Abstract
The recent proliferation of constellations of recurrent satellites enables the constitution of temporally dense times series of registered images. We therefore propose in this paper a more in depth detection and analysis of observable changes. This approach is intended to be generic and independent of the type of satellite used, whether band limited or multispectral. It is based on a global analysis of the sequence. The detection stage is based on the definition of a residual sequence calculated from the novelty filter. A statistical approach based on the NFA test is then employed to detect significant changes. We then use these detections to classify the changes according to their nature: unique or lasting. To establish the efficiency of the method, we created an open dataset of 28 sequences of 20 images acquired by Sentinel-2 in different regions of the world. We obtain satisfactory results which are consistent with the visual observations of experts.
| Original language | English |
|---|---|
| Title of host publication | IGARSS 2021: 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings |
| Publisher | IEEE |
| Pages | 4360-4363 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781665403696 |
| ISBN (Print) | 9781665447621 |
| DOIs | |
| Publication status | Published - 2021 |
| Externally published | Yes |
| Event | 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium Duration: 12 Jul 2021 → 16 Jul 2021 |
Conference
| Conference | 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 |
|---|---|
| Country/Territory | Belgium |
| City | Brussels |
| Period | 12/07/21 → 16/07/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE
Funding
Work partly financed by Office of Naval research grant N00014-20-S-B001, DGA Astrid project “Filmer la Terre” no ANR-17-ASTR-0013-01 and Kayrros SAS.
Keywords
- change detection
- dataset
- multi-temporal
- satellite
- time series