Submitted by Celso Magalhaes (celsomagalhaes@ufrrj.br) on 2017-09-15T12:49:01Z No. of bitstreams: 1 2017 - Camila Caetano da Cruz.pdf: 2972481 bytes, checksum: 198acc8d9a70ab72c6437d4e52f11dd8 (MD5) / Made available in DSpace on 2017-09-15T12:49:01Z (GMT). No. of bitstreams: 1 2017 - Camila Caetano da Cruz.pdf: 2972481 bytes, checksum: 198acc8d9a70ab72c6437d4e52f11dd8 (MD5) Previous issue date: 2017-02-15 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / The Atlantic Forest biome is a biogeographic region with high biodiversity, containing several natural reserves that generate essential resources for all living beings. With its high degree of deforestation over the years due to anthropogenic action, it is necessary to identify and monitor changes in land use and cover, which enables a better understanding of the future of forests and how their changes are occurring. This work aims to evaluate the vegetation dynamics in the Atlantic Forest biome through the Enhanced Vegetation Index (EVI) and its relation with the meteorological variables: average air temperature, rainfall, global solar radiation, relative humidity and evapotranspiration. The study was carried out in the municipality of Pinheiral in the State of Rio de Janeiro. The vegetation data of the product MOD13Q1, from 2001 to 2013, totaling 299 images and monthly data of the meteorological variables of the same period, totaling 780 data, were used. The analyzes of the interannual trends of the time series of vegetation indices were performed using the methodologies of linearity, linear correlation, linear trend, monotonic tendency of Mann Kendall, median trend of Theil-Sen and analysis of temporal profiles as well as trend analysis seasonal. The correlation between the meteorological data and the vegetation index was studied through the multiple linear regression, expressed by the regression coefficient and the coefficient of determination (R?) estimates. Therefore, a land use analysis was carried out in the same study period, from 2001, 2006 and 2013 through classifiers generated for each pixel value of the image. With the generation of temporal profiles of vegetation indices, it was observed that there was a decrease in vegetative vigor, this result was in line with the interannual trends studied, which indicated a decrease in vegetation values for both the monotonic tendency of Mann Kendall and Median trend with values close to 0 and negative, being a non-linear behavior according to the methodologies of linear correlation, linearity and linear trend. According to the Seasonal Trend Analysis, EVI did not present a cycle pattern, with a mixture of cycles, annual and semi-annual. In relation to the correlation of the vegetation indices with the meteorological variables, correlation values were found that reached 0.97 for the R?. Thus, there is a high explanation of the dynamics of the landscape through these climatic variables. The landscape EVI for the Atlantic Forest Biome behaves seasonally and depending on the environmental conditions of the region / O bioma Mata Atl?ntica ? uma regi?o biogeogr?fica com alta biodiversidade, contendo diversas reservas naturais que geram recursos indispens?veis para todos os seres vivos. Com o seu alto grau de desmatamento ao longo dos anos devido a a??o antr?pica, faz-se necess?rio a identifica??o e o monitoramento das mudan?as do uso e cobertura do solo o que possibilita a melhor compreens?o do futuro das florestas e como est?o ocorrendo as suas mudan?as. Com isso, esse trabalho tem o objetivo de avaliar a din?mica da vegeta??o no bioma Mata Atl?ntica atrav?s do ?ndice de Vegeta??o Melhorado (EVI) e qual a sua rela??o com as vari?veis meteorol?gicas: temperatura m?dia do ar, chuva, radia??o solar global, umidade relativa do ar e evapotranspira??o. O trabalho foi realizado no munic?pio de Pinheiral no Estado do Rio de Janeiro. Foram utilizados os dados de vegeta??o