An Hybrid Approach for Soil Moisture Estimation with Sentinel Data

Mehrez Zribi; Simon Nativel; Emna Ayari; Simon Gascoin; Clement Albergel; Nicolas Baghdadi; Remi Madelon; Nemesio Rodriguez-Fernandez

doi:10.1109/IGARSS52108.2023.10281450

An Hybrid Approach for Soil Moisture Estimation with Sentinel Data

Mehrez Zribi^*
, Simon Nativel
, Emna Ayari
, Simon Gascoin
, Clement Albergel
, Nicolas Baghdadi
, Remi Madelon
, Nemesio Rodriguez-Fernandez

^*Corresponding author for this work

Publication: Chapter in Book/Report/Conference proceeding › Conference paper in proceedings › peer-review

Abstract

We propose a methodology combining a change detection approach with a neural network algorithm to monitor soil moisture. The methodology utilizes Sentinel-1 and Sentinel-2 data, incorporating various metrics such as radar signals (VV and VH polarization), surface soil moisture index (I_SSM), radar incidence angle, normalized difference vegetation index (NDVI), and VH/VV ratio. In situ data from the International Soil Moisture Network (ISMN) across diverse climatic contexts are used for testing. The results demonstrate improved soil moisture estimations using the hybrid algorithms.

Original language	English
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3186-3189
Number of pages	4
ISBN (Electronic)	9798350320107
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10281450
Publication status	Published - 2023
Externally published	Yes
Event	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States Duration: 16 Jul 2023 → 21 Jul 2023

Publication series

Series	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2023-July

Conference

Conference	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/Territory	United States
City	Pasadena
Period	2023-07-16 → 2023-07-21

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

ANN
change detection
Sentinel-1
Sentinel-2
Soil moisture

Access to Document

10.1109/IGARSS52108.2023.10281450

Cite this

Zribi, M., Nativel, S., Ayari, E., Gascoin, S., Albergel, C., Baghdadi, N., Madelon, R., & Rodriguez-Fernandez, N. (2023). An Hybrid Approach for Soil Moisture Estimation with Sentinel Data. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 3186-3189). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS52108.2023.10281450

Zribi, Mehrez ; Nativel, Simon ; Ayari, Emna et al. / An Hybrid Approach for Soil Moisture Estimation with Sentinel Data. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 3186-3189 (International Geoscience and Remote Sensing Symposium (IGARSS), Vol. 2023-July).

@inproceedings{d5a66a54dc484c418cea0a8807999689,

title = "An Hybrid Approach for Soil Moisture Estimation with Sentinel Data",

abstract = "We propose a methodology combining a change detection approach with a neural network algorithm to monitor soil moisture. The methodology utilizes Sentinel-1 and Sentinel-2 data, incorporating various metrics such as radar signals (VV and VH polarization), surface soil moisture index (I\_SSM), radar incidence angle, normalized difference vegetation index (NDVI), and VH/VV ratio. In situ data from the International Soil Moisture Network (ISMN) across diverse climatic contexts are used for testing. The results demonstrate improved soil moisture estimations using the hybrid algorithms.",

keywords = "ANN, change detection, Sentinel-1, Sentinel-2, Soil moisture",

author = "Mehrez Zribi and Simon Nativel and Emna Ayari and Simon Gascoin and Clement Albergel and Nicolas Baghdadi and Remi Madelon and Nemesio Rodriguez-Fernandez",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 ; Conference date: 16-07-2023 Through 21-07-2023",

year = "2023",

doi = "10.1109/IGARSS52108.2023.10281450",

language = "English",

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

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Zribi, M, Nativel, S, Ayari, E, Gascoin, S, Albergel, C, Baghdadi, N, Madelon, R & Rodriguez-Fernandez, N 2023, An Hybrid Approach for Soil Moisture Estimation with Sentinel Data. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2023-July, pp. 3186-3189, 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, United States, 2023-07-16. https://doi.org/10.1109/IGARSS52108.2023.10281450

An Hybrid Approach for Soil Moisture Estimation with Sentinel Data. / Zribi, Mehrez; Nativel, Simon; Ayari, Emna et al.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. p. 3186-3189 (International Geoscience and Remote Sensing Symposium (IGARSS), Vol. 2023-July).

Publication: Chapter in Book/Report/Conference proceeding › Conference paper in proceedings › peer-review

TY - GEN

T1 - An Hybrid Approach for Soil Moisture Estimation with Sentinel Data

AU - Zribi, Mehrez

AU - Nativel, Simon

AU - Ayari, Emna

AU - Gascoin, Simon

AU - Albergel, Clement

AU - Baghdadi, Nicolas

AU - Madelon, Remi

AU - Rodriguez-Fernandez, Nemesio

PY - 2023

Y1 - 2023

N2 - We propose a methodology combining a change detection approach with a neural network algorithm to monitor soil moisture. The methodology utilizes Sentinel-1 and Sentinel-2 data, incorporating various metrics such as radar signals (VV and VH polarization), surface soil moisture index (I_SSM), radar incidence angle, normalized difference vegetation index (NDVI), and VH/VV ratio. In situ data from the International Soil Moisture Network (ISMN) across diverse climatic contexts are used for testing. The results demonstrate improved soil moisture estimations using the hybrid algorithms.

AB - We propose a methodology combining a change detection approach with a neural network algorithm to monitor soil moisture. The methodology utilizes Sentinel-1 and Sentinel-2 data, incorporating various metrics such as radar signals (VV and VH polarization), surface soil moisture index (I_SSM), radar incidence angle, normalized difference vegetation index (NDVI), and VH/VV ratio. In situ data from the International Soil Moisture Network (ISMN) across diverse climatic contexts are used for testing. The results demonstrate improved soil moisture estimations using the hybrid algorithms.

KW - ANN

KW - change detection

KW - Sentinel-1

KW - Sentinel-2

KW - Soil moisture

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DO - 10.1109/IGARSS52108.2023.10281450

M3 - Conference paper in proceedings

AN - SCOPUS:85178341585

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

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BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings

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Zribi M, Nativel S, Ayari E, Gascoin S, Albergel C, Baghdadi N et al. An Hybrid Approach for Soil Moisture Estimation with Sentinel Data. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. p. 3186-3189. (International Geoscience and Remote Sensing Symposium (IGARSS), Vol. 2023-July). doi: 10.1109/IGARSS52108.2023.10281450

An Hybrid Approach for Soil Moisture Estimation with Sentinel Data

Abstract

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Bibliographical note

Keywords

Access to Document

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