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Tech4Earth: Capgemini’s platform to foster the digital transformation of theEarth Observation ecosystem

Digital Transformation is now a key topic at the top of the agenda for CxOs inevery line of business. The Earth Observation (EO) ecosystem is no exception,and this ecosystem is not limited to the Space sector: almost every line ofbusiness can benefit from new EO digital services to come.

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Contact :Olivier Flebusolivier.flebus@capgemini.com

1 Google has published an Oxera report that estimates the revenues from global Geo services at $150 billionto $270 billion per year (http://www.oxera.com/Latest-Thinking/News/January-2013/Oxera-quantifies-the-benefits-of-Geo-services-to-g.aspx). In the 2014 State of the Satellite Industry Report published by theSatellite Industry Association, the revenue from remote sensing activities are valued at $1.5 billion.

2 See Capgemini Consulting publicationhttps://www.capgemini-consulting.com/rebooting-the-business-model-for-the-digital-age

3 Google owns and operate EO satellites through Skybox. See http://www.skyboximaging.com/ 4 Amazon has made Landsat 8 data freely available on S3 so that anyone can create new products usingAWS.

5 See http://www.cesbio.ups-tlse.fr/index_us.htm

© Capgemini - June 2015

We have identified four main drivers for the upcoming digitaltransformation of the Earth Observation ecosystem:

• A downstream extension of the image processingvalue chain in the digital world, opening new marketsthrough new business models. The traditional, product-based, “remote sensing” B2B market will evolve towardsdownstream digital application for business, consumerand local authorities markets. Completely new ways ofconsuming and leveraging imagery will generate demandand will have a huge economic impact1. Rebooting thebusiness model is a “common” practice when enteringthe digital world2!

• Newcomers among the key actors of imagery valuestream. Google3 and Amazon4 already have movedtowards these huge opportunities of the future EarthObservation market.

New imagery and moregenerally information comingfrom new sensors isbecoming available all thetime. For example, theEuropean CommissionCopernicus program withSentinel satellites providesfree and open imagery. The goal is to stimulate theemergence of new marketsand actors, including startupsthat will disrupt the value thatcan be extracted from imageryand other open data.

• The use of Platforms that bring scalability andflexibility to boost creativity, increasing businessagility while controlling risks and reducing time-to-market. These platforms combine all required state-of-the-art capabilities (storage, processing, large-scalecollaboration, mobile access, connectivity with sensorsand end-users, etc) that have emerged from the digitaltransformation in the pioneer sectors. The same platformcan be used for developing new services as well as foroperating them, thus drastically reducing the time to marketfor new services.

• A more open, collaborative culture reshapingorganizations and developing ecosystems withSpatial Agencies, Satellite manufacturers, Storage &Processing platform providers, Research labs, scientificcommunities, startups and even end-users.

New technologies for new usages, fromdark matter to smart citiesIt’s a revolution that comes from Technology. We believethat the EO processing chains that used to be designed,then developed, and then operated in a fixed-everythingcontext are completely outdated. Even their layeredstructure (Level 0 to Level 4) is to be challenged.

It’s a revolution that also comes from usages. To makescientific discoveries (dark matter, gravitational waves) or toinvent new services for the consumer market (smart cities),space scientists actually have to address new challenges:

• Space scientists will have to deal with unprecedenteddata volumes coming from next-generation instrumentsand sensors, and also simulation data that will be used todevelop and refine next-gen processing chains. Severalhundreds of petabytes will be common in the nextdecade for a single space mission. Moreover, to get moreinsights from space data, scientists will combine datafrom multiple space missions or instruments withadditional, “common” data.

• Space scientists will also design new kinds of processingchains, not limited to image processing at pixel level, butalso using machine learning or statistical algorithms, muchlike “big data” enterprises are doing.

• The operation of these new processing chains will alsosignificantly change, moving towards more collaborationand more interactivity, real-time insights and “test &learn” approaches involving automatic, “artificialintelligence” analyses as well as interactive, “human” ones.It can also mean systematically processing all observationsto find out which ones are relevant for further analysissteps.

Tech4Earth key features and benefits

For the last 4 years, Capgemini Aerospace & Defenseteams have explored multiple ways to address the driversand challenges of the upcoming EO digital transformationmentioned previously by leveraging new disruptive Big Dataand Digital technologies. This experience has led to severalProof-of-Concepts, an overall Vision and more recently toour operational Cloud platform:Tech4Earth.

As of today, we have running applications in the followingbusiness domains:

• Flooding Risk Forecast (partnership with the CESBIO5

French lab), integrated into a Disaster Managementdigital application we’re developing

• Rice crop monitoring

• Ocean pollution and lifeform analysis

Our Tech4Earth platform is designed for building “vertical”applications, to foster the discovery and the emergence ofnew usages in specific business domains. We have beendeveloping multiple “flavours” of all the components thatare required: data storage, processing engines, collaborativedevelopment environment, digital “application store”:

• At the “core”, a Data Hub or Data Lake that stores alldata. Its key characteristics are to be scalable and opento both structured and non-structured data. It’s poweredby hadoop 2.0 that sets up a “Data Operating System”combining multiple processing engines: Map/Reduce for“simple” batch jobs on disk-resident data, Spark forin-memory processing to drastically increase processingspeed, R for statistical analysis and Complex EventProcessing frameworks like Storm to process streamsof data in an event-oriented way.

• The Collaborative Development Environment and theAlgorithms Repository are a set of services that enablescientific communities to collaboratively and iterativelydevelop small processingcapabilities that enablethe “distillation” of inputdata into higher levelinformation. From atechnology point of viewit relies on notebookenvironments (Jupyter),continuous integration,automated testing,packaging anddeployment solutions(Jenkins, Sonar, Nexus).

• Common services aresplit up into 2 layers: onthe one hand, platform-attached services on top of thecore data hub (eg: search and sql-on-hadoop services)and on the other hand, context-specific “toolbox”services that customize the platform to your needs.

• Interactive Applications hold the business logic and theuser experience. The objective is to go beyond simplydisplaying images (eg: flooding forecast visualized in aheat map), to help end-users make faster and morerelevant decisions (eg: combine images with informationgathered from the field into a fully-featured disastermanagement application).

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Tech4Earth addresses

the complete value

chain from scientific

processing to digital

applications for

end-users. All services

are available on

a single platform!

A platform-centricapproach brings

disruptivecapabilities and a more agile culture

for developing ecosystems and

creating new services