L’objectif de la thèse s’inscrit dans le cadre de contribuer à l’estimation des paramètres du système des carbonates en Mer Méditerranée, en particulier la pression partielle du CO2 dans l’eau (pCO2sw), l’alcalinité totale (AT), le carbone inorganique total (CT) et le pH. En premier lieu, on a calculé à partir des données des campagnes Boum en 2008 et MedSeA en 2013 les coefficients de mélange des masses d’eau dans les bassins Ouest et Est. L’analyse de ces coefficients nous a permis d’étudier l’évolution des masses d’eau en Mer Méditerranée entre les années 2008 et 2013.En deuxième lieu, on a présenté à partir des données de la mission MedSeA en mai 2013, les résultats des mesures récentes de pCO2sw sur une section longitudinale assez étendue allant du détroit de Gibraltar jusqu’au sous-bassin Levantin. Les résultats ont indiqué que les bassins Ouest et Est sont gouvernés par deux régimes différents de pCO2sw. Ces deux régimes ont été influencés par les propriétés physico-chimiques assez distinctes des deux bassins. A partir des mesures directes de pCO2sw on a calculé les flux journaliers de CO2 à travers l’interface air-mer en mai 2013 et cela pour le trajet couvert par la mission MedSeA. Pour aboutir à une analyse plus globale on s’est référé dans une étude ultérieure, aux données des campagnes Thresholds et MedSeA. On a établit ainsi deux équations pour estimer en mai 2007 et 2013, la pCO2sw à partir des données satellites de température de surface, Chlorophylle_a et l’index de la couleur de la matière organique dissoute. Puis, on a calculé et cartographié les flux air-mer de CO2 en mai 2013 à l’échelle de toute la Mer Méditerranée et pour une résolution spatiale de 4 km.Ensuite, on a établi à partir des données de la mission MedSeA, des régressions linéaires pour estimer l’AT et le CT à partir de la salinité, et cela pour chaque sous-bassin de la Mer Méditerranée et pour plusieurs intervalles de profondeur. Ultérieurement, on s’est concentré aux données physico-chimiques dans les eaux de surface, compilées de plusieurs campagnes océanographiques entre 1998 et 2013. Les équations établies pour estimer l’AT et le CT dans les eaux de surface, ont indiqué que le meilleur polynôme inclue la salinité et la température. Ces polynômes ont été appliqués sur les cartes climatologiques de température et de salinité du World Ocean Atlas, pour cartographier les variabilités spatiales et saisonnières de l’AT et du CT sur une moyenne de 7 ans. En outre, à partir des données de la mission MedSeA, on a estimé les concentrations en carbone anthropique (CANT) et la variation de l’acidification (∆pH) en Mer Méditerranée. Les résultats ont indiqué que la Mer Méditerranée est fortement contaminée par le CANT avec des concentrations bien plus élevées que celles enregistrées dans l’océan Pacifique ou Indien. Le calcul du ∆pH a indiqué que la Mer Méditerranée est déjà acidifiée de la surface jusqu’en profondeur. Enfin, on a présenté un modèle pour prédire le ∆pH en fonction de concentrations théoriques de CANT. On a montré que le seuil en CANT pour lequel l’acidification va fortement s’intensifier en Mer Méditerranée est déjà atteint. Aussi, les eaux profondes des bassins Occidental et Oriental, deviendront très probablement sous saturées par rapport à la calcite et à l’aragonite d’ici la fin du siècle prochain. / The objective of the thesis is to contribute to the estimation of the carbonate system parameters in the Mediterranean Sea, in particular the partial pressure of CO2 in water (pCO2sw), total alkalinity (AT), total inorganic carbon (CT) and pH.The study was initiated by an adequate calculation of the water masses mixing coefficients in the Western and Eastern basins, using data from the Boum and MedSeA cruises in 2008 and 2013, respectively. The analysis of the mixing coefficients, allowed us to study the evolution of water masses in the Mediterranean Sea between the years 2008 and 2013.Subsequently, using data from the 2013 MedSeA cruise, we presented the results of recent measurements of pCO2sw on a wide longitudinal section from the Strait of Gibraltar to the Levantine sub-basin. The results indicated that the Western and Eastern basins were characterized by two different pCO2sw regimes. These regimes were mainly affected by the distinctive physico-chemical properties of each basin. From the direct measurements of pCO2sw we calculated along the track of the MedSeA cruise, the daily CO2 fluxes across the air-sea interface in May 2013. To achieve a more comprehensive analysis, we referred in a consecutive study to the data of the Thresholds and MedSeA cruises. From these data, we provided two equations to estimate in May 2007 and 2013; pCO2sw