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

^*Huvudförfattare för detta arbete

Publikation: Kapitel i bok/rapport/konferenshandling › Konferensartikel i proceedings › Peer review

Sammanfattning

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.

Originalspråk	Engelska
Titel på värdpublikation	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Förlag	Institute of Electrical and Electronics Engineers (IEEE)
Sidor	3186-3189
Antal sidor	4
ISBN (elektroniskt)	9798350320107
DOI	https://doi.org/10.1109/IGARSS52108.2023.10281450
Status	Publicerad - 2023
Externt publicerad	Ja
Evenemang	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, USA Varaktighet: 16 juli 2023 → 21 juli 2023

Publikationsserier

Serie	International Geoscience and Remote Sensing Symposium (IGARSS)
Volym	2023-July

Konferens

Konferens	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Land/Territorium	USA
Ort	Pasadena
Period	2023-07-16 → 2023-07-21

Bibliografisk information

Publisher Copyright:
© 2023 IEEE.

Åtkomst av dokument

10.1109/IGARSS52108.2023.10281450

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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. I IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (s. 3186-3189). Institute of Electrical and Electronics Engineers (IEEE). 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 (IEEE), 2023. s. 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.",

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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",

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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. i IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers (IEEE), International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2023-July, s. 3186-3189, 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, USA, 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 (IEEE), 2023. s. 3186-3189 (International Geoscience and Remote Sensing Symposium (IGARSS), Vol. 2023-July).

Publikation: Kapitel i bok/rapport/konferenshandling › Konferensartikel i proceedings › Peer review

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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

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