ExtremeEarth is a H2020 project that aims to develop extreme data analytics techniques using big Copernicus data and apply these technologies to food security and polar use cases. The project involves 11 partners from 7 countries and has a budget of ~6 million Euro over 36 months. It will integrate artificial intelligence and deep learning methods to extract information from Copernicus satellite imagery for applications in monitoring crop growth/yield and sea ice conditions. The food security use case will generate water availability maps for irrigation management while the polar use case focuses on automated regional sea ice charts for maritime safety.

1. © VISTA 2019 www.vista-geo.de No. 1
Silke Migdall, Heike Bach, Florian Appel
Koubarakis M., Bereta K. , Stamoulis G.
ExtremeEarth
Extreme Data Analytics to
Manage an Extremely
Dynamic Planet
Eltoft T. ,Kraemer T.,
Fleming A.,
Bruzzone L. , Paris C. ,
Dowling J., Kakantousis T.,
Haridi S., Vlassov V.,
Arthurs D.,
Dumitru O.,Datcu M.,
Hughes N.,
Karkaletsis V. ,Konstantopoulos S.,
Charalambidis A.
AI and Data Analytics: Technologies and Applications

2. © VISTA 2019 www.vista-geo.de No. 2
Overview
o ExtremeEarth is a H2020 project that aims at developing
o Extreme Analytics techniques and technologies using big Copernicus data,
o applying these technologies in two of the ESA TEPs (Food Security and Polar)
o demonstrating two highly societal and environmental relevant use cases.
1. National and Kapodistrian University of Athens (GR)
2. VISTA Geowissenschaftliche Fernerkundung GmbH (DE)
3. UiT - The Arctic University of Norway (NO)
4. University of Trento (IT)
5. Royal Institute of Technology (SE)
6. National Center for Scientific Research - Demokritos (GR)
7. German Aerospace Center DLR (DE)
8. Polar View Earth Observation Ltd. (UK/DK)
9. Meteorologisk Institutt Norway (NO)
10. LogicalClocks (SE)
11. British Antarctic Survey (UK)
Start:
1.1. 2019
Duration:
36 Months
Budget:
~ 6. Mio Euro
Funded by call:
ICT-12-2018-2020
Project Number:
825258
http://earthanalytics.eu

3. © VISTA 2019 www.vista-geo.de No. 3
Motivation & Background
Copernicus
the most important digital big data
resource: Volume – Velocity – Variety –
Veracity - Value
ESA thematic exploitation platforms:
virtual environments for user relevant
EO data and applications
advantage of available computing
resources
DIASs:
Data and Information Access
Service (DIAS) platforms
computing power close to
the data
AI & Deep Learning
deep neural network architectures for satellite data
large benchmark datasets, clouds and GPU technologies
Applications / Use Cases:
• Food Security - irrigation support for agricultural areas
• Polar - maritime safety for traffic in critical polar environments
Copernicus
TEPs DIASs
Artificial
Intelligence
Relevant
Applications
Big Data
linked geospatial data
software stack with tools that
scale to PBs of data
Big Data

4. © VISTA 2019 www.vista-geo.de No. 4
Background & Team
Previous Projects
• Four projects funded by the European Commission
which University of Athens led or participated in
context of Copernicus data:
• TELEIOS
• LEO
• Melodies
• Copernicus App Lab
• Successful dealing with the variety dimension of
Copernicus big data.
• Progress in R&D in the areas of linked geospatial data
and ontology-based geospatial data access.
• Strong team and connections have been established
in previous EU and ESA projects
• New participants had been gained

5. © VISTA 2019 www.vista-geo.de No. 5
Extreme Analytics
integrating innovative AI players to EO
Deep neural networks
technique for optical
multispectral Sentinel
2 images
Scalable
deep
learning and
big data
Deep neural network
techniques for SAR
data
Remote sensing for the
Arctic, AI for sea ice
monitoring
Developers of HOPS
and Hopsworks

6. © VISTA 2019 www.vista-geo.de No. 6
ExtremeEarth
Objectives & Concept
Use Cases
WP4 and WP5
Copernicus and DIASs
WP1
Impact
WP6
Thematic Exploitation Platforms
Food Security TEP
Polar TEP
WP2 and WP3
Deep Learning &
Linked Open Data
HOPS
WP3 and WP2

