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The rapid pace of new commercial satellite constellation launches has led to a corresponding increase in the amount and availability of geospatial data. While these constellations largely focus on non-military uses, their data has numerous military applications. For example, the new constellations provide optical, synthetic aperture radar (SAR), and Radio Frequency (RF) data that could provide situational awareness, event detection, monitoring, and tracking capabilities. Unlike traditional geospatial data collection approaches, these constellations provide global coverage at high revisit rates without requiring specific tasking.
Further, non-satellite geospatial data is also now widespread, including crowdsourced information such as OpenStreetMap, which provides insight on places and objects. There is currently no comprehensive repository or straightforward way to access and exploit this multimodal data.
Unfortunately, no straightforward way currently exists for analysts to access and analyze all of that imagery. The current ad hoc, time-intensive approach requires gathering and curating data from a large number of available sources, downloading it to specific locations, and running it through separate suites of analytics tools.
To help overcome these challenges, DARPA’s new Geospatial Cloud Analytics (GCA) program seeks to enable instant access to the most up-to-date images anywhere in the world, as well as cutting-edge tools to analyze them. It would achieve this capability by virtually aggregating vast amounts of commercial and open-source satellite data that is available in multiple modes—optical, synthetic aperture radar (SAR), and radio frequency (RF)—in a common cloud-based repository with automated curation tools. The platform and tools would provide DoD geospatial analysts global situational awareness, event detection, monitoring, and tracking capabilities beneficial to U.S. forces around the world.
In addition to developing a scalable geospatial data platform with tools and a user interface, GCA aims to create analytical applications that would allow analysts at the operational and tactical level to draw specific information from the aggregated data. GCA will pilot an analytical services business model where commercial entities offer analytics services and apps via a competitive marketplace.
“The goal of GCA is to provide a secure cloud-based platform that automatically curates multi-source global data and metadata, allowing analysts to focus their attention and expertise on analysis—not data collection, aggregation, and curation,” said Joe Evans, program manager in DARPA’s Strategic Technology Office (STO). “The vision is for commercial analytics providers to use the common data platform to develop and offer their services in an analytics marketplace. This marketplace framework would allow the DoD to more cost-effectively leverage constantly refreshed, robust commercial analytics services.”
To test the utility of the cloud-based platform and apps in the analytics marketplace, the GCA program will look at problems at a variety of time scales. These include predicting food shortages in a region of the world (weeks to months), locating the construction of oil fracking sites (days to weeks), illegal fishing detection (minutes to days), and an open-call scenario where proposers may suggest other problems of military relevance.
DARPA Awards Maxar 2nd Contract for Geospatial Cloud Analytics Hub
Maxar Technologies was awarded a follow-on contract valued at $4.3 million by the U.S. Defense Advanced Research Projects Agency (DARPA) to test its Geospatial Cloud Analytics (GCA) Hub, in May 2019. The GCA Hub is an unclassified environment with multi-source content that helps enable military users to leverage Machine Learning (ML) to extract insights about the planet at scale and make critical decisions for projects like predicting food shortages, political unrest and Illegal, Unreported, and Unregulated (IUU) fishing. This raises Maxar’s total award amount for the GCA Hub to $7.5 million.
Under its first GCA Hub contract awarded by DARPA in 2018, Maxar built the cloud-based GCA Hub on the foundations of its Geospatial Big Data (GBDX) platform, a commercially-developed, cloud-based analytics platform. Maxar integrated 18 geospatial data sources, including its 100-petabyte high-resolution optical satellite imagery library, RADARSAT-2 Synthetic Aperture Radar (SAR) data and SAR data curation and processing tools, Automatic Identification System (AIS) data, open-source and commercial data provided by the company’s growing list of content ecosystem partners. These datasets help users detect features and changes on the surface of the Earth faster and more accurately.
Descartes Labs will receive up to $7.2 million from DARPA
A New Mexico startup called Descartes Labs will receive up to $7.2 million from the Defense Advanced Research Projects Agency (DARPA) to help bring geospatial data from satellites to the cloud.
Images of Earth, ranging from traditional optical photos to heat imagery and cloud-penetrating radar snapshots, are increasingly widely available from a variety of satellite sources. They can be used for everything from analyzing global changes in the oil market to predicting where food shortages might pop up around the world.
The trouble is that those images can still be unwieldy to work with. Huge volumes of raw data of various types arrive every day, and that information must be processed, standardized, and cleaned up to make it usable by analysts and uploaded to a cloud environment powerful enough to process it efficiently.
“For some of these analyses, you’re talking terabytes and terabytes of data,” says Descartes Labs CEO Mark Johnson.
In a first, roughly six-month phase of the project, Descartes Labs will receive $2.9 million from DARPA to build out cloud infrastructure that can be used to import, store, and process geospatial data as part of what DARPA calls its Geospatial Cloud Analytics program. The system will integrate up to 75 different types of data from a variety of sources.
If all goes well, a second yearlong phase will see Descartes Labs get another $4.2 million to support organizations building data models and automated processing tools on top of its cloud for specific sample projects, according to the company.
Those will include spotting potential food shortages, detecting oil fracking site construction and detecting illegal fishing operations, according to DARPA. Ultimately, the agency envisions an open marketplace where analytics providers can offer services, machine learning algorithms and automated apps to military and other users to parse and slice data in various ways.
“The goal of GCA is to provide a secure cloud-based platform that automatically curates multi-source global data and metadata, allowing analysts to focus their attention and expertise on analysis—not data collection, aggregation, and curation,” said Joe Evans, a partner in DARPA’s Strategic Technology Office, in a statement announcing the program last fall. “The vision is for commercial analytics providers to use the common data platform to develop and offer their services in an analytics marketplace. This marketplace framework would allow the Department of Defense to more cost-effectively leverage constantly refreshed, robust commercial analytics services.”
More efficient processing can help make human analysis of certain types of images more practical by filtering out irrelevant data, Johnson says.
“If they have to look at tens of thousands of images, that’s a really expensive process,” he says. “It’s really about augmenting them with machine intelligence.”
Descartes Labs, which spun out from Los Alamos National Laboratory in 2015, won’t be the only company building a cloud system as part of the DARPA project. BAE Systems, a defense contractor that has done other geospatial work in the past, is also building out its own infrastructure with $2 million DARPA funding.
BAE Systems to help DARPA provide intelligence analysts with satellite imagery using cloud computing
GCA seeks to create scalable computer cloud-based repository of global satellite data, make it accessible via common interfaces, and start developing analytics-as-a-service for U.S. military users.
BAE Systems experts will try to do this virtually in a common cloud-based repository with automated curation tools that would provide global situational awareness, event detection, monitoring, and tracking capabilities. The project also aims to create analytical applications to enable analysts to draw specific information from the aggregated data.
GCA will carry out an analytical services business model where commercial entities offer analytics services and applications via a competitive marketplace.
In this project, BAE Systems experts will look at problems at a variety of time scales, such as food shortages over a period of weeks or months; locating oil fracking sites or days and weeks; detecting illegal fishing over minutes to days; and an open-call scenario where proposers may suggest other problems of military relevance.
Other companies will be working on procuring and processing data for use in the cloud systems: GeoNorth Information Systems, based in Anchorage, will be transforming satellite data for use in the Descartes Labs platform, says Jonathan Heinsius, general manager and director of geospatial programs at GeoNorth.
“We can normalize that data, so if you have, say, a number of images over a given area that were collected over different seasonal times, there will be varying characteristics to it,” he says. “If you run software against that, you can normalize that so it looks like a visually consistent and seamless mosaic of imagery.”