from satellite data of sea surface temperature, Chlorophyll_a and the chromophoric dissolved organic matter index. Furthermore, we calculated and mapped the air-sea CO2 fluxes in May 2013 across the whole Mediterranean Sea, with a spatial resolution of 4 km.Successively, we established from the MedSeA cruise data, linear regressions to estimate AT and CT from salinity, in each sub-basin of the Mediterranean Sea and for several depths. Later on, we focused on the physico-chemical data in surface waters, compiled from several oceanographic cruises between 1998 and 2013. The equations developed to estimate the AT and CT in surface waters, indicated that it is best to include in these polynomials both salinity and temperature. These polynomials were applied to the climatological fields of salinity and temperature of the World Ocean Atlas, in order to map the spatial and seasonal variability of AT and CT on a 7 years average.Moreover, we estimated from the MedSeA cruise data, the concentrations of anthropogenic carbon (CANT) and the variation of acidification (ΔpH) in the Mediterranean Sea. The results indicated that the Mediterranean Sea is heavily contaminated by CANT, with higher concentrations than those recorded in the Pacific or Indian Ocean. Also, the calculated ΔpH indicated that the Mediterranean Sea is already acidified from the surface to the deep waters. Finally, we presented a model to predict the ΔpH according to theoretical concentrations of CANT. Consequently, we showed that we already reached the tipping point of CANT, for which the acidification will strongly intensify in the Mediterranean Sea. Moreover, the deep waters of the Western and Eastern basins are very likely to become under saturated in calcite and aragonite by the end of the next century.

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Rectangular-shaped building detection from high resolution aerial/satellite images is proposed for two different methods. Shadow information plays main role in both of these algorithms. One of the algorithms is based on Hough transformation, the other one is based on mean shift segmentation algorithm. Satellite/aerial images are firstly converted to YIQ color space to be used in shadow segmentation. Hue and intensity values are used in computing the ratio image which is used to segment shadowed regions. For shadow segmentation Otsu&rsquo / s method is used on the histogram of the ratio image. The segmented shadow image is used as the input for both of two building detection algorithms. In the proposed methods, shadowed regions are believed to be the building shadows. So, non-shadowed regions such as roads, cars, trees etc. are discarded before processing the image. In Hough transform based building detection algorithm, shadowed regions are firstly segmented one by one and filtered for noise removal and edge sharpening. Then, the edges in the filtered image are detected by using Canny edge detection algorithm. Then, line segments are extracted. Finally, the extracted line segments are used to construct rectangular-shaped buildings. In mean shift based building detection algorithm, image is firstly segmented by using mean shift segmentation algorithm. By using shadow image and segmented image, building rooftops are investigated in shadow boundaries. The results are compared for both of the algorithms. In the last step a shadow removal algorithm is implemented to observe the effects of shadow regions in both of two implemented building detection algorithms. Both of these algorithms are applied to shadow removed image and results are compared.

This thesis is devoted to the shadow detection and compensation in aerial images with application of the detection results to building height detection. Shadows could be defined as the parts of the scene that is not directly illuminated by a light source due to obstructing object or objects. Usually the shadows in images or video are undesirable, since they could cause degradation of the expected results during processing of the image or video for object detection, segmentation, scene surveillance or similar purposes. However shadow information could also be used for beneficial purposes like revealing information about the object&rsquo / s shape, orientation and even about the light source. In this thesis firstly shadow detection methods are overviewed. Beside the selected methods from literature, some novel approaches are also proposed and experimented. Then shadow compensation methods are overviewed and experimented. Finally an example of beneficial utilizations of shadow information is studied, where buildings&rsquo / heights are estimated from their shadow length and sun angles.

