Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-08-23T19:10:00Z No. of bitstreams: 1 ALBERTO CÉSAR DO NASCIMENTO SILVA – DISSERTAÇÃO (PPGECA) 2017.pdf: 2656117 bytes, checksum: 0b2a6d38796702f280814934f96445dc (MD5) / Made available in DSpace on 2018-08-23T19:10:00Z (GMT). No. of bitstreams: 1 ALBERTO CÉSAR DO NASCIMENTO SILVA – DISSERTAÇÃO (PPGECA) 2017.pdf: 2656117 bytes, checksum: 0b2a6d38796702f280814934f96445dc (MD5) Previous issue date: 2017-08-28 / O sensoriamento remoto possibilita o acompanhamento da cobertura do solo a partir de índices de vegetação. Análises das tendências de longo prazo da cobertura do solo são, geralmente, executadas com sensores de alta resolução temporal e baixa resolução espacial. No entanto, em regiões como a Semiárida, a compreensão da dinâmica da cobertura do solo em escalas locais é muito importante, particularmente devido à ação humana. O uso de imagens de satélite com média resolução espacial permite identificar alterações na escala da ação humana no bioma Caatinga. Através da abordagem aplicada a este trabalho, é possível identificar o período em que ocorreram tais alterações. Neste trabalho, utilizou-se o teste de tendência de Mann-Kendall para avaliar o desempenho ou a capacidade dos indicadores biofísicos EVI (Enhanced Vegetation Index); e albedo de superfície para identificar alterações na cobertura do solo. Foram também identificados, através de estimativas de tendências temporais, as áreas e períodos com possíveis variações na cobertura do solo em agrupamentos temporais de 5 anos. Utilizaram-se 162 imagens LANDSAT 5, 7 e 8 no período de 1986 a 2015, da Bacia do Rio Taperoá, localizada no semiárido do estado da Paraíba. Embora o EVI seja o indicador biofísico mais amplamente utilizado para avaliar alterações na cobertura do solo, o albedo de superfície mostrou-se mais sensível ao indicar prováveis áreas alteradas bem como em apontar em qual período tal mudança ocorreu. As avaliações executadas fornecem um ferramental para o desenvolvimento de sistemas de monitoramento remoto e gestão de ecossistemas, podendo ser usado para identificar regiões para intervenções e observações mais detalhadas. / Remote sensing allows monitoring of land cover from vegetation indexes. Analyses of longterm trends in land´s cover are generally performed with high temporal resolution´s and low spatial resolution´s sensors. However, in heterogeneous regions such as the Brazilian Semi-arid Region, understanding the dynamics of land cover at local scales is very important, particularly in relation to the scale of human action. The medium spatial resolution allows identifying alterations in the scale of small rural properties and it is compatible with human action scale in Caatinga´s biome. The approach applied to this work makes possible to measure the period in which such changes occurred. In this work, the Mann-Kendall trend´s test was used to evaluate the performance or the capacity of the biophysical indicators EVI (Enhanced Vegetation Index); and surface Albedo to identify changes in soil cover. It was possible, as well, to identify, through estimates of temporal trends, areas and periods with possible variations in soil cover in 5-year temporal groupings. In total, 162 LANDSAT images were used, in the period from 1986 to 2015, focusing on Taperoá´s river basin, in the State of Paraíba, Brazilian semiarid region. Although EVI is the biophysical indicator most widely used to assess changes in soil cover, surface Albedo has been more sensitive in indicating probable areas altered as well as in indicating in which period such a change occurred. The evaluations provide tools for the development of remote monitoring and ecosystem management systems and can be used to identify regions of priority for interventions and observations that are more detailed.

Due to the high economic and social importance of the common bean in Brazil, still has doubts regarding the manner mode and use of topdressing nitrogen fertilizer aiming to obtain high yields, concern about the excessive use of nitrogenous fertilizers, associated with the development of new tools to assess quickly and accurately the nutritional status of crops.TIn this sense, the study aimed to evaluate the use of Sufficiency Chlorophyll Index (SCI) as a tool to identify the necessity for application and estimate the top dress nitrogen rate (N) should be applied, to obtain the common bean yield and its yield components and monitor the behavior of the index Falker chlorophyll (IFC), the normalized difference vegetation index (NDVI), the N content in the leaf tissue and available N in the soil with different N rates application and nitrogen topdressing application timing . The experimental design was randomized blocks in a factorial arrangement of 8 x 5 x 4 (N rates x topdressing application timing x evaluation periods), with three repetitions. N rates evaluated were: 0, 40, 80, 120, 160, 200, 240 and 280 kg ha-1, topdressing application. The evaluation periods were: 15, 25, 35 and 45 days after emergence (DAE). The application timing were as follows: E1: application of N rates on seeding; E2: application of N rates at 10 DAE; E3: application of N rates when the SCI ≤ 95%; E4: application of N rates at 20 DAE and E5: application of N rates when SCI ≤ 90%. From the results obtained it was concluded that the SCI was efficient to identify differences in IFC levels of 15 to 40 DAE, however, it was not possible to estimate the N rates that should be applied according to the SCI, because the yield showed no significance differences due to N rates and application timing. The mean yield was 2,061 kg ha-1. With increasing of N rates occurs linear increase in the number of pods plant-1 and a linear decrease in the number of grain legume-1. Soil mineral N content showed linear increase with increasing N rates, but were not showed the same behavior to IFC, NDVI and leaf tissue N values, which showed low significant variation depending of the N rates. NDVI increased over DAE, reaching the highest value between 35 and 45 DAE and in 45 DAE the IFC values did not differ among