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Data pipelines for inter-communal
conflict impact analysis
Terradue
BETTER - Nigeria change detection
7-8 Novembre 2019 - Frascati Italy H2020 EARTH OBSERVATION BIG DATA HACKATHON
Nigeria context
https://www.wfp.org/countries/nigeria
Earth Observation dataset:
Sentinel-1
Search parameters:
productType: SLC
start: 2018-09-09
end: 2018-09-21
box: 5.1,10.8,8.1,13.7
Sentinel-1 data discovery over Nigeria
Goal: discover a pair of Sentinel-1 SLC for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
https://ellip.terradue.com/geobrowser/?id=better-eobd-hack/better-hack-nigeria-app#!
Select the product that “covers the area of
interest”
Platform: S1A
Sensor: SAR
Product Type: SLC
Start Time:
2018-09-16T17:46:57.0540000Z
End Time:
2018-09-16T17:47:24.0030000Z
Orbit:23727 ASCENDING
Track:30
Mode: IW_DP
Swath: IW1 IW2 IW3
Sentinel-1 data discovery over Nigeria
Goal: discover a pair of Sentinel-1 SLC for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
Sentinel-1 data discovery over Nigeria
Earth Observation dataset:
Sentinel-1
Search parameters:
productType: SLC
start: 2019-09-09
end: 2019-09-21
orbitDirection: ASCENDING
track: 30
Platform: S1A
box: 5.1,10.8,8.1,13.7
Goal: discover a pair of Sentinel-1 SLC for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
Coherence and backscatter change detection
COIN Processing service
Use the discovered pair of Sentinel-1
SLC procuts to fill the processing
parameters:
- Master
- Slave
Then set the parameter
- Pixel spacing in meters to 10.0
Run the job
Goal: process Sentinel-1 SLC pair for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
Coherence and backscatter change detection
COIN Processing service
Use the discovered pair of Sentinel-1
SLC procuts to fill the processing
parameters:
- Master
- Slave
Then set the parameter
- Pixel spacing in meters to 10.0
Run the job
Goal: process Sentinel-1 SLC pair for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
Change detection visualization
Hands-on: data discovery, processing and data pipelines
Steps:
1. Set-up your credentials
2. Data discovery
3. COIN processing
4. COIN results
5. Sentinel-2 RGB composites data
processing pipeline
6. SNAC data processing pipeline
7. COIN data processing pipeline
8. SNAC exploitation
Hackathon kit available at: https://gitlab.com/ellip/training/wfp-nigeria-training
Hands-on: access and setup
Open a Web Browser (best experience
with Chrome)
Type the address:
https://notebooks.terradue.com
You’ll be redirected to a login page.
Use the credentials found on the card
given to you
Hands-on: access and setup
Open the folder:
wfp-nigeria-training
Double-click on the notebook:
1 Setup.ipybnb
Run the cells and fill the information
requested:
username: same as in card
API key: click on the link shown
copy/paste the API key
Goal: set-up the authentication/authorization information for all notebooks
Hands-on: data discovery
Double-click on the notebook:
2 Data discovery.ipybnb
Run the cells to repeat the data
discovery steps done on the
Geobrowser
Goal: discover the pair of Sentinel-1 SLC acquisitions with the Ellip APIs following the same approach done using the Geobrowser
Hands-on: data discovery
Goal: discover the pair of Sentinel-1 SLC acquisitions with the Ellip APIs following the same approach done using the Geobrowser
Hands-on: Sentinel-1 COIN processing
Double-click on the notebook:
3 COIN processing.ipybnb
Run the cells to submit the COIN
processing request as done on the
Geobrowser
Goal: discover the COIN processing service and submit a processing request with the discovered pair of Sentinel-1 SLC acquisitions
Hands-on: RGB composites data processing pipeline
Double-click on the notebook:
4 COIN results.ipybnb
Run the cells to inspect the processing
results
Goal: explore the results of the COIN processing service
Data processing pipelines rely on the ATC
model with:
- Application - data driven application
- Trigger - date or event driven
application
- Coordinator - schedule the execution of
the Trigger instances periodically at fixed
times, dates, or intervals
Data processing pipelines
The ATC model starts with a data driven
application taking as inputs one or more
references to EO catalogue entries:
- A single input reference
- A pair of input references (e.g.
