Made available in DSpace on 2017-05-12T14:46:46Z (GMT). No. of bitstreams: 1 Carlos Henrique Wachholz de Souza.pdf: 9172700 bytes, checksum: 974911a1d2a6ffa227da2b1e9937a56d (MD5) Previous issue date: 2013-01-30 / The use of remote sensing technology has been studied as a way to make the current system of monitoring and crop forecasting in Brazil more efficient, dynamic and reliable. One of the difficulties found in the use of medium spatial resolution images as MODIS (250 Meters) is that the spectral profiles of temporary crops, as soybean and corn, may present similar curves, difficulting the separation of these cultures at the time of classification of the seeded areas. In this sense, the aim of this work was analyzing the pattern of temporal profiles, from the vegetation index (VI) EVI (Enhanced Vegetation Index), NDVI (Normalized Difference Vegetation Index) and WDRVI (Wide Dynamic Range Vegetation Index), obtained by the MODIS images for the crops of corn and soybean in the crop years of 2010/2011 and 2011/2012 in the state of Paraná. The aim was performing the spectral separation of these cultures to make its mapping. The applied methodology allowed the discrimination of areas with soybean and corn (masks) for each crop year. The areas of the masks were extracted and compared with SEAB official data, finding adjustments in "R ²" between 0.89 and 0.94 for soybean and from 0.43 to 0.83 for corn. For the Willmott coefficient (d) values were between 0.85 to 0.87 for the soybean crop and 0.63 to 0.76 for corn. The accuracy of spatial masks using images with high spatial resolution achieved the best results with the IV WDRVI with overall accuracy (OA) = 86% and = 0.78, and Kappa Index (KI) IV EVI with OA and KI = 83% = 0.74. Based on these results, it can be conclude that the proposed methodology is promising and may be used for mapping of these crops in the estimation of the state area. / A utilização de tecnologias de Sensoriamento Remoto vem sendo estudada como forma de tornar o sistema atual de monitoramento e previsão de safras no Brasil mais eficiente, dinâmica e confiável. Uma das dificuldades encontrada na utilização de imagens de média resolução espacial como as do sensor MODIS (250 metros), é que os perfis espectrais de culturas temporárias, como a soja e o milho, podem apresentar curvas semelhantes, dificultando a separação dessas culturas na hora da classificação das áreas semeadas. Neste sentido, o objetivo da realização deste trabalho foi analisar o padrão de perfis temporais, provenientes dos índices de vegetação (IV) EVI (Enhanced Vegetation Index), NDVI (Normalized Difference Vegetation Index) e WDRVI (Wide Dynamic Range Vegetation Index), obtidos por meio de imagens do sensor MODIS, para as culturas do milho e soja, nos anos-safra 2010/2011 e 2011/2012, no estado do Paraná. Para realizar a separação espectral das referidas culturas e efetuar o seu mapeamento. A metodologia aplicada permitiu a discriminação das áreas com soja e milho (máscaras) para cada ano-safra. As áreas das máscaras foram extraídas e comparadas com os dados oficiais da SEAB, encontrando-se ajustes de coeficiente de correlação (R²) entre 0,89 a 0,94 para a cultura da soja e de 0,43 a 0,83 para milho. Para o coeficiente de Willmott d foram encontrados valores entre 0,85 e 0,87 para a cultura soja e de 0,63 a 0,76 para milho. A exatidão espacial das máscaras utilizando imagens de alta resolução espacial obteve os melhores resultados com o IV WDRVI com Exatidão Global (EG) = 86% e Índice Kappa (IK) = 0,78 e o IV EVI com EG = 83% e IK = 0,74. Com base nestes resultados, pode-se concluir que a metodologia proposta é promissora, podendo ser utilizada para mapeamento dessas culturas na estimação da área estadual.