treatments. / Devido à elevada importância econômica e social do feijoeiro para o Brasil, ainda persistem dúvidas quanto a o modo e uso de fertilizante nitrogenado em cobertura visando à obtenção de altas produtividades, a preocupação com o uso excessivo de fertilizantes nitrogenados, associado ao desenvolvimento de novas ferramentas para avaliar o estado nutricional das culturas de maneira rápida e precisa. Nesse sentido este estudo tem como objetivos avaliar a utilização do Índice de Suficiência de Clorofila (ISC) como ferramenta para identificar a necessidade de aplicação e estimar qual a dose de nitrogênio (N) a ser aplicada em cobertura, obter a produtividade do feijoeiro comum e seus componentes de rendimento e monitorar o comportamento do índice de clorofila falker (ICF), do índice de vegetação por diferença normalizada (NDVI), do teor de N no tecido foliar e do N mineral no solo, com a aplicação de diferentes doses de N e épocas de aplicação do N em cobertura. O delineamento experimental utilizado foi o de blocos ao acaso, num arranjo fatorial de 8 x 5 x 4 (doses de N x épocas da aplicação do N em cobertura x épocas de avaliação), com três repetições. As doses de N avaliadas foram de 0, 40, 80, 120, 160, 200, 240 e 280 kg ha-1, aplicados em cobertura. As épocas de avaliação foram aos 15, 25, 35 e 45 dias após a emergência (DAE). As épocas de aplicação do N foram os seguintes: E1: aplicação das doses no dia da semeadura; E2: aplicação das doses de N aos 10 DAE; E3: aplicação das doses de N quando o ISC ≤ 95%; E4: aplicação das doses de N aos 20 DAE e E5: aplicação das doses de N quando ISC ≤ 90%. A partir dos resultados obtidos concluiu-se que o ISC foi eficiente para identificar diferenças nos teores de ICF dos 15 aos 40 DAE, porem não foi possível estimar qual a dose de N que deveria ser aplicada em função dos ISC, pois a produtividade não apresentou diferença para as fontes de variação dose e manejo, a média da produtividade foi de 2.061 kg ha1. Com o incremento das doses de N ocorre um aumento linear do número de legumes planta-1 e uma redução linear do número de grãos legume-1. O Teor de N mineral no solo apresentou incremento linear com o aumento das doses, mas não repercutiu em mesmo comportamento das variáveis ICF, NDVI e N no tecido foliar, os quais apresentam variação pouco significativa em função das doses. O NDVI aumentou com o passar dos DAE, atingindo valor mais elevado entre 35 e 45 DAE e aos 45 DAE o ICF não diferiu entre os tratamentos.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The objective of this study was to test the potential of satellite imagery, TM/Landsat 5, for discrimination of plantations of different ages of Eucalyptus dunnii and Eucalyptus urograndis and correlate the volume of these plantations, obtained from forest inventory, with the spectral responses. The values of spectral reflectance of the surface of the original images were recovered and after image geocoding the values of reflectance were extracted in six spectral bands TM sensor (B1, B2, B3, B4, B5 and B7) stand for the four groups studied: E. dunnii age 3 and age 5 and E. urograndis to 2.2 years and 4.2 years of age. In addition to the spectral bands vegetation indices SR, NDVI, SAVI_0.5, SAVI_0.25, MVI and GNDVI were used. To evaluate the behavior of the spectral variables for each stand, it was performed an analysis of principal components which, for the year 2009 , the variables B2 , B3 , GNDVI , B4 , B5 and B1 , were, in descending order , the most significaqnt. And for the year 2011, the most significant values were the SAVI_0.25, SAVI_0.5, B4, SR, MVI, NDVI and B2 variables, in descending order. From the discriminant analysis data of three discriminant functions (λ) to separate the four groups were generated. The structural attributes with better discriminatory power (in order of importance) were: SAVI_0.25, SAVI_0.5, B5, MVI, B7, B1 and B3. The discriminant model generated showed that functions correctly classified 100% of the cases in their predicted groups, revealing that the spectral variables were good predictors for distinguishing plantations. Correlation analysis between the biophysical variable (timber volume) was not significant for the planting of E. dunnii at 3 years old. For the planting of E. dunnii at 5 years was the most correlated variable B2 (r= -0.55). The B4 was the variable most strongly correlated with the volume in plantations of E. urograndis at 2.2 years old (r= 0.75) followed by the index Ln (SAVI_0.5) with r= 0.72. For E. urograndis at 4.2 years of age, the variables with the highest correlation were B2 (r= 0.67), followed by Ln (SAVI_0.5) with r= 0.63. From the correlation coefficients obtained, equations to estimate the volume were modeled. For the settlement of E. dunnii at 5 years, the best fitted equation explained 48% of the variability in the volume. The population of E. urograndis at 2.2 years obtained the best results, in which 57% of the variability was explained by the volume of spectral variables. The population of E. urograndis at 4.2 years obtained the lowest results, where only 45% of the variability was explained by the volume spectral variables. It was concluded that the methodology can be used to aid in species identification from satellite images and further studies should be conducted to estimate volume from spectral variables. / O objetivo deste trabalho foi testar o potencial de imagem de satélite, TM/Landsat 5, na discriminação de plantios de diferentes idades de Eucalyptus dunnii e Eucalyptus urograndis e, correlacionar o volume desses plantios, obtidos a partir de inventário florestal, com as respostas espectrais. Os valores de reflectância espectral de superfície foram recuperados das imagens originais e após o georreferenciamento da imagem foram extraídos os valores das reflectâncias em seis bandas espectrais do sensor TM (B1, B2, B3, B4, B5 e B7) para os quatro povoamentos estudados: E. dunnii aos 3 anos e aos 5 anos e E. urograndis aos 2,2 anos e 4,2 anos de idade. Além das bandas espectrais foram utilizados os índices de vegetação SR, NDVI, SAVI_0,5, SAVI_0,25, MVI