The Sea Level Rise and its Relationships with Non-oceanic Variables: a Bibliometric Analysis

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Nilton de Souza Ribas Junior
https://orcid.org/0000-0003-2170-136X
Aloísio Machado da Silva Filho
https://orcid.org/0000-0001-8250-1527

Abstract

Approximately 70% of our planet is occupied by water, which for the most part, forms our oceans. In addition to enchanting us with its beauty, the sea, with its strictly regular vertical movement driven by gravitational forces, has been suffering increasingly intense disturbances, causing its elevation due to several factors, mainly environmental and climatic. An integral part of one of the sustainable development objectives (ODS 13 - Action against Global Climate Change), a global agenda adopted during the United Nations Summit, consisting of 17 goals and 169 targets to be achieved by 2030, the mean sea level rise has been a concern for governments, non-governmental and researchers for some time, especially when the future scenarios are not encouraging at all. These risks are even more accentuated when we refer to coastal regions, as the consequences are felt in a much more direct and accentuated way, such as erosion of beaches, coastal flooding, and loss of ecosystems, among others. Creating negative impacts both from a socioeconomic and environmental point of view. To contribute to research related to the topic, through bibliometric techniques, the referring study analyzed 35 articles between the years 2009 and 2021 extracted from the Scopus database with the application of mathematical and statistical methods as a way of quantitatively evaluating these researches, among them: historical and geographic trends, main journals and institutions, keyword characteristics and citation network analysis. The objective is to have an overview of how the theme "mean sea level" has been studied over time and its relationship with its disturbing factors, such as land subsidence and climatic factors, which techniques are being used and which are the main discoveries.

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How to Cite
RIBAS JUNIOR , N. de S.; SILVA FILHO , A. M. da. The Sea Level Rise and its Relationships with Non-oceanic Variables: a Bibliometric Analysis. Revista Brasileira de Cartografia, [S. l.], v. 74, n. 4, p. 895–910, 2022. DOI: 10.14393/rbcv74n4-65734. Disponível em: https://seer.ufu.br/index.php/revistabrasileiracartografia/article/view/65734. Acesso em: 22 jul. 2024.
Section
Review Articles
Author Biographies

Nilton de Souza Ribas Junior , Universidade Estadual de Feira de Santana

Natural de Recife/PE e nascido em 1975. Possui graduação em Engenharia Cartográfica pela Universidade Federal de Pernambuco (1999), mestrado em Ciências Ambientais pela Universidade Estadual de Feira de Santana (2019) e doutorando pela mesma instituição. Servidor Público Federal desde 2002, já executou diversos trabalhos de engenharia a nível local, regional e nacional. Atualmente gerencia o Setor de Geodésia e Cartografia do IBGE no Estado da Bahia

Aloísio Machado da Silva Filho , State University of Feira de Santana

Doutor e Mestre em Modelagem Computacional e Tecnologia Industrial pelo SENAI CIMATEC (2009-2014). Especialização em Metodologia do Ensino Superior pela Faculdade Olga Metiing (2003-2004). Especialização em Estatística Aplicada pela UNIJORGE (2015-2017). Bacharel em Estatística pela Escola Superior de Estatística da Bahia (1998-2002). Professor Titular A da Universidade Estadual de Feira de Santana-UEFS no Departamento de Ciências Exatas na área de estudo Probabilidade e Estatística. Na UEFS atua nos seguintes programas de Pós-Graduação: Modelagem em Ciências da Terra e do Ambiente (Permanente), Mestrado Profissional em Enfermagem (Permanente), Saúde Coletiva (Colaborador). Desde de 2005 tem se dedicado a ensino, pesquisa e extensão. Áreas de interesse: Bioestatística, Controle Estatístico de resíduos sólidos, Saúde Coletiva, Análise Temporal de Fenômenos Climatológicos, Modelagem de Séries Temporais, Estatística criminal, Física Estatística, Educação Estatística e Séries temporais econômicas. É líder do grupo de pesquisa do CNPq "MODELAGEM E ANÁLISE DE DADOS: TEORIAS E APLICAÇÕES.", credenciado pela UEFS. Nos últimos anos tem se dedicado a Modelagem de dados com a Linguagem Estatística e Computacional conhecida na literatura como R (https://www.r-project.org). Atualmente possui 523 citações no Google Acadêmico e 368 na Web of Science. É possível ter acesso as minhas publicações em: https://www.researchgate.net/profile/Aloisio-Machado

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