Le Bourget 2017 - From earth observation to actionable intelligence

From Earth Observation to actionable intelligence:
Big-data analytics for Space 4.0
Ing. Luigi Pasquali – Director of Space Line of Business and CEO at Telespazio

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© Leonardo - Società per azioni
Internet of Things + Social Data +
Earth observation data
New systems and missions will
generate huge amount of Earth
Observation data
with highly reduced information age

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4 radar satellites for
Earth Observation
• Very High Resolution
• Best in class for revisit time
• Day and Night
• Any weather conditions
THE ITALIAN RADAR CONSTELLATION
e-GEOS is the exclusive commercial world
wide distributor of COSMO-SKyMed

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We are moving towards a service model where data are just part of the game
EARTH OBSERVATION BUSINESS MODEL IS CHANGING
• High temporal resolution to complement
high and very high spatial resolution sensors
• Federation of existing and planned new
assets through smart multi missions tasking
platforms
• Convergence in the data analytics business
for the Earth Observation industry
• Data derived info driven market
• Data pricing no longer entry barrier
Biggest Trends in
Satellite Earth Observation
Direct Tasking
Programs
EO Big Data
& Analytics
Pricing Pressure
On Archive
Data
New
Constellations

07 June 2016 ©e-GEOS2017 – www.e-GEOS.it 6
More value addition/processing to the raw data
THE VALUE CHAIN FOR THE NEW VALUE ADDED SERVICES
Data
Value
Added
Services
Information
Products
Big data
analysis
Low
High
Level of Value Addition
We are involved in each layer of the
value chain of the new scenario of
Value Added Services and
Information Products

More value addition/processing to the raw data
Big Data Analytics
I maggio APP
Data
Low
High
Value
Added
Services
Information
Products
Big data
analysis

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Emergency Response
how Social Data became part of the
COPERNICUS rapid mapping process

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Integration of (Geo)Social Data – Social damage map -Central Italy Earthqake
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5
5

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Damage Proxy Map
Damage Proxy Map
highlights the area where
a strong decrease of
coherence has been
detected.
AMATRICE – COSMO SkyMed H1 Damage Proxy Map. 08/06/2016 – 24/06/2016 – 26/08/2016
Coherence Decrease

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Big EO Data in Agricutlure, are
transforming the use of EO data

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Geoinformation partnerships for
big data analytics transformation
New services for new markets

See a better world.™
The Multi-Billion Dollar Artificial Intelligence Market
and How DigitalGlobe Plays In It
ALBERTO LÓPEZ

DigitalGlobe® Proprietary and Business Confidential
Big Takeaway From Davos 2017
1/31/2017To update the footer with the presentation title, find Header & Footer in the Insert tab and Apply to All14
Artificial Intelligence has arrived and will
globally add disruption and create a huge
opportunity for skill training

What Is Artificial Intelligence?
To update the footer with the presentation title, find Header & Footer in the Insert tab and Apply to All

AI From Bust to Boom

What is Deep Learning?
Deep Learning is an algorithm inspired by how the brain works. No theoretical limitation to
what it can do. It’s enabled by neural networks, fueled by big data and computation.
And Many More
Categories…
Oil Tankers
Fighter
Aircraft
Bridges
DG Basemap
+Daily
Training Dataset
Tanks
Airliners
Heliports
Deep
Learning
Web Tile Service
OpenStreet
Map POIs
Manual
Extraction

DigitalGlobe Radiant is the market leader in Optical remote sensing
IKONOS®
.82 meter
resolution
9 m CE90
QuickBird®
.65 meter
resolution
23 m CE90
WorldView-4®
Launched Nov’16
.30 meter
resolution
<3.0 m CE90
WorldView-3®
.30 meter
resolution
<3.0 m CE90
WorldView-2®
.46 meter
resolution
<3.5 m CE90
GeoEye-1®
.46 meter
resolution
<3.5 m CE90
WorldView-1®
.50 meter
resolution
<4 m CE90
AVAILABLE VIA DIGITALGLOBE ARCHIVE
CURRENTLY IMAGING IN ORBIT

+100 Petabyte over 16 years
DigitalGlobe Proprietary. ©DigitalGlobe. All rights reserved.