Made available in DSpace on 2017-05-12T14:47:02Z (GMT). No. of bitstreams: 1 _diego_della_justina.pdf: 3123259 bytes, checksum: 7482af0ac4e10eb7e14854f470ff3593 (MD5) Previous issue date: 2014-01-30 / Soybeans are an important agricultural crop, with expressive economical participation; thus, it is necessary the adoption of practices that enable crop forecasting, contributing for a better market position of this commodity. Remote sensing methodologies for monitoring production through are highly effective, due to their low cost, large-scale coverage and smaller time consumption. One of these techniques used is the NDVI Normalized Difference Vegetation Index, which has been employed on a large scale through use of the MODIS sensor. However, orbital sensors are subject to the influence of atmospheric factors and the culture dynamics, which may have different spectral behaviors among cultivars of the same species. In this context, non-orbital spectroscopy would be a viable solution for studying the existence of variations in the spectral behavior of any crop without further interference from exogenous factors. Thus, the aim of this work was to evaluate the temporal profiles of NDVI obtained with orbital MODIS sensor and non-orbital sensor GreenSeeker during the soybean development cycle. The study was conducted in two plots (T1 and T2) located on the Central Cooperative of Agricultural Research - COODETEC, in Cascavel State of Paraná. Samples of NDVI of thirteen pixels, three of them called pure pixels and ten non pure pixels, were taken at irregular intervals, but representing crop cycle. The data obtained by the non-orbital sensor were analyzed by exploratory analysis. Means of both orbital and non-orbital sensors were compared by test-t at 5% significance level. The means comparison test demonstrated the data obtained through the two sensors to be statistically different. However, both showed good dynamic range and sensibility to monitor and access spatial and temporal variations in the vegetation. / Uma vez que a soja é uma importante cultura agrícola, com expressiva participação econômica, se faz necessário a adoção de práticas que viabilizem a previsão de safra, contribuindo para melhor posicionamento da commodity no mercado. Metodologias de acompanhamento de produção por sensoriamento remoto orbital são alternativas eficazes devido ao baixo custo, grande escala de abrangência e rapidez. Uma das técnicas de acompanhamento agrícola empregada são os índices de vegetação, dentre eles o NDVI Índice de Vegetação por Diferença Normalizada, que vem sendo empregado em larga escala por meio do sensor MODIS. Porém, sensores orbitais estão sujeitos à influência dos fatores atmosféricos e da dinâmica das culturas, que podem apresentar diferentes comportamentos espectrais entre cultivares de uma mesma espécie. Nesse contexto, a espectroscopia terrestre, (não-orbital), pode ser uma solução viável para o estudo da existência de variações no comportamento espectral de qualquer cultura agrícola, sem maiores interferências de fatores exógenos. Sendo assim, o objetivo deste trabalho foi avaliar os perfis temporais de NDVI obtidos com o sensor orbital MODIS e o sensor não-orbital GreenSeeker durante o ciclo de desenvolvimento da soja. O estudo foi conduzido em dois talhões (T1 e T2) localizados nas dependências da Cooperativa Central de Pesquisa Agrícola COODETEC, no município de Cascavel PR. Amostras de NDVI de treze pixels, sendo três puros e dez não puros, foram tomadas em intervalos não regulares, porém, representativos ao desenvolvimento da cultura. Os dados obtidos por meio do sensor não-orbital foram submetidos a análise exploratória. As médias de ambos os sensores orbital e não-orbital foram comparadas pelo teste-t a 5% de significância. O teste de comparação de médias demonstrou que os dados obtidos entre os dois sensores são estatisticamente diferentes. No entanto, ambos demonstraram um bom alcance dinâmico e sensibilidade para monitorar e acessar variações espaciais e temporais da vegetação.

