Evaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fields

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dc.contributor.authorArias Cuenca, María
dc.contributor.authorNotarnicola, Claudia
dc.contributor.authorCampo-Bescós, Miguel
dc.contributor.authorArregui Odériz, Luis Miguel
dc.contributor.authorÁlvarez-Mozos, Jesús
dc.contributor.departmentAgronomía, Biotecnología y Alimentaciónes_ES
dc.contributor.departmentAgronomia, Bioteknologia eta Elikaduraeu
dc.contributor.departmentIngenieríaes_ES
dc.contributor.departmentIngeniaritzaeu
dc.contributor.departmentInstitute on Innovation and Sustainable Development in Food Chain - ISFOODen
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoaes
dc.date.accessioned2023-09-06T09:26:51Z
dc.date.available2023-09-06T09:26:51Z
dc.date.issued2023
dc.date.updated2023-09-06T09:18:07Z
dc.description.abstractSoil moisture (SM) is a key variable in agriculture and its monitoring is essential. SM determines the amount of water available to plants, having a direct impact on the development of crops, on the forecasting of crop yields and on the surveillance of food security. Microwave remote sensing offers a great potential for estimating SM because it is sensitive to the dielectric characteristics of observed surface that depend on surface soil moisture. The objective of this study is the evaluation of three change detection methodologies for SM estimation over wheat at the agricultural field scale based on Sentinel-1 time series: Short Term Change Detection (STCD), TU Wien Change Detection (TUWCD) and Multitemporal Bayesian Change Detection (MTBCD). Different methodological alternatives were proposed for the implementation of these techniques at the agricultural field scale. Soil moisture measurements from eight experimental wheat fields were used for validating the methodologies. All available Sentinel-1 acquisitions were processed and the eventual benefit of correcting for vegetation effects in backscatter time series was evaluated. The results were rather variable, with some experimental fields achieving successful performance metrics (ubRMSE ~ 0.05 m3 /m3 ) and some others rather poor ones (ubRMSE > 0.12 m3 / m3 ). Evaluating median performance metrics, it was observed that both TUWCD and MTBCD methods obtained better results when run with vegetation corrected backscatter time series (ubRMSE ~0.07 m3 /m3 ) whereas STCD produced similar results with and without vegetation correction (ubRMSE ~0.08 m3 /m3 ). The soil moisture content had an influence on the accuracy of the different methodologies, with higher errors observed for drier conditions and rain-fed fields, in comparison to wetter conditions and irrigated fields. Taking into account the spatial scale of this case study, results were considered promising for the future application of these techniques in irrigation management.en
dc.description.sponsorshipThis work was supported by the Spanish Ministry of Science and Innovation and the European Regional Development Fund (MICINN/ FEDER-UE) through projects [CGL2016–75217-R and PID2019–107386RB-I00 / AEI / 10.13039/501100011033] and doctoral grant [BES-2017–080560]. Open access funding provided by the Public University of Navarre.en
dc.format.mimetypeapplication/pdfen
dc.format.mimetypeapplication/msworden
dc.identifier.citationArias, M., Notarnicola, C., Campo-Bescós, M. Á., Arregui, L. M., & Álvarez-Mozos, J. (2023). Evaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fields. Agricultural Water Management, 287, 108422. https://doi.org/10.1016/j.agwat.2023.108422en
dc.identifier.doi10.1016/j.agwat.2023.108422
dc.identifier.issn0378-3774
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/46235
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofAgricultural Water Management, 287 (2023) 108422en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/ PID2019–107386RB-I00/ES/
dc.relation.publisherversionhttps://doi.org/10.1016/j.agwat.2023.108422
dc.rights© 2023 The Author(s). This is an open access article under the CC BY-NC-ND license.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSoil wetnessen
dc.subjectAgricultureen
dc.subjectSARen
dc.subjectChange detectionen
dc.subjectField scaleen
dc.titleEvaluation of soil moisture estimation techniques based on Sentinel-1 observations over wheat fieldsen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
relation.isAuthorOfPublication08624ac7-fa16-4271-bcf9-8947430cf5ce
relation.isAuthorOfPublicatione9ca0d9f-24bc-4ce1-871f-81ce4e86b5bd
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relation.isAuthorOfPublicationf2f80825-fc58-4e45-9814-9eb10b68c4a9
relation.isAuthorOfPublication.latestForDiscovery08624ac7-fa16-4271-bcf9-8947430cf5ce

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