do produto MOD13Q1, no per?odo de 2001 a 2013, totalizando 299 imagens e dados mensais das vari?veis meteorol?gicas, do mesmo per?odo, totalizando 780 dados. As an?lises das tend?ncias interanuais das s?ries temporais de ?ndices de vegeta??o foram realizadas por meio das metodologias de linearidade, correla??o linear, tend?ncia linear, tend?ncia monot?nica de Mann Kendall, tend?ncia mediana de Theil-Sen e an?lise dos perfis temporais e tamb?m a an?lise de tend?ncia sazonal. Atrav?s da regress?o linear m?ltipla, expressas pelas estimativas dos coeficientes da regress?o e do coeficiente de determina??o (R2) foi estudada a correla??o entre os dados meteorol?gicos e o ?ndice de vegeta??o. Diante disso, foi realizado uma an?lise de uso do solo no mesmo per?odo de estudo, de 2001, 2006 e 2013 atrav?s de classificadores gerados para cada valor do pixel da imagem. Com a gera??o dos perfis temporais dos ?ndices de vegeta??o, observou-se que houve uma diminui??o no vigor vegetativo, esse resultado foi de encontro ?s tend?ncias interanuais estudadas, que indicaram decr?scimo nos valores da vegeta??o tanto para a tend?ncia monot?nica de Mann Kendall como para a tend?ncia mediana com valores pr?ximos de 0 e negativos, sendo um comportamento n?o linear de acordo com as metodologias de correla??o linear, linearidade e tend?ncia linear. De acordo com a An?lise de Tend?ncia Sazonal, o EVI n?o apresentou um padr?o de ciclo, ocorrendo uma mistura de ciclos, anual e semi-anual. Em rela??o a correla??o dos ?ndices de vegeta??o com as vari?veis meteorol?gicas, foram encontrados valores de correla??o que chegaram a 0,97 para o R?. Dessa forma, verifica-se uma alta explica??o da din?mica da paisagem atrav?s dessas vari?veis clim?ticas. O EVI da paisagem para o Bioma Mata Atl?ntica se comporta de forma sazonal e em fun??o das condi??es ambientais da regi?o

Submitted by Celso Magalhaes (celsomagalhaes@ufrrj.br) on 2017-06-07T17:24:31Z No. of bitstreams: 1 2015 - Thiago Bernardo Pedro.pdf: 895954 bytes, checksum: 51cf79437e4ec796c2634cdc0a4b0498 (MD5) / Made available in DSpace on 2017-06-07T17:24:32Z (GMT). No. of bitstreams: 1 2015 - Thiago Bernardo Pedro.pdf: 895954 bytes, checksum: 51cf79437e4ec796c2634cdc0a4b0498 (MD5) Previous issue date: 2015-02-23 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico - CNPq / This study evaluates the influence of climatic variables on the occurrence distribution of Amblyomma sculptum adult ticks in four sample areas in Serop?dica and Mangaratiba, two municipalities in Rio de Janeiro Metropolitan mesoregion. The data used is relative to tick sampling between the spring of 2008 and the winter of 2012. The climatic variables included in the study were mean temperature, relative humidity and rainfall, in the day of sampling and in the 15 days prior to each sampling. For the statistical analysis, four types of generalized linear models were used: Poisson, Negative Binomial, Quasi Poisson (?2) and Zero Inflated Poisson (ZIP). A total of 574 ticks were found, most of them in the autumn. The bivariate analysis between each one of the independent variables and the response variable, tick count, showed seven variables that were significant at least in two types of models (being ZIP one of them): temperature in the day before sampling, temperature between the 4th and 6th days prior to sampling, temperature between the 11th and 15th days prior, humidity in the day before sampling, humidity in 5th day before, humidity between the 9th and 12th days prior and rainfall in the 12th day prior to sampling. These variables were combined in the multivariate analysis, therewith, nine models were fitted. Analyzing the prevalence ratio (PR), Akaike Information Criterion (AIC), mean square of residuals (MSR) and correlation between expected Y and observed Y (Corr), the best model was chosen, with the following variables (PR [CI 90%]): temperature between the 11th and 15th