Submitted by Amanda Silva (amanda.osilva2@ufpe.br) on 2015-03-11T12:51:30Z No. of bitstreams: 2 TESE Antonio Paulo da Silva Júnior.pdf: 3733072 bytes, checksum: b8bf07418425952f81fdbb30e63f6ed6 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-03-11T12:51:30Z (GMT). No. of bitstreams: 2 TESE Antonio Paulo da Silva Júnior.pdf: 3733072 bytes, checksum: b8bf07418425952f81fdbb30e63f6ed6 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2014 / CNPq; PROPESQ; Fundação o Boticário de proteção à natureza / Introdução: O presente estudo tem por objetivos testar a influência de fatores ambientais, da produtividade do ambiente e da heterogeneidade ambiental, sobre a diversidade e abundância de mamíferos, bem como testar a relação massa corpórea x abundância, verificando os fatores que a influencia na região da bacia do Rio Negro. Métodos: Avaliamos a comunidade de mamíferos de médio e grande em porte em cinco áreas na bacia do Rio Negro, utilizando o método de transecto linear, através do qual obtivemos variáveis dependentes, as quais: (1) densidade de grupo, (2) densidade individual, (3) biomassa, (4) tamanho médio de grupo e (5) índices de diversidade. Através de técnicas de sensoriamento remoto obtivemos índices de vegetação de diferença normalizada (NDVI), índice de área foliar (LAI), Declividade do ambiente e heterogeneidade. Utilizamos o Modelo Linear Generalizado (GLM), baseado no Critério de informação de Akaike (AIC), para determinar quais das variáveis preditivas explicariam essa relação para os primatas das áreas estudadas. Para isso, utilizamos o modelo de regressão linear simples para relacionar massa corpórea com os diversos parâmetros de abundância de toda comunidade de mamíferos. Utilizamos a correlação produto-momento Pearson, para testar a influência da diversidade e NDVI sobre o coeficiente de regressão. Resultados: Houve uma correlação entre NDVI e tamanho médio de grupo (R= -0,65; p=0,015), LAI e tamanho médio de grupo de primatas (R= -0,64; p=0,017), declividade e tamanho médio de grupo (R= -0,67; p=0,008) e heterogeneidade e tamanho médio de grupo (R= -0,67; p=0,008). O GLM baseado no AIC, mostrou NDVI e declividade como a melhor variável explicativa para tamanho médio de grupo. Para toda a comunidade de mamíferos as relações significativas entre massa corpórea e abundância variaram consideravelmente, com valores entre -0,76 a 0,75, o que dependeu do parâmetro de abundância avaliado, da categoria trófica e do hábito das espécies. As correlações apontaram para uma influência da diversidade de mamíferos sobre as inclinações das retas. Discussão: Os índices de vegetação, declividade do terreno e heterogeneidade não explicaram a diversidade de primatas. A relação inversa entre tamanho médio de grupo e NDVI, LAI e declividade mostrou que nos ambientes menos produtivos os primatas tendem a formar grupos maiores como uma estratégia para aumentar a defesa contra predadores e a eficiência de forrageamento. As relações massa corpórea x abundância mostraram que em ambientes mais equilibrados os recursos estariam melhor partilhados e a inclinação da reta seria mais negativa, o que estaria mais de acordo com a regra da equivalência energética. Análises de acordo com o hábito terrestre mostraram correlação com a produtividade das florestas e, de acordo com a dieta, verificamos relações significativas para a categoria dos frugívoros, a qual possui maior amplitude de massa corpórea.

Knowledge og the crop yield with sufficient lead time prior to harvest is crucial for the farm management or national agro-food policy. Spectral characteristics provided by satellite based remote sensing have both spatial and temporal resolution which allow crop yields from agricultural fields. The aim of this thesis was to test feasibility of developing crop yield. The study was focused on three major crops in the Czech Republic: spring barely, winter wheat and oilseed rape. The crop yield data were collected from 14 districts that represent regions with more intensive agricultural production and include a variety of climate, topographic and soil conditions. As a main data source for this thesis was series of digital images acquired by MODIS (Moderate Resolution Imaging Spectroradiometr) aboard Terra satellite from 2001-2014 period. Were analyzed two vegetation idices NDVI (Noramized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) from the 16-days composite product with a spatial resolution of 250 m. In most cases, EVI showed higher correlations to the crop yied, which can be explained due to the negative saturation effect of NDVI.

A minute change in human body temperature can get one collapsed permanently. If this is the case with human body, one might wonder what would be the case with Earth. The result is the greenhouse. The main function of the greenhouse gases (GHG’s) is to tap energy from the sun and prevent the heat energy escaping to space, thus sustaining life on earth. Because of increased human activity, industrialization, and deforestation, the concentration of the GHG’s in the atmosphere has increased, resulting in a temperature rise. Considering the effects of temperature rise, caused by the GHG’s, one should know the ways to minimize them. In order to do this, an estimation of the amount of GHG’s is important. The CASA model is one such model that estimate the GHG’s and also the amount of carbon in the atmosphere by estimating the Net Ecosystem Productivity (NEP) and Net Primary Productivity (NPP).

