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Evaluation of the factors explaining the use of agricultural land: a machine learning and model-agnostic approach

2021Artigo científico Acesso aberto
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dc.contributor.authorViana, Cláudia M.
dc.contributor.authorSantos, José Maurício
dc.contributor.authorFreire, Dulce
dc.contributor.authorAbrantes, Patrícia
dc.contributor.authorRocha, Jorge
dc.date.accessioned2021-09-29T15:12:57Z
dc.date.available2021-09-29T15:12:57Z
dc.date.issued2021
dc.description.abstractTo effectively plan and manage the use of agricultural land, it is crucial to identify and evaluate the multiple human and environmental factors that influence it. In this study, we propose a model framework to identify the factors potentially explaining the use of agricultural land for wheat, maize, and olive grove plantations at the regional level. By developing a machine-learning model coupled with a model-agnostic approach, we provide global and local interpretations of the most influential factors. We collected nearly 140 variables related to biophysical, bioclimatic, and agricultural socioeconomic conditions. Overall, the results indicated that biophysical and bioclimatic conditions were more influential than socioeconomic conditions. At the global interpretation level, the proposed model identified a strong contribution of conditions related to drainage density, slope, and soil type. In contrast, the local interpretation level indicated that socioeconomic conditions such as the degree of mechanisation could be influential in specific parcels of wheat. As demonstrated, the proposed analytical approach has the potential to serve as a decision-making tool instrument to better plan and control the use of agricultural land.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationViana, C. M., Santos, M., Freire, D., Abrantes, P., & Rocha, J. (2021). Evaluation of the factors explaining the use of agricultural land: a machine learning and model-agnostic approach. Ecological Indicators. 131, 108200. https://doi.org/https://doi.org/10.1016/j.ecolind.2021.108200pt_PT
dc.identifier.doi10.1016/j.ecolind.2021.108200pt_PT
dc.identifier.issn1470-160X
dc.identifier.urihttp://hdl.handle.net/10451/49691
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationSFRH/BD/115497/2016]pt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1470160X21008657?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectInterpretabilitypt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectxAIpt_PT
dc.subjectLIMEpt_PT
dc.titleEvaluation of the factors explaining the use of agricultural land: a machine learning and model-agnostic approachpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/157386/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/157990/PT
oaire.citation.startPage108200pt_PT
oaire.citation.titleEcological Indicatorspt_PT
oaire.citation.volume131pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameM. Viana
person.familyNameSantos
person.familyNameABRANTES
person.familyNameRocha
person.givenNameCláudia
person.givenNameJosé Maurício
person.givenNamePATRICIA
person.givenNameJorge
person.identifier1830826
person.identifier0000000069085031
person.identifier.ciencia-id0712-B263-3133
person.identifier.ciencia-idC913-032A-9B76
person.identifier.ciencia-idEC15-76DC-9B96
person.identifier.orcid0000-0001-6858-4522
person.identifier.orcid0000-0001-7119-6280
person.identifier.orcid0000-0002-5477-8657
person.identifier.orcid0000-0002-7228-6330
person.identifier.ridA-9352-2019
person.identifier.ridN-3554-2016
person.identifier.ridF-3185-2017
person.identifier.scopus-author-id57200209862
person.identifier.scopus-author-id57194575198
person.identifier.scopus-author-id56428061000
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
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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