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Spatial analysis, geospatial data and land-change models for modelling agricultural land changes

dc.contributor.authorViana, Cláudia M.
dc.date.accessioned2022-08-31T11:26:08Z
dc.date.available2022-08-31T11:26:08Z
dc.date.issued2022
dc.description.abstractAt the core of global initiatives, several relevant adaptive management and policy approaches are being discussed and redirected towards achieving global food production objectives and food security for the present and future generations. In particular, agricultural land systems are the principal biogeophysical source to ensure food security and nutritional benefits. However, agricultural land systems change over time, indirectly influencing global food production and food security. Thus, in the coming decades, agricultural land systems will face complex challenges (e.g. the changing of food consumption pattern, climate change, land abandonment and/or intensification); the extent to which they will be able to support the security of the global food system will be determined by their efficiency, sustainability and equitability. With the integration of spatial analysis, geospatial data and land-change models, there is a practical opportunity for modelling agricultural land systems. This, in turn, can provide meaningful information to assist decision-making processes, anticipate future changes and design robust strategies in the long term to manage impending challenges.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationViana, C. M. (2022). Spatial analysis, geospatial data and land-change models for modelling agricultural land changes. In P. Pereira, E. Gomes, & J. Rocha (eds.). Mapping and Forecasting Land Use: The Present and Future of Planning (pp. 95–113). Elsevier. https://doi.org/10.1016/B978-0-323-90947-1.00008-9pt_PT
dc.identifier.doi10.1016/B978-0-323-90947-1.00008-9pt_PT
dc.identifier.isbn978-0-323-90947-1
dc.identifier.urihttp://hdl.handle.net/10451/54245
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationUIDP/ 00295/2020]pt_PT
dc.relationModelo de otimização espacial do Uso do Solo Agrícola: Integração de Autómatos Celulares e algorítmos inteligentes na análise de dados quantitativos e qualitativos
dc.relationCentre of Geographical Studies
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/B9780323909471000089?via%3Dihubpt_PT
dc.subjectFood productionpt_PT
dc.subjectFood securitypt_PT
dc.subjectAgricultural researchpt_PT
dc.subjectLand-use changespt_PT
dc.subjectCroplandpt_PT
dc.titleSpatial analysis, geospatial data and land-change models for modelling agricultural land changespt_PT
dc.typebook part
dspace.entity.typePublication
oaire.awardNumberSFRH/BD/115497/2016
oaire.awardNumberUIDB/00295/2020
oaire.awardTitleModelo de otimização espacial do Uso do Solo Agrícola: Integração de Autómatos Celulares e algorítmos inteligentes na análise de dados quantitativos e qualitativos
oaire.awardTitleCentre of Geographical Studies
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F115497%2F2016/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00295%2F2020/PT
oaire.citation.endPage113pt_PT
oaire.citation.startPage95pt_PT
oaire.citation.titleMapping and Forecasting Land Use: The Present and Future of Planningpt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameM. Viana
person.givenNameCláudia
person.identifier.ciencia-id0712-B263-3133
person.identifier.orcid0000-0001-6858-4522
person.identifier.ridA-9352-2019
person.identifier.scopus-author-id57200209862
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.rightsclosedAccesspt_PT
rcaap.typebookPartpt_PT
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relation.isAuthorOfPublication.latestForDiscoveryf0bca8f1-525f-49ba-a2ab-c4794d88e2c8
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