e GNDVI. Para avaliar o comportamento das variáveis espectrais para cada povoamento foi realizada uma análise de componentes principais em que, para o ano de 2009, as variáveis B2, B3, GNDVI, B4, B5 e B1, foram, em ordem decrescente, as mais significativas. E para o ano de 2011, os valores mais significativos corresponderam as variáveis SAVI_0,25, SAVI_0,5, B4, SR, MVI, NDVI e B2, em ordem decrescente. A partir da análise discriminante dos dados foram geradas três funções discriminantes (λ) para separação dos quatro grupos. Os atributos estruturais com melhor poder de discriminação (em ordem de importância) foram: SAVI_0,25, SAVI_0,5, B5, MVI, B7, B1 e B3. O modelo discriminante gerado demonstrou que as funções classificaram 100% dos casos em seus grupos preditos, revelando que as variáveis espectrais foram boas preditoras para distinguir os plantios. A análise de correlação entre a variável biofísica (volume de madeira) não foi significativa para o plantio de E. dunnii aos 3 anos de idade. Para o plantio de E. dunnii aos 5 anos a variável mais correlacionada foi B2 (r= -0,55). A B4 foi a variável com maior correlação com o volume nos plantios de E. urograndis aos 2,2 anos de idade (r= 0,75) seguido do índice Ln (SAVI_0,5) com r= 0,72. Para E. urograndis aos 4,2 anos de idade, as variáveis com maior correlação foram B2 (r= 0,67), seguido de Ln (SAVI_0,5) com r= 0,63. A partir dos coeficientes de correlação obtidos, foram modeladas equações para estimativa do volume. Para o povoamento de E. dunnii aos 5 anos, a melhor equação ajustada explicou 48% da variabilidade do volume. O povoamento de E. urograndis aos 2,2 anos obteve os melhores resultados, em que 57% da variabilidade do volume foi explicada pelas variáveis espectrais estudadas. O povoamento de E. urograndis aos 4,2 anos obteve os menores resultados, em que apenas 45% da variabilidade do volume foi explicada pelas variáveis espectrais. Conclui-se que a metodologia empregada pode ser utilizada para auxiliar na identificação de espécies a partir de imagens de satélite e novos estudos devem ser realizados para a estimativa de volume a partir de variáveis espectrais.

Orientador: Mara de Andrade Marinho Weill / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-05T13:28:12Z (GMT). No. of bitstreams: 1 Lourenco_LeonardoSenede_M.pdf: 607870 bytes, checksum: fe4db0d68393c2258c9d6605c0faa233 (MD5) Previous issue date: 2005 / Resumo: O desenvolvimento de sensores orbitais de alta resolução espacial e espectral e a perspectiva de maior periodicidade na obtenção de imagens tem incentivado a aplicação crescente de técnicas de sensoriamento remoto no estudo de características espectrais das culturas relacionadas com seu potencial de produção. Os chamados índices de vegetação têm sido utilizados como critérios para estimar a resposta espectral da cultura e, indiretamente, sua produtividade. A resposta espectral é uma medida do vigor vegetativo da cultura, sendo afetada por fatores ambientais, do manejo e da planta. O presente estudo teve por objetivo central estudar a influência de atributos do solo e da planta na variação da resposta espectral da cultura da cana-de-açúcar, medida por meio do índice de vegetação da diferença normalizada (NDVI), aplicando métodos estatísticos uni e multivariados. O estudo foi realizado em um talhão de produção comercial de cana-de-açúcar de cerca de 26 ha, no município de Araras (SP), entre as coordenadas 47º19¿02¿ e 47º19¿26¿ W e 22º21¿53¿ e 22º22¿12¿ S. A lavoura foi implantada em setembro de 1997 com a variedade SP80-1842, precoce, de hábito decumbente e acamamento regular. O delineamento amostral constou de uma grade regular, composta por 67 pontos amostrais georreferenciados e espaçados de 50 m nas direções X e Y, de onde foram extraídas amostras de solo (camadas 0- 30 cm e 30-60 cm) e foliares. As amostras de solo foram extraídas em setembro de 2000 e de 2001, logo após a colheita. As amostras foliares foram extraídas durante a fase de desenvolvimento vegetativo da cultura, no mês de janeiro de 2001 e de 2002. Os anos agrícolas estudados correspondem ao 4º (2000/01) e 5º (2001/02) cortes. Foram avaliados atributos granulométricos e de fertilidade do solo e os teores foliares de macro e micronutrientes (variáveis preditoras). O índice de vegetação NDVI (variável predita) foi calculado a partir de imagens LANDSAT 7, sensor ETM+, obtidas em duas épocas durante a fase de desenvolvimento vegetativo da cultura. Para análise da influência da variação dos atributos edáficos e foliares na variação observada no NDVI foram empregados os métodos estatísticos referidos por análise exploratória, análise de agrupamentos, análise de componentes principais e análise de regressão linear múltipla, adotando-se o método stepwise para seleção de variáveis e ajuste dos modelos. Foram ajustados dois modelos de regressão linear múltipla. O modelo de regressão ajustado aos dados de 2000/01 explicou 30,8% da variação observada da resposta espectral em função da matéria orgânica (M.O., 0-30 cm) e dos teores foliares de fósforo (P, Planta) e de ferro (Fe, Planta). A inclusão desses atributos no modelo pode ser interpretada no caso da matéria orgânica pela similaridade com o NDVI, conforme resultado da análise de agrupamento; no caso do ferro por sua representatividade como integrante do 1º componente principal, e no caso do fósforo por sua baixa correlação com os demais atributos analisados, conforme indicado pela análise exploratória. O modelo de regressão ajustado aos dados de 2001/02 explicou 29,8% da variação observada da resposta espectral em função dos teores de cobre (Cu) e ferro (Fe) na camada 0-30 cm e do teor de enxofre (S-SO4) na camada 30-60 cm. Interpreta-se a inclusão desses atributos no modelo no caso do enxofre por sua representatividade como integrante do 1º componente principal e do ferro como integrante do 3º componente. No caso do cobre, sua inclusão deve estar baseada na média correlação com a resposta espectral (NDVI) e baixa correlação com os demais atributos do modelo, de acordo com os dados da análise exploratória. Os resultados obtidos permitiram