Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps

Detalhes bibliográficos
Autor(a) principal: Akande, Adeoluwa Stephen
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/34214
Resumo: Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
id RCAP_76858bacb4fd4014a9788e4a323bb96c
oai_identifier_str oai:run.unl.pt:10362/34214
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str
spelling Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing mapsSelf Organizing MapsExtreme ClimatePrecipitationNigeriaDissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification, and high precipitation in parts of the south west and south east leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency and amount of rainfall over Nigeria. A type of Artificial Neural Network called Self Organizing Map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties for each cluster are discussed. The cluster spatially closest to the Atlantic has high values of precipitation intensity, frequency and duration, whereas the cluster spatially closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days in the northern region of Nigeria.Henriques, Roberto André PereiraCosta, Ana Cristina Marinho daMateu Mahiques, JorgeRUNAkande, Adeoluwa Stephen2018-04-10T12:45:31Z2017-03-012017-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/34214TID:201896192enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-10T15:43:24ZPortal AgregadorONG
dc.title.none.fl_str_mv Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
title Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
spellingShingle Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
Akande, Adeoluwa Stephen
Self Organizing Maps
Extreme Climate
Precipitation
Nigeria
title_short Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
title_full Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
title_fullStr Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
title_full_unstemmed Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
title_sort Geospatial analysis of extreme weather events in Nigeria (1985-2015) using self organizing maps
author Akande, Adeoluwa Stephen
author_facet Akande, Adeoluwa Stephen
author_role author
dc.contributor.none.fl_str_mv Henriques, Roberto André Pereira
Costa, Ana Cristina Marinho da
Mateu Mahiques, Jorge
RUN
dc.contributor.author.fl_str_mv Akande, Adeoluwa Stephen
dc.subject.por.fl_str_mv Self Organizing Maps
Extreme Climate
Precipitation
Nigeria
topic Self Organizing Maps
Extreme Climate
Precipitation
Nigeria
description Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
publishDate 2017
dc.date.none.fl_str_mv 2017-03-01
2017-03-01T00:00:00Z
2018-04-10T12:45:31Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/34214
TID:201896192
url http://hdl.handle.net/10362/34214
identifier_str_mv TID:201896192
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1777302961786978304

Registros relacionados