Levando em consideração a influência das variáveis meteorológicas no desenvolvimento dos cultivos e na definição do rendimento de grãos, o monitoramento da resposta da cultura da soja frente às condições ambientais se torna necessário devido sua importância tanto no cenário internacional quanto nacional. Sabe-se que para a cultura da soja, a estiagem é a causa mais frequente das perdas em safras no Rio Grande do Sul. Neste contexto, testar ferramentas de monitoramento em tempo quase real das condições hídricas das lavouras de soja ao longo do ciclo torna-se relevante e permite verificar se a cultura está em adequadas condições de crescimento e desenvolvimento. Os objetivos deste estudo foram avaliar a aptidão do índice TVDI em representar as condições de disponibilidade hídrica em áreas de cultivo de soja no Rio Grande do Sul; caracterizar e analisar a sensibilidade dos parâmetros da relação entre a temperatura de superfície (TS) e o índice de vegetação por diferença normalizada (NDVI) e, por fim, comparar as abordagens por cena e por safra no processo de parametrização do índice TVDI para a cultura da soja. Para tanto, foram utilizados os produtos MODIS TS (MOD11A2) e NDVI (MOD13A2) com resolução espacial de 1.000 m e temporal de 8 e 16 dias, respectivamente, assim como dados de precipitação pluvial de 3 estações meteorológicas localizadas na área de estudo e dados oficiais do IBGE de área e de rendimento. Os resultados mostraram que a abordagem de parametrização por cena possibilita o entendimento da distribuição espacial das condições hídricas da área de estudo frente aos limites hídricos de cada imagem. Os parâmetros "b" e “TSmin” utilizados para determinar as retas dos limites seco e úmido do triângulo evaporativo na determinação do TVDI com parametrização por cena podem auxiliar na compreensão do perfil temporal deste índice ao longo da safra. Já a parametrização por safra, mostrou aptidão do índice em representar o momento e a frequência de ocorrência de restrição hídrica ao longo do ciclo da cultura. O método do triângulo evaporativo para a obtenção do índice TVDI mostra-se eficiente, pois permite a partir de dados de sensoriamento remoto, o entendimento do padrão espacial e temporal de resposta da vegetação frente à disponibilidade hídrica, além de informações de grande utilidade para sistemas de monitoramento e estimativas de safras. / In view of the influence of meteorological variables on crop growth and grain yield, monitoring the response of soybean to different environmental conditions is essential, given the international and domestic importance of this crop. Drought is the leading cause of soybean crop losses in the Brazilian state of Rio Grande do Sul. In this context, testing tools for monitoring in near real time the water conditions of soybean fields throughout their cycle becomes relevant and allows for checking if the crop is under proper conditions for growth and development. The objectives of this study were: to assess the adequacy of the temperature–vegetation dryness index (TVDI) to represent water availability status in soybean growing areas in Rio Grande do Sul; to characterize and analyze the sensitivity of the surface temperature (TS)/normalized difference vegetation index (NDVI) ratio; and to compare the scene-specific and crop-specific approaches for parameterization of TVDI. To this end, the MODIS TS (MOD11A2) and NDVI (MOD13A2) products were used, with a spatial resolution of 1000 m and a temporal resolution of 8 and 16 days respectively, as well as precipitation data from 3 weather stations located in the study area and official area and yield data from the Brazilian Institute of Geography and Statistics (IBGE). Results showed that the scene-specific parameterization approach was able to provide an understanding of the spatial distribution of water status in the area of interest as derived from the dry and wet edges of each image. With scene-based parameterization, the “b” and “TSmin” parameters used to determine the dry and wet edges of the TS/NDVI can help elucidate the temporal profile of this index throughout the harvest period. With crop-type parameterization, the TVDI was able to represent the timing and frequency of limited water availability during the crop cycle. The triangle method proved effective in deriving the TVDI, as it provides a means of using remote sensing data to understand the spatiotemporal response pattern of vegetation to water availability, as well as other information that can be highly useful for monitoring systems and crop estimation.

