Abstract
Satellite Image Time Series (SITS) analysis is an important domain with various applications in land study. In the coming years, both high temporal and high spatial resolution SITS will be available. This article aims at providing both temporal and spatial analysis of SITS. We propose first segmenting each image of the series, and then using these segmentations in order to characterize each pixel of the data with a spatial dimension (i.e. with contextual information). Providing spatially characterized pixels, pixel-based temporal analysis can be performed. Experiments carried out with this methodology show the relevance of this approach and the significance of the resulting extracted patterns in the context of the analysis of SITS.
| Original language | English |
|---|---|
| Title of host publication | 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 495-498 |
| Number of pages | 4 |
| ISBN (Print) | 9781457710056 |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
| Event | IEEE International Geoscience and Remote Sensing Symposium 2011 - Vancouver Convention Center, Vancouver BC, Canada Duration: 24 Jul 2011 → 29 Jul 2011 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6034618 (IEEE Conference Proceedings) |
Conference
| Conference | IEEE International Geoscience and Remote Sensing Symposium 2011 |
|---|---|
| Abbreviated title | IGARSS 2011 |
| Country | Canada |
| City | Vancouver BC |
| Period | 24/07/11 → 29/07/11 |
| Internet address |
|
Keywords
- Data Mining
- Mean-Shift
- Multi-temporal analysis
- Satellite Image Time Series
- Segmentation
Cite this
}
A context-based approach for the classification of satellite image time series. / Kurtz, Camille; Petitjean, François; Gançarski, Pierre.
2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings. IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 495-498 6049173.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review
TY - GEN
T1 - A context-based approach for the classification of satellite image time series
AU - Kurtz, Camille
AU - Petitjean, François
AU - Gançarski, Pierre
PY - 2011
Y1 - 2011
N2 - Satellite Image Time Series (SITS) analysis is an important domain with various applications in land study. In the coming years, both high temporal and high spatial resolution SITS will be available. This article aims at providing both temporal and spatial analysis of SITS. We propose first segmenting each image of the series, and then using these segmentations in order to characterize each pixel of the data with a spatial dimension (i.e. with contextual information). Providing spatially characterized pixels, pixel-based temporal analysis can be performed. Experiments carried out with this methodology show the relevance of this approach and the significance of the resulting extracted patterns in the context of the analysis of SITS.
AB - Satellite Image Time Series (SITS) analysis is an important domain with various applications in land study. In the coming years, both high temporal and high spatial resolution SITS will be available. This article aims at providing both temporal and spatial analysis of SITS. We propose first segmenting each image of the series, and then using these segmentations in order to characterize each pixel of the data with a spatial dimension (i.e. with contextual information). Providing spatially characterized pixels, pixel-based temporal analysis can be performed. Experiments carried out with this methodology show the relevance of this approach and the significance of the resulting extracted patterns in the context of the analysis of SITS.
KW - Data Mining
KW - Mean-Shift
KW - Multi-temporal analysis
KW - Satellite Image Time Series
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=80955144960&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2011.6049173
DO - 10.1109/IGARSS.2011.6049173
M3 - Conference Paper
AN - SCOPUS:80955144960
SN - 9781457710056
SP - 495
EP - 498
BT - 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings
PB - IEEE, Institute of Electrical and Electronics Engineers
ER -