interferometry)
- A stack of input references
A(pplication)TC
The Trigger is a date and/or event
driven application that, when there’s
new data available or an event:
- Creates Data Items
- Queues Data Items
- Pipes Data Items
AT(rigger)C
OWS Context (*) documents
encapsulating all the information for
processing the application and get it
through the data processing pipeline
AT(rigger)C - Data items
(*) https://www.opengeospatial.org/standards/owc
The Coordinator submits Trigger
instances periodically at fixed
times, dates, or intervals
ATC(oordinator)
Hands-on: RGB composites data processing pipeline
Double-click on the notebook:
5 RGB composites data
processing pipeline.ipybnb
Run the cells to create and queue
Data Items containing Sentinel-2 RGB
Composites processing requests
The data processing pipeline will
produce, for a set of areas of interest,
several RGB composites for all
Sentinel-2 acquisitions during the
period 2019-08-15 to 09-15.
Goal: create a data processing pipeline for Sentinel-2 RGB composites over a few areas of interest in Nigeria
Hands-on: SNAC data processing pipeline
Double-click on the notebook:
6 SNAC data processing
pipeline.ipybnb
Run the cells to create and queue
Data Items containing SNAC
processing requests
Goal: create a data processing pipeline for Sentinel-1 SNAC over a large area in Nigeria
Hands-on: SNAC data processing pipeline
Hands-on: COIN data processing pipeline
Double-click on the notebook:
7 COIN data processing
pipeline.ipybnb
Run the cells to create and queue
Data Items containing COIN processing
requests
Goal: create a data processing pipeline for Sentinel-2 RGB composites over a few areas of interest in NigeriaGoal: create a data processing pipeline for Sentinel-1 COIN over a large area in Nigeria
Hands-on: COIN data processing pipeline
Hands-on: monitor a data processing pipeline
Double-click on the notebook:
8 SNAC exploitation.ipybnb
Monitor the Data Items status and
access the associated results when
done
Goal: monitor and exploit the results of the Sentinel-1 SNAC data processing pipeline over a large area in Nigeria
▪ Get in touch with Terradue:
support(at)terradue.com
www.terradue.com
▪ Become a BETTER data challenge
promoter:
https://www.ec-better.eu/
Way forward
Horizon 2020 Research and Innovation Programme
under grant agreement no 776280

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BETTER Session, Excercise 1 @ EO Joint Big Data Hackathon

  • 1. Data pipelines for inter-communal conflict impact analysis Terradue BETTER - Nigeria change detection 7-8 Novembre 2019 - Frascati Italy H2020 EARTH OBSERVATION BIG DATA HACKATHON
  • 3. Earth Observation dataset: Sentinel-1 Search parameters: productType: SLC start: 2018-09-09 end: 2018-09-21 box: 5.1,10.8,8.1,13.7 Sentinel-1 data discovery over Nigeria Goal: discover a pair of Sentinel-1 SLC for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service https://ellip.terradue.com/geobrowser/?id=better-eobd-hack/better-hack-nigeria-app#!
  • 4. Select the product that “covers the area of interest” Platform: S1A Sensor: SAR Product Type: SLC Start Time: 2018-09-16T17:46:57.0540000Z End Time: 2018-09-16T17:47:24.0030000Z Orbit:23727 ASCENDING Track:30 Mode: IW_DP Swath: IW1 IW2 IW3 Sentinel-1 data discovery over Nigeria Goal: discover a pair of Sentinel-1 SLC for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
  • 5. Sentinel-1 data discovery over Nigeria Earth Observation dataset: Sentinel-1 Search parameters: productType: SLC start: 2019-09-09 end: 2019-09-21 orbitDirection: ASCENDING track: 30 Platform: S1A box: 5.1,10.8,8.1,13.7 Goal: discover a pair of Sentinel-1 SLC for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
  • 6. Coherence and backscatter change detection COIN Processing service Use the discovered pair of Sentinel-1 SLC procuts to fill the processing parameters: - Master - Slave Then set the parameter - Pixel spacing in meters to 10.0 Run the job Goal: process Sentinel-1 SLC pair for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
  • 7. Coherence and backscatter change detection COIN Processing service Use the discovered pair of Sentinel-1 SLC procuts to fill the processing parameters: - Master - Slave Then set the parameter - Pixel spacing in meters to 10.0 Run the job Goal: process Sentinel-1 SLC pair for change detection with the Coherence and Intensity change for Sentinel-1 (COIN) processing service
