1. RSS support to scientific exploitation of EO data
Giancarlo Rivolta
ESRIN, 11 October 2012

2. Summary RSS Overview RSS G-POD process
RSS flexible resources for on-demand processing
Success stories
Future directions
GPOD demo
Questions & Answers

3. RSS Overview Research and Service Support Let’s focus on G-POD
The ESA Research and Service Support (RSS) service provides resources for supporting Earth Observation (EO) data exploitation
RSS users are EO Principal Investigators and EO Service Providers
The environments made available to RSS users are:
Grid Processing On-Demand (G-POD)
Service Support Environment (SSE)
E-collaboration environment (Join&Share)
OGC services (WMS, WFS, WCS)
Virtual Reality Theatre (VRT)
Knowledge-based Earth Observation (KEO)
Reference Data Sets (RDS)
EO Ontology search engine
More than 3500 people are registered as RSS users
On the industry side Logica delivers the RSS service as part of the ESRIN O&M Framecontract
More information available from the RSS Portal (rssportal.esa.int )
Let’s focus on G-POD

4. Research Process

5. RSS G-POD process steps
Principal Investigators
EO algorithms delivery
Data type and range indication
Output validation
On-demand EO data processing
Use of produced data (projects delivery, publications, etc)
RSS
Data are made available in the RSS catalogue
Algorithm porting
Integration design
Implementation
Test and validation (involving the PI)
On-demand EO data processing
Delivery

6. RSS Flexible Resources
On-demand processing service:
EO Scientists
Principal Investigators
Process
delivery
EO data
Application
Technology
Infrastructure
ESRIN
- 172 cores
- 400 TB
UK-PAC
- 88 cores
- 300 TB
Flexible Infrastructure
cores TB
Flexible Infrastructure satisfies:
HW requirements
Connectivity requirements
SLA (HA, help desk, ticketing systems, etc.)

7. RSS G-POD Team
On-demand Processing: team composition and responsibility
The G-POD team is composed by 4 selected highly skilled resources
Key areas of responsibility are:
Interaction with Principal Investigators
Algorithm Understanding and proposal evaluation
Resources planning (data, storage, integration, capacity, etc)
Algorithm integration (porting, design, implementation, test)
Data management
Processing environment set-up
User support (for on-demand processing)
Bulk Processing management
Key skills are:
Remote sensing background / EO data exploitation expertise
Software development /software integration
Virtualization technology
Grid / Cloud technology
Operations and Maintenance
Scientific goal orientation

8. Success Story: MGVI MERIS Global Vegetation Index Cat-1 project
Objective: Development of MERIS derived products based on the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) algorithm
IPR: MGVI algorithm developed and owned by the Joint Research Centre
Evolution and time span: Several GPOD-MGVI versions integrated since 2007, bulk re-processings over the entire ENVISAT mission ( )
Outcomes/Benefits:
Access to online data for bulk re-processing
Systematic global products published on ESA Earthnet Portal
Regional products distributed via RSS SSE and RSS OGC service as well
On-demand MGVI regional available
MGVI Europe / Africa distributed to JRC for creating products for desertification monitoring
Several scientific papers published
MGVI delivered as complementary information to Fire detection products over Senegal
From JRC contribution to the paper “A Model for the Scientific Exploitation of Earth Observation Missions”:
RSS supported the process of algorithm development, test and deployment over a general purpose processing on demand environment dedicated to the scientific exploitation of EO data generated by ESA missions, as well as the provision of tools and environments in support to that process.

9. Success Story: KLIMA-IASI
The KLIMA-IASI ESA Cat-1 project was initially structured along 3 phases
1- The KLIMA-IASI application is integrated in G-POD
The data set used consists of: IASI data levels L1B, L1C and L2, in EPS format; for the month of July 2008;
The results of the application on this data set are used to determine if results produced from Level L1B data are better than the results produced from Level L1C;
The phase is concluded with the decision to use Level L1B or Level L1C data;
Also, during this phase, processing performance is measured and the processing time for the qualification campaign is estimated
2- IASI Level L1 (B or C) and L2 are ingested for the whole year 2009, in EPS format, up to 5Tb
As a "qualification campaign", the KLIMA-IASI application is run upon the year 2009 data and results are used to validate the quality of the algorithm in relation to Gosat measurements;
Also, during this phase processing performance is measured and the exploitation scenario defined
3- Full IASI Mission data and EumetCast NRT are systematically ingested in G-POD
The KLIMA-IASI application performance is optimized in line with NRT requirements;
The KLIMA-IASI application is enhanced to accept BUFR data format;
KLIMA-IASI application is provided as a service to the User Community
IPR: KLIMA-IASI algorithm developed and owned by the IFAC-CNR, Florence
Evolution and time span: Several GPOD-MGVI versions integrated since 2011, bulk processing on dataset from 1 year IASI data (Mar 2010 – Feb 2011)
Outcomes/Benefits:
On-demand KLIMA-IASI service available to PI for pre-analysis
Access to cloud resources for flexible capacity to meet the deadline
Access to online data for bulk re-processing (11 out of 12 months processed)
Several scientific papers published and presentations at conferences
Process speeded-up by 2 orders of magnitude (flexible)

10. Success Story: SMOS SMOS testbed
Objective: Provide a flexible test environment to support ESA GQ users for L1 calibration and developers for L2 OS
Evolution and time span: Several SMOS L1 and L2 OS re-processing campaigns with custom configuration (recently processed sample SMOS L1 products over 25 months (from June 2010 to June 2012, 1728 L1A/B CRS products), SMOS L2 OS 1 month)
Outcomes/Benefits:
Fast integration of new versions (if ICD unchanged)
Access to online data for bulk re-processing
Access to flexible cloud resources for meeting deadlines
On-demand SMOS L1 available for GQ
On-demand SMOS L2 OS available for developer
SMOS L0 NRT ingestion chain set-up for L1 NRT custom re-processing
Testbeds required for other sensors as well
Open call for proposal published on EOPI

11. Future directions
In the light of the RSS success story the following should be considered
RSS model as basis for the definition of a harmonized model of research and service support
Federation of payload data ground segment services to the scientific community

12. Contacts & further information
Giancarlo Rivolta
RSS Team
GPOD Team
G-POD Portal gpod.eo.esa.int
Join&Share wiki.services.eoportal.org

13. GPOD demo Now the GPOD Team will give a 15-minute GPOD demo
GPOD Portal: gpod.eo.esa.int

14. Questions and Answers
Q&A?

15. Thank you Giancarlo Rivolta
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