Monitoring rainfed alfalfa growth in semiarid agrosystems using Sentinel-2 imagery

Echeverría Obanos, Andrés; Urmeneta, Alejandro; González de Audícana Amenábar, María; González de Andrés, Ester

Monitoring rainfed alfalfa growth in semiarid agrosystems using Sentinel-2 imagery

dc.contributor.author	Echeverría Obanos, Andrés
dc.contributor.author	Urmeneta, Alejandro
dc.contributor.author	González de Audícana Amenábar, María
dc.contributor.author	González de Andrés, Ester
dc.contributor.department	Zientziak	eu
dc.contributor.department	Ingeniaritza	eu
dc.contributor.department	Institute for Multidisciplinary Research in Applied Biology - IMAB	en
dc.contributor.department	Institute on Innovation and Sustainable Development in Food Chain - ISFOOD	en
dc.contributor.department	Ciencias	es_ES
dc.contributor.department	Ingeniería	es_ES
dc.contributor.funder	Gobierno de Navarra / Nafarroako Gobernua	es
dc.date.accessioned	2022-03-10T08:00:01Z
dc.date.available	2022-03-10T08:00:01Z
dc.date.issued	2021
dc.description.abstract	The aim of this study was to assess the utility of Sentinel-2 images in the monitoring of the fractional vegetation cover (FVC) of rainfed alfalfa in semiarid areas such as that of Bardenas Reales in Spain. FVC was sampled in situ using 1 m2 surfaces at 172 points inside 18 alfalfa fields from late spring to early summer in 2017 and 2018. Different vegetation indices derived from a series of Sentinel-2 images were calculated and were then correlated with the FVC measurements at the pixel and parcel levels using different types of equations. The results indicate that the normalized difference vegetation index (NDVI) and FVC were highly correlated at the parcel level (R 2 = 0.712), where as the correlation at the pixel level remained moderate across each of the years studied. Based on the findings, another 29 alfalfa plots (28 rainfed; 1 irrigated) were remotely monitored operationally for 3 years (2017–2019), revealing that location and weather conditions were strong determinants of alfalfa growth in Bardenas Reales. The results of this study indicate that Sentinel-2 imagery is a suitable tool for monitoring rainfed alfalfa pastures in semiarid areas, thus increasing the potential success of pasture management.	en
dc.description.sponsorship	Andres Echeverria was supported by a predoctoral fellowship from the Government of Navarra. This work was supported by the knowledge transfer contract 2018020023 UPNA-Bardenas Reales Committee with partial collaboration of the project PID2019-107386RB-I00/AEI/10.13039/ 501100011033 (MINECO/FEDER-UE).	en
dc.format.extent	13 p.
dc.format.mimetype	application/pdf	en
dc.format.mimetype	application/zip	en
dc.identifier.doi	10.3390/rs13224719
dc.identifier.issn	2072-4292 (Electronic)
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/42492
dc.language.iso	eng	en
dc.publisher	MDPI	en
dc.relation.ispartof	Remote Sensing 2021, 13, 4719	en
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107386RB-I00/ES/
dc.relation.publisherversion	https://doi.org/10.3390/rs13224719
dc.rights	© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.	en
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.rights.uri	https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject	Satellite	en
dc.subject	Vegetation indices	en
dc.subject	Semiarid environment	en
dc.subject	Bardenas Reales	en
dc.subject	Legumes	en
dc.subject	Forage crops	en
dc.subject	Sustainable agrosystems	en
dc.title	Monitoring rainfed alfalfa growth in semiarid agrosystems using Sentinel-2 imagery	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
dspace.entity.type	Publication
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