CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES

T. Dagobert; R. Grompone von Gioi; C. Hessel; J.-M. Morel; C. de Franchis

doi:10.1109/IGARSS47720.2021.9554700

CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES

T. Dagobert
, R. Grompone von Gioi^*
, C. Hessel
, J.-M. Morel
, C. de Franchis

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

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. © 2021 IEEE

Original language	English
Title of host publication	IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publication	Proceedings
Publisher	IEEE
Pages	4360-4363
ISBN (Electronic)	978-1-6654-0369-6, 978-1-6654-0368-9
ISBN (Print)	978-1-6654-4762-1
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9554700
Publication status	Published - 2021
Externally published	Yes
Event	2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021) - Virtual, Brussels, Belgium Duration: 11 Jul 2021 → 16 Jul 2021

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021)
Place	Belgium
City	Brussels
Period	11/07/21 → 16/07/21

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.

Research Keywords

change detection
dataset
multi-temporal
satellite
time series

Access Output

10.1109/IGARSS47720.2021.9554700

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Dagobert, T., von Gioi, R. G., Hessel, C., Morel, J.-M., & de Franchis, C. (2021). CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES. In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium: Proceedings (pp. 4360-4363). (International Geoscience and Remote Sensing Symposium (IGARSS)). IEEE. https://doi.org/10.1109/IGARSS47720.2021.9554700

@inproceedings{0223de98432d465da727b7522c241b13,

title = "CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES",

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. {\textcopyright} 2021 IEEE",

keywords = "change detection, dataset, multi-temporal, satellite, time series",

author = "T. Dagobert and \{von Gioi\}, \{R. Grompone\} and C. Hessel and J.-M. Morel and \{de Franchis\}, C.",

year = "2021",

doi = "10.1109/IGARSS47720.2021.9554700",

language = "English",

isbn = "978-1-6654-4762-1",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "IEEE",

pages = "4360--4363",

booktitle = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium",

address = "United States",

note = "2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021) ; Conference date: 11-07-2021 Through 16-07-2021",

}

Dagobert, T, von Gioi, RG, Hessel, C, Morel, J-M & de Franchis, C 2021, CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES. in IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, pp. 4360-4363, 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021), Brussels, Belgium, 11/07/21. https://doi.org/10.1109/IGARSS47720.2021.9554700

CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES. / Dagobert, T.; von Gioi, R. Grompone; Hessel, C. et al.
IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium: Proceedings. IEEE, 2021. p. 4360-4363 (International Geoscience and Remote Sensing Symposium (IGARSS)).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES

AU - Dagobert, T.

AU - von Gioi, R. Grompone

AU - Hessel, C.

AU - Morel, J.-M.

AU - de Franchis, C.

PY - 2021

Y1 - 2021

N2 - 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. © 2021 IEEE

AB - 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. © 2021 IEEE

KW - change detection

KW - dataset

KW - multi-temporal

KW - satellite

KW - time series

UR - https://www.scopus.com/pages/publications/85129818719

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85129818719&origin=recordpage

U2 - 10.1109/IGARSS47720.2021.9554700

DO - 10.1109/IGARSS47720.2021.9554700

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-6654-4762-1

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 4360

EP - 4363

BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2021)

Y2 - 11 July 2021 through 16 July 2021

ER -

CHANGE ANALYSIS IN REGISTERED SATELLITE IMAGE TIME SERIES

Abstract

Publication series

Conference

Funding

Research Keywords

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this