Road extraction from satellite or aerial images is a popular issue in remote sensing. Extracted road maps or networks can be used in various applications. Normally, maps for roads are available in geographic information systems (GIS), however these informations are not being produced automatically. Generally they are formed with the aid of human. Road extraction algorithms are trying to detect the roads from satellite or aerial images with the minimum in-teraction of human. Aim of this thesis is to analyze a previously defined algorithm about road extraction and to present alternatives and possible improvements to this algorithm. The base-line algorithm and proposed alternative algorithm and steps are based on mean-shift segmen-tation procedure. Proposed alternative methods are generally based on structural features of the image. Firstly, fundamental definitions of applied algorithms and methods are explained, mathematical definitions and visual examples are given for better understanding. Then, the chosen baseline algorithm and its alternatives are explained in detail. After the presentation of alternative methods, experimental results and inferences which are obtained during the implementation and analysis of mentioned algorithms and methods are presented.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Com a necessidade de extrair as informações contidas nas imagens de satélite de forma rápida, eficiente e econômica, são utilizadas cada vez mais as técnicas computacionais de processamento de imagens como a de segmentação automática. Segmentar uma imagem consiste em dividí-la em regiões através de um critério de similaridade, onde os pixels que estão contidos nestas possuem características semelhantes, como por exemplo, nível de cinza, textura, ou seja, a que melhor represente os objetos presentes na imagem. Existem vários exemplos de algoritmos segmentadores, como o de crescimento de regiões onde os pixels crescem e são aglutinados formando regiões. Para determinar quais os melhores parâmetros utilizados nestes algoritmos segmentadores é necessário que se avalie os resultados a partir dos métodos mais utilizados, que são os supervisionados onde há necessidade de uma imagem de referência, considerada ideal fazendo com que se tenha um conhecimento a priori da região de estudo. Os não supervisionados, onde não há a necessidade de uma imagem de referência, fazendo com que o usuário economize tempo. Devido à dificuldade de se obter avaliadores para diferentes tipos de imagem, é proposta a metodologia que permite avaliar imagens que possuam áreas com vegetação, onde serão formadas grandes regiões (Crianass) e o que avaliará as imagens com áreas urbanas onde será necessário mais detalhamento (Cranassir). / With the need of extracting the information contained in satellite images in a quick, efficent and economic way computational image process tecniques are being used more frequently, such as the automatic segmentation. Segmenting an image consists on dividing it in regions acording to a similarity standard, where the pixels which are contained there have the same characteristic, for example, level of gray, texture, that is, the one that best represents the objects on the image. There are lots of examples of segmentary algorithm like the development of areas where the pixels 'grow" and are agglutinated forming regions. To determine which are the best parameters utilized in these segmentary algorithms it is necessary to evaluate the results from the methods used more often, they are the supervized where there is a need of a reference image, considered ideal, giving us a priori knowledge of the regions in study. The unsupervised, where there is not the need of a reference image, make the user save time. Due to the difficulty of obtaining evaluators, for different kinds of images, is proposed the methodology that allows to evaluate images that have vegetation areas, where it will be formed large regions (Crianass), and the one that will evaluate the images with urban areas, where it will be needed more detailing (Cranassir).

Orientador: Sérgio Campos / Banca: Zacarias Xavier de Barros / Banca: Osmar Delmanto Junior / Banca: Teresa Cristina T. Pissarra / Banca: Sergio Paschoal de Campos / Resumo: A grande importância da citricultura no Estado de São Paulo, particularmente no Município de Botucatu, e sua grande expansão em área nos últimos anos e o avanço das técnicas de monitoramento ambiental, como o sensoriamento remoto motivou a presente pesquisa. O objetivo deste trabalho foi avaliar as alterações espaço-temporal da citricultura no Município de Botucatu-SP, no período de 1962 a 2005, utilizando-se de: fotografias aéreas pancromáticas de 1962, 1972 e 1977 e coloridas de 2000 e 2005, imagens de satélite Landsat 2000 e 2005; juntamente com técnicas de Sensoriamento Remoto e Sistemas de Informações Geográficas, visando avaliar as diferenças na determinação de áreas e perímetros, por meio dos aplicativos: CartaLinx, SIG-Idrisi e SPLAN. Os resultados obtidos permitem concluir que: a área ocupada pela citricultura no Município de Botucatu-SP em 2000 representava 5,22% da área total do Município; passando a ocupar 8,63 % no ano de 2005, representando