Jonas Eberle 25th March 2015 1 Automatization of information extraction to build up a crowd-sourced reference database for vegetation changes Jonas Eberle, Dr. Christian Hüttich, Prof. Christine Schmullius Friedrich-Schiller-University Jena, Germany Institute 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
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Jonas Eberle 25th March 20151 Automatization of information extraction to build up a crowd-sourced reference database for vegetation changes Jonas Eberle,
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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
Jonas Eberle 25th March 2015 4
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
Jonas Eberle 25th March 2015 5
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
Jonas Eberle 25th March 2015 6
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