Natural and anthropogenic disturbances drive change in ecosystems, especially highly disturbed coastal systems, which are at the interface between the land and the sea and contain both aquatic and terrestrial ecosystems. This transitional zone is at the forefront of climate change. As sea level rises, disturbance regimes are expected to change. Simultaneously, the frequency and intensity of extreme storm events, such as hurricanes, may increase, along with increases in fire intensity and severity in certain regions. Historically, fire was a natural disturbance along the northern Gulf of Mexico where lightning frequency is high; however, today fire along the Gulf is often anthropogenic in origin (i.e., prescribed fire). As disturbance regimes change, the interaction between hurricanes and fire is likely to become increasingly prevalent, since increased production of dead debris from more intense hurricanes is likely to serve as additional fuel material for fires. Sea level rise may also act synergistically with the typical pulse disturbances coastal ecosystems face, including hurricanes and fire. This combination of acute and chronic stressors may prevent coastal ecosystems from recovering and returning to their pre-disturbance state if layered legacies of these events decrease ecosystem stability and resilience. The goal of this study was to investigate the effects of layered legacies of disturbances on community composition, species distributions, extent of coastal zones (e.g., salt marsh, fresh marsh, forest) and vegetation vigor in coastal communities over a 17-year period (2004 to 2021) in coastal Alabama to explore the resilience of coastal systems and their persistence in the face of sea level rise. A combination of ground-collected data from 2004, 2011 and 2021, and fine resolution satellite images taken every other year from 2006-2019 were analyzed. Disturbances altered community composition between 2004 and 2021, which coincided with expansion of salt marsh and fresh marsh species distributions at lower elevations, and declines in woody species in the scrub-shrub ecotone and forest at higher elevations. The scrub-shrub ecotone disappeared, and the forest began to deteriorate, while the extent of the fresh marsh increased. Additionally, vegetation vigor (as measured by the Normalized Difference Vegetation Index; NDVI) was calculated from moderate resolution Landsat images within one month prior to and following each extreme storm event from 2004-2020. NDVI decreased after some extreme storm events but increased after others, and there was an overall increase in NDVI over the last five years of the study period. This study was conducted at a critical time; coastal systems are facing an increasing amount of chronic stress from sea level rise, in addition to more immediate stress from pulse disturbances. Despite these stressors, coastal systems along the northern Gulf of Mexico appear to be more resilient than previously realized because upslope migration of species is evident. Extreme storm events and fires appear to contribute to, and even promote, the persistence of coastal wetlands in the face of sea level rise. However, persistence of coastal wetlands along the northern Gulf of Mexico coast may be prevented in areas dominated by upslope barriers to migration (i.e., current/future urban development and levees), such as in Louisiana.

This dissertation is focused on multiple testing procedures to be used in data that are naturally grouped or possess a spatial structure. We propose `Two-Stage' procedure to control the False Discovery Rate (FDR) in situations where one-sided hypothesis testing is appropriate, such as astronomical source detection. Similarly, we propose a `Three-Stage' procedure to control the mixed directional False Discovery Rate (mdFDR) in situations where two-sided hypothesis testing is appropriate, such as vegetation monitoring in remote sensing NDVI data. The Two and Three-Stage procedures have provable FDR/mdFDR control under certain dependence situations. We also present the Adaptive versions which are examined under simulation studies. The `Stages' refer to testing hypotheses both group-wise and individually, which is motivated by the belief that the dependencies among the p-values associated with the spatially oriented hypotheses occur more locally than globally. Thus, these `Staged' procedures test hypotheses in groups that incorporate the local, unknown dependencies of neighboring p-values. If a group is found significant, further investigation is done to the individual p-values within that group. For the vegetation monitoring data, we extend the investigation by providing some spatio-temporal models and forecasts to some regions where significant change was detected through the multiple testing procedure. / Statistics

