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@MastersThesis{Silva:2017:PrBiMa,
               author = "Silva, Jean Farhat de Ara{\'u}jo da",
                title = "Prov{\'{\i}}ncias Biogeoqu{\'{\i}}micas Marinhas no Oceano 
                         Atl{\^a}ntico Sul por Sensoriamento Remoto",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2017",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2017-07-31",
             keywords = "prov{\'{\i}}ncias biogeoqu{\'{\i}}micas marinhas, 
                         sensoriamento remoto, fei{\c{c}}{\~o}es oceanogr{\'a}ficas, 
                         Oceano Atl{\^a}ntico Sul, fuzzy, marine biogeochemical provinces, 
                         remote sensing, oceanographic features, South Atlantic Ocean, 
                         fuzzy.",
             abstract = "Compreender a estrutura espacial e a fun{\c{c}}{\~a}o do 
                         ecossistema pel{\'a}gico est{\'a} no cerne da oceanografia 
                         atual. Abordagens categ{\'o}ricas j{\'a} foram aplicadas {\`a} 
                         parti{\c{c}}{\~a}o do dom{\'{\i}}nio oce{\^a}nico em 
                         prov{\'{\i}}ncias biogeoqu{\'{\i}}micas marinhas (PBGQ). A 
                         classifica{\c{c}}{\~a}o em PBGQ fornece uma estrutura {\'u}til 
                         para a compreens{\~a}o dos mecanismos de intera{\c{c}}{\~a}o e 
                         controle de processos f{\'{\i}}sicos e biogeoqu{\'{\i}}micos 
                         que refletem a heterogeneidade do ambiente oce{\^a}nico. O 
                         presente trabalho teve como objetivo particionar o oceano 
                         Atl{\^a}ntico Sul em prov{\'{\i}}ncias biogeoqu{\'{\i}}micas 
                         marinhas, com uso do classificador n{\~a}o supervisionado Fuzzy 
                         C-Means (FCM), utilizando dados m{\'e}dios anuais e sazonais da 
                         concentra{\c{c}}{\~a}o de clorofila-a na superf{\'{\i}}cie do 
                         mar (CSM), temperatura da superf{\'{\i}}cie do mar (TSM) e 
                         radia{\c{c}}{\~a}o fotossinteticamente dispon{\'{\i}}vel 
                         estimados por sat{\'e}lite. Dados da profundidade da camada de 
                         mistura (PCM) e batimetria tamb{\'e}m foram utilizados. A partir 
                         do crit{\'e}rio Silhouette foram definidas 8 classes para 
                         aplica{\c{c}}{\~a}o do classificador FCM, que possibilitou 
                         identificar as PBGQ denominadas como: Sistema Equatorial/Tropical, 
                         Giro Subtropical, Converg{\^e}ncia Subtropical Norte e Sul, 
                         Subant{\'a}rtica, Polar e Circumpolar Ant{\'a}rtica. Foram 
                         calculadas as {\'a}reas de cada PBGQ e os respectivos graus de 
                         pertin{\^e}ncia, assim como, os valores m{\'e}dios, m{\'a}ximos 
                         e m{\'{\i}}nimos de cada vari{\'a}vel ambiental considerada. 
                         Estas informa{\c{c}}{\~o}es foram analisadas de modo a se 
                         descrever as principais fei{\c{c}}{\~o}es oceanogr{\'a}ficas 
                         presentes em cada PBGQ.Considerando a import{\^a}ncia das 
                         mudan{\c{c}}as clim{\'a}ticas, foi realizada uma 
                         simula{\c{c}}{\~a}o de cen{\'a}rio futuro (ano 2099) das 
                         vari{\'a}veis CSM, TSM e PCM estimadas pelo Projeto 
                         Inter-comparativo na fase 5 de Modelos Acoplados (CMIP5), Com a 
                         aplica{\c{c}}{\~a}o do crit{\'e}rio Silhouette foram definidas 
                         5 classes para o algoritmo FCM. Da mesma forma, foram 
                         identificadas 5 PBGQ, calculando-se os respectivos graus de 
                         pertin{\^e}ncia, {\'a}reas e valores m{\'e}dios, m{\'a}ximos e 
                         m{\'{\i}}nimos das vari{\'a}veis ambientais. A 
                         redu{\c{c}}{\~a}o do numero de PBGQ e da CSM, assim como, ou 
                         aumento de TSM no cen{\'a}rio futuro s{\~a}o 
                         indica{\c{c}}{\~o}es que as mudan{\c{c}}as clim{\'a}ticas 
                         podem impactar significativamente essas prov{\'{\i}}ncias no 
                         Atl{\^a}ntico Sul. ABSTRACT: The understanding of spatial 
                         structure and function of the pelagic ecosystem is on focus of 
                         current oceanography. Categorical approaches have already been 
                         applied to the partition of the oceanic region in marine 
                         biogeochemical provinces (BGQP).The classification of BGQP 
                         provides an useful framework in order to comprehend the 
                         interaction mechanisms and control of physical, chemical and 
                         biological processes that reflect the heterogeneity of ocean 
                         environment. The present work aims to divide South Atlantic Ocean 
                         in marine biogeochemical provinces, using an unsupervised 
                         classifier Fuzzy C-Means (FCM) using mean data in yearly and 
                         seasonal basis, such as Chlorophylla Concentration on sea surface 
                         (CCS), Sea Surface Temperature (SST) and photosynthetically 
                         available radiation data estimated by satellite. Mixed layers 
                         depths (MLD) and bathymetry data were also used. From the 
                         application of the Silhouette criteria, 8 input classes were 
                         defined in the FCM classifier which, in turn, produced BGQP named 
                         as: Equatorial/Tropical System; Subtropical Gyre; Subtropical 
                         Convergence North; Subtropical Convergence South; Sub- Antarctic; 
                         Polar and Circumpolar Antarctic. Each BGQP were calculated and its 
                         respective membership values, as well as, mean, maximum and 
                         minimum values of each considered parameter. This information was 
                         analyzed in order to describe the main oceanographic features in 
                         each BGQP. Considering the importance of climate change issues, a 
                         simulation of future scenarios (year 2099) of the variables CCS, 
                         SST and MLD estimated by Inter-Comparison Project in Phase 5 of 
                         Coupled Models (CMIP5). By the application of the Silhoutte 
                         criteria were defined 5 classes for FCM algorithm. Similarly, were 
                         indentified 5 BGQP and were calculated its respective membership 
                         values, as well as, mean, maximum and minimum values of each these 
                         parameters. The reduction in the number of BGQPs and the decline 
                         of the concentration of chlorophyll a (CSM), as well as, the 
                         increase in sea surface temperature (SST) in the future scenario 
                         are indications that the climatic changes can significantly impact 
                         these provinces in the South Atlantic Ocean.",
            committee = "Kampel, Silvana Amaral (presidente) and Kampel, Milton 
                         (orientador) and Monteiro, Antonio Miguel Vieira and Conti, Luis 
                         Am{\'e}rico",
         englishtitle = "Marine biogeochemical provinces in the South Atlantic Ocean by 
                         remote sensing",
             language = "pt",
                pages = "135",
                  ibi = "8JMKD3MGP3W34P/3P9B3LH",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34P/3P9B3LH",
           targetfile = "publicacao.pdf",
        urlaccessdate = "23 nov. 2020"
}


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