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 |
|---|---|
| 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 |
|---|---|
| Abbreviated title | IGARSS 2012 |
| Country | Germany |
| City | Munich |
| Period | 22/07/12 → 27/07/12 |
| Internet address |
|
Keywords
- Crops
- Image classification
- Image segmentation
- Remote Sensing
- Time series analysis
Cite this
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Towards efficient satellite image time series analysis : Combination of dynamic time warping and quasi-flat zones. / Weber, Jonathan; Petitjean, Francois; Gancarski, Pierre.
IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, Institute of Electrical and Electronics Engineers, 2012. p. 4387-4390 6350401.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Towards efficient satellite image time series analysis
T2 - Combination of dynamic time warping and quasi-flat zones
AU - Weber, Jonathan
AU - Petitjean, Francois
AU - Gancarski, Pierre
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Crops
KW - Image classification
KW - Image segmentation
KW - Remote Sensing
KW - Time series analysis
UR - http://www.scopus.com/inward/record.url?scp=84873105828&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2012.6350401
DO - 10.1109/IGARSS.2012.6350401
M3 - Conference Paper
AN - SCOPUS:84873105828
SP - 4387
EP - 4390
BT - IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium
PB - IEEE, Institute of Electrical and Electronics Engineers
ER -