Monitoring and understanding plant phenology is becoming an increasingly important way to identify and model global changes in vegetation life cycle events. Although numerous studies have used synoptically sensed data to study phenological patterns at the continental and global scale, relatively few have focused on characterizing the land surface phenology of specific ecosystems. Mountain environments provide excellent examples of how variations in topography, elevation, solar radiation, temperature, and spatial location affect vegetation phenology. High elevation biomes cover twenty percent of the Earth's land surface and provide essential resources to both the human and non-human population. These areas experience limited resource availability for plant growth, development, and reproduction, and are one of the first ecosystems to reflect the harmful impact of climate change. Despite this, the phenology of mountain ecosystems has historically been understudied due to the rough and variable terrain and inaccessibility of the area. Here, we use two MODIS/Terra satellite 16-day products, Vegetation Index and Nadir BRDF Adjusted Reflectance, to assess start of season (SOS) for the 2007 calendar year. Independent data for elevation, slope, aspect, solar radiation, and temperature as well as longitude and latitude were then related to the SOS output. Based on the results of these analyses, we found that SOS can be predicted with a significant R² (0.55-0.64) for each individual zone as well as the entire western mountain range. While both elevation and latitude have significant influences on the timing of SOS for all six study areas. When examined at the regional scale and accounting for aspect, SOS follows closely with Hopkins' findings in regard to both elevation and latitude. / Master of Science

In this study we applied the asymmetric Gaussian, double-logistic, and Savitzky-Golay filters to MODIS time-series NDVI data to compare the capability of smoothing algorithms in noise reduction for improving land cover classification in the Great Lakes Basin, and providing groundwork to support cyanobacteria and cyanotoxin monitoring efforts. We used inter-class separability and intra-class variability, at varying levels of pixel homogeneity, to evaluate the effectiveness of three smoothing algorithms. Based on these initial tests, the algorithm which returned the best results was used to analyze how image stratification by ecoregion can affect filter performance. MODIS 16-day 250m NDVI imagery of the Great Lakes Basin from 2001-2013 were used in conjunction with National Land Cover Database (NLCD) 2006 and 2011 data, and Cropland Data Layers (CDL) from 2008 to 2013 to conduct these evaluations. Inter-class separability was measured by Jeffries-Matusita (JM) distances between selected land cover classes (both general classes and specific crops), and intra-class variability was measured by calculating simple Euclidean distance for samples within a land cover class. Within the study area, it was found that the application of a smoothing algorithm can significantly reduce image noise, improving both inter-class separability and intra-class variability when compared to the raw data. Of the three filters examined, the asymmetric Gaussian filter consistently returned the highest values of interclass separability, while all three filters performed very similarly for within-class variability. The ecoregion analysis based on the asymmetric Gaussian dataset indicated that the scale of study area can heavily impact within-class separability. The criteria we established have potential for furthering our understanding of the strengths and weaknesses of different smoothing algorithms, thereby improving pre-processing decisions for land cover classification using time-series data. / Master of Science

Dans le sud tunisien, tous les périmètres irrigués de type oasis n’ont pas connu le même développement au cours de 50 dernières années. On observe ainsi depuis plusieurs décennies, une évolution des surfaces couvertes qui dans certaines régions ont plus que doublé, alors que pour d’autres elles sont restées pratiquement stables et dans certains cas, ont même connu une régression. Face aux enjeux que ces changements impliquent tant sur le plan environnemental qu’économique et social, l’élaboration d’une typologie des oasis ainsi que l’estimation de leur état sont d’une importance stratégique aux niveaux national, régional et international. Pour connaître l'état de la végétation dans ces oasis, des systèmes de surveillance de ces écosystèmes oasiens devraient être mis au point et renseignés régulièrement par des données prises sur ces surfaces cultivées. Ces données peuvent être obtenues en partie par les systèmes d’observations satellitaires à haute et à moyenne résolution spatiale, et forte répétitivité temporelle, qui par leur vision synoptique, constituent une source d’informations particulièrement adéquate. Le travail de recherche présenté ici porte sur l’exploration de méthodes développées à partir de deux types de séries temporelles d’images d’observation de la Terre : celles produites par l’expérience SPOT-5 (Take5) et le produit MOD13Q1 du capteur MODIS, respectivement à 10m et 250 m de résolution spatiale, et avec des répétitivités de 5 et 26 jours. Ces méthodes et données ont