Made available in DSpace on 2017-05-12T14:47:02Z (GMT). No. of bitstreams: 1 Paulo H_Peruzzo De Lima.pdf: 4355288 bytes, checksum: 7a30c90530431576795c16cccbc00337 (MD5) Previous issue date: 2014-02-21 / The economic importance of the soy culture demands the development of techniques that allow monitoring the development conditions of large-scale cultures. In this context crop monitoring by remote sensing is a tool with great potential. This monitoring is accomplished by vegetation indices, being commonly used the Normalized Difference Vegetation Index - NDVI. The temporal profiles of NDVI indicate the temporal evolution of biomass, which enables to monitor the phenological development, the duration of growth period, the vegetative peak, the physiological changes of leaves, and the periods of culture senescence. Thus, the aim of this study was analyzing the relations of the spectral response of soybean cultivars with their phenological development by NDVI. To accomplish this, two experiments were carried out within the Cooperativa Central de Pesquisa Agrícola - COODETEC, in Cascavel, in the state of Paraná. To study plants growth habits and different development cycles, five soy cultivars were used. Furthermore, two irrigation regimes were also tested: the normal one (N), in which there was no water stress, and the water stress regimen (CEH). For experiment 1, NDVI data was collected, while for experiment 2, NDVI and Leaf Area Index (LAI) data were collected. These elements were analyzed by comparative charts of the temporal evolution of NDVI profiles for cultivars, considering treatments N and CEH. The mean ratios were compared using the t-student test at the 5% significance level. The relation between NDVI of each cultivar with their respective phenological development stage was also established. For experiment 2, models of simple linear regression were generated between NDVI and LAI for each cultivar and irrigation condition. For experiment 1, the temporal profile of NDVI described the normal behavior of the culture in the first days after sowing (DAS), and it showed values close to 0.2; as the plants developed, the NDVI values increased until the maximum value, close to 0.9. Determinate cycle cultivars obtained maximum NDVI at 56 DAS and V7 stage, while cultivars of indeterminate cycle obtained NDVI maximum at 70 DAS and V8 stage. In general, normal water regime treatments showed higher NDVI than water stress treatments. Regarding the experiment 2, coefficients of determination from 0.50 to 0.86 were found. The NDVI was efficient in monitoring soybean culture development. Thus, functions set between NDVI and LAI can be used for monitoring the crop. / A importância econômica da cultura da soja requer o desenvolvimento de técnicas que possibilitem o monitoramento das condições de desenvolvimento de culturas em larga escala. Neste contexto, o monitoramento agrícola por sensoriamento remoto é uma ferramenta com muito potencial. Este monitoramento é realizado por meio de índices de vegetação, sendo mais utilizado o Índice de Vegetação por Diferença Normalizada NDVI. Os perfis temporais do NDVI indicam a evolução temporal da biomassa, permitindo monitorar o desenvolvimento fenológico, a duração do período de crescimento, o pico vegetativo, as mudanças fisiológicas das folhas e os períodos de senescência das culturas. Sendo assim, o objetivo do trabalho foi analisar a relação da resposta espectral de cultivares de soja com seu desenvolvimento fenológico por meio do NDVI. Para tanto, foram realizados dois experimentos nas dependências da Cooperativa Central de Pesquisa Agrícola COODETEC, no município de Cascavel PR. Buscando estudar plantas com hábitos de crescimento e ciclos de desenvolvimento distintos, foram utilizadas cinco cultivares de soja. Além disso, também foram testados dois regimes de irrigação, o normal (N) em que não houve estresse hídrico e o regime com estresse hídrico (CEH). Para o experimento 1, foram coletados dados de NDVI e para o experimento 2, foram coletados dados de NDVI e Índice de Área Foliar IAF. Os dados foram analisados por meio de gráficos comparativos da evolução temporal dos perfis de NDVI para as cultivares, considerando os tratamentos N e CEH. As médias dos índices foram comparadas pelo teste t-student, ao nível de 5% de significância. Também foi verificada a relação entre o NDVI de cada cultivar com o seu respectivo estádio de desenvolvimento fenológico. Para o experimento 2, foram gerados modelos de regressão linear simples entre NDVI e IAF para cada cultivar e condição de irrigação. Para o experimento 1, o perfil temporal do NDVI descreveu o comportamento normal da cultura, nos primeiros dias após a semeadura (DAS), e apresentou valores próximos a 0,2; à medida que as plantas se desenvolveram, os valores de NDVI aumentaram até o valor máximo, próximo de 0,9. As cultivares de ciclo determinado obtiveram NDVI máximo aos 56 DAS e estádio V7 e as cultivares de ciclo indeterminado obtiveram NDVI máximo aos 70 DAS e estádio V8. De maneira geral, os tratamentos do regime hídrico normal apresentaram NDVI superiores ao tratamento com estresse hídrico. Em relação ao experimento 2, foram encontrados coeficientes de determinação de 0,50 a 0,86. Verificou-se que o NDVI foi eficiente no monitoramento do desenvolvimento cultura da soja e conclui-se que as funções ajustadas entre o NDVI e IAF podem ser utilizadas para o monitoramento dessa cultura.