7. © VISTA 2019 www.vista-geo.de No. 7
ExtremeEarth Applications
The Food Security Use Case
o FOOD SECURITY IS ONE OF
THE MOST CHALLENGING
ISSUES OF THIS CENTURY
(ESPECIALLY IN A
CHANGING EARTH
ENVIRONMENT)
o POPULATION GROWTH,
INCREASED FOOD
CONSUMPTION AND
CHALLENGES OF CLIMATE
CHANGE AND INCREASED
VARIABILITIES WILL EXPAND
OVER THE NEXT DECADES
• Biomass production and yield will need to
be increased
• Risks of yield loss even under extreme
environmental conditions need to be
minimized
• Irrigation requires reliable water resources
either from ground water or surface water
• Large portion fresh water is linked to
snowfall, snow/ice storage and seasonal
release of the water
• Water Availability Maps as EO based
product to support farmers decision making
and irrigation management

8. © VISTA 2019 www.vista-geo.de No. 8
Need of Water
Polar
TEP
EO Processing
Sentinel-1
Snow
Parameters
Medium Resolution
Modelling:
Water Balance
Parameters
High Resolution
Modelling:
Crop Growth
Food Security
TEP
EO Processing
Sentinel-2
Crop
Parameters
… for secure food production
Water Availability for Irrigation
• Surface Water
• Soil Moisture
• Groundwater
Origin of the Water
Water from seasonal snow …
The Food Security Use Case
Tools and Methods

9. © VISTA 2019 www.vista-geo.de No. 9
The Food Security Use Case
Tools and Methods
Integration of DL algorithm
into Food Security TEP
Outputs:
Crop type map
Crop boundaries
Training Data
Validation Data
Deep learning algorithm
for agricultural analysis
Data Access for Food TEP via Copernicus DIAS
Thematic Products
• biomass / plant productivity
including water use

10. © VISTA 2019 www.vista-geo.de No. 10
ExtremeEarth Applications
The Polar Use Case
o MARITIME SAFETY
o INCREASED ACTIVITY =
INCREASED RISK OF
INCIDENT
o COST OF AN INCIDENT (E.G.
SPILLAGE OF OIL) IS
IMMENSE
o VESSEL SINKINGS IN THE
POLAR REGIONS ARE RARE
BUT NOTABLE INCIDENTS
o HIGHLIGHT THE NEED FOR
ACCURATE AND ROUTINE
SEA ICE INFORMATION
PRODUCTS
• Polar Regions play a critical role in
regulating and driving the Earth’s climate
and ecological systems
• High quality, timely and reliable
information about sea ice and iceberg
conditions is vital
• IMO Polar Code requires users to have
access to a system for assessing the
limitations for operating in ice
• EO has a key role in information gain, but is
still relying of expert interpretations
• Sea Ice information will be filled by
ExtremeEarth developments by
automatically extract information content
and data availability in near-real-time

11. © VISTA 2019 www.vista-geo.de No. 11
The Polar Use Case
Tools and Methods
Integration of DL algorithm into Polar
TEP
Outputs:
Automated regional sea ice charts
Sea ice surface feature
information
Training Data
Covering diverse sea ice
types, seasons and
imaging conditions
Validation Data
Deep learning algorithm
for sea ice characterization
Data Access for Polar TEP via Copernicus DIAS
Sea ice information for safe and
efficient maritime operations and
IMO Polar Code compliance

12. © VISTA 2019 www.vista-geo.de No. 12
ExtremeEarths Tasks
Scalable Deep Learning and Extreme Earth Analytics for Big Copernicus Data
• Large Training Database Creation
• Deep Learning Architecture Design

13. © VISTA 2019 www.vista-geo.de No. 13
Work Plan & Status
ExtremeEarth is organized in three
phases.
 First phase (months M1-M4), the
requirements had been collected
o Based on these requirements, a software
architecture is now designed (in M5-M6)
o First phase of software development,
integration and evaluation will take place
(until M18).
o In M19 first review of the project.
o The final phase of software development,
integration and evaluation in months M19
to M36.
Participatory and agile approach based on
requirements of user communities:
Three focused User Community workshops for
capturing user requirements and obtaining user
feedback on our designs and implementations.
 Workshop 1 (Munich, March 2019)
1
2
3
After the project M36 /42/60
Commercialisation and Services
Invitation to provide your feedback
> http://earthanalytics.eu

14. © VISTA 2019 www.vista-geo.de No. 14
ExtremeEarth @ ESA
• Big Data,
Processing and
User Interfaces
based on the TEPs
• ESA PHI Week
appearance within
side event…
https://tep.eo.esa.int/

15. © VISTA 2019 www.vista-geo.de No. 15
Thank you….
VISTA Remote Sensing in Geosciences GmbH
Gabelsbergerstraße 51
D-80333 München
www.vista-geo.de
Florian Appel
appel@vista-geo.de
Heike Bach
bach@vista-geo.de
Silke Migdall
migdall@vista-geo.de
http://earthanalytics.eu