Resumo: Considerando a importância da compreensão da dinâmica espaço temporal dos componentes do balanço de energia (BE) em escala regional para o gerenciamento de recursos hídrico e o manejo agrícola, o objetivo principal desta tese foi construir e analisar uma série temporal dos componentes do BE adequada às condições de clima subtropical úmido do Estado do Rio Grande do Sul. Para tanto, inicialmente foi avaliada a adequação de modelos de estimativa de BE para o Estado. Nesta etapa foram utilizados produtos MODIS e dados de referência medidos em uma torre micrometeorológica instalada em Cruz Alta – RS, usando valores instantâneos para um período de estudo de 2009 a 2011. Na sequência foi avaliada a adequação dos modelos em representar a variabilidade espacial dos componentes do BE. Nesta etapa foram usados produtos MODIS, dados de reanálise ERA Interim, dados de referência da torre micrometeorológica e dados de estações meteorológicas do INMET, para o mesmo período de estudo. Na última etapa do trabalho foi construída a série temporal dos componentes do BE usando o modelo METRIC, a qual abrangeu um período de 14 anos, de 2002 a 2016. Os resultados demonstraram que os três modelos analisados apresentam coerência com as medidas de referência, sendo as maiores limitações apresentadas pelo modelo SEBAL, as quais se atribui principalmente às condições ecoclimáticas do Estado e a baixa resolução espacial das imagens. Na análise da variabilidade espacial, o modelo METRIC apresentou maior consistência nos resultados e proporcionou maior número de dias com resultados válidos, sendo assim apontado como o mais apto para realização do restante do estudo. A série temporal construída possibilitou a compreensão dos padrões de distribuição espaço temporal dos componentes do BE no estado do Rio Grande do Sul. Há uma marcada sazonalidade nos componentes do BE, com maiores valores no verão e menores no inverno. G (fluxo de calor no solo) é o componente de menor magnitude e sua distribuição espacial e temporal é determinada pela distribuição de Rn (saldo de radiação). Já os componentes LE (fluxo de calor latente) e H (fluxo de calor sensível), são os que mostram magnitude maior e apresentam padrões de distribuição espacial e temporal coerentes com as condições climáticas e com os tipos de uso e cobertura na área de estudo. Observase um padrão inverso, com um gradiente de LE no sentido noroeste para sudeste e para o componente H, no sentido sudeste para noroeste. Sendo estas informações de grande importância para gerenciamento de recursos hídricos em escala regional, para estudos de zoneamento agrícola. / Abstract: Given the importance of understanding the temporal and spatial dynamics of of the energy balance (EB) components in a regional scale for the management of water resources and agricultural, the main objective of this thesis was to construct and analyze a time series of the components of BE appropriate to the subtropical humid climate conditions of the State of Rio Grande do Sul. In order to reach the objective initially, the adequacy of the models for the humid climate conditions was evaluated, in this step we used MODIS data and reference data measured in a micrometeorological tower installed in Cruz Alta - RS. The analyzes performed with instantaneous values and the study period was from 2009 to 2011. The next step evaluate the spatial variability of the BE components, the data used were the MODIS products, ERA Interim reanalysis data, reference data of the micrometeorological tower and INMET meteorological stations, for the same study period. In the last stage the time series of the BE components was constructed from the METRIC model. The period series was 14 years from 2002 to 2016.The results showed that the three models analyzed were consistent with the reference measurements, with the greatest limitations presented by the SEBAL model, which are mainly attributed to the state's eco-climatic conditions and the low spatial resolution of the images In the analysis of the spatial variability, the METRIC model presented greater consistency in the results and provided greater number of days with valid results, this model thus indicated as the most suitable for the rest of the study. The time series constructed allowed us to understand the temporal distribution patterns of BE components in the state of Rio Grande do Sul. There is a marked seasonality in the BE components, with higher values in summer and lower in winter. G is the smallest magnitude component and its spatial and temporal distribution is determined by the Rn distribution. On the other hand, the LE and H components are those that show higher magnitude and present spatial and temporal distribution patterns consistent with the climatic conditions and the types of use and coverage in the study area. An inverse pattern is observed, with a LE gradient from north-west to south-east and for H-component, from southeast to northwest.

