WESTMINSTER, Colo. — (BUSINESS WIRE) — August 14, 2017 — DigitalGlobe, Inc. (NYSE: DGI), the global leader in Earth imagery and information about our changing planet, today announced the SpaceNet Challenge Round 2 results and plans for the next two SpaceNet Challenges. A collaboration between DigitalGlobe, CosmiQ Works, and NVIDIA, SpaceNet leverages an online repository of publicly accessible satellite imagery, co-registered data layers for training algorithms, and prize challenges to accelerate innovation in machine learning.

The SpaceNet Challenge Round 2, hosted on TopCoder, was a continuation of the first competition and invited participants to improve automated mapping algorithms for building footprint feature extraction from overhead imagery. Building on the success of the first competition, SpaceNet Round 2 incorporated several enhancements, including the release of higher resolution imagery from WorldView-3 (30 cm resolution), improved building footprint training data from four new geographically diverse areas and an extended competition length to provide more time for algorithm development.

The winning algorithms achieved performance with potential for automated mapping tasks. Such algorithms can help keep maps up-to-date at scale and serve end-users when current information is needed to direct resources, such as first responders during natural disasters. CosmiQ Works’ blog post provides further technical detail on the top three winning solutions. As in the first challenge, the winning algorithms are available to the open source community through the SpaceNet GitHub repository and users of DigitalGlobe’s Geospatial Big Data platform, GBDX.

“SpaceNet’s innovation is having a meaningful impact within the first year, thanks to the collaboration between developers and data scientists to apply open data and machine learning in the geospatial field,” said Tony Frazier, Senior Vice President and General Manager of DigitalGlobe | Radiant. “The results from Round 2 show developers are harnessing machine learning and high-resolution training data to achieve outcomes that indicate automation could be used in the near future to support broader geospatial analytics. We are excited to grow the SpaceNet training datasets library for an even broader range of applications and hosting additional public competitions to further machine learning capabilities in the future.”

The third SpaceNet Challenge will shift focus from automated building footprint extraction to road network extraction and optimized vehicle routing. This challenge will utilize machine learning to gain insights into transportation networks and navigation. The fourth competition will focus on processing off-nadir imagery produced by high-revisit constellations, like DigitalGlobe’s next-generation WorldView Legion constellation, in unprecedented rapid timelines and at global scale. The goal of this challenge will be to create algorithms that automatically detect objects from more diverse angles than current nadir imagery. More information on these upcoming challenges will be available as they approach starting in fall 2017.

About DigitalGlobe

DigitalGlobe is a leading provider of commercial high-resolution Earth observation and advanced geospatial solutions that help decision makers better understand our changing planet in order to save lives, resources and time. Sourced from the world's leading constellation, our imagery solutions deliver unmatched coverage and capacity to meet our customers' most demanding mission requirements. Each day customers in defense and intelligence, public safety, civil agencies, map making and analysis, environmental monitoring, oil and gas exploration, infrastructure management, navigation technology, and providers of location-based services depend on DigitalGlobe data, information, technology and expertise to gain actionable insight.

Special note about forward-looking statements

Certain statements contained herein, including statements about our 2017 outlook, contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, as amended. Forward-looking statements relate to future events or our future financial performance. We generally identify forward-looking statements by terminology such as “ can,” “may,” “will,” “should,” “expects,” “plans,” “anticipates,” “would,” “could,” “intends,” “target,” “projects,” “contemplates,” “believes,” “estimates,” “predicts,” “potential,” “continue” or “looks forward to” or the negative of these terms or other similar words, although not all forward-looking statements contain these words.

Forward-looking statements are based upon our current expectations and assumptions of future events and are subject to risks and uncertainties that could cause our actual results or performance to differ materially from those indicated by such forward-looking statements. Some of the risks or uncertainties that could cause actual results to differ include, but are not limited to: the loss or reduction in scope of any of our primary contracts, or decisions by customers not to exercise renewal options; the availability of government funding for our products and services both domestically and internationally; our ability to meet our obligations under the EnhancedView contract; our reliance on a limited number of vendors to provide certain key products or services to us; breach of our system security measures or loss of our secure facility clearance and accreditation; the loss or damage to any of our satellites; delays in the construction and launch of any of our satellites or our ability to achieve and maintain full operational capacity of all our satellites; loss or damage to the content contained in our ImageLibrary; interruption or failure of our ground systems and other infrastructure; decrease in demand for our imagery products and services; increased competition that may reduce our market share or cause us to lower our prices; changes in political or economic conditions, including fluctuations in the value of foreign currencies, interest rates, energy and commodity prices, trade laws and the effects of governmental initiatives to manage economic conditions; our ability to recruit, hire or retain key employees or a highly skilled and diverse workforce; failure to obtain or maintain required regulatory approvals and licenses; and, changes in U.S. or foreign law or regulation that may limit our ability to distribute our imagery products and services. Additional risks and uncertainties related to the proposed transaction with MacDonald, Dettwiler and Associates Ltd. (“MDA”) include the possibility that the parties may be unable to obtain required regulatory approvals or that other conditions to closing the transaction may not be satisfied, such that the transaction will not close or that the closing may be delayed; the potential adverse effect on partner and customer relationships, operating results and business generally resulting from the proposed transaction; the proposed transaction will require significant time, attention and resources, potentially diverting attention from the conduct of DigitalGlobe’s business; the anticipated benefits of the proposed transaction may not be realized; the anticipated and unanticipated costs, fees, expenses and liabilities related to the transaction; the outcome of any legal proceedings related to the transaction; and the occurrence of any event, change or other circumstances that could give rise to the termination of the transaction agreement. Additional information concerning these and other risk factors can be found in our filings with the U.S. Securities and Exchange Commission, including Item 1A of our Annual Report on Form 10-K for the year ended December 31, 2016.