Abstract
Satellite Image Time Series (SITS, for short) are useful resources for Earth monitoring. Upcoming satellites will provide a global coverage of the Earth's surface with a short revisit time (five days); a huge amount of data to analyze will be produced. In order to be able to analyze efficiently and accurately these images, new methods have to be designed. In this article, we propose to combine a spatio-temporal segmentation pre-processing method - quasi-flat zones, which have been recently extended to video analysis - and the distortion power of DTW to simplify the representation of the SITS, in order to reduce both the time and the memory consumption. Experiments carried out on a series of 46 images show that the memory consumption can be reduced by an order of magnitude without reducing the relevance of the analysis.
Original language | English |
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Title of host publication | IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 4387-4390 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2012 |
Externally published | Yes |
Event | IEEE International Geoscience and Remote Sensing Symposium 2012 - International Congress Centre, Munich, Germany Duration: 22 Jul 2012 → 27 Jul 2012 Conference number: 32nd http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6334512 (IEEE Conference Proceedings) |
Conference
Conference | IEEE International Geoscience and Remote Sensing Symposium 2012 |
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Abbreviated title | IGARSS 2012 |
Country/Territory | Germany |
City | Munich |
Period | 22/07/12 → 27/07/12 |
Internet address |
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Keywords
- Crops
- Image classification
- Image segmentation
- Remote Sensing
- Time series analysis