A evapotranspiração (ET) é um fenômeno natural que influencia diretamente mudanças no clima local e global, possuindo grande importância hidrológica e meteorológica. Este trabalho teve como objetivo estimar a ET através do método Penman-Monteith, e comparar com os resultados estimados pelo Método da Covariância de Vórtices Turbulentos. Os dados de IAF (Índice de Área Foliar) para descrição da vegetação foram obtidos a partir do sensor MODIS e de medições em campo da Rede SulFlux. A área de estudo desta pesquisa localizou-se no município de Cachoeira do Sul-RS, em uma propriedade de cultivo de arroz irrigado. O período de estudo referiu-se a safra que estendeu-se de outubro de 2010 a março de 2011. Os resultados mostraram que o IAF e as estimativas de ET apresentam um comportamento temporal semelhante. A comparação entre os resultados das estimativas de ET, utilizando dados obtidos em campo e estimados através de sensoriamento remoto, foram satisfatórios. No entanto, o resultado que apresentou os maiores valores para a ET foi proveniente do sensor MODIS. Sendo assim, pode-se concluir que a estimativa da ET, a partir de dados de vegetação, obtidos através de técnicas de sensoriamento remoto, constituem-se como uma alternativa para os métodos de ET que utilizam dados de vegetação medidos em campo. / The Evapotranspiration (ET) is a natural phenomenon that directly causes changes in the local and global climate, having a great hydrologic and meteorological importance. This work has as objective to estimate ET through the Penman-Monteith method and compare with the estimated results by the Eddy Covariance Method. The LAI (Leaf Area Index) data for the vegetation description were obtained from the MODIS sensor and from field measurements of the SulFlux network. The field of study of this research had place in the city of Cachoeira do Sul – Rio Grande do Sul state, in a irrigated rice crop property. The study period is referred to the crop that extended from October 2010 to March 2011. The results showed that the LAI and the ET estimates have a similar temporal behavior. The comparison between the results of ET estimates, using data obtained in field and estimated through remote sensing, were satisfactory. However, the result that showed the highest values for ET was from the MODIS sensor. This way, it can be concluded that the ET estimate, through vegetation data, obtained by remote sensing techniques, are an alternative for the ET methods that use vegetation field measured data.

No description available.