comprovar a hipótese do trabalho. Parte da variação observada da resposta espectral na área de estudo pôde ser explicada pela variação de atributos do solo (fator de produção) e da planta. No entanto, entende-se que a capacidade de explicação dos modelos poderia ter sido maior caso tivessem sido incluídas na análise outras variáveis, sobretudo climáticas, bem como, variáveis edáficas que permitissem avaliar o efeito de fatores como compactação e resistência à penetração, tendo em vista se tratar de solos argilosos e muito argilosos / Abstract: The development of multispectral sensors with high spatial and spectral resolutions and the perspective of greater regularity in the attainment of the images have stimulated the increasing application of the remote sensing techniques in the study of spectral response patterns of the crops relating with their potential of production. The spectral response pattern is a measure of the vegetative vigor of a crop, being affected by genotype, management and environmental factors. The main objective of the present research was to study the influence of selected soil and plant attributes in the observed variation of the spectral response pattern of the sugarcane crop, measured by means of the normalized difference vegetation index (NDVI), applying multivariate statistics methods. The study was developed in a commercial area (26 ha) of sugarcane production in Araras (SP), between the coordinates 47º19'02 "and 47º19'26" W and 22º21'53"and 22º22'12" S. The crop was installed in September/1997 with the variety SP80-1842. The experimental delineation was a regular grid, composed by 67 points of sampling, georeferenced, and spaced of 50 m in the X and Y directions, from where had been extracted the plant (leaves) and the soil samples (0-30 cm and 30-60 cm). The soil samples were extracted in September (2000 and 2001), after the harvest. The plants were sampled during the phase of vegetative development of the crop, in January (2001 and 2002). The attributes evaluated were grain sized and fertility attributes (soils) and nutrient contents in leaves (plant). The vegetation index NDVI was calculated from LANDSAT 7, sensor ETM+ images. The statistics methods of analysis have included exploratory analysis, cluster analysis, principal component analysis (PCA), and multiple regression analysis, using the stepwise criterion for selection of the variables and model adjustment. Two linear multiple regression models have been adjusted. The first model (2001/02) could explain 30,8% of the observed variation of NDVI as a function of the soil organic matter (M.O., 0-30 cm) and of the phosphorus (P, Plant) and of the iron (Fe, Plant) contents in leaves. The inclusion of these attributes in the model can be interpreted with basis on the case of the soil organic matter for its similarity with the NDVI, as indicated by cluster analysis. In the case of the iron content its inclusion could be interpreted for its significance as integrant of the first component in PCA, and in the case of the P content with basis on its low correlation with the all others attributes, as indicated for the exploratory analysis. The second regression model (2001/02) could explain 29,8% of the observed variation of NDVI as a function of soil contents of copper (Cu) and iron (Fe) in the first layer (0-30 cm) and the sulphur content (S-SO4) in the second layer (30-60 cm). The inclusion of these attributes in the second model can be interpreted in the case of the S-SO4 content according its significance as integrant of first component in PCA, and the iron content according its significance as integrant of third component in PCA. In the case of copper, its inclusion must be explained with basis in its average correlation with the NDVI and small correlation with the all other attributes of the model, as indicated for the exploratory analysis. The results have permitted to accept the hypothesis of the work. Part of the observed variation of the spectral response pattern in the study area could be explained by the local variation of some soil (production factor) and plant attributes. However, that the capacity of explanation of the two adjusted models could have been better if another variables, in particular the ones related with climate and soil hardness, have been included in the analysis / Mestrado / Planejamento e Desenvolvimento Rural Sustentável / Mestre em Engenharia Agrícola

Orientadores: Rubens Augusto Camargo Lamparelli, Jansle Vieira Rocha / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola / Made available in DSpace on 2018-08-12T21:23:17Z (GMT). No. of bitstreams: 1 Ramme_FernandoLuizProchnow_D.pdf: 9393591 bytes, checksum: a6d5183861f5be0ab0ed23ba7a8838da (MD5) Previous issue date: 2008 / Resumo: O objetivo do trabalho foi avaliar a relação entre as fases do crescimento da cana-de-açúcar com as formas de curvas do perfil temporal do Índice de Vegetação por Diferença Normalizada - NDVI, obtidas a partir do sensor remoto orbital MODerate-resolution Imaging Spectroradiometer - MODIS, na região de estudo. A avaliação desta relação é realizada utilizando-se técnicas de sensoriamento remoto para a geração do perfil temporal do NDVI, ao longo do ciclo de desenvolvimento fenológico da cana-soca, nas maturações Precoce, Média e Tardia. Os talhões de cana-soca analisados foram agrupados de acordo com a variedade, solo, data de plantio e corte, e contigüidade. A visualização gráfica das formas de curvas analisadas é realizada através de aplicativo, desenvolvido neste trabalho na linguagem de programação Java, e do sistema gerenciador de banco de dados PostgreSQL. O aplicativo realiza a filtragem de ruídos presentes nas imagens, composição na resolução temporal de 8 dias, através dos dados da banda de controle de qualidade do produto MOD09Q1, realiza a eliminação de valores discrepantes ao longo do perfil temporal do NDVI para a safra analisada, corrige as influências dos períodos de corte e rebrota da cana-soca, e propicia a suavização da forma de curva através do filtro Savitzky-Golay. Três janelas temporais de monitoramento da cultura são