Made available in DSpace on 2017-05-12T14:47:29Z (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

The construction of Baku-Tbilisi-Ceyhan (BTC) Oil and South Caucasus Gas (SCP) pipelines was completed in 2005. The Azerbaijan section of BTC Oil and SCP Gas pipelines is 442 km long and 44 m wide corridor named as the Right-of-Way. BTC and SCP pipelines are aligned parallel to each other within the same 44m corridor. The construction process of the pipelines significantly disturbed vegetation and soil cover along Right-of-Way of pipelines. The revegetation and erosion control measures were conducted after the completion of construction to restore the disturbed footprints of construction activities. The general goals of the present studies, dedicated to the environmental monitoring of revegetation and planning of erosion control measures were: to evaluate the status of the revegetation in 2007 since the completion of the construction activities in 2005, to determine the climate and ground factors controlling the vegetation regrowth and to predict erosion-prone areas along Right-of-Way of pipelines. Regression and root mean square error analysis between the Normalized Difference Vegetation Index (NDVI) of IKONOS images acquired in 2007 and in-situ estimations of vegetation cover percentage revealed R2 equal to 0.80 and RMSE equal to 6% which were optimal for the normalization of NDVI to vegetation cover. The total area of restored vegetation cover between 2005 and 2007 was 8.9 million sq. m. An area of 10.7 million sq. m. of ground vegetation needed restoration in order to comply with the environmental acceptance criteria. Based on the Global Spatial Regression Model, precipitation, land surface temperature and evapotranspiration were determined as the main climate factors controlling NDVI of grasslands along Right-of-Way of pipelines. In case of croplands, precipitation, evapotranspiration and annual minimum temperature were determined as the main factors controlling NDVI of croplands. The regression models predicting NDVI for grasslands and croplands were also formulated. The Geographically Weighted Regression analyses in comparison with the global regression models results clearly revealed that the relationship between NDVI of grasslands and croplands and the predictor variables was spatially non-stationary along the corridor of pipelines. Even though the observed R2 value between elevation and NDVI of grasslands was low (R2= 0.14), the accumulation of the largest NDVI patterns was observed higher than 150m elevation. This revealed that elevation has non-direct control of NDVI of grasslands through its control of precipitation and temperature along the grasslands of Right-of-Way. The spatial distribution percentage of NDVI classes within slope aspect categories was decreasing in the southern directions of slope faces. Land surface temperature was decreasing with elevation but no particular patterns of land surface temperature in the relationship with NDVI accumulation within the aspect categories were observed. Aspect categories have non-direct control of NDVI and there are some other factors apart from land surface temperature which require further investigations. Precipitation was determined to be controlling the formation of topsoil depth and the topsoil obviously controls the VC growth of grasslands as one of the main ground factors. The regression analysis between NDVI of grasslands and croplands with groundwater depth showed very low correlation. But the clustered patterns of vegetation cover were observed in the relationship with groundwater depth and soil moisture for both grasslands and croplands. The modeling of groundwater depth relative to soil moisture and MODIS NDVI of grasslands determined that the threshold of groundwater depth for vegetation growth is in the range of 1-5 m. MODIS NDVI and soil moisture did not reveal a significant correlation. Soil moisture revealed R2 equal to 0.34 with elevation, R2 equal to 0.23 with evapotranspiration, R2 equal to 0.57 with groundwater depth and R2 equal to 0.02 with precipitation. This allowed to suspect that precipitation is not the main factor controlling soil moisture whereas elevation, evapotranspiration and groundwater depth have non-direct control of soil moisture. Therefore, soil moisture has also non-direct control of vegetation cover growth along the corridor of pipelines. The variations of soil moisture in the 1-3 m soil depth range may have the threshold of depth controlling vegetation cover regrowth and this requires more detailed soil moisture data for further investigations. The reliability of the Global Spatial Regression Model and Geographically Weighted Regression predictions is limited by the MODIS images spatial resolution equal to 250 m and spectral characteristics. The Morgan-Morgan-Finney (MMF) and Universal Soil Loss Equation (USLE) predictions revealed non-similarity in the spatial distribution of soil loss rates along Right-of-Way. MMF model revealed more clustered patterns of predicted critical erosion classes with soil loss more than 10 ton/ha/year in particular ranges of pipelines rather than Universal Soil Loss Equation model with the widespread spatial distribution. Paired-Samples T-Test with p-value less than 0.05 and Bivariate correlation with the Pearson\'s correlation coefficient equal to 0.23 showed that the predictions of these two models were significantly different. Verification of USLE- and MMF- predicted erosion classes against in-situ 316 collected erosion occurrences collected in the period of 2005-2012 revealed that USLE performed better than MMF model along pipeline by identifying of 192 erosion occurrences out of 316, whereas MMF identified 117 erosion sites. USLE revealed higher ratio of frequencies of erosion occurrences within the critical erosion classes (Soil Loss > 10 t/ha), what also showed higher reliability of soil loss predictions by USLE. The validation of quantitative soil loss predictions using the measurements from 48 field erosion plots revealed higher R2 equal to 0.67 by USLE model than by MMF. This proved that USLE-predicted soil loss rates were more reliable than MMF not only in terms of spatial distributions of critical erosion classes but also in the quantitative terms of soil loss rates. The total number of erosion-prone pipeline segments with the identified