  • 9. Hands-on: data discovery, processing and data pipelines Steps: 1. Set-up your credentials 2. Data discovery 3. COIN processing 4. COIN results 5. Sentinel-2 RGB composites data processing pipeline 6. SNAC data processing pipeline 7. COIN data processing pipeline 8. SNAC exploitation Hackathon kit available at: https://gitlab.com/ellip/training/wfp-nigeria-training
  • 10. Hands-on: access and setup Open a Web Browser (best experience with Chrome) Type the address: https://notebooks.terradue.com You’ll be redirected to a login page. Use the credentials found on the card given to you
  • 11. Hands-on: access and setup Open the folder: wfp-nigeria-training Double-click on the notebook: 1 Setup.ipybnb Run the cells and fill the information requested: username: same as in card API key: click on the link shown copy/paste the API key Goal: set-up the authentication/authorization information for all notebooks
  • 12. Hands-on: data discovery Double-click on the notebook: 2 Data discovery.ipybnb Run the cells to repeat the data discovery steps done on the Geobrowser Goal: discover the pair of Sentinel-1 SLC acquisitions with the Ellip APIs following the same approach done using the Geobrowser
  • 13. Hands-on: data discovery Goal: discover the pair of Sentinel-1 SLC acquisitions with the Ellip APIs following the same approach done using the Geobrowser
  • 14. Hands-on: Sentinel-1 COIN processing Double-click on the notebook: 3 COIN processing.ipybnb Run the cells to submit the COIN processing request as done on the Geobrowser Goal: discover the COIN processing service and submit a processing request with the discovered pair of Sentinel-1 SLC acquisitions
  • 15. Hands-on: RGB composites data processing pipeline Double-click on the notebook: 4 COIN results.ipybnb Run the cells to inspect the processing results Goal: explore the results of the COIN processing service
  • 16. Data processing pipelines rely on the ATC model with: - Application - data driven application - Trigger - date or event driven application - Coordinator - schedule the execution of the Trigger instances periodically at fixed times, dates, or intervals Data processing pipelines
  • 17. The ATC model starts with a data driven application taking as inputs one or more references to EO catalogue entries: - A single input reference - A pair of input references (e.g. interferometry) - A stack of input references A(pplication)TC
  • 18. The Trigger is a date and/or event driven application that, when there’s new data available or an event: - Creates Data Items - Queues Data Items - Pipes Data Items AT(rigger)C
  • 19. OWS Context (*) documents encapsulating all the information for processing the application and get it through the data processing pipeline AT(rigger)C - Data items (*) https://www.opengeospatial.org/standards/owc
  • 20. The Coordinator submits Trigger instances periodically at fixed times, dates, or intervals ATC(oordinator)
  • 21. Hands-on: RGB composites data processing pipeline Double-click on the notebook: 5 RGB composites data processing pipeline.ipybnb Run the cells to create and queue Data Items containing Sentinel-2 RGB Composites processing requests The data processing pipeline will produce, for a set of areas of interest, several RGB composites for all Sentinel-2 acquisitions during the period 2019-08-15 to 09-15. Goal: create a data processing pipeline for Sentinel-2 RGB composites over a few areas of interest in Nigeria
  • 22. Hands-on: SNAC data processing pipeline Double-click on the notebook: 6 SNAC data processing pipeline.ipybnb Run the cells to create and queue Data Items containing SNAC processing requests Goal: create a data processing pipeline for Sentinel-1 SNAC over a large area in Nigeria
  • 23. Hands-on: SNAC data processing pipeline
  • 24. Hands-on: COIN data processing pipeline Double-click on the notebook: 7 COIN data processing pipeline.ipybnb Run the cells to create and queue Data Items containing COIN processing requests Goal: create a data processing pipeline for Sentinel-2 RGB composites over a few areas of interest in NigeriaGoal: create a data processing pipeline for Sentinel-1 COIN over a large area in Nigeria
  • 25. Hands-on: COIN data processing pipeline
  • 26. Hands-on: monitor a data processing pipeline Double-click on the notebook: 8 SNAC exploitation.ipybnb Monitor the Data Items status and access the associated results when done Goal: monitor and exploit the results of the Sentinel-1 SNAC data processing pipeline over a large area in Nigeria
  • 27. ▪ Get in touch with Terradue: support(at)terradue.com www.terradue.com ▪ Become a BETTER data challenge promoter: https://www.ec-better.eu/ Way forward Horizon 2020 Research and Innovation Programme under grant agreement no 776280