été testées sur la région du Djérid dans le but final de mettre en place un système de surveillance des oasis basé sur l'analyse des signatures temporelles à partir d’images d’observations de la Terre prises très régulièrement dans le temps.Deux démarches différentes d’analyse ont été menées pour chaque type de données, basées sur le traitement de séries temporelles d’un indice de végétation, le NDVI. La première repose sur les variations temporelles de l’activité végétale sur une courte période d’avril à septembre 2015 à travers la série d’images SPOT-5 (Take5) : la comparaison entre oasis s’est faite à l’échelle du périmètre irrigué (une oasis peut être composée de plusieurs périmètres irrigués) en utilisant la méthode statistique de classification ascendante hiérarchique. La seconde utilise une technique de décomposition temporelle d’un signal pour extraire la tendance d’une série d’images pluriannuelles à l’échelle d’un point géographique (un pixel de 250mx250m) à travers la série temporelle MOD13Q1 de 2000 à 2016.Les résultats obtenus à partir du traitement et de l’analyse de ces séries temporelles optiques ont permis de montrer qu’il est possible d’identifier les principaux types de périmètres irrigués présents dans la région de Djérid, et retrouver rétrospectivement l’histoire récente de leur développement. Ils mettent aussi en évidence le fait que les images SPOT-5 (Take5), qui préfigurent celles actuellement disponibles avec les images produites par les satellites Sentinel2, améliorent considérablement la caractérisation spatio-temporelle du fonctionnement des oasis grâce à la finesse de leur résolution spatiale et de leur répétitivité temporelle.Les résultats de cette thèse permettent de dégager de nouvelles pistes de couplage entre télédétection, données de terrain et analyses statistiques en apportant une information continue dans le temps et dans l’espace pour le suivi et la surveillance des écosystèmes oasiens. En effet avec deux capteurs tel que Sentinel2, couplé aux données historiques de MOD13Q1, il est permis désormais de caractériser précisément les oasis d’une façon presque continue. / In southern Tunisia, not all irrigated oasis-type perimeters have undergone the same development, we observed an evolution of the covered surfaces which more than doubled in the last half-century, while for other regions they have remained practically stable and in some cases, a decrease in these areas. These changes have affected environmental and economic systems. In this context, the evaluation of the state of oases and the development of a typology of oases systems is a key-issue for sustainable agriculture. To know the state of vegetation in these oases, monitoring systems for oasis ecosystems must be informed by data on cultivated areas. These data can be obtained in part by satellite observation systems with high and moderate spatial resolution and high temporal repetitiveness, offer a synoptic vision that makes them a particularly appropriate information source for the estimation of such data. The research work presented here focuses on the exploration of methods developed from two types of time series of Earth observation images: those produced by the SPOT-5 experiment (Take5) and the MOD13Q1 product of the MODIS sensor, at 10m and 250m spatial resolution respectively. These methods and data were tested in the Djerid region with the final aim of setting up an oasis monitoring system based on the analysis of time signatures from Earth observation images made very regularly over time.Two change detection approaches based on NDVI time series. The first consists on temporal variations in vegetation activity over a short period from April to September 2015 through the SPOT-5 time series (Take5): the comparison between oases was made at the scale of the irrigated perimeter (an oasis can be composed of several irrigated perimeters) using agglomerative hierarchical clustering (AHC) method.The second uses a temporal decomposition technique to extract the trend from a multi-year time series at the scale of a geographical point (a 250mx250m pixel) across the MOD13Q1 time series (2000-2016).Results obtained from the processing and analysis of optical time series have shown that it is possible to identify the main types of irrigated perimeters present in the Djerid region, and to retrospectively trace their recent development history. They also highlight the fact that SPOT-5 (Take5) images, which prefigure those currently available with images produced by Sentinel2 satellites, significantly improve the spatio-temporal characterization of oases functioning through their 10m spatial resolution and 5-day temporal repetitiveness.The results of this thesis highlight new possibilities for the combination of remote sensing, field data and statistical analysis, delivering nonstop information in time and space on the characterization of oases systems. Indeed, with a single sensor such as Sentinel2, coupled with the historical data of MOD13Q1, it is now possible to accurately characterize oases on a continuous basis.