erosion occurrences was 316 out of 38376. The number of erosion-prone pipeline segments realistically predicted by USLE model e.g. soil loss more than 10 t/ha was 97 whereas MMF predicted only 70 erosion-prone pipeline segments. The regression analysis between 354 USLE and MMF erosion-prone segments revealed R2 equal to 0.36 what means that the predictions by USLE and MMF erosion models are significantly different on the level of pipeline segments. The average coefficients of variation of predicted soil loss rates by USLE and MMF models and the number of accurately predicted erosion occurrences within the geomorphometric elements of terrain, vegetation cover and landuse categories were larger in the USLE model. This supported the hypothesis that larger spatial variations of erosion prediction models can contribute to the better soil loss prediction performance and reliability of erosion prediction models. This also supported the hypothesis that better understanding of spatial variations within geomorphometric elements of terrain, land-use and vegetation cover percentage classes can support in the selection of the appropriate erosion models with better performance in the particular areas of pipelines. Qualitative multi-criteria assessment for the determination of erosion-prone areas revealed stronger relations with the USLE predictions rather than with MMF. Multi-criteria assessment identified 35 of erosion occurrences but revealed more reliable predictions on the level of terrain units. Predicted erosion-prone areas by USLE revealed higher correlation coefficient with erosion occurrences than MMF model within terrain units what proved higher reliability of the USLE predictions and its stronger relation with the multi-criteria assessment.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2017-05-08T13:39:28Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) tese_doutorado_keyla_alencar_corrigido.pdf: 4259978 bytes, checksum: 96a2f04485b9fd7893d2140badf07cbe (MD5) / Made available in DSpace on 2017-05-08T13:39:28Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) tese_doutorado_keyla_alencar_corrigido.pdf: 4259978 bytes, checksum: 96a2f04485b9fd7893d2140badf07cbe (MD5) Previous issue date: 2016-02-29 / FACEPE / A pesquisa aqui presente visou compreender os aspectos das mudanças ambientais (climática e da cobertura vegetal), e os impactos e vulnerabilidades produzidas por tais mudanças na Bacia Hidrográfica do Rio Moxotó, que se encontra localizada no semiárido pernambucano. Para análise das mudanças ambientais foram utilizadas a técnica de análise de tendência de precipitação Mann-Kendall, aplicada a uma série de dados de 84 anos extraídos de 38 estações meteorológicas, e para análise espaço-temporal das mudanças da cobertura vegetal a técnica NDVI utilizando imagens satelitais Landsat 5 e 7. Com base nos dados obtidos a partir dessas técnicas, observaram-se os impactos e também serviram para compor como indicadores na construção do índice de vulnerabilidade às mudanças climáticas. O resultado da análise de tendência de precipitação apresentou que as tendências na área da bacia não são homogenias; e que o resultado referente à análise do comportamento da cobertura vegetal demonstra que a vegetação nativa apresenta-se mais conservadas nas áreas de altitudes mais elevadas e nas áreas de morros testemunhos e relevos residuais da bacia sedimentar do Jatobá. Para construção do índice de vulnerabilidade às mudanças climáticas foram selecionados indicadores tomando como critério de seleção a relação conceitual \cientifica que cada um destes possuía com as mudanças climáticas e a área de estudo. Assim foram selecionados indicadores de caráter social, econômico e físico que foram agrupados em três subíndices (exposição, sensibilidade e capacidade adaptativa), onde cada um desses subíndices representava a variabilidade climática e as mudanças na cobertura vegetal, as vulnerabilidades sociais e econômicas e os aspectos positivos que favorecem a adaptação às mudanças ambientais, respectivamente. Dentre os resultados gerados pelos subíndices e índice final, observou-se que os municípios em situação mais grave são Jatobá, Ibimirim e Tupanatinga, que apresentaram os níveis mais elevados de vulnerabilidades ás mudanças climáticas. A partir de todos os resultados e análises apresentados fica evidente a importância dos estudos de vulnerabilidades sociais e ambientais como recursos para o entendimento dos efeitos das mudanças climáticas sobre sistemas sociais e ambientais. / This research aimed to understand environmental changes aspects (climate and vegetation cover), and the impacts and vulnerabilities produced by those changes in Moxotó watershed, located in semiarid. In order to investigate the environmental changes, Mann-Kendall trends test was applied to analyze precipitation trends by using a series of 84-year data obtained from 38 meteorological stations, and to evaluate space-temporal changes in vegetation cover NDVI method was used through Landsat 5 and 7 imagery. The data provided by these methods permitted to observe the impacts and served as indicators of climate change vulnerability index. The results of Mann-Kendall test showed that trends of precipitation in Moxotó watershed are not homogeneous; and the analysis of vegetation cover behavior demonstrates that native vegetation is well-preserved in higher altitude areas and residual landforms of Jatobá sedimentary basin. Indicators used to construct the climate changes vulnerabilities index were selected trough their conceptual/scientific relation between climate changes and the study area. Therefore, social, economic and physical indicators were selected and clustered in three sub- indexes (exposure, sensibility and adaptive capacity), each one represented the climate variability and changes in vegetation cover, social and economic vulnerabilities and positive aspects that favors adaptation to climate change, respectively. The outcomes obtained through the sub-indexes and final index presented that Jatobá, Ibimirim and Tupanatinga municipalities presented the highest vulnerability levels to climate changes. Based on the results and analysis mentioned, became evident the importance of researches in social and environmental vulnerabilities issues to support the understanding of climate changes effects on social and environmental systems.