um incremento de 3,41% na área total estudada e uma expansão de 65,27% da área citrícola no período de cinco anos; sendo que, no período de 43 anos (1962 a 2005), houve um incremento de 12722,56 ha desta área. As áreas obtidas por meio de fotografias aéreas e avaliadas pelo Carta Linx apresentam valores mais próximos da verdade terrestre para a determinação de áreas e perímetros. A falta de nitidez das imagens de satélite dificulta a identificação de pequenas áreas de cobertura vegetal; o SIG-Idrisi apresentou discrepâncias para a determinação de perímetros, em função de trabalhar de forma matricial e que o SPLAN, é próximo do Carta Linx, para a determinação de áreas e perímetros, devido ao fato de ambos trabalharem de forma vetorial / Abstract: The great importance of citrus in São Paulo, particularly in Botucatu, its major expansion in area in recent years and the advanced techniques for environmental monitoring, such as remote sensing, are all factors that have motivated the present research. The aim of this study was to evaluate the spatial and temporal changes of citrus in Botucatu-SP from 1962 to 2005. For this, was used, panchromatic aerial photographs from 1962, 1972 and 1977, color ones from 2000 and 2005, Landsat satellite images from 2000 and 2005. Along with those, Remote Sensing and Geographic Information Systems were also used in order to evaluate the differences in determining areas and perimeters, by using software such as CartaLinx, GISIdrisi and SPLAN. The results showed that the area occupied by citrus in Botucatu-SP was 5.22% of the total area of the county in 2000. In 2005, it represented 8.63%, showing a 3.41% increase of the total area and an expansion of 65.27% of the citrus area within five years, being that during the period of 43 years (1962-2005), there was an increase of 12722.56 ha of this area. The areas obtained from aerial photographs and evaluated with CartaLinx present values closer to ground truth for the determination of areas and perimeters. The lack of accuracy in the satellite images makes it difficult to identify small areas of vegetation. GISIdrisi showed discrepancies in perimeter determination, as it works with matrixes. SPLAN is similar to CartaLinx for the determination of areas and perimeters, due to the fact that both work with vectors / Doutor

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Com a necessidade de extrair as informações contidas nas imagens de satélite de forma rápida, eficiente e econômica, são utilizadas cada vez mais as técnicas computacionais de processamento de imagens como a de segmentação automática. Segmentar uma imagem consiste em dividí-la em regiões através de um critério de similaridade, onde os pixels que estão contidos nestas possuem características semelhantes, como por exemplo, nível de cinza, textura, ou seja, a que melhor represente os objetos presentes na imagem. Existem vários exemplos de algoritmos segmentadores, como o de crescimento de regiões onde os pixels crescem e são aglutinados formando regiões. Para determinar quais os melhores parâmetros utilizados nestes algoritmos segmentadores é necessário que se avalie os resultados a partir dos métodos mais utilizados, que são os supervisionados onde há necessidade de uma imagem de referência, considerada ideal fazendo com que se tenha um conhecimento a priori da região de estudo. Os não supervisionados, onde não há a necessidade de uma imagem de referência, fazendo com que o usuário economize tempo. Devido à dificuldade de se obter avaliadores para diferentes tipos de imagem, é proposta a metodologia que permite avaliar imagens que possuam áreas com vegetação, onde serão formadas grandes regiões (Crianass) e o que avaliará as imagens com áreas urbanas onde será necessário mais detalhamento (Cranassir). / With the need of extracting the information contained in satellite images in a quick, efficent and economic way computational image process tecniques are being used more frequently, such as the automatic segmentation. Segmenting an image consists on dividing it in regions acording to a similarity standard, where the pixels which are contained there have the same characteristic, for example, level of gray, texture, that is, the one that best represents the objects on the image. There are lots of examples of segmentary algorithm like the development of areas where the pixels 'grow" and are agglutinated forming regions. To determine which are the best parameters utilized in these segmentary algorithms it is necessary to evaluate the results from the methods used more often, they are the supervized where there is a need of a reference image, considered ideal, giving us a priori knowledge of the regions in study. The unsupervised, where there is not the need of a reference image, make the user save time. Due to the difficulty of obtaining evaluators, for different kinds of images, is proposed the methodology that allows to evaluate images that have vegetation areas, where it will be formed large regions (Crianass), and the one that will evaluate the images with urban areas, where it will be needed more detailing (Cranassir).

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-02-24T13:58:39Z No. of bitstreams: 2 