The most valuable companies are technology (particularly A.I.) companies
Source: The Market for Machine Intelligence, presented by Mo Islam at USGIF Machine Learning Summitt, Jan 10, 2017

DigitalGlobe Radiant Has a Broad Portfolio of Capabilities
Space ISR Planning Studies
Multi-INT Collection Management
Open Source Data Management
Geospatial Big Data Integration
Enterprise Agile Development
Cloud DevOps Processes
4D Data Visualization
Crowdsourced Mapping Solutions
Machine Learning Solutions
Automated Object Detection
Terrain Analytics and VR Apps
OSINT Indicators and Warning
Geographic Signature Search
Deskside Development Services
Intelligence Tradecraft
Marine Services Data and Tools
Human Geography Data
Geospatial Intelligence Reports
POI and Activity Discovery
Machine Learning Training Data
Analytic Solutions
Standard Commercial
Products and Services
Mission Solutions

DigitalGlobe Has Established Industry Leadership in Deep Learning
Big Data and
Compute fuels deep
learning
Drives deep learning
algorithm innovation
and development
Provides capability
for creating training
data
Crowdsourcing

Use Case Example:
Airfield Monitoring

Campaign Workflow
Point of Interest
Dataset
Feature
Extraction
Training Dataset
Automated
Airfield Feature
Extraction
Feature
Validation
Automated
Point of Interest
Monitoring
Training Dataset
Development
Applied Deep
Learning

Airfield Feature Extraction
Use or disclosure of data contained on this sheet is subject to the restriction on the title page of this
document.
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Features Discovered: 5,779
• Aircraft: 3,617
• Hangars: 981
• Air Traffic Control Towers: 281
• Fuel Tanks: 900
Airfields with tags: 332 / 371
Total Area: 13,930 Km2
Time to Complete: 1d 22h 23m
Total Users: 235
Total Coverage: 3x

Training Dataset Development
document.
Shuimen Airbase
Xiapu, China
26.945585°, 120.068198°
Xian-Yanliang Airfield
Xi'an Yanliang, China
34.648852°, 109.247841°
J-11/ J-15 KJ-2000 AWACS
Nanning Wuxu International Airport
Wuxuzhen, China
22.604570°, 108.177942°
Commercial Aircraft
Xian-Yanliang Airbase
Xian-Yanliang, China
34.640519°, 109.232538°
Wugong Airbase
Wugong, China
34.271817°, 108.263197°
J-20 Xian H-6 Bomber
Shenyang Beiling Airport
Shenyang, China
41.867419°, 123.436546°
Divine Eagle Drone
(Largest UAV in the World)

Applied Deep Learning
document.
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Features Validated: 4169
• Civilian Airplane: 1614
• Fighters: 79
• Helicopter: 12
• None of the Above: 2464
Time to Complete: 0h 28m
Total Users: 58
Total Coverage: 3x
Total Images Used: 250
• Customer Imagery: 86
• DGCS Imagery: 164
Total Area of Polygons: 792.11 Km2

Automated Airfield Monitoring

DigitalGlobe | WorldView-2 + Aircraft + Ship Object Detection

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many antennas and ground networks
to get data from space on global scale
many satellites in orbit today….
and the number is growing fast….

