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@PhDThesis{Azeredo:2017:ExPaCo,
               author = "Azeredo, Marcio",
                title = "Minera{\c{c}}{\~a}o e an{\'a}lise de trajet{\'o}rias de 
                         mudan{\c{c}}a de cobertura da terra: explorando padr{\~o}es 
                         comportamentais no contexto da degrada{\c{c}}{\~a}o florestal",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2017",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2017-03-23",
             keywords = "trajet{\'o}rias de mudan{\c{c}}a, cobertura da terra, 
                         degrada{\c{c}}{\~a}o florestal, padr{\~a}o comportamental, 
                         minera{\c{c}}{\~a}o de trajet{\'o}ria, change trajectory, land 
                         cover, forest degradation, behavioral pattern, trajectory data 
                         mining.",
             abstract = "Considerando os processos que envolvem coberturas florestais, o 
                         Processo de Degrada{\c{c}}{\~a}o Florestal {\'e} 
                         particularmente importante, uma vez que, mantidas as 
                         condi{\c{c}}{\~o}es que lhe d{\~a}o origem, altera a estrutura 
                         da floresta de forma lenta e progressiva. Para a cobertura 
                         florestal, implica na redu{\c{c}}{\~a}o das fun{\c{c}}{\~o}es 
                         ecol{\'o}gicas e do armazenamento de carbono, na 
                         fragmenta{\c{c}}{\~a}o de ecossistemas e na perda do potencial 
                         do uso florestal para atividades econ{\^o}micas. Dada a sua 
                         relev{\^a}ncia, {\'e} preciso n{\~a}o s{\'o} compreender a 
                         din{\^a}mica de como tal processo ocorre, mas tamb{\'e}m onde, 
                         quando e como se comportam os atores e os mecanismos associados a 
                         essas altera{\c{c}}{\~o}es. Envolvendo etapas de maior e menor 
                         intensidade e at{\'e} mesmo a possibilidade de revers{\~a}o, a 
                         degrada{\c{c}}{\~a}o florestal requer longos per{\'{\i}}odos 
                         de observa{\c{c}}{\~a}o em grandes bases de dados 
                         espa{\c{c}}o-temporais, de forma continuada e sistem{\'a}tica, 
                         definindo as Trajet{\'o}rias de Mudan{\c{c}}a de Cobertura 
                         Florestal. Tais trajet{\'o}rias, por sua vez, s{\~a}o 
                         identificadas a partir das altera{\c{c}}{\~o}es recorrentes 
                         presentes nas propriedades das unidades de an{\'a}lise observadas 
                         e utilizadas na sua constitui{\c{c}}{\~a}o. Para a 
                         identifica{\c{c}}{\~a}o e explora{\c{c}}{\~a}o das referidas 
                         trajet{\'o}rias, s{\~a}o definidos e ampliados conceitos 
                         estabelecidos na literatura de trajet{\'o}rias de objetos 
                         m{\'o}veis. Desse modo, esta Tese prop{\~o}e, formaliza e 
                         implementa, na forma de uma biblioteca de fun{\c{c}}{\~o}es 
                         parametriz{\'a}veis, os elementos que permitem estabelecer uma 
                         nova metodologia computacional para auxiliar analistas na 
                         explora{\c{c}}{\~a}o de grandes bases de dados no 
                         dom{\'{\i}}nio dos estudos florestais, por interm{\'e}dio da 
                         minera{\c{c}}{\~a}o de padr{\~o}es de trajet{\'o}rias e de 
                         seus agrupamentos. Para tal, este trabalho traz duas 
                         contribui{\c{c}}{\~o}es: (1) define e implementa os Padr{\~o}es 
                         Comportamentais de Converg{\^e}ncia, Encontro, 
                         Detec{\c{c}}{\~a}o de Inconsist{\^e}ncias, Detec{\c{c}}{\~a}o 
                         de Anomalias, Rebanho e Lideran{\c{c}}a, encontrados na 
                         literatura de objetos m{\'o}veis, para o contexto das 
                         Trajet{\'o}rias de Mudan{\c{c}}a de Cobertura. Tal conjunto de 
                         defini{\c{c}}{\~o}es foi aqui denominado de Behavioral Patterns 
                         Mining on Land Cover Change (BPML); e (2) define e implementa uma 
                         metodologia para agrupar as trajet{\'o}rias de mudan{\c{c}}a de 
                         cobertura florestal, aqui denominada de Grouping by Similarity of 
                         Temporal Evolution (GSTE), baseada nas semelhan{\c{c}}as entre as 
                         evolu{\c{c}}{\~o}es temporais dessas trajet{\'o}rias. Esta 
                         metodologia utiliza de forma combinada os algoritmos 
                         computacionais Dynamic Time Warping (DTW), Classical 
                         Multidimensional Scaling (CMDS) e K-Means Clustering. Como prova 
                         de conceito, tr{\^e}s estudos de caso foram conduzidos, nos quais 
                         os padr{\~o}es comportamentais (BPML) e o m{\'e}todo de 
                         agrupamento de trajet{\'o}rias por semelhan{\c{c}}a de 
                         evolu{\c{c}}{\~a}o temporal (GSTE) foram testados em dois 
                         conjuntos de dados de degrada{\c{c}}{\~a}o florestal referentes 