apresentadas neste trabalho. Cada janela temporal é determinada em função do tipo de maturação da cultura, do coeficiente de cultura (Kc) ao longo do ciclo fenológico da cana-soca e do comportamento na evolução do perfil temporal do NDVI. Concluiu-se que na região de estudo, diferentes maturações são caracterizadas por diferentes formas de curvas do perfil temporal do NDVI / Abstract: The objective of the work was to evaluate the relationship among the phases of the growth of the sugarcane with the forms of curves of the Normalized Difference Vegetation Index - NDVI temporal profile, obtained from remote sensor orbital MODerate-resolution Imaging Spectroradiometer - MODIS, in the study area. The evaluation of this relationship is accomplished by using of the techniques of remote sensing to generate the NDVI profile, along the phenological development phase of stubble-cane, in the Carly, Medium and Late maturations. The fields of stubble-cane analyzed were contained in agreement with the variety, soil, planting date and cut, and proximity. The graphic visualization of curves shape analyzed is accomplished through application, developed in this work in the Java programming language, and of the PostgreSQL system database manager. The application accomplishes the filtering of present noises in the images, composition in the temporal resolution of 8 days, through the data of the band of quality control of the MOD09Q1 product, accomplishes the elimination of outliers along the NDVI temporal profile for the culture analyzed, corrects the influences of the cut periods and regrowth of the stubble-cane, and propitiates the smoothing in the curve shape through the filter Savitzky-Golay. Three temporal windows of culture monitoring are presented in this work. Each temporal window is determined in function of the type of crop maturation, of the culture coefficient (Kc) along the phenological development phase of stubble-cane and of the behavior in the evolution of the NDVI profile. It concluded that in the study area, different maturations are characterized by different forms of NDVI profile curves / Doutorado / Planejamento e Desenvolvimento Rural Sustentável / Doutor em Engenharia Agrícola

Uma das alternativas bastante abordada na literatura para a melhoria do gerenciamento da adubação nitrogenada nas culturas é o sensoriamento remoto, tendo destaque a utilização de sensores espectrais na região do visível e infravermelho. Neste trabalho, buscou-se estabelecer as relações existentes entre variações no teor foliar de nitrogênio (TFN) e a resposta espectral da folha de cana-de-açúcar, utilizando um sensor hiperespectral, com avaliações em três áreas experimentais do estado de São Paulo, com diferentes solos e variedades. Cada experimento foi alocado em blocos ao acaso, com parcelas subdividas e quatro repetições. Foram aplicadas doses de 0, 50, 100 e 150 kg de nitrogênio por hectare. A análise espectral foi realizada na folha \"+1\" em laboratório, sendo coletadas 10 folhas por subparcela, estas foram posteriormente submetidas a análise química para o TFN. Observou-se que existe correlação significativa entre o TFN e as variações na resposta espectral da cana-de-açúcar, sendo que a região do verde e de transição entre o vermelho e o infravermelho próximo (\"red-edge\") foram as mais consistentes e estáveis entre as áreas em estudo e safras avaliadas. A análise de componentes principais permitiu reforçar estes resultados, uma vez que as pontuações (\"scores\") dos componentes que apresentaram correlações significativas com o TFN, tiveram maiores pesos (\"loadings\") nas regiões espectrais citadas anteriormente. A partir das curvas espectrais foram também realizados os cálculos dos índices de vegetação já descritos em literatura, e estes submetidos a análise de regressão simples para predição do TFN, sendo os modelos calibrados com dados da safra 2012/13 e validados com os dados da safra 2013/14. Índices espectrais calculados com a combinação dos comprimentos de onda do verde e/ou \"red-edge\" com comprimentos de onda do infravermelho próximo tiveram bom desempenho na fase de validação, sendo que os cinco mais estáveis foram os índices BNi (500, 705 e 750 nm), GNDVI (550 e 780 nm), NDRE (790 e 720 nm), RI-1db (735 e 720 nm) e VOGa (740 e 720 nm). A variedade SP 81 3250 foi cultivada nas três áreas experimentais, o que permitiu a comparação do potencial de modelos calibrados por área, com um modelo generalista para uma mesma variedade cultivada em diferentes condições edáficas. Observou-se que embora o modelo generalista apresente parâmetros estatísticos significativos, existe redução expressiva da sensibilidade de predição quando comparado aos modelos calibrados por área experimental. Empregou-se também nesta pesquisa a análise de regressão linear múltipla por \"stepwise\" (RLMS) que gerou modelos com boa precisão na estimativa do TFN, mesmo quando calibrados por área experimental, independentes da variedade, utilizando de 5 a 6 comprimentos de onda. Concluímos com a presente pesquisa que comprimentos de onda específicos estão associados a variação do TFN em cana-de-açúcar, e estes são reportados na região do verde (próximos a 550 nm) e na região de transição entre os comprimentos de onda do vermelho e infravermelho próximo (680 a 720 nm). Apesar da baixa correlação entre a região do infravermelho próximo com o TFN, índices de vegetação calculados a partir destes comprimentos de onda ou a inserção destes na geração de modelos lineares foram importantes para melhorar a precisão da predição. / An alternative method, quite cited in literature to improve nitrogen fertilization management on crops is the remote sensing, highlighted with the use of spectral sensors in the visible and infrared region. In this work, we sought to establish the relationship between variations in leaf nitrogen content and the spectral response of sugarcane leaf using a hyperspectral sensor, with assessments in three experimental areas of São Paulo state, Brazil, with evaluations in different soils and varieties. Each experimental area was allocated in randomized block, with