This thesis presents the use of data assimilation with optimal interpolation (OI) to develop atmospheric aerosol concentration estimates for the United States at high spatial and temporal resolutions. Concentration estimates are highly desirable for a wide range of applications, including visibility, climate, and human health. OI is a viable data assimilation method that can be used to improve Community Multiscale Air Quality (CMAQ) model fine particulate matter (PM2.5) estimates. PM2.5 is the mass of solid and liquid particles with diameters less than or equal to 2.5 μm suspended in the gas phase. OI was employed by combining model estimates with satellite and surface measurements. The satellite data assimilation combined 36 x 36 km aerosol concentrations from CMAQ with aerosol optical depth (AOD) measured by MODIS and AERONET over the continental United States for 2002. Posterior model concentrations generated by the OI algorithm were compared with surface PM2.5 measurements to evaluate a number of possible data assimilation parameters, including model error, observation error, and temporal averaging assumptions. Evaluation was conducted separately for six geographic U.S. regions in 2002. Variability in model error and MODIS biases limited the effectiveness of a single data assimilation system for the entire continental domain. The best combinations of four settings and three averaging schemes led to a domain-averaged improvement in fractional error from 1.2 to 0.97 and from 0.99 to 0.89 at respective IMPROVE and STN monitoring sites. For 38% of OI results, MODIS OI degraded the forward model skill due to biases and outliers in MODIS AOD. Surface data assimilation combined 36 × 36 km aerosol concentrations from the CMAQ model with surface PM2.5 measurements over the continental United States for 2002. The model error covariance matrix was constructed by using the observational method. The observation error covariance matrix included site representation that scaled the observation error by land use (i.e. urban or rural locations). In theory, urban locations should have less effect on surrounding areas than rural sites, which can be controlled using site representation error. The annual evaluations showed substantial improvements in model performance with increases in the correlation coefficient from 0.36 (prior) to 0.76 (posterior), and decreases in the fractional error from 0.43 (prior) to 0.15 (posterior). In addition, the normalized mean error decreased from 0.36 (prior) to 0.13 (posterior), and the RMSE decreased from 5.39 μg m-3 (prior) to 2.32 μg m-3 (posterior). OI decreased model bias for both large spatial areas and point locations, and could be extended to more advanced data assimilation methods. The current work will be applied to a five year (2000-2004) CMAQ simulation aimed at improving aerosol model estimates. The posterior model concentrations will be used to inform exposure studies over the U.S. that relate aerosol exposure to mortality and morbidity rates. Future improvements for the OI techniques used in the current study will include combining both surface and satellite data to improve posterior model estimates. Satellite data have high spatial and temporal resolutions in comparison to surface measurements, which are scarce but more accurate than model estimates. The satellite data are subject to noise affected by location and season of retrieval. The implementation of OI to combine satellite and surface data sets has the potential to improve posterior model estimates for locations that have no direct measurements.

The capability to monitor bushfires on a large scale from space has long been identified as an important contribution to climate and atmospheric research as well as a tool an aid in natural hazard response. Since the work by Dozier (1981), fire monitoring from space has relied on the principles he described. His method of identifying fires within a pixel significantly larger than the fire by utilizing the different responses of the 3 μm and 11 μm channels has been applied to a number of sensors. Over the last decade a lot of work has been invested to refine and validate fire detections based on this approach. So far, the application of the method proposed by Dozier (1981) reached its peak with the launch of the MODIS instrument on board the Terra satellite. In contrast to earlier sensors, MODIS was equipped with spectral channels specifically designed for the detection of fires with algorithms based on the work by Dozier (1981). These channels were designed to overcome problems experienced with other platforms, the biggest of which is the saturation of the 3 μm channel caused by big, hot fires. Since its launch, MODIS has proven itself to be a capable platform to provide worldwide fire detection at a moderate resolution of 1 km on a daily basis. / It is the intention of this work to open up new opportunities in remote sensing of fires from satellites by showing capabilities and limitations in the application of other spectral channels, in particular the 2.1 μm channel of MODIS, than the ones currently used. This channel is chosen for investigation as fires are expected to emit a significant amount of energy in this bandwidth and as it is available at a native resolution of 500 m on MODIS; double the resolution of the 3 μm and 11 μm channels. The modelling of blackbodies of typical bushfire temperatures shows that a fire detection method based on the 2.1 μm channel will not be able to replace the current methods. Blackbodies of temperatures around 600 to 700 K, that are common for smoldering fires, do not emit a great amount of energy at 2.1 μm. It would be hardly possible to detect those fires by utilizing the 2.1 μm channel. The established methods based on the 3 μm and 11 μm channels are expected to work better in these cases. Blackbodies of typically flaming fires (above 800 K) however show a very high emission around 2.1 μm that should make their detection using the 2.1 μm channel possible. / In order to develop a fire detection method based on the 2.1 μm channel, it is necessary to differentiate between the radiance caused by a fire of sub pixel size and the radiance of a pixel caused by the reflection of sunlight. This is attempted by using time series of past observations to model a reflectance value for a given pixel expected in absence of a fire. A fire detection algorithm exploiting the difference between the expected and observed reflectance is implemented and its detection results are compared to high resolution ASTER fire maps, the standard MODIS fire detection algorithm (MOD14) and burnt area maps. The detections of the method based on the 2.1 μm channel are found to correspond very well with the other three datasets. However, the comparison showed detections that do not align with MOD14 active fire detections but are generally aligned with burn areas. This phenomena has to be investigated in the future.