A leishmaniose visceral é uma zoonose de grande importância para a saúde pública, com ampla distribuição geográfica e epidemiologia complexa. Apesar de diversas estratégias de controle, a doença continua se expandindo, tendo o cão como principal reservatório. Levando em consideração que análises espaciais são úteis para compreender melhor a dinâmica da doença, avaliar fatores de risco e complementar os programas de prevenção e controle, o presente estudo teve como objetivo caracterizar a distribuição da leishmaniose visceral canina e relacionar sua dinâmica com características ou feições espaciais no município de Panorama (SP). A partir de dados secundários coletados em um inquérito sorológico entre agosto de 2012 e janeiro de 2013, 986 cães foram classificados como positivos e negativos de acordo com o protocolo oficial do Ministério da Saúde. Posteriormente uma análise espacial foi conduzida, compreendendo desde a visualização dos dados até a elaboração de um mapa de risco relativo, passando por análises de cluster global (função K) e local (varredura espacial). Para avaliar uma possível relação entre o cluster detectado com a vegetação na área de estudo, calculou-se o Índice de Vegetação por Diferença Normalizada (NDVI). A prevalência da doença encontrada na população de cães estudada foi de 20,3% (200/986). A visualização espacial demonstrou que tanto animais positivos quanto negativos estavam distribuídos por toda a área de estudo. O mapa de intensidade dos animais positivos apontou duas localidades de possíveis clusters, quando comparado ao mapa de intensidade dos animais negativos. As análises de cluster confirmaram a presença de um aglomerado e um cluster foi detectado na região central do município, com um risco relativo de 2,63 (p=0,01). A variação espacial do risco relativo na área de estudo foi mapeada e também identificou a mesma região como área significativa de alto risco (p<0,05). Não foram observadas diferenças no padrão de vegetação comparando as áreas interna e externa ao cluster. Sendo assim, novos estudos devem ser realizados com o intuito de compreender outros fatores de risco que possam ter levado à ocorrência do cluster descrito. A prevalência, a localização do cluster espacial e o mapa de risco relativo fornecem subsídios para direcionamento de esforços do Setor de Vigilância Epidemiológica de Panorama para áreas de alto risco, o que pode poupar recursos e aperfeiçoar o controle da leishmaniose visceral no município. / Visceral leishmaniasis is a zoonosis of great importance for public health, having worldwide distribution and complex epidemiology. Despite several control strategies, the disease continues to expand, being dogs its main reservoir. Considering that spatial analysis is useful to better understand the disease dynamics, to evaluate risk factors and to complement prevention and control programs, this study aimed to characterize the distribution of canine visceral leishmaniasis and relate it to spatial features in Panorama, an endemic city of São Paulo State, Brazil. Using secondary data collected in a serological survey between August 2012 and January 2013, 986 dogs were classified as positive and negative for leishmaniasis. Later, a spatial analysis was conducted comprising from data visualization to the elaboration of a relative risk map, undergoing global (K function) and local cluster analysis (spatial scan). To evaluate a possible relation between the detected cluster and vegetation in the study area, the Normalized Difference Vegetation Index (NDVI) was calculated. The prevalence in the studied dog population was 20.3% (200/986). Spatial visualization showed that both positive and negative animals were distributed throughout the study area. Intensity map of positive animals showed two sites of possible clusters compared to the intensity map of negative animals. A cluster was detected in a central region of the city, with a relative risk of 2.63 (p=0,01). The spatial variation of the relative risk in the study area was mapped and the same region was identified as a significant high risk area (p<0.05). No differences were observed in the vegetation pattern comparing the cluster internal and external areas. Therefore, further studies should be conducted in order to understand other risk factors that may have led to the occurrence of the described cluster. The prevalence data, the cluster location and the relative risk map provide subsidies for the efforts of the city epidemiological surveillance department towards high risk areas. This can save resources and improve control of visceral leishmaniasis in the study area.

