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Temporal analysis of Sentinel-1 coherence images. / Nico, Giovanni; Mira, Nuno; Masci, Olimpia; Catalão, João; Panidi, Evgeny.

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI. ред. / Christopher M. U. Neale; Antonino Maltese. SPIE, 2019. 1114904 (Proceedings of SPIE - The International Society for Optical Engineering; Том 11149).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Nico, G, Mira, N, Masci, O, Catalão, J & Panidi, E 2019, Temporal analysis of Sentinel-1 coherence images. в CMU Neale & A Maltese (ред.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI., 1114904, Proceedings of SPIE - The International Society for Optical Engineering, Том. 11149, SPIE, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019, Strasbourg, Франция, 9/09/19. https://doi.org/10.1117/12.2534979

APA

Nico, G., Mira, N., Masci, O., Catalão, J., & Panidi, E. (2019). Temporal analysis of Sentinel-1 coherence images. в C. M. U. Neale, & A. Maltese (Ред.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI [1114904] (Proceedings of SPIE - The International Society for Optical Engineering; Том 11149). SPIE. https://doi.org/10.1117/12.2534979

Vancouver

Nico G, Mira N, Masci O, Catalão J, Panidi E. Temporal analysis of Sentinel-1 coherence images. в Neale CMU, Maltese A, Редакторы, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI. SPIE. 2019. 1114904. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2534979

Author

Nico, Giovanni ; Mira, Nuno ; Masci, Olimpia ; Catalão, João ; Panidi, Evgeny. / Temporal analysis of Sentinel-1 coherence images. Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI. Редактор / Christopher M. U. Neale ; Antonino Maltese. SPIE, 2019. (Proceedings of SPIE - The International Society for Optical Engineering).

BibTeX

@inproceedings{5abeb0d84a78423091654981f1de8c9e,
title = "Temporal analysis of Sentinel-1 coherence images",
abstract = "This paper presents the results of a study aiming to identify targets in Synthetic Aperture Radar (SAR) images having different properties in terms of microwave scattering and temporal stability using the interferometric SAR coherence and the Principal Component Analysis (PCA). Coherence maps used in this analysis are generated starting from a time series of Sentinel-1 images. A flat area in Padan plain (Italy), characterized by agricultural fields with different crops, urban settlements and water surfaces is chosen as study area.",
keywords = "Interferometric coherence, Principal Component Analysis (PCA), SAR interferometry (InSAR), Sentinel-1, Synthetic Aperture Radar (SAR)",
author = "Giovanni Nico and Nuno Mira and Olimpia Masci and Jo{\~a}o Catal{\~a}o and Evgeny Panidi",
year = "2019",
month = jan,
day = "1",
doi = "10.1117/12.2534979",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Neale, {Christopher M. U.} and Antonino Maltese",
booktitle = "Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI",
address = "United States",
note = "Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019 ; Conference date: 09-09-2019 Through 11-09-2019",

}

RIS

TY - GEN

T1 - Temporal analysis of Sentinel-1 coherence images

AU - Nico, Giovanni

AU - Mira, Nuno

AU - Masci, Olimpia

AU - Catalão, João

AU - Panidi, Evgeny

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This paper presents the results of a study aiming to identify targets in Synthetic Aperture Radar (SAR) images having different properties in terms of microwave scattering and temporal stability using the interferometric SAR coherence and the Principal Component Analysis (PCA). Coherence maps used in this analysis are generated starting from a time series of Sentinel-1 images. A flat area in Padan plain (Italy), characterized by agricultural fields with different crops, urban settlements and water surfaces is chosen as study area.

AB - This paper presents the results of a study aiming to identify targets in Synthetic Aperture Radar (SAR) images having different properties in terms of microwave scattering and temporal stability using the interferometric SAR coherence and the Principal Component Analysis (PCA). Coherence maps used in this analysis are generated starting from a time series of Sentinel-1 images. A flat area in Padan plain (Italy), characterized by agricultural fields with different crops, urban settlements and water surfaces is chosen as study area.

KW - Interferometric coherence

KW - Principal Component Analysis (PCA)

KW - SAR interferometry (InSAR)

KW - Sentinel-1

KW - Synthetic Aperture Radar (SAR)

UR - http://www.scopus.com/inward/record.url?scp=85078159576&partnerID=8YFLogxK

U2 - 10.1117/12.2534979

DO - 10.1117/12.2534979

M3 - Conference contribution

AN - SCOPUS:85078159576

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI

A2 - Neale, Christopher M. U.

A2 - Maltese, Antonino

PB - SPIE

T2 - Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019

Y2 - 9 September 2019 through 11 September 2019

ER -

ID: 51466539