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Forecasting biocapacity and ecological footprint at a worldwide level to 2030 using neural networks

dc.contributor.authorMoros Ochoa, María Andreínaspa
dc.contributor.authorCastro Nieto, Gilmer Yovanispa
dc.contributor.authorQuintero Español, Andersonspa
dc.contributor.authorLlorente Portillo, Carolinaspa
dc.date.accessioned2023-06-21T22:22:58Z
dc.date.available2023-06-21T22:22:58Z
dc.date.issued2022-08-27
dc.identifier.urihttp://hdl.handle.net/10726/5034
dc.language.isoeng
dc.publisherMDPI AG
dc.titleForecasting biocapacity and ecological footprint at a worldwide level to 2030 using neural networkseng
dc.typearticle
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.localAbierto (Texto Completo)
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.identifier.instnameinstname:Colegio de Estudios Superiores de Administración – CESA
dc.identifier.reponamereponame:Biblioteca Digital – CESA
dc.identifier.repourlrepourl:https://repository.cesa.edu.co/
dc.description.abstractenglishConstant environmental deterioration is a problem widely addressed by multiple international organizations. However, given the current economic and technological limitations, alternatives that immediately and significantly impact environmental degradation negatively affect contemporary development and lifestyle. Because of this, rather than limiting population consumption patterns or developing sophisticated and highly expensive technologies, the solution to environmental degradation lies more in the progressive transformation of production and consumption patterns. Thus, to support this change, the objective of this article is to forecast the behavior of consumption and regeneration of biologically productive land until the year 2030, using a deep neural network adjusted to Global Footprint Network data for prediction, and to provide information that favors the development of local economic strategies based on the territorial strengths and weaknesses of each continent. The most relevant findings about biocapacity and ecological footprint data are: fishing grounds have the great renewable potential in the global consumption of products and focused on the Asian region being approximately 55% of the world’s ecological footprint; grazing lands indicate an exponential growth in terms of ecological footprint, however South America and Africa have almost 55% of the distribution in the world biocapacity, being great powers in the generation of agricultural products; forest lands show a decrease in biocapacity, there is a progressive and exponential deterioration of forest resources, the highest deficit in the world is generated in Asia; cropland presents an environmental balance between biocapacity and ecological footprint; and built land generates great impacts on development and regeneration in other lands, indicating the exponential crisis that could eventually be established by needing more and more resources from large built metropolises to replace the natural life provided by other lands.eng
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.relation.citationvolume14
dc.relation.citationissue17
dc.contributor.orcidMoros Ochoa, María Andreína [0000-0001-8428-9056]
dc.contributor.orcidCastro Nieto, Gilmer Yovani [0000-0001-9861-5588]
dc.contributor.orcidQuintero Español, Anderson [0000-0002-6562-6245]
dc.contributor.orcidLlorente Portillo, Carolina [0000-0002-2350-5891]
dc.type.driverinfo:eu-repo/semantics/article
dc.type.redcolhttp://purl.org/redcol/resource_type/ART
dc.type.coarversionhttp://purl.org/coar/version/c_71e4c1898caa6e32
dc.contributor.scopusMoros Ochoa, María Andreína [57195503017]
dc.contributor.scopusCastro Nieto, Gilmer Yovani [24544764500]
dc.contributor.scopusQuintero Español, Anderson [57888736800]
dc.contributor.scopusLlorente Portillo, Carolina [57888736900]
dc.description.orcidhttps://orcid.org/0000-0001-8428-9056
dc.description.orcidhttps://orcid.org/0000-0001-9861-5588
dc.description.orcidhttps://orcid.org/0000-0002-6562-6245
dc.description.orcidhttps://orcid.org/0000-0002-2350-5891
dc.description.scopushttps://www.scopus.com/authid/detail.uri?authorId=57195503017
dc.description.scopushttps://www.scopus.com/authid/detail.uri?authorId=24544764500
dc.description.scopushttps://www.scopus.com/authid/detail.uri?authorId=57888736800
dc.description.scopushttps://www.scopus.com/authid/detail.uri?authorId=57888736900
dc.identifier.eissn2071-1050
dc.relation.ispartofjournalSustainability
dc.identifier.doihttps://doi.org/10.3390/ su141710691
dc.subject.proposalBiocapacity
dc.subject.proposalEcological footprint
dc.subject.proposalSustainable business models
dc.subject.proposalNeural networks
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2


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