Les milieux oroméditerranéens sont considérés comme particulièrement sensibles aux changements climatiques. Deux questions sont posées dans ce contexte : quelles sont la nature et l'ampleur des modifications climatiques à l'échelle régionale (climat et enneigement) au Chili central, depuis les années 70 ? Quels sont les changements de la végétation en montagne (dans la tranche d'altitude 1.500 - 2.500 m), en particulier au niveau de la limite supérieure de la forêt à Kageneckia angustifolia ? La première partie de la thèse présente les spécificités des milieux de montagne et les changements climatiques déjà observés de façon générale et au Chili en particulier. Elle présente aussi les sites d'étude au niveau climatique et biogéographique. La deuxième partie concerne les données et la méthodologie. Une approche scalaire est mise œuvre, avec confrontation et mise en complémentarité de différentes techniques : télédétection, chroniques climatiques et mesures in situ. La troisième partie présente les résultats. Les données climatiques enregistrées les 30 dernières années aux stations d'El Yeso (2.500 m) et de Los Bronces (3.500 m), montre une croissance d'environ 1 °C pour la température moyenne annuelle, réchauffement plus marqué à El Yeso, au niveau des températures minimales. Pour l'enneigement, il est montré une haute variation interannuelle de la couverture de neige et une élévation de la limite de la neige durant les dernières décennies, d'environ 300 m. Ces résultats, sont accompagnés d'une augmentation faible du NDVI. Au niveau de la vallée Yerba Loca, l'étude diachronique de l'écotone supraforestier montre des transformations vers une augmentation de la superficie des espaces forestiers et leur densification. Enfin, l'expérience de germination, à Yerba Loca montre qu'il existe une différence significative entre le pourcentage de germination des graines à l'intérieur des enclos et à l'extérieur, avec un effet négatif de la couverture neigeuse sur la germination des plantules. / Mediterranean areas are considered particularly sensitive to climate change. Two questions are asked in this context: what is the nature and magnitude of regional climate change (climate and snow cover) in central Chile, since the 70's? What are the changes in mountain vegetation (in the altitude range of 1,500-2,500 m), especially at the upper limit of Kageneckia angustifolia forest? The first part of the thesis shows the characteristics of mountain environments and observed climate change at global and Chilean local level. It also presents the study area, from the standpoint of biogeography and climate. The second part refers to the data and methodology. We used a multiscale approach to the confrontation and the application of several complementary techniques: remote sensing, climatic data and field measurements. The third part presents the results. Climate data recorded in the last 30 years in the stations of El Yeso (2,500 m) and Los Bronces (3,500 m), shows an increase of about 1° C in mean annual temperature, been the sharpest increase in El Yeso, especially in average of low temperatures. In relation to snow cover, it shows high variation and a rise up in the limit of snowline in recent decades, about 300 m. These results are accompanied by a slight increase in NDVI. In the Yerba Loca valley, the diachronic study of Kageneckia angustifolia forest ecotone shows changes towards an increase forest areas and densification. Finally, the experience of germination in Yerba Loca indicates a significant difference between the percentage of germination of the seeds under protection from snow and the ones without treatment, with a negative effect of snow cover on the germination.

