Date post: | 09-Apr-2017 |
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REMOTE SENSING DATA
EXPLOITATION IN THE
SECURE SOCIETIES PILOT
2nd BDE Hangout “Big Data in Secure societies”21 April 2016
Michele Lazzarini, EU SatCen
RTDI Project Officer
Why Earth Observation (EO) data are Big
Data?
EO data are showing an unprecedented scenario
o Volume: Tb of EO data received each day from satellites
o Variety: Data coming from different EO sensors
o Velocity: Data to be delivered timely to users requiring fast responses
o Veracity: Decision making and operations require reliable sources
o Value: Information to be provided has to be clear and useful
Datasets for Security also composed by data from other sources…
C.Reck, G.Campuzano, K.Dengler, T. Heinen and M. Winkler, “German Copernicus Data Access and Exploitation Platform”,
Big Data from Space Conference, 15-17 March, Santa Cruz de Tenerife (ES), 2016.
BigDataEurope Pilot
Remote Sensing Big Data Platform Social Sensing
• Input (Data Access)
• Pre-Processing (Calibration
and Co-registration)
• Change Detection
• Output (Visualization)
• Monitor News
• Event Analysis (cluster,
enrich, store)
• Extract AoI
• Comparison with change
detection and visualization
Change Detection Workflow
Event Detection Workflow
Change Detection
Workflow
Event Detection
Workflow
Common
Workflow
Pilot Change Detection Workflow
Input
(Data Access)
Calibration
Co-registration
Change detection
Output
(Visualization)
The change detection workflow starts with ingestion
of satellite images
A set of operations (calibration and co-registration)
is performed to create a stack (time series) of data
Appropriated algorithms are applied to detect
areas with changes on land cover by using change
detection and characterization techniques
The identified Areas of Interest are then associated
with social media and news items and presented to
the end-user for cross-validation
Input: sensor type
SAR (radar) Optical
Input: Sentinels
Sentinels data are free and open, available from the Sentinel Scientific Data Hub
or other Collaborative Data Hubs
SENTINEL-2A (to be used in the second phase)
Launched in 2015 (Sentinel-2B lunch planned
mid-2016)
Optical sensor
Ground resolution from 10 to 60 m
Rep. cycle: 10 days with one satellite,
5 days with 2 satellites
SENTINEL-1A
Launched in 2014 (Sentinel-1B lunch
scheduled on 22nd of April 2016)
SAR sensor
Ground resolution of 5 x 20 m
Rep. cycle: 12 days with one satellite,
6 days with 2 satellites
Input: Sentinel 1
All weather capabilities
(even with clouds)
Day and night acquisition
Difficult to interpret (i.e.
ascending and descending
orbits, geometric effects)
Calibration
(Radiometric) calibration consists in linking pixels intensities to a physical parameter.
This operation is necessary to compare two or more images in a time series.
Same area, acquired from two different angles, looks different
Co-registration
Geometric correction
and co-registration of
an image stack consist in
the conversion of data in
a common ground
coordinates system in
order to:
Removal of
distortions from
sensor geometry
Enable to mapping
it with other
geographic data
Change detection and characterization
Input Output
Conclusions and future works
Input
(Data acquisition)
Calibration
Co-registration
Change detection and
characterization
Output
(Map of changes and
identified features)
Sentinel 1A GRD images are currently acquired from the Sentinels Data
Hub; Sentinel 1A SLC, Sentinel 1B and Sentinel 2 images will be added
in the data acquisition step
Sentinel 1 calibration algorithm has been deployed based on SNAP*
algorithm
Sentinel 1 co-registration algorithm has been deployed based on SNAP
algorithm
Sentinel 1 change detection algorithm has been deployed based on
SNAP algorithm, in-house tools to change detection and characterization
are currently under development
Output Binary map (changes/no changes) is available, other output
formats are under development*http://step.esa.int/main/toolboxes/snap/
UNCLASSIFIED / FOR OFFICIAL USE ONLY
European Union Satellite Centre © 2016
Michele LazzariniRTDI Project Officer