DigitalGlobe® Proprietary and Business Confidential58 6/19/2017

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Geoinformation partnerships for big data
analtyics transformation
COSMO-SkyMed data analytics

Taking the economic pulse of the planet
Our Partnership with Leonardo / Telespazio
Paris Le Bourget

www.orbitalinsight.com © Orbital Insight Inc. Proprietary Information 2017
About Our Company
Incorporated: December of 2013 by Dr. James Crawford
Resume: AI Ph.D., NASA Ames, and Google Books
Employees: 65+. 45 Eng. 17 Ph.D., 12 Masters
Customers: Global 500, Financial Services Firms, US Government, World Bank, WRI
Investors:
Partners:

Why Now
Deep LearningSatellite
Industry
Growth
Cloud + GPU
Cloud and GPU

Orbital Insight Cloud / AWS Web Portal
RESTful
APIrundeeplearningalgorithms
rundatasciencenormalizations
imageingestionandprocessing
imagesloadedintoGPUs
PublishdatatoAPIsandportal
What We Do
PaaS*
Structured Data
Geospatial
Outputs
Insights & Forecasts
Time Location Counts
2012-2-12 Walmart2044 213
2012-2-24 Walmart2044 256

Computer Vision Capabilities
Car Counting Commodity Stockpiles Building Classifying

Example of Orbital Insight: Complete Port Dynamics
AIS + Orbital Ship DetectorAIS + Orbital Ship Detector
Auto import/exportAuto import/export
Oil Storage VolumesOil Storage Volumes
Commodity
Stockpiles
Commodity
Stockpiles
We provide a pulse
on the Earth’s
activity

Limitations of Visual Imagery
• Limitations to EO imagery
o Key areas, such as ports, can be cloud
covered up to 80% of the time
o Key Global Production (e.g. Energy) and
Consumption (Retail) and Infrastructure
(Transportation) sectors have major
coverage gaps.
o Time of collection for most orbits is limited to
10am-2pm
• Service Level Agreements cannot be
guaranteed
o Critical for serious operational use of analytics
• Morning, evening, and nighttime activities
cannot be tracked
o Creates major information gaps
The port of Rotterdam, one of
Europe’s key oil hubs, is difficult to
monitor optically due to frequent
cloud cover

These Limitations Cause Gaps in
Economic Activity Monitoring
Production Sectors Consumption Sectors Infrastructure Sectors
• Decision making is being constrained by significant EO coverage gaps.
• Presents greater risk to asset owners, employees, investors and citizens.
• Increases costs to businesses and consumers.
• Inefficient asset monitoring costs are ultimately passed onto consumers.
• Decisions by Public and Private may be incorrect
• Unnecessarily inflates operating and capital allocation budgets due to a lack of
information.

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Q&A
Luigi Pasquali – Leonardo SpA
Kevin E. O'Brien Chief Business Officer of Orbital Insight
Alberto Lopez - Digital Globe Business Development Director .

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Happy birthday #10COSMOSKYMED

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ENI – Large Interferometric monitoring for subsidence

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Rapid mappin will improve with big data

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SatCen – COPERNICUS SEA - Support for EU External Action

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From Radar Data to Analytics - Damage proxy map – Central Italy Earthquake
Damage Proxy Map is a point map obtained by analyzing the coherence between two pairs of COSMO SkyMed images - Pair 1: PRE-
PRE; Pair 2: PRE-POST
Damage Proxy Map is generated with the following steps:
– In the coherence from image pair 1 are extracted all pixels with higher coherence
– For all these pixels is analyzed the coherence from image pair 2. Only pixels with high coherence decrease are extracted and inserted in the
Damage Proxy Map
Damage Proxy Map is a vector product from the Multi-Coherence Map, obtained by discretizing the RGB imagery
Coherence from image pair 1 PRE-PRE Coherence from image pair 2 PRE-POST with
high coherence decrease points
Damage Proxy Map

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Aerei Tucson e tool per il riconoscimento automatico (PF)

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Analist – Aircraft Recognition Tool
User selection of aircraft points of
interest:
- Fuselage extremities
- Wing end-point
Main aircraft models matching the
measurements done are shown together
with the desired ancillary information.
XAd hoc resized and rotated orthographic
projection of selected aircraft models
can be superimposed in order to cross-
check the shape.

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We are monitioring
and mapping the
changes
of the Earth

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COSMO-SkyMed in the East

Le Bourget 2017 - From earth observation to actionable intelligence

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Le Bourget 2017 - From earth observation to actionable intelligence