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As the cost of unmanned aerial systems (UAS) and their sensing payloads decrease the practical applications for such systems have begun expanding rapidly. Couple the decreased cost of UAS with the need for increased crop yields under minimal applications of agrochemicals, and the immense potential for UAS in commercial agriculture becomes immediately apparent. What the agriculture community needs is a cost effective method for the field-wide monitoring of crops in order to determine the precise application of fertilizers and pesticides to reduce their use and prevent environmental pollution. To that end, this thesis presents an unmanned aerial system aimed at monitoring a crop's status. The system presented uses a Yamaha RMAX unmanned helicopter, operated by Virginia Tech']s Unmanned Systems Lab (USL), as the base platform. Integrated with helicopter is a dual-band multispectral camera that simultaneously captures images in the visible and near-infrared (NIR) spectrums. The UAS is flown over a quarter acre corn crop undergoing a fertilizer rate study of two hybrids. Images gathered by the camera are post-processed to form a Normalized Difference Vegetative Index (NDVI) image. The NDVI images are used to detect the most nutrient deficient corn of the study with a 5% margin of error. Average NDVI calculated from the images correlates well to measured grain yield and accurately identifies when one hybrid reaches its yield plateau. A secondary test flight over a late-season tobacco field illustrates the system's capabilities to identify blocks of highly stressed crops. Finally, a method for segmenting bleached tobacco leaves from green leaves is presented, and the segmentation results are able to provide a reasonable estimation of the bleached tobacco content per image. / Master of Science

This study computed the Normalized Difference Vegetation Index (NDVI) products derived from NOAA AVHRR, MODIS, and SPOT VGT sensors. NDVI products from different instruments vary in spatial resolution, temporal coverage and spectral range. As a result, multi-sensor NDVI products are rarely used in a single phenological study. In order to evaluate the difference and similarity of NDVI records from the three sensors, I used EPA Eco-region frameworks to determine the average annual Start of Season (SOS) and End of Season (EOS) of Contiguous United States, and analyzed dates among datasets. In addition, I created 1127 sample points within the study area, and compared relationship between SOS/EOS based on land cover. The objectives of this thesis are to: 1) compare multi-sensor NDVI data using phenological models, 2) define a strategy to merge multi-sensor NDVI products to a single phenological product without direct NDVI conversion. The spatial and statistical analysis revealed that the Land Surface Phenology (LSP) measurements retrieved from NDVI time series from different sensors follow linear and positive relationships where compared by either eco-region or sample point. The historical record of AVHRR combined with the modern MODIS and SPOT data provides a critical and reliable perspective on phenological patterns in Contiguous United States area. The success of this study will help LSP by providing understanding of how different instruments can be combined to generate multi-sensor NDVI data for phenology. / Master of Science

Electromagnetic radiation reflectance increases dramatically around 700 nm for vegetation. This increase in reflectance is known as the vegetation red edge. The NDVI (Normalized Difference Vegetation index) is an imaging technique for quantifying red edge contrast for the identification of vegetation. This imaging technique relies on reflectance values for radiation with wavelength equal to 680 nm and 830 nm. The imaging systems required to obtain this precise reflectance data are commonly space-based; limiting the use of this technique due to satellite availability and cost. This thesis presents a robust and inexpensive new terrestrial-based method for identifying the vegetation red edge. This new technique does not rely on precise wavelengths or narrow wavelength bands and instead applies the NDVI to the visible and NIR (near infrared) spectrums in toto. The measurement of vegetation fluorescence has also been explored, as it is indirectly related to the efficiency of photochemistry and heat dissipation and provides a relative method for determining vegetation health. The imaging methods presented in this thesis represent a unique solution for the real time monitoring of vegetation growth and senesces and the determination of qualitative vegetation health. A single, inexpensive system capable of field and greenhouse deployment has been developed. This system allows for the early detection of variations in plant growth and status, which will aid production of high quality horticultural crops. / Master of Science

