Repository logo
 
Publication

Remote Sensing Applications in Almond Orchards: A Comprehensive Systematic Review of Current Insights, Research Gaps, and Future Prospects

2024Journal article Open access
Simple item page
dc.contributor.authorGuimarães, Nathalie
dc.contributor.authorSousa, Joaquim J.
dc.contributor.authorPádua, Luís
dc.contributor.authorBento, Albino
dc.contributor.authorCouto, Pedro
dc.date.accessioned2024-05-09T14:24:55Z
dc.date.available2024-05-09T14:24:55Z
dc.date.issued2024
dc.description.abstractAlmond cultivation is of great socio-economic importance worldwide. With the demand for almonds steadily increasing due to their nutritional value and versatility, optimizing the management of almond orchards becomes crucial to promote sustainable agriculture and ensure food security. The present systematic literature review, conducted according to the PRISMA protocol, is devoted to the applications of remote sensing technologies in almond orchards, a relatively new field of research. The study includes 82 articles published between 2010 and 2023 and provides insights into the predominant remote sensing applications, geographical distribution, and platforms and sensors used. The analysis shows that water management has a pivotal focus regarding the remote sensing application of almond crops, with 34 studies dedicated to this subject. This is followed by image classification, which was covered in 14 studies. Other applications studied include tree segmentation and parameter extraction, health monitoring and disease detection, and other types of applications. Geographically, the United States of America (USA), Australia and Spain, the top 3 world almond producers, are also the countries with the most contributions, spanning all the applications covered in the review. Other studies come from Portugal, Iran, Ecuador, Israel, Turkey, Romania, Greece, and Egypt. The USA and Spain lead water management studies, accounting for 23% and 13% of the total, respectively. As far as remote sensing platforms are concerned, satellites are the most widespread, accounting for 46% of the studies analyzed. Unmanned aerial vehicles follow as the second most used platform with 32% of studies, while manned aerial vehicle platforms are the least common with 22%. This up-to-date snapshot of remote sensing applications in almond orchards provides valuable insights for researchers and practitioners, identifying knowledge gaps that may guide future studies and contribute to the sustainability and optimization of almond crop management.pt_PT
dc.description.sponsorshipFinancial support was provided by the national funds through FCT—Portuguese Foundation for Science and Technology (UI/BD/150727/2020), under the Doctoral Programme “Agricultural Production Chains—from fork to farm” (PD/00122/2012) and from the European Social Funds and the Regional Operational Programme Norte 2020. This study was also supported by CITAB research unit (UIDB/04033/2020, https://doi.org/10.54499/UIDB/04033/2020), Inov4Agro (LA/P/0126/2020) and by CIMO (UIDB/00690/2020).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationGuimarães, Nathalie; Sousa, Joaquim J.; Pádua, Luís; Bento, Albino; Couto, Pedro (2024). Remote Sensing Applications in Almond Orchards: A Comprehensive Systematic Review of Current Insights, Research Gaps, and Future Prospects. Applied Sciences. EISSN 2076-3417. 14:5, p. 1-26pt_PT
dc.identifier.doi10.3390/app14051749pt_PT
dc.identifier.eissn2076-3417
dc.identifier.urihttp://hdl.handle.net/10198/29746
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationPD/00122/2012pt_PT
dc.relationAerial high-resolution imagery to assess almond orchard conditions
dc.relationCentre for the Research and Technology of Agro-Environmental and Biological Sciences
dc.relationInstitute for innovation, capacity building and sustainability of agri-food production
dc.relationMountain Research Center
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPrunus dulcispt_PT
dc.subjectPrecision agriculturept_PT
dc.subjectSatellitept_PT
dc.subjectManned aircraftpt_PT
dc.subjectUnmanned aerial vehiclept_PT
dc.subjectTree segmentation and parameters extractionpt_PT
dc.subjectImagery classificationpt_PT
dc.subjectHealth monitoring and disease detectionpt_PT
dc.subjectWater managementpt_PT
dc.subjectYield predictionpt_PT
dc.titleRemote Sensing Applications in Almond Orchards: A Comprehensive Systematic Review of Current Insights, Research Gaps, and Future Prospectspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleAerial high-resolution imagery to assess almond orchard conditions
oaire.awardTitleCentre for the Research and Technology of Agro-Environmental and Biological Sciences
oaire.awardTitleInstitute for innovation, capacity building and sustainability of agri-food production
oaire.awardTitleMountain Research Center
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_NORTE/UI%2FBD%2F150727%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04033%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0126%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.citation.endPage26pt_PT
oaire.citation.issue5pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleApplied Sciencespt_PT
oaire.citation.volume14pt_PT
oaire.fundingStreamPOR_NORTE
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameBento
person.givenNameAlbino
person.identifier.ciencia-idD516-325A-9AD7
person.identifier.orcid0000-0001-5215-785X
person.identifier.ridN-9706-2016
person.identifier.scopus-author-id35247694000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication233115be-9d46-49d0-8b7d-2d64406d64a0
relation.isAuthorOfPublication.latestForDiscovery233115be-9d46-49d0-8b7d-2d64406d64a0
relation.isProjectOfPublication379f6576-df64-4575-94ed-ae2fa723a2a9
relation.isProjectOfPublicationac4fb709-719a-450b-8c96-17592d46f5e9
relation.isProjectOfPublication3c81413c-6a3a-453a-bb53-9e883a270537
relation.isProjectOfPublication29718e93-4989-42bb-bcbc-4daff3870b25
relation.isProjectOfPublication.latestForDiscovery3c81413c-6a3a-453a-bb53-9e883a270537

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
applsci-14-01749.pdf
Size:
6.27 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.75 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

CIMO - Artigos em Revistas Indexados à WoS/Scopus