splitted plots and four repetition, hence, receiving doses of 0, 50, 100 and 150 kg of nitrogen per hectare. Spectral analysis was performed on the \"+1\" leaf in laboratory; we collected 10 leaves per subplots; which were subsequently subjected to chemical analysis to leaf nitrogen content determination. We observed a significant correlation between leaf nitrogen content and variations in sugarcane spectral response, we noticed that the region of the green light and red-edge were the most consistent and stable among the studied area and the crop seasons evaluated. The principal component analysis allowed to reinforce these results, since that the scores for principal components showed significant correlations with the leaf nitrogen content, had higher loadings values for the previous spectral regions mentioned. From the spectral curves were also performed calculations of spectral indices previously described in literature, being these submitted to simple regression analysis to direct prediction of leaf nitrogen content. The models were calibrated with 2012/13 and validated with 2013/14 crop season data. Spectral indices that were calculated with green and/or red-edge, combined with near-infrared wavelengths performed well in the validation phase, and the five most stable were the BNi (500, 705 and 750 nm), GNDVI (550 and 780 nm), NDRE (790 and 720 nm), IR-1dB (735 and 720 nm) and VOGa (740 and 720 nm). The variety SP 81 3250 was cultured in the three experimental areas, allowing to compare the performance of a specific site model with a general model for the same variety growing on different soil conditions. Although the general model presents meaningful statistical parameters, there is a significant reduction in sensitivity to predict leaf nitrogen content of sugarcane when compared with specific site calibrated models. We also used on this research the stepwise multiple linear regression (SMLR) that generated models with good precision to estimate the leaf nitrogen content, even when models are calibrated for an experimental area, regardless of spectral differences between varieties, using 5 to 6 wavelengths. This study shows that specific wavelengths are associated with variation in leaf nitrogen content of sugarcane, and these are reported in the region of green (near to 550 nm) and red-edge (680 to 720nm). Despite the low correlation observed between the infrared wavelengths to the leaf nitrogen content of sugarcane, vegetation indices calculated from these wavelengths, or its insertion on linear models generation were important to improve prediction accuracy.

Made available in DSpace on 2014-08-20T13:44:45Z (GMT). No. of bitstreams: 1 dissertacao_felipe_nobre.pdf: 1392556 bytes, checksum: d4e08f0635d94bd71a605aee76674bfe (MD5) Previous issue date: 2010-10-24 / The objective of this study was to look into the viability of using the images acquired by the Moderated Orbital resolution Imaging Spectroradiometer (MODIS) sensor in order to determining the period of occurrence of phenological stages in order to assist determining the best conducive to harvesting of seed rice. The study area consisted of 12 farms located in the municipalities of Arroio Grande and Rio Grande - RS, of which we had information regarding to sowing, V4, R1, R6 and harvest dates. The delimitation of the field crops was performed by geodetic coordinates obtained by a GPS navigation receiver, aided by medium spatial resolution images from Landsat-5 Thematic Mapper (TM) sensor. In order to generate the spectro-temporal profiles were used daily images from MODIS sensor products MOD09GQ (Terra satellite) and MYD09GQ (Aqua satellite) with 250m spatial resolution, turned in the Enhanced Vegetation Index 2 (EVI2), ranging from before sowing to after harvest. Daily images from Terra and Aqua satellites were composited in images containing the maximum EVI2 for each day. Then we excluded from the analysis the composite images with cloud cover noise contamination and those showing values significantly discrepant with those of adjacent days. The temporal profiles of EVI2 for each crop field were associated with the dates of sowing, V4, R1 and R6 phenological stages and harvesting of crops fields. The EVI2 spectro-temporal profile for paddy rice presented considerable increases around the V4 stage, reaching its highest values around the R6 stage and then begin to decrease even after harvesting. However, we observed a wide range of EVI2 values for each developmental stage analized and the harvest date for different crops fields. Thus, in this study we could not establish reliable parameters that indicate the possibility of using daily images from MODIS as a single indicator for determining both phenological stages and most propitious time for rice harvesting. However, it is possible to monitor the temporal profile EVI2 of irrigated rice fields, which can be used as auxiliary data to approximately determine the crop phonological stage, since cloud free images are available. / O objetivo deste trabalho foi analisar a viabilidade da utilização das imagens adquiridas pelo sensor orbital MODerated resolution Imaging Spectroradiometer (MODIS) na determinação do período de ocorrência dos estádios fenológicos de modo a facilitar a identificação do ponto de maturidade fisiológica e do momento mais propício à colheita de lavouras de sementes de arroz irrigado. A área de estudo constitui-se de 12 talhões situados nos municípios de Arroio Grande e Rio Grande RS, das quais se dispunha de informações das datas de semeadura, dos estádios fenológicos V4, R1, R6 e de colheita. A delimitação das lavouras foi realizada por meio de coordenadas geodésicas obtidas por um receptor GPS de navegação, auxiliadas por imagens de média resolução espacial do sensor TM do satélite Landsat 5. Na geração dos perfis espectro-temporais foram utilizadas imagens diárias do sensor MODIS produtos MOD09GQ (satélite Terra) e MYD09GQ (satélite Aqua), com resolução espacial de 250 metros, transformadas no índice de vegetação EVI2 (Enhanced Vegetation Index 2), abrangendo desde o período anterior a semeadura até