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Analysis of Potential Supply of Ecosystem Services in Forest Remnants through Neural Networks

dc.contributor.authorLongo, Regina Marcia
dc.contributor.authorSilva, Alessandra Leite da
dc.contributor.authorNunes, Adelia N.
dc.contributor.authorMelo Conti, Diego de
dc.contributor.authorGomes, Raissa Caroline
dc.contributor.authorSperandio, Fabricio Camillo
dc.contributor.authorRibeiro, Admilson Irio [UNESP]
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionUniv Coimbra UC
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2025-04-29T18:58:32Z
dc.date.issued2023-10-01
dc.description.abstractAnalyzing the landscape configuration factors where they are located can ensure a more accurate spatial assessment of the supply of ecosystem services. It can also show if the benefits promoted by ecosystems depend not only on the supply of these services but also on the demand, the cultural values, and the interest of the society where they are located. The present study aims to demonstrate the provision potential of regulating ecosystem services by forest remnants in the municipality of Campinas/SP, Brazil, from the analysis and weighting of geospatial indicators, considering the assumptions of supply of and demand for these ecosystem services. The potential supply of regulating ecosystem services was evaluated through the application of an artificial neural network using landscape indicators previously surveyed for the 2319 forest remnants identified in six watersheds. The findings show that the classified remnants have a medium to very high regulating potential for the provision of ecosystem services. The use of artificial intelligence fundamentals, based on artificial neural networks, proved to be quite effective, as it enables combined analysis of various indicators, analysis of spatial patterns, and the prediction of results, which could be informative guides for environmental planning and management in urban spaces.en
dc.description.affiliationPontifical Catholic Univ Campinas PUC Campinas, Postgrad Program Urban Infrastruct Syst, BR-13087571 Campinas, SP, Brazil
dc.description.affiliationPontifical Catholic Univ Campinas PUC Campinas, Postgrad Program Sustainabil, BR-13087571 Campinas, SP, Brazil
dc.description.affiliationUniv Coimbra UC, Ctr Studies Geog & Spatial Planning CEGOT, Dept Geog & Tourism, P-3004530 Coimbra, Portugal
dc.description.affiliationSao Paulo State Univ Julio de Mesquita Filho UNESP, Postgrad Program Environm Sci, BR-18087180 Sorocaba, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ Julio de Mesquita Filho UNESP, Postgrad Program Environm Sci, BR-18087180 Sorocaba, SP, Brazil
dc.description.sponsorshipThanks to the Pontifical Catholic University of Campinas for providing the necessary infrastructure to carry out this study.
dc.format.extent16
dc.identifierhttp://dx.doi.org/10.3390/su152015017
dc.identifier.citationSustainability. Basel: Mdpi, v. 15, n. 20, 16 p., 2023.
dc.identifier.doi10.3390/su152015017
dc.identifier.urihttps://hdl.handle.net/11449/301544
dc.identifier.wosWOS:001093516100001
dc.language.isoeng
dc.publisherMdpi
dc.relation.ispartofSustainability
dc.sourceWeb of Science
dc.subjectlandscape metrics
dc.subjecturban forest
dc.subjectecosystem services
dc.subjectneural network
dc.subjectBrazil
dc.titleAnalysis of Potential Supply of Ecosystem Services in Forest Remnants through Neural Networksen
dc.typeArtigopt
dcterms.rightsHolderMdpi
dspace.entity.typePublication
relation.isOrgUnitOfPublication0bc7c43e-b5b0-4350-9d05-74d892acf9d1
relation.isOrgUnitOfPublication.latestForDiscovery0bc7c43e-b5b0-4350-9d05-74d892acf9d1
unesp.author.orcid0000-0003-1889-0462[4]
unesp.author.orcid0000-0001-5062-7918[5]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Ciência e Tecnologia, Sorocabapt

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