Made available in DSpace on 2017-07-10T19:23:35Z (GMT). No. of bitstreams: 1 Carlos Henrique Wachholz de Souza.pdf: 9172700 bytes, checksum: 974911a1d2a6ffa227da2b1e9937a56d (MD5) Previous issue date: 2013-01-30 / The use of remote sensing technology has been studied as a way to make the current system of monitoring and crop forecasting in Brazil more efficient, dynamic and reliable. One of the difficulties found in the use of medium spatial resolution images as MODIS (250 Meters) is that the spectral profiles of temporary crops, as soybean and corn, may present similar curves, difficulting the separation of these cultures at the time of classification of the seeded areas. In this sense, the aim of this work was analyzing the pattern of temporal profiles, from the vegetation index (VI) EVI (Enhanced Vegetation Index), NDVI (Normalized Difference Vegetation Index) and WDRVI (Wide Dynamic Range Vegetation Index), obtained by the MODIS images for the crops of corn and soybean in the crop years of 2010/2011 and 2011/2012 in the state of Paraná. The aim was performing the spectral separation of these cultures to make its mapping. The applied methodology allowed the discrimination of areas with soybean and corn (masks) for each crop year. The areas of the masks were extracted and compared with SEAB official data, finding adjustments in "R ²" between 0.89 and 0.94 for soybean and from 0.43 to 0.83 for corn. For the Willmott coefficient (d) values were between 0.85 to 0.87 for the soybean crop and 0.63 to 0.76 for corn. The accuracy of spatial masks using images with high spatial resolution achieved the best results with the IV WDRVI with overall accuracy (OA) = 86% and = 0.78, and Kappa Index (KI) IV EVI with OA and KI = 83% = 0.74. Based on these results, it can be conclude that the proposed methodology is promising and may be used for mapping of these crops in the estimation of the state area. / A utilização de tecnologias de Sensoriamento Remoto vem sendo estudada como forma de tornar o sistema atual de monitoramento e previsão de safras no Brasil mais eficiente, dinâmica e confiável. Uma das dificuldades encontrada na utilização de imagens de média resolução espacial como as do sensor MODIS (250 metros), é que os perfis espectrais de culturas temporárias, como a soja e o milho, podem apresentar curvas semelhantes, dificultando a separação dessas culturas na hora da classificação das áreas semeadas. Neste sentido, o objetivo da realização deste trabalho foi analisar o padrão de perfis temporais, provenientes dos índices de vegetação (IV) EVI (Enhanced Vegetation Index), NDVI (Normalized Difference Vegetation Index) e WDRVI (Wide Dynamic Range Vegetation Index), obtidos por meio de imagens do sensor MODIS, para as culturas do milho e soja, nos anos-safra 2010/2011 e 2011/2012, no estado do Paraná. Para realizar a separação espectral das referidas culturas e efetuar o seu mapeamento. A metodologia aplicada permitiu a discriminação das áreas com soja e milho (máscaras) para cada ano-safra. As áreas das máscaras foram extraídas e comparadas com os dados oficiais da SEAB, encontrando-se ajustes de coeficiente de correlação (R²) entre 0,89 a 0,94 para a cultura da soja e de 0,43 a 0,83 para milho. Para o coeficiente de Willmott d foram encontrados valores entre 0,85 e 0,87 para a cultura soja e de 0,63 a 0,76 para milho. A exatidão espacial das máscaras utilizando imagens de alta resolução espacial obteve os melhores resultados com o IV WDRVI com Exatidão Global (EG) = 86% e Índice Kappa (IK) = 0,78 e o IV EVI com EG = 83% e IK = 0,74. Com base nestes resultados, pode-se concluir que a metodologia proposta é promissora, podendo ser utilizada para mapeamento dessas culturas na estimação da área estadual.