o que precede a colheita. A partir das imagens diárias Terra e Aqua foram geradas imagens compostas contendo o valor máximo do EVI2 para a média de cada lavoura, em cada dia. Posteriormente, foram eliminadas da análise as imagens compostas contaminadas pela presença de nuvens e/ou ruídos e aquelas apresentando valores consideravelmente discrepantes às dos dias adjacentes. Aos perfis temporais do EVI2 foram associadas as informações sobre as datas de semeadura, dos estádios V4, R1, R6 e de colheita das lavouras. O perfil espectrotemporal sob a forma do EVI2 para a cultura do arroz irrigado apresenta-se com acréscimos consideráveis dos valores em torno do estádio V4, alcançando os valores mais altos por volta do estádio R6 que em seguida começam a decrescer até mesmo após a colheita da lavoura. Entretanto, observou-se grande amplitude de valores de EVI2 para cada estádio fenológico analisado e para a data de colheita, para as diferentes lavouras. Desta forma, neste estudo, não foi possível estabelecer parâmetros confiáveis que indiquem a possibilidade da utilização das imagens diárias do MODIS como único indicador para determinação tanto dos estádios fenológicos estudados quanto do momento mais propício à colheita de lavouras de arroz irrigado. Entretanto, é possível monitorar o perfil temporal do EVI2 das lavouras de arroz irrigado, que pode ser utilizado como ferramenta auxiliar para se determinar o provável estádio fenológico da cultura, desde que se disponham imagens livres de nuvens.

The use of Normalized Difference Vegetation Index (NDVI) time series over the last decades has increased our understanding of vegetation change dynamics from global to regional scale through quantitative analysis of inter-annual trends in NDVI and climatological parameters (rainfall and temperature). Change in land cover induced by human activities such as livestock grazing and deforestation for large-scale farming (subsistence and mechanized) has influenced the ecological pattern of the Guinea savannah region (GSR) of Nigeria, thereby resulting in loss of biodiversity and changes in vegetation cover. In the context of the GSR of Nigeria where agriculture still plays a major role in people’s economy, it is important to identify the relationship between climatic variables, vegetation productivity and human activities which can be used to understand the on-going transition processes. This study, therefore, examines the spatial and temporal relationship between NDVI and climate parameters, land use land cover change (LULCC) and the perspective of local people on vegetation change dynamics in the study region. In order to do this, bi-monthly NDVI3g time series datasets from Global Inventory Modeling and Mapping Studies (GIMMS), monthly rainfall datasets from Tropical Applications of Meteorology Satellite (TAMSAT), monthly temperature datasets from Climate Research Unit (CRU), national land use land cover (LULC) data of Nigeria from Forestry Management Evaluation & Coordination Unit (FORMECU), global land cover datasets from European Space Agency, Landsat imagery and socio-economic field data collection were used in order to understand vegetation change dynamics across the Guinea savannah regions of Nigeria. Time series analysis (TSA) was applied to both NDVI and climate data used in order to examine the temporal dynamics of vegetation cover change and to detect NDVI-climate relationship during the period from 1983 through 2011. Both parametric and non-parametric statistical models were employed for the assessment of long-term inter-annual trend on the decomposed time series datasets for the whole region (Guinea savannah region) and selected locations. In addition to the TSA, harmonic regression analysis was performed on NDVI and rainfall datasets in order to examine change in seasonality and phyto-phenological characteristics of vegetation. Detection of change in land use and land cover was done by extracting information from existing land cover datasets (ancillary datasets). CLASlite was used for the assessment of the extent of deforestation, while linkage between remotely sensed data and social science was carried out via field surveys based on questionnaires in order to understand the drivers of vegetation change. The study reveals that about 90 % of the Guinea savannah region show positive NDVI trends which indicate greening over time, while about 10 % of the region shows negative trends. This greening trends are closely related to regions where intensive agriculture is being practiced (also along inland valleys) while regions with negative trends show significant loss in woodlands (forest and shrublands) as well as herbaceous vegetation cover due to over-grazing by agro-pastoralism. The result confirms that there is a good relationship (statistically significant positive correlation) between rainfall and NDVI both on intra-annual and inter annual time scale for some selected locations in the study region (> 65 %), while negative statistical correlation exists between NDVI and temperature in the selected locations. This implies that vegetation growth (productivity) in the region is highly dependent on rainfall. The result of the harmonic regression analysis reveals a shift in the seasonal NDVI pattern, indicating an earlier start and a more prolonged growing season in 2011 than in 1983. This study proves significant change in LULC with evidence of an increase in the spatial extent of agricultural land (+ 30 %) and loss of woodlands (- 55 %) between 2000 and 2009 for Kogi State. The results of the socio-economic analysis (people’s perception) highlight that vegetation change dynamics in the study region are the resultant effects of increased anthropogenic activities rather than climatic variability. This study couples data from remote sensing and ground survey (socio-economics) for a better understanding of greening trend phenomena across the Guinea savannah region of Nigeria, thus filling the gap of inadequate information on environmental condition and human perturbation which is essential for proper land use management and vegetation monitoring.