Depuis 2005, le Mato Grosso est devenu le premier Etat producteur de soja du Brésil. Cette évolution est le résultat de la progression d'un front pionnier qui a apporté un développement socioéconomique indéniable, mais a entraîné une déforestation intense. Cette thèse vise à définir l'état des interactions climat / société au Mato Grosso en déterminant le rôle de la dynamique du soja en tant que moteur du front pionnier et en évaluant comment les précipitations sont un facteur guidant l'évolution des territoires du soja. Ces dynamiques sont étudiées à partir de classifications de séries temporelles de données satellitaires MODIS TERRA/EVI. Les résultats indiquent que l'expansion agricole entre 2000 et 2007 explique 12% de la déforestation au Mato Grosso ; 71% des nouvelles cultures de soja au Mato Grosso ont été semées sur des parcelles anciennement défrichées. Actuellement, le secteur agricole semble rentrer dans une nouvelle phase de développement axée sur l'intensification agricole : 46% de l'augmentation de la production agricole est due à des changements de pratiques culturales. Ceci est la conséquence de l'adoption de systèmes de production en double cultures commerciales qui concernent 30% des surfaces agricoles en 2007 (contre 6% en 2000). Ces changements sont affectés par une forte variabilité spatiale qui est notamment liée aux conditions pluviométriques (cumul annuel, début, fin et durée de la saison des pluies). Celles-ci sont déterminées à partir des estimations de précipitations des produits TRMM 3B42. Les résultats démontrent que les régions les plus intensives sont celles où la saison des pluies est la plus longue et où le volume précipité est le plus important.

La plaine semi-aride du Tensift au centre du Maroc est une région confrontée à des difficultés croissantes en terme de gestion de l'eau (pluviométrie faible et irrégulière, croissance des besoins sous l'effet de la démographie galopante et l'extension des zones irriguées). Dans ce contexte et dans le cadre du projet SudMed, l'objectif de la thèse est de décrire, dans l'espace (à la résolution kilométrique) et sur de longues périodes temporelles (la décennie), le fonctionnement hydrique des agro-systèmes irrigués de la plaine du Tensift (~3000 km²). La méthodologie développée repose sur le contrôle de modèles agro-météorologiques par des données satellites issues de capteurs optique à large champ (données MODIS de 2000 à 2006). Dans un premier temps, nous nous sommes intéressés à l'occupation du sol, connaissance préalable à la quantification des besoins en eau des cultures. Etant donné la résolution spatiale de MODIS (250 m), nous avons eu recours à des méthodes de désagrégation, qui ont permis d'identifier et de cartographier les trois principales classes d'occupation du sol: zones non irriguées, cultures annuelles, plantations arborées. Dans une deuxième partie, nous avons utilisé cette information pour spatialiser un modèle de bilan hydrique, en étudiant tout particulièrement les termes d'évapotranspiration et d'irrigation. L'évaluation du modèle est effectuée par comparaison: (1) aux données collectées sur les parcelles d'expérimentation du projet SudMed; (2) à des cartes établies à l'aide d'images à haute résolution spatiale et temporelleFORMOSAT-2 et (3) aux volumes d'eau des barrages distribués par l'office agricole régional. Cette étude ouvre des perspectives pour l'estimation des volumes d'eau d'irrigation transitant par les différents réseaux d'irrigation, et en particulier ceux prélevés dans la nappe phréatique du Tensift.