Made available in DSpace on 2017-07-10T19:23:49Z (GMT). No. of bitstreams: 1 _diego_della_justina.pdf: 3123259 bytes, checksum: 7482af0ac4e10eb7e14854f470ff3593 (MD5) Previous issue date: 2014-01-30 / Soybeans are an important agricultural crop, with expressive economical participation; thus, it is necessary the adoption of practices that enable crop forecasting, contributing for a better market position of this commodity. Remote sensing methodologies for monitoring production through are highly effective, due to their low cost, large-scale coverage and smaller time consumption. One of these techniques used is the NDVI Normalized Difference Vegetation Index, which has been employed on a large scale through use of the MODIS sensor. However, orbital sensors are subject to the influence of atmospheric factors and the culture dynamics, which may have different spectral behaviors among cultivars of the same species. In this context, non-orbital spectroscopy would be a viable solution for studying the existence of variations in the spectral behavior of any crop without further interference from exogenous factors. Thus, the aim of this work was to evaluate the temporal profiles of NDVI obtained with orbital MODIS sensor and non-orbital sensor GreenSeeker during the soybean development cycle. The study was conducted in two plots (T1 and T2) located on the Central Cooperative of Agricultural Research - COODETEC, in Cascavel State of Paraná. Samples of NDVI of thirteen pixels, three of them called pure pixels and ten non pure pixels, were taken at irregular intervals, but representing crop cycle. The data obtained by the non-orbital sensor were analyzed by exploratory analysis. Means of both orbital and non-orbital sensors were compared by test-t at 5% significance level. The means comparison test demonstrated the data obtained through the two sensors to be statistically different. However, both showed good dynamic range and sensibility to monitor and access spatial and temporal variations in the vegetation. / Uma vez que a soja é uma importante cultura agrícola, com expressiva participação econômica, se faz necessário a adoção de práticas que viabilizem a previsão de safra, contribuindo para melhor posicionamento da commodity no mercado. Metodologias de acompanhamento de produção por sensoriamento remoto orbital são alternativas eficazes devido ao baixo custo, grande escala de abrangência e rapidez. Uma das técnicas de acompanhamento agrícola empregada são os índices de vegetação, dentre eles o NDVI Índice de Vegetação por Diferença Normalizada, que vem sendo empregado em larga escala por meio do sensor MODIS. Porém, sensores orbitais estão sujeitos à influência dos fatores atmosféricos e da dinâmica das culturas, que podem apresentar diferentes comportamentos espectrais entre cultivares de uma mesma espécie. Nesse contexto, a espectroscopia terrestre, (não-orbital), pode ser uma solução viável para o estudo da existência de variações no comportamento espectral de qualquer cultura agrícola, sem maiores interferências de fatores exógenos. Sendo assim, o objetivo deste trabalho foi avaliar os perfis temporais de NDVI obtidos com o sensor orbital MODIS e o sensor não-orbital GreenSeeker durante o ciclo de desenvolvimento da soja. O estudo foi conduzido em dois talhões (T1 e T2) localizados nas dependências da Cooperativa Central de Pesquisa Agrícola COODETEC, no município de Cascavel PR. Amostras de NDVI de treze pixels, sendo três puros e dez não puros, foram tomadas em intervalos não regulares, porém, representativos ao desenvolvimento da cultura. Os dados obtidos por meio do sensor não-orbital foram submetidos a análise exploratória. As médias de ambos os sensores orbital e não-orbital foram comparadas pelo teste-t a 5% de significância. O teste de comparação de médias demonstrou que os dados obtidos entre os dois sensores são estatisticamente diferentes. No entanto, ambos demonstraram um bom alcance dinâmico e sensibilidade para monitorar e acessar variações espaciais e temporais da vegetação.

Made available in DSpace on 2017-07-10T19:23:49Z (GMT). No. of bitstreams: 1 Paulo H_Peruzzo De Lima.pdf: 4355288 bytes, checksum: 7a30c90530431576795c16cccbc00337 (MD5) Previous issue date: 2014-02-21 / The economic importance of the soy culture demands the development of techniques that allow monitoring the development conditions of large-scale cultures. In this context crop monitoring by remote sensing is a tool with great potential. This monitoring is accomplished by vegetation indices, being commonly used the Normalized Difference Vegetation Index - NDVI. The temporal profiles of NDVI indicate the temporal evolution of biomass, which enables to monitor the phenological development, the duration of growth period, the vegetative peak, the physiological changes of leaves, and the periods of culture senescence. Thus, the aim of this study was analyzing the relations of the spectral response of soybean cultivars with their phenological development by NDVI. To accomplish this, two experiments were carried out within the Cooperativa Central de Pesquisa Agrícola - COODETEC, in Cascavel, in the state of Paraná. To study plants growth habits and different development cycles, five soy cultivars were used. Furthermore, two irrigation regimes were also tested: the normal one (N), in which there was no water stress, and the water stress regimen (CEH). For experiment 1, NDVI data was collected, while for experiment 2, NDVI and Leaf Area Index (LAI) data were collected. These elements were analyzed by comparative charts of the temporal