days prior to sampling (1,06 [1,01; 1,11]), humidity in the day before (1,04 [1,02; 1,05]) and rainfall in the 12th day prior to sampling (0,97 [0,94; 0,99]). Regarding the fitted models, it was possible to notice that the most satisfactory parameters were presented by ZIP models, in which the MSR values were the lowest and Corr values were the highest. The bivariate analyzes performed as of ZIP models contrasted the fact that temperature acts as a protection factor for the occurrence of A. sculptum adult ticks in the day of sampling and in the two days before, but it acts as a risk factor form the 3rd to the 15thday before. Humidity and rainfall act as protection factors for tick occurrence as from the 3rd and the 5th day prior to sampling, respectively. In the days closer to sampling, these two latter variables did not show a definite conduct of risk or protection with respect to the studied tick occurrence. Within this context, we conclude that understanding the parameters responsible for controlling the life cycle of A. sculptum is essential to generate risk models of disease transmission / O presente estudo avalia a influ?ncia de vari?veis clim?ticas sob a distribui??o de ocorr?ncia de carrapatos Amblyomma sculptum adultos em quatro ?reas amostrais nos munic?pios de Serop?dica e Mangaratiba, na mesorregi?o Metropolitana do Rio de Janeiro. Foram utilizados dados referentes a coletas de carrapatos realizadas entre a primavera de 2008 e o inverno de 2012. As vari?veis clim?ticas consideradas foram temperatura m?dia, umidade relativa do ar e volume de precipita??o, no dia das coletas e nos 15 dias anteriores a cada coleta. Para a an?lise estat?stica, foram utilizados quatro tipos de modelos de regress?o lineares generalizados: Poisson, Binomial Negativa, Extra Poisson (?2) e Poisson Inflacionada de Zeros. Foram coletados, ao todo, 574 carrapatos, sendo a maioria no outono. A an?lise bivariada entre cada uma das vari?veis explicativas e a vari?vel de desfecho, contagem de carrapatos, apresentou sete vari?veis significativas em pelo menos dois modelos (sendo um deles o ZIP): temperatura no dia anterior ? coleta, temperatura entre o 4? e o 6? dia anterior, temperatura entre o 11? e o 15? dia anterior, umidade no dia anterior ? coleta, umidade no 5? dia anterior, umidade entre o 9? e o 12? dia anterior e precipita??o no 12? dia anterior ? coleta. Essas vari?veis foram combinadas na an?lise multivariada, com isso, nove modelos foram ajustados. Atrav?s da an?lise da raz?o de preval?ncia (RP), Akaike Information Criterion (AIC), quadrado m?dio dos res?duos (QMR) e correla??o entre Y esperado e Y observado (Corr), foi escolhido o melhor modelo, com as seguintes vari?veis (RP [IC 90%]): temperatura entre o 11? e o 15? dia antes da coleta (1,06 [1,01; 1,11]), umidade no dia anterior ? coleta (1,04 [1,02; 1,05]) e precipita??o no 12? dia anterior (0,97 [0,94; 0,99]). Considerando-se os modelos ajustados, foi poss?vel observar que os par?metros mais satisfat?rios foram apresentados pelos modelos ZIP, em que os valores de QMR foram os mais baixos, e os valores de Corr, os mais elevados. As an?lises bivariadas realizadas a partir do modelo ZIP destacaram o fato de que a temperatura se apresenta como fator de prote??o para a ocorr?ncia de A. sculptum adultos no dia da coleta e nos dois dias anteriores, mas como fator de risco a partir do 3? dia anterior at? o 15?. J? umidade e precipita??o apresentam-se como fatores de prote??o para a ocorr?ncia de carrapatos a partir do 3? e do 5? dia anterior ? coleta, respectivamente, at? o 15?. Nos dias mais pr?ximos ? coleta, essas duas ?ltimas vari?veis n?o apresentam um comportamento definido de risco ou prote??o em rela??o ? ocorr?ncia dos carrapatos em estudo. Dentro desse contexto, conclui-se que entender os par?metros que controlam o ciclo de vida de A. sculptum ? essencial para a gera??o de modelos de risco de transmiss?o de doen?as