objects, forecast change and deliver high-performance intelligence solutions. The platforms have been developed to ingest archived and new imagery captured by legacy satellite systems, such as Landsat and Sentinel, in addition to data from all launched and planned small satellites.”

The 2017 Small Satellite Conference is being held August 5-10 in Logan, Utah.