evolution of NDVI profiles for cultivars, considering treatments N and CEH. The mean ratios were compared using the t-student test at the 5% significance level. The relation between NDVI of each cultivar with their respective phenological development stage was also established. For experiment 2, models of simple linear regression were generated between NDVI and LAI for each cultivar and irrigation condition. For experiment 1, the temporal profile of NDVI described the normal behavior of the culture in the first days after sowing (DAS), and it showed values close to 0.2; as the plants developed, the NDVI values increased until the maximum value, close to 0.9. Determinate cycle cultivars obtained maximum NDVI at 56 DAS and V7 stage, while cultivars of indeterminate cycle obtained NDVI maximum at 70 DAS and V8 stage. In general, normal water regime treatments showed higher NDVI than water stress treatments. Regarding the experiment 2, coefficients of determination from 0.50 to 0.86 were found. The NDVI was efficient in monitoring soybean culture development. Thus, functions set between NDVI and LAI can be used for monitoring the crop. / A importância econômica da cultura da soja requer o desenvolvimento de técnicas que possibilitem o monitoramento das condições de desenvolvimento de culturas em larga escala. Neste contexto, o monitoramento agrícola por sensoriamento remoto é uma ferramenta com muito potencial. Este monitoramento é realizado por meio de índices de vegetação, sendo mais utilizado o Índice de Vegetação por Diferença Normalizada NDVI. Os perfis temporais do NDVI indicam a evolução temporal da biomassa, permitindo monitorar o desenvolvimento fenológico, a duração do período de crescimento, o pico vegetativo, as mudanças fisiológicas das folhas e os períodos de senescência das culturas. Sendo assim, o objetivo do trabalho foi analisar a relação da resposta espectral de cultivares de soja com seu desenvolvimento fenológico por meio do NDVI. Para tanto, foram realizados dois experimentos nas dependências da Cooperativa Central de Pesquisa Agrícola COODETEC, no município de Cascavel PR. Buscando estudar plantas com hábitos de crescimento e ciclos de desenvolvimento distintos, foram utilizadas cinco cultivares de soja. Além disso, também foram testados dois regimes de irrigação, o normal (N) em que não houve estresse hídrico e o regime com estresse hídrico (CEH). Para o experimento 1, foram coletados dados de NDVI e para o experimento 2, foram coletados dados de NDVI e Índice de Área Foliar IAF. Os dados foram analisados por meio de gráficos comparativos da evolução temporal dos perfis de NDVI para as cultivares, considerando os tratamentos N e CEH. As médias dos índices foram comparadas pelo teste t-student, ao nível de 5% de significância. Também foi verificada a relação entre o NDVI de cada cultivar com o seu respectivo estádio de desenvolvimento fenológico. Para o experimento 2, foram gerados modelos de regressão linear simples entre NDVI e IAF para cada cultivar e condição de irrigação. Para o experimento 1, o perfil temporal do NDVI descreveu o comportamento normal da cultura, nos primeiros dias após a semeadura (DAS), e apresentou valores próximos a 0,2; à medida que as plantas se desenvolveram, os valores de NDVI aumentaram até o valor máximo, próximo de 0,9. As cultivares de ciclo determinado obtiveram NDVI máximo aos 56 DAS e estádio V7 e as cultivares de ciclo indeterminado obtiveram NDVI máximo aos 70 DAS e estádio V8. De maneira geral, os tratamentos do regime hídrico normal apresentaram NDVI superiores ao tratamento com estresse hídrico. Em relação ao experimento 2, foram encontrados coeficientes de determinação de 0,50 a 0,86. Verificou-se que o NDVI foi eficiente no monitoramento do desenvolvimento cultura da soja e conclui-se que as funções ajustadas entre o NDVI e IAF podem ser utilizadas para o monitoramento dessa cultura.

Remote-sensing based indices such as Normalized Difference Vegetation Index have yielded valuable information about plant health. As the availability of water is one of the factors that controls plant's response to their environment, it is possible to indirectly studythe hydrology of an area via vegetation indices. Hence the thesis work used this tool to characterize the potential shifts in vegetation cover within and between years in Kilombero river catchment in Tanzania and make connection to the hydrology in the area. Separate time series analyses conducted on data pertaining to NDVI values and the areal coverage variability of arbitrarily defined NDVI-classes. The former data was extracted from a naturally vegetated wetland in the middle of the catchment while the latter from the topographically defined areas of the catchment. Results from the analyses showed that bothdatasets are sensitive to the seasonal rainfall while at inter-annual scale the areal coverage variability displayed significant correlations with past precipitation. Meanwhile the relatively higher sensitivity of the lowland area‟s NDVI to precipitation conforms to the initial assumption which emphasizes the importance of the wetland sub-catchment codenamed 1KB17 in describing Kilombero‟s hydrology. But the datasets show weak trends and it was not possible to make accurate future predictions on the hydrological conditions in the area. Meteorological distortions like clouds and environmental processes such as climate patterns or disturbances might have caused the problem in trend detection. Further studies needed to shed more light on the connection between land cover and hydrologic response in Kilombero.