As human populations increase along coastal watersheds, the understanding and monitoring of Harmful Algal Blooms (or red tides) is an increasingly important issue. A consistent method for accurately detecting red tides using satellite measurements would bring tremendous societal benefits to resource managers, the scientific community and to the public as well. In the West Florida Shelf, blooms of the toxic dinoflagelate Karenia brevis are responsible for massive red tides causing fish kills, massive die-offs of marine mammals, shellfish poisoning, and acute respiratory irritation in humans. In this work, for the first time a long-term dataset (2002~2006) the MODerate Resolution Imaging Spectroradiometer (MODIS) is compared (i.e., matched-up) to an extensive data set of in situ cell counts of K. brevis; provided by the Florida Fish and Wildlife Conservation Commission's Fish and Wildlife Research Institute. The pairing of remote sensing data with near-coincident field measurements of cell abundance was successfully used to derive the basis for the development of an alternative ocean color based algorithm for detecting the optical signatures associated with blooms of K. brevis in waters of the West coast of Florida. Conclusions are geographically limited to the Central West Florida Shelf during the boreal Summer-Fall (i.e., the K. brevis blooming season). The new simpler Empirical approach is compared with other two more complicated published techniques. Their potential is verified and uncertainties involved in the identification of blooms of K. brevis are presented. The results shown here indicate that the operational NOAA method for detecting red tides in the Gulf of Mexico (Stumpf et al., 2003; Tomlinson et al., 2004) performs less accurately than the other two algorithms at identifying K. brevis blooms. The sensitivity and specificity of the Bio-optical (Cannizzaro, 2004; Cannizzaro et al., 2008) and Empirical algorithms are simultaneously maximized with an optimization procedure. The combined use of these two optimized algorithms in sequence provides another new monitoring tool with improved accuracy at detecting K. brevis of blooms. The ability of this Hybrid scheme ranges about 80% for both sensitivity and specificity; and the capability at predicting a correct red tides is 70%, and ~85% for non-blooms conditions. The spatial and temporal knowledge of K. brevis blooms can improve the direction of field monitoring to areas that should receive special attention, allowing better understanding of the red tide phenomenon by the scientific community. The relevant agencies can also develop more appropriate mitigation action plans, and public health guidance can be improved with the enhancement of sustainable costal management strategies.

The Greenland Ice Sheet is the largest ice sheet in the northern hemisphere. Ongoing melting of the ice sheet, resulting in increased mass loss relative to the longer term trend, has raised concerns about the stability of the ice sheet. Melt water generated at the surface is temporarily stored in supra-glacial lakes on the ice sheet. Connections between melt water generation, storage and ice sheet dynamics highlight the importance of the surface hydrological system. In this thesis different methods are used that improve our ability to observe the supra-glacial lake system on the west Greenland Ice Sheet. This region of the Greenland Ice Sheet has the most extensive supra-glacial hydrological system with a dense network of streams connecting lakes that can exceed several square kilometres in area. Synthetic Aperture Radar (SAR) and visible-near infrared (VNIR) images are used to explore the potential of different sensor systems for regular observations of the supra-glacial lakes. SAR imagery is found to be a useful complement to VNIR data. VNIR data from moderate resolution sensors are preferred as these provide high temporal resolution data, ameliorating problems with cloud cover. The dynamic nature of the lakes makes automated classification difficult and manual mapping has been widely used. Here a new method is proposed that improves on existing methods by automating the identification and classification of lakes, and by introducing a flexible system that can capture the full range of lake forms. Applying our new method we are better able to analyse the evolution of lakes over a number of melt seasons. We find that lakes initiate after approximately 40 positive degree days. Most lakes exist for less than 20 days before draining, or later in the season, and less often, freezing over. Using the automated method developed in this thesis lakes have been mapped in imagery from 2001–2010 at approximately five day intervals. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript. Paper 5: Manuscript.</p>