Jonas Eberle 25th March 2015 1
Automatization of information extractionto build up a crowd-sourced reference
database for vegetation changes
Jonas Eberle, Dr. Christian Hüttich, Prof. Christine Schmullius
Friedrich-Schiller-University Jena, GermanyInstitute for Geography, Department for Earth Observation
www.eo.uni-jena.de
Joint Breakout Session 1: Intelligent use of data quantity vs focusing on data quality
Jonas Eberle 25th March 2015 2
Lots of data is freely available
Jonas Eberle 25th March 2015 3
Lots of data is freely available
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How to process available data?
For any dataset For different data formats For any time stamp
1. Find download files2. Download data3. Convert data4. Clip data to study area5. Apply quality masks
1. Find download files2. Download data3. Convert data4. Clip data to study area5. Apply quality masks
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Intelligent use of data quantity
• What is needed?1. Automation in data access
2. Easy to use clients
3. Possibility to create / publish new information
• What should be achieved in our case?– Try to explain a change detected in the time series Evaluate changes based on additional data
– Easy use of a wide range of datasets (no processing needed) Interactive change evaluation of spatial time-series data
Create new knowledge and information
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Intelligent use of data quantity
1. Automation in data access– Data Processing
Middleware
– Standardized data publishing
• OGC Web Services
– Necessary inputs• Name of dataset• Geometry (Point,
Polygon)• Further optional
parametersFigure: Multi-Source Data Processing Middleware
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Intelligent use of data quantity
2. Easy to use clients
– Web Portal• Modern web technologies• Based on web services• User accounts
– Mobile Application• Data access & analysis tools
in the field• GPS position
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Intelligent use of data quantity
3. Possibility to create / publish new information
– Scientific algorithms has to be linked to automated data access Provide scientific algorithms as web services
– Users can validate the results of these algorithms based on additional datasets and create new information
• e.g., valid change areas
We need automated data access linked with automated execution of scientific algorithms!
Automated access, analysis, and monitoring of global vegetation time-series data
Automated access, analysis, and monitoring of global vegetation time-series data
Earth Observation Monitor
Datasets: •MODIS 16-Daily Vegetation Index (NDVI, EVI)
Data access:•Pixel or Polygon-based extraction service
Analyses: •Trend calculations•Breakpoint detection•Phenological parameters
Applications:•Web Portal•Mobile App (mobileEOM) for iOS and Android
www.earth-observation-monitor.net
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Earth Change Monitor
• Objectives– Detect areas based on environmental change events in high
density time series data (MODIS)
– Provide high resolution images (Landsat) of the pre- and after change events
– Add further datasets to distinguish between different types of change
– Provide simple tools for users and developers with web services and web interfaces.
Make use of wide variety of available data (data quantity) to create new information to build up a reference database.
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Intelligent use of data quantity
Concept of the „Earth Change Monitor“:
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Focusing on data quality
• We have to consider quality flags (if available!) when using data– Good example: MODIS products
• Crowd-sourced reference database needs to be checked on errors / wrong interpretations– Access only to “experts”
– Users can gain “expert” status for their user account
– Users reference database vs. global reference database
Use data quantity to increase quality of algorithm results (e.g., break-point in vegetation time-series)
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Conclusions
• Crowd-sourced intiative can help scientists to better test their algorithms for information extraction and benefit from the input of users
• Web 2.0 leads us to a new way of – how algorithms can be tested and – how a crowd-sourced reference database can be build up
We need simple web services for data access linked with web services for algorithm execution registered to GEOSS
EO time-series data are better useable and lead to new knowledge to further improve algorithms and validated reference information.
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Thank you for your attention!
Questions?
Contact information:
Jonas EberleFriedrich-Schiller-University
Institute for GeographyDepartment Earth Observation
Loebdergraben 3207743 Jena, Germany
phone: +49 3641 94 88 89email: [email protected]
Acknowledgement: Friedrich-Schiller-University Jena and EU FP7 EuRuCAS
project (No. 295068) for financing work and travel.