Magister Artium - MA / Climate has been changing significantly around the globe; hence climate variability is of great interest to researchers. The changes in climate have caused variances in rainfall and temperature, both elements of paramount importance in farming, whether commercial or communal farming. As these fluctuations in temperature and rainfall occur, they cause direct impacts on different livelihoods, fauna and flora. The aim of this thesis is to investigate the human management responses of farmers in two different contexts of communal farming (Makolokwe) and commercial farming (Touws River valley), with a focus investigation on the adaptation and coping strategies of the farmers, as well as spatial analysis of the vegetation and rainfall variability. Farmers were asked to discuss climate and adaptation based on the rainfall data available as well as far as they could remember the occurrence of changes. Rainfall data was available between 1988 and 2017 for Touws River, while the data utilised for Makolokwe was available between 1928 and 2016. The link between the local knowledge of the farmers and scientific knowledge is an important aspect of this research. The Normalised Difference Vegetation Index (NDVI) was used to analyse the vegetation changes on a temporal and spatial scale in the context of Makolokwe and Touws River valley respectively. The differing variations in climate variability and change experienced by the two farming communities are placed alongside an exploration of the adaptation and coping measures which are put in place by farmers as a response to the changes evident in climate, as it allows for better and thorough understanding of the occurring changes in the two communities. The study found that perceptions about climate variability vary in the two communities although there are some common factors. Farmers’ perceptions about climate variability are drawn from their own observations at a local level as well as knowledge from the media regarding terms such as El Niño and drought. Farmers in both communities indicated that they experienced insufficient rain in the winter months which had an impact on the grazing areas and the management of the livestock. These months also threatened livelihoods, especially for farmers who depend on their livestock for their livelihood, in particular communal farmers. Perceptions of factors such as decreasing grazing and vegetation in their environments have led to the adoption of adaptation and coping strategies on the part of farmers. Commercial farmers have more choices in this regard than communal farmers, such as converting to game farming. Common coping strategies include: (1) farmers have had to subsidise and use alternative food sources for the livestock, (2) livestock numbers have been reduced in order to adapt to climate variability, with an impact on livelihoods (3) farmers have had to rely on their hope and faith that things will get better. Planning for climate variability is challenging for land managers. Knowledge and access to resources is therefore essential in ensuring that farmers are kept on track with the changing environment.

Flue-cured tobacco (Nicotiana tabacum L.) is a high value-per-acre crop that is intensively managed to optimize the yield of high quality cured leaf. Aerial remote sensing, specifically unmanned aerial vehicles (UAVs), present flue-cured tobacco producers and researchers with a potential tool for scouting and crop management. A two-year study, conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms, assessed the potential of aerial remote sensing in flue-cured tobacco. The effort encompassed two key objectives. First, examine the use of the enhanced normalized difference vegetation index (ENDVI) for separating flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and/or machine learning classification models capable of detecting Phytophthora nicotianae (black shank) incidence in flue-cured tobacco. In 2017, UAV-acquired ENDVI surveys demonstrated the ability to consistently separate between flue-cured tobacco varieties and nitrogen rates from topping to harvest. In 2018, ENDVI revealed significant differences among N-rates as early as 34 days after transplanting. Two hyperspectral indices were developed to detect black shank incidence based on differences in the spectral profiles of asymptomatic flue-cured tobacco plants compared to those with black shank symptoms. Testing of the indices showed significant differences between the index values of healthy and symptomatic plants (alpha = 0.05). In addition, the indices were able to detect black shank symptoms pre-symptomatically (alpha = 0.09). Subspace linear discriminant analysis, a machine learning classification, was also used for prediction of black shank incidence with up to 85.7% classification accuracy. / Master of Science / Unmanned Aerial Vehicle’s (UAVs) or drones, as they are commonly referred to, may have potential as a tool in flue-cured tobacco research and production. UAVs combined with sensors and cameras provide the opportunity to gather a large amount of data on a particular crop, which may be useful in crop management. Given the intensive management of flue-cured tobacco, producers may benefit from extra insight on how to better assess threats to yield such as under-fertilization and disease pressure. A two-year study was conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms. There were two objectives to this effort. First, assess the ability of UAV-acquired multispectral near-infrared imagery to separate flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and machine learning models that can accurately predict the incidence of black shank in flue-cured tobacco. Flue-cured tobacco nitrogen rates were significantly different in 2017 from 59 days after transplanting to harvest using UAV-acquired near-infrared imagery. In 2018, heavy rainfall may have led to nitrogen leaching from the soil resulting in nitrogen rates being significantly different as early as 34 days after transplanting. The imagery also showed a significant relationship with variety maturation type in the late stages of crop development during ripening. Two hyperspectral indices were developed and one machine learning model was trained. Each had the ability to detect black shank incidence in fluecured tobacco pre-symptomatically, as well as separated black shank infested plants from healthy plants.