Land Use Land Cover Change (LULCC) is a major component of global environmental change, which could result in huge impacts on biodiversity, water yield and quality, climate, soil condition, food security and human welfare. Of all the LULCC types, urbanization is considered to be the most impactful one. Monitoring past and current urbanization processes could provide valuable information for ecosystem services evaluation and policy-making. The National Land Cover Database (NLCD) provides land use land cover data covering the entire United States, and it is widely used as land use land cover data input in numerous environmental models. One major drawback of NLCD is that it is updated every five years, which makes it unsatisfactory for some models requiring land use land cover data with a higher temporal resolution. This dissertation integrated a rich time series of Landsat imagery and NLCD to achieve annual urban change mapping in the Washington D.C. metropolitan area by using time series data change point detection methods. Three different time series change point detection methods were tested and compared to find out the optimal one. One major limitation of using the above time series change point detection method for annual urban mapping is that it relies heavily on NLCD, thus the method is not applicable to near-real time monitoring of urban change. To achieve the near real-time urban change identification, this research applied machine learning-based classification models, including random forest and Artificial Neural Networks (ANN), to automatically detect urban changes by using a rich time series of Landsat imagery as inputs. Urban growth could result in a higher probability of flooding by reducing infiltration and evapotranspiration (ET). ET plays an important role in stormwater mitigation and flood reduction, thus assessing the changes of ET under different urban growth scenarios could yield valuable information for urban planners and policy makers. In this study, spatial-explicit annual ET data at 30-m resolution was generated for Virginia Beach by integrating daily ET data derived from METRIC model and Landsat imagery. Annual ET rates across different major land cover types were compared, and the results indicated that converting forests to urban could result in a huge deduction in ET, thus increasing flood probability. Furthermore, we developed statistical models to explain spatial ET variation using high resolution (1m) land cover data. The results showed that annual ET will increase with the increase of the canopy cover, and it would decrease with the increase of impervious cover and water table depth. / Doctor of Philosophy / Motoring past and current urbanization processes is of importance in terms of ecosystem services evaluation and policy-making because urban growth has huge impacts on the environment. First, this dissertation designed and compared three different methods for annual urban change mapping in Washington D.C. metropolitan area by using a rich time series of Landsat imagery and National Land Cover Database (NLCD). Then, machine-learning based classification models were implemented to achieve near real-time urban change identification. Finally, spatially-explicit evapotranspiration (ET) data for Virginia Beach, a case study location, were generated and annual ET rates for major land cover types were compared to assess the urbanization's impacts on ET.

This paper studies the effects of long-term climate change on the dynamics of violent conflict in the Kenyan crisis of 2007-2008. Climate change has been found to worsen livelihood conditions in East Africa, leading to a higher competition for resources and increased intergroup tensions. This, in turn, leads to a higher risk for violent conflict. The findings indicate that geographical areas that were more severely affected by the effects of long-term climate change were more likely to experience eruptions of violence during the 2007-2008 conflict. Even when controlling for other factors thought to influence the outbreak of violent conflict, this relationship continues to hold. The exact nature of the links between the two phenomena is still to be proven, but the findings seem to be relatively robust, providing a solid basis for future research on the often overlooked area of long-term climate change and its effects on violent conflict.

Os ecossistemas costeiros sofrem impactos antrópicos de fontes diversas, entre eles os despejos de efluentes, que podem potencializar o desenvolvimento de produtores primários em costões rochosos resultante do enriquecimento por nutrientes. Ao mesmo tempo, o crescimento dos produtores pode ser controlado pela presença dos herbívoros. No presente estudo buscamos descrever o efeito dos despejos de efluentes sobre o acúmulo de biofilme em costões rochosos, sob diferentes níveis de despejos de efluentes em uma área subtropical (São Paulo, Brasil), bem como o efeito dos efluentes sobre as lapas. Estimamos a biomassa do biofilme in situ, por medidas indiretas de NDVI e por análises taxonômicas de amostras fixadas. A estrutura populacional de lapas foi descrita por contagem e medição do comprimento da concha. Um experimento em campo foi realizado sob presença e ausência de efluentes, bem como presença e ausência de lapas. Observamos que o efeito de efluentes potencializa o acúmulo de biofilme, entretanto não observamos um consumo significativo das lapas sobre o biofilme. O tamanho e densidade de lapas não foram alteradas pelo gradiente de efluentes. Em geral, foi observada uma predominância de diatomáceas em relação às cianobactérias, o que pode diferir da tendência de dominância de cianobactérias verificada em outras regiões. É importante ressaltar a importância de outros pastadores sobre o desenvolvimento de biofilme, não considerados neste estudo, além da alta variabilidade temporal e espacial que as comunidades de biofilme apresentam. Ressaltamos a importância da aplicação de organismos bentônicos como indicadores da qualidade do ambiente. / Coastal ecosystems suffer anthropogenic impacts from many sources such as sewage disposal, which may potencialize de primary productors growth in rocky shores. In the same time, this growth amy be controlled by grazers. In this study we aimed to investigate the biofilm accumulation in rocky shores under different level of sewage disposal in a subtropical area (São Paulo State, Brazil), and its influence on the grazers. The biofilm biomass was estimated in situ indirectly by NDVI measures and taxonomic analysis of fixed samples. The size structure of limpets was described through counting and measurement of the shell length. We also performed a field experiment under presence and ausence of sewage, as presence and ausence of limpets. We observed a sewage effect improve the biofilm accumulation, but the limpets did not have a clear control on the biofilm growth. No clear effect of sewage disposal was verified on the size and density of limpets. In general, we observed a domination of diatoms relative to cianobacterias, which could differ of the trend observed in another sites. It is noteworthy that the possible effects of other grazers on the biofilm were not quantified and the high temporal and spatial variability of biofilm communities. We emphasize the importance of studies that use benthic organisms as environmental quality indicators.