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Ecological risk assessment based on land cover changes

2020-10Artigo científico Acesso aberto
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dc.contributor.authorOmar, Hassan
dc.contributor.authorCabral, Pedro
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.pblMolecular Diversity Preservation International (MDPI)
dc.date.accessioned2020-10-26T23:53:23Z
dc.date.available2020-10-26T23:53:23Z
dc.date.issued2020-10
dc.descriptionOmar, H., & Cabral, P. (2020). Ecological risk assessment based on land cover changes: A case of Zanzibar (Tanzania). Remote Sensing, 12(19), 1-24. [3114]. https://doi.org/10.3390/RS12193114
dc.description.abstractLand use and land cover (LULC) under improper land management is a major challenge in sub-Saharan Africa and has drastically affected ecological security. Addressing environmental impacts related to this challenge requires efficient planning strategies based on the measured information of land use patterns. This study assessed the ecological risk index (ERI) of Zanzibar based on LULC. A random forest classifier was used to classify three Landsat images of Zanzibar for the years 2003, 2009, and 2018. Then, a land change model was employed to simulate the LULC changes for 2027 under a business-as-usual (BAU), conservation, and extreme scenarios. Results showed that the built-up areas and farmland of Zanzibar Island have increased constantly, while the natural grassland and forest cover have decreased. The forest, agricultural, and grassland were highly fragmented into several small patches. The ERI of Zanzibar Island increased at a constant rate and, if the current trend continues, this index will increase by up to 8.9% in 2027 under an extreme scenario. If a conservation scenario is adopted, the ERI will increase by 4.6% whereas if a BAU policy is followed, this value will increase by 6.2%. This study provides authorities with useful information to understand better the ecological processes and LULC dynamics and prevent unmanaged growth and haphazard development of informal housing and infrastructure.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent24
dc.format.extent5404615
dc.identifier.doi10.3390/RS12193114
dc.identifier.issn2072-4292
dc.identifier.otherPURE: 26084301
dc.identifier.otherPURE UUID: f255330e-e7ae-43a3-aaa5-25341a774441
dc.identifier.otherScopus: 85092488849
dc.identifier.otherORCID: /0000-0001-8622-6008/work/82552387
dc.identifier.otherWOS: 000586740600001
dc.identifier.urihttp://hdl.handle.net/10362/106240
dc.identifier.urlhttps://www.scopus.com/pages/publications/85092488849
dc.identifier.urlhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000586740600001
dc.language.isoeng
dc.peerreviewedyes
dc.relationinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCTA-AMB%2F28438%2F2017/PT
dc.relationAssessment of ecosystem services, biodiversity, and well-being in Portugal
dc.subjectEcosystem services
dc.subjectLand change modeling
dc.subjectLandscape ecological statistics
dc.subjectRandom forest classifier
dc.subjectGeneral Earth and Planetary Sciences
dc.subjectSDG 11 - Sustainable Cities and Communities
dc.subjectSDG 15 - Life on Land
dc.titleEcological risk assessment based on land cover changesen
dc.title.subtitleA case of Zanzibar (Tanzania)en
dc.typejournal article
degois.publication.firstPage1
degois.publication.issue19
degois.publication.lastPage24
degois.publication.titleRemote Sensing
degois.publication.volume12
dspace.entity.typePublication
oaire.awardNumberPTDC/CTA-AMB/28438/2017
oaire.awardTitleAssessment of ecosystem services, biodiversity, and well-being in Portugal
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FCTA-AMB%2F28438%2F2017/PT
oaire.fundingStream3599-PPCDT
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication4f9d368d-6cde-4bac-95fb-417c920fd842
relation.isProjectOfPublication.latestForDiscovery4f9d368d-6cde-4bac-95fb-417c920fd842

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