                         {\`a}s regi{\~o}es do entorno dos munic{\'{\i}}pios de Novo 
                         Progresso - PA e Sinop - MT. As referidas bases de dados 
                         utilizadas s{\~a}o constitu{\'{\i}}das por 27.815 e 27.367 
                         unidades de an{\'a}lise (c{\'e}lulas), respectivamente, com 
                         resolu{\c{c}}{\~a}o espacial de 1x1km, resolu{\c{c}}{\~a}o 
                         temporal de 1 ano e extens{\~a}o temporal de 28 anos (1984 a 
                         2011). ABSTRACT: Considering the processes that involves forest 
                         cover, the Forest Degradation Process is particularly important 
                         because, keeping its original conditions, the structure of the 
                         forest is changed in a slow and progressive way. Regarding the 
                         forest cover, such process implies in a reduction of ecological 
                         functions and carbon storage in the fragmentation of ecosystems 
                         and the loss of the forest use potential for economic activities. 
                         Given its relevance, it is necessary not only to understand the 
                         dynamics of how these processes occur, but also where, when and 
                         how the actors and mechanisms associated with those changes 
                         behave. Concerning higher and lower intensity stages and even the 
                         possibility of reversal, forest degradation requires long periods 
                         of observation in large space-time databases, in a continuous and 
                         systematic way, defining the Forest Cover Change Trajectories. 
                         These trajectories, on the other hand, are identified from the 
                         recurrent changes in the properties of the units of analysis 
                         observed and used in its constitution. For the identification and 
                         exploration of these trajectories, this work defines and expands 
                         concepts established in the literature of moving objects 
                         trajectories. Thus, this thesis proposes, formalizes and 
                         implements, in the form of a library of parametrized functions, 
                         the elements that allow the establishment of a new computational 
                         methodology to assist analysts to deal with large databases of 
                         forest studies, through the data mining of trajectory patterns and 
                         their groupings. This study brings two innovative contributions: 
                         (1) it defines and implements the Behavior Patterns of 
                         Convergence, Encounter, Inconsistencies Detection, Anomalies 
                         Detection, Flock and Leadership, found in the literature to deal 
                         with moving objects, in the context of Forest Cover Change 
                         Trajectories. This set was called Behavioral Patterns Mining on 
                         Land Cover Change (BPML); and (2) it defines and implements a 
                         methodology to group the Forest Cover Change Trajectories, here 
                         called Grouping by Similarity of Temporal Evolution (GSTE), 
                         considering the similarities between the respective temporal 
                         evolutions and using computational algorithms of Dynamic Time 
                         Warping (DTW), Classical Multidimensional Scaling (CMDS) and 
                         K-Means Clustering. As proof of concept, three case studies were 
                         generated and the behavior patterns (BPML) as well as the method 
                         of trajectory grouping by similarity of temporal evolution (GSTE) 
                         were tested in two sets of forest degradation data, referring to 
                         the regions surrounding the municipalities of Novo Progresso - PA 
                         and Sinop - MT. These databases are composed by 27,815 and 27,367 
                         units of analysis (cells), respectively, with spatial resolution 
                         of 1x1km, temporal resolution of 1 year and temporal extension of 
                         28 years (1984 to 2011).",
            committee = "Santos, Rafael Duarte Coelho dos (presidente) and Monteiro, 
                         Ant{\^o}nio Miguel Vieira (orientador) and Escada, Maria Isabel 
                         Sobral (orientadora) and Ferreira, Karine Reis and Vinhas, 
                         L{\'u}bia and Pinheiro, Taise Farias and Davis Junior, Clodoveu 
                         Augusto",
         englishtitle = "data mining and analysis of land cover change trajectories: 
                         exploring behavioral patterns in the context of forest 
                         degradation",
             language = "pt",
                pages = "150",
                  ibi = "8JMKD3MGP3W34P/3NGPJ7H",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34P/3NGPJ7H",
           targetfile = "publicacao.pdf",
        urlaccessdate = "25 nov. 2020"
}


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