Submitted by Jean Medeiros (jeanletras@uepb.edu.br) on 2016-05-12T12:41:00Z No. of bitstreams: 1 PDF - Magno Ferreira da Silva.pdf: 2667909 bytes, checksum: 7b2a4349f2b8d350eb7b2685af53d135 (MD5) / Made available in DSpace on 2016-05-12T12:41:00Z (GMT). No. of bitstreams: 1 PDF - Magno Ferreira da Silva.pdf: 2667909 bytes, checksum: 7b2a4349f2b8d350eb7b2685af53d135 (MD5) Previous issue date: 2016-02-26 / The present study examined the changes of the caatinga vegetation in response to climatic conditions in the municipality of Gado Bravo in the State of Paraíba, corresponding to the Agreste region. To this end, images from the MODIS sensor/land of the municipality, have been processed to obtain the Normalized Difference vegetation index-NDVI, rainy and dry periods during the years from 2011 to 2014. The use of historical data of precipitation rainfall of the Executive Agency for the Management of Waters of the State of Paraiba -EAWS, allowed to evaluate the wettest months of the year (April, may and June), the drought season months (september, october, november and december) and the months of low precipitation (january, february, march, august and july). In the years of study, the month of may was the wettest december and the drought season. Most plants in the drought season, has a typical adaptation, consisting of the miss of the leaves avoiding the dehydration through the process of transpiration, thus the caatinga biome appears to be a poor in biodiversity and/or high levels of degradation. However, during the rainy season, the plants respond quickly to rainfall, showing a biological regeneration. The NDVI is an index of the remote sensing that is directly connected the photosynthetic activity of vegetation, and is calculated by a normalized difference between two bands of the electromagnetic spectrum, the spectral band of red and near infrared band. The greater the difference between the spectral bands of red and near infrared vegetation is in full photosynthetic activity, and if the grass for some reason is having a stress where its components are vegetables at low photosynthetic activity, the differences between the reflectâncias of spectral bands decrease and with this the results of NDVI are smaller. In the study period, one can realize that there is a differentiation in the caatinga vegetation of the municipality of Gado Bravo-PB, in response to climate change that occurred in the annual cycle of precipitation and in the biological cycle of vegetation. The loss of leaves during the dry season, appears as adaptive process that can interfere directly on the results of the NDVI, because the vegetation without leaves presents significant photosynthetic activity and the results next to zero of the NDVI can be understood as an area degraded or severely degraded. / O presente estudo analisou as mudanças da vegetação do bioma caatinga em resposta as condições climáticas no município de Gado Bravo no Estado da Paraíba, correspondente a microrregião do agreste. Para tanto, imagens do sensor MODIS/TERRA do território do município foram processadas para obtenção do Índice de Vegetação por Diferença Normalizada – NDVI, dos períodos chuvosos e de estiagem durante os anos de 2011 à 2014. A utilização dos dados históricos de precipitação pluviométricas da Agência Executiva de Gestão das Águas do Estado da Paraíba – AESA permitiu avaliar os meses mais chuvosos do ano (abril, maio e junho), os meses de estiagem (setembro, outubro, novembro e dezembro) e os meses de baixa precipitação pluviométrica (janeiro, fevereiro, março agosto e julho). Nos anos de estudo , o mês de maio foi o mais chuvoso e o mês de dezembro o de estiagem. A maioria das plantas, no período de estiagem, possui uma adaptação típica, que consiste na perca das folhas, evitando a desidratação por meio do processo de transpiração, deste modo à caatinga aparenta ser um bioma pobre em sua biodiversidade e/ou com altos índices de degradação. Porém, no período chuvoso, as plantas respondem rapidamente à pluviosidade, apresentando uma regeneração biológica. O NDVI é um índice do sensoriamento remoto que está diretamente ligado as atividades fotossintéticas da vegetação e é calculado por uma diferença normalizadas entre duas bandas do espectro eletromagnético, a banda espectral do vermelho e a banda do infravermelho próximo. Quanto maior a diferença entre as bandas espectrais do vermelho e do Infravermelho próximo a vegetação está em plena atividade fotossintética, e se a vegetação por algum motivo estiver passando por um estresse onde seus componentes vegetais estejam em baixas atividades fotossintética, as diferenças entre as reflectâncias das bandas espectrais diminuem e com isso os resultados do NDVI são menores. No período de estudo, pode-se perceber que ocorre uma diferenciação na vegetação do bioma caatinga do município de Gado Bravo-PB, em resposta às mudanças climáticas ocorridas no ciclo anual de precipitação pluviométrica e no ciclo biológico da vegetação. A perda das folhas, durante o período de estiagem, configura-se como processo adaptativo que pode interferir diretamente nos resultados do NDVI, pois a vegetação sem folhas não apresenta atividades fotossintéticas significativas e os resultados próximos a zero do NDVI podem ser compreendidos como uma área degradada ou severamente degradada.

A leishmaniose visceral é uma zoonose de grande importância para a saúde pública, com ampla distribuição geográfica e epidemiologia complexa. Apesar de diversas estratégias de controle, a doença continua se expandindo, tendo o cão como principal reservatório. Levando em consideração que análises espaciais são úteis para compreender melhor a dinâmica da doença, avaliar fatores de risco e complementar os programas de prevenção e controle, o presente estudo teve como objetivo caracterizar a distribuição da leishmaniose visceral canina e relacionar sua dinâmica com características ou feições espaciais no município de Panorama (SP). A partir de dados secundários coletados em um inquérito sorológico entre agosto de 2012 e janeiro de 2013, 986 cães foram classificados como positivos e negativos de acordo com o protocolo oficial do Ministério da Saúde. Posteriormente uma análise espacial foi conduzida, compreendendo desde a visualização dos dados até a elaboração de um mapa de risco relativo, passando por análises de cluster global (função K) e local (varredura espacial). Para avaliar uma possível relação entre o cluster detectado com a vegetação na área de estudo, calculou-se o Índice de Vegetação por Diferença Normalizada (NDVI). A prevalência da doença encontrada na população de cães estudada foi de 20,3% (200/986). A visualização espacial demonstrou que tanto animais positivos quanto negativos estavam distribuídos por toda a área de estudo. O mapa de intensidade dos animais positivos apontou duas localidades de possíveis clusters, quando comparado ao mapa de intensidade dos animais negativos. As análises de cluster confirmaram a presença de um aglomerado e um cluster foi detectado na região central do município, com um risco relativo de 2,63 (p=0,01). A variação espacial do risco relativo na área de estudo foi mapeada e também identificou a mesma região como área significativa de alto risco (p<0,05). Não foram observadas diferenças no padrão de vegetação comparando as áreas interna e externa ao cluster. Sendo assim, novos estudos devem ser realizados com o intuito de compreender outros fatores de risco que possam ter levado à ocorrência do cluster descrito. A prevalência, a localização do cluster espacial e o mapa de risco relativo fornecem subsídios para direcionamento de esforços do Setor de Vigilância Epidemiológica de Panorama para áreas de alto risco, o que pode poupar recursos e aperfeiçoar o controle da leishmaniose visceral no município. / Visceral leishmaniasis is a zoonosis of great importance for public health, having worldwide distribution and complex epidemiology. Despite several control strategies, the disease continues to expand, being dogs its main reservoir. Considering that spatial analysis is useful to better understand the disease dynamics, to evaluate risk factors and to complement prevention and control programs, this study aimed to characterize the distribution of canine visceral leishmaniasis and relate it to spatial features in Panorama, an endemic city of São Paulo State, Brazil. Using secondary data collected in a serological survey between August 2012 and January 2013, 986 dogs were classified as positive and negative for leishmaniasis. Later, a spatial analysis was conducted comprising from data visualization to the elaboration of a relative risk map, undergoing global (K function) and local cluster analysis (spatial scan). To evaluate a possible relation between the detected cluster and vegetation in the study area, the Normalized Difference Vegetation Index (NDVI) was calculated. The prevalence in the studied dog population was 20.3% (200/986). Spatial visualization showed that both positive and negative animals were distributed throughout the study area. Intensity map of positive animals showed two sites of possible clusters compared to the intensity map of negative animals. A cluster was detected in a central region of the city, with a relative risk of 2.63 (p=0,01). The spatial variation of the relative risk in the study area was mapped and the same region was identified as a significant high risk area (p<0.05). No differences were observed in the vegetation pattern comparing the cluster internal and external areas. Therefore, further studies should be conducted in order to understand other risk factors that may have led to the occurrence of the described cluster. The prevalence data, the cluster location and the relative risk map provide subsidies for the efforts of the city epidemiological surveillance department towards high risk areas. This can save resources and improve control of visceral leishmaniasis in the study area.

Made available in DSpace on 2017-07-10T19:24:13Z (GMT). No. of bitstreams: 1 HUMBERTO MARTINS_BENEDUZZI .pdf: 2255923 bytes, checksum: d4b88d0d65161bde59b32f36180d59b6 (MD5) Previous issue date: 2015-07-27 / Currently, optimizing the management of nitrogen fertilizers has been one of the great challenges in grain production, since N has the potential to increase yield, but if it is applied in excess, it can cause environmental damage due to the leaching process. Precision agriculture aims at solving this problem by applying fertilizer at different rates, in order to apply the right amount of fertilizer at each point of a certain cropped area. The N estimate is essential at each point and can be carried out by reflectance sensors, which is an equipment with proven efficacy in this task. Passive sensors, however, are directly influenced by solar radiation since they do not have an emission source, thereafter they use solar radiation to perform measurements. On the other hand, the active sensors could, in theory, be used at any time of the day and in different weather conditions, since they have their own emission source. In practice, some researches have already shown that even these devices are influenced by the amount of solar radiation and weather changes. Thus, this paper studied the temporal variability of the NDVI vegetation index, registered by an active reflectance sensor on crops such as maize, soybeans and wheat. The NDVI and irradiation data were collected by a GreenSeeker sensor at every 15 minutes over 12, 14 or 26 hours straight. The NDVI index was negatively influenced by irradiation in all experiments with maize, soybean and wheat. Thus, it has shown higher values at the beginning and end of the day and there also were changes in cloud cover that affected the NDVI in most experiments. / A otimização do manejo de fertilizantes nitrogenados apresenta-se como um dos grandes desafios na produção de grãos, uma vez que o N tem o potencial de elevar a produtividade, mas se aplicado em excesso pode gerar danos ambientais devido ao processo de lixiviação. A agricultura de precisão visa resolver este problema com a aplicação de fertilizantes a taxas variadas, aplicando a quantidade de fertilizante adequada em cada ponto da área cultivada. A estimativa da necessidade de N em cada ponto pode ser feita por sensores de reflectância, equipamentos de eficácia comprovada na realização desta tarefa. Os sensores passivos, porém, sofrem influência direta da irradiação solar, uma vez que não possuem fonte emissora e usam a irradiação solar para realizar medições. Por outro lado, os sensores ativos poderiam, em teoria, ser utilizados em qualquer horário do dia e em diferentes condições atmosféricas, uma vez que possuem a própria fonte emissora. Na prática, pesquisas têm demonstrado que mesmo esses equipamentos sofrem influência da quantidade de irradiação solar e variações climáticas. Por esta razão, este trabalho estudou a variabilidade temporal do índice de vegetação NDVI, registrado por um sensor ativo de reflectância nas culturas de milho, soja e trigo. Os dados de NDVI e de irradiação foram coletados por um sensor GreenSeeker, a cada 15 minutos, ao longo de 12, 14 ou 26 horas consecutivas. O NDVI foi influenciado negativamente pela irradiação em todos os experimentos realizados nas culturas de milho, soja e trigo, e apresentou-se mais elevado no início e no fim do dia. As mudanças na cobertura de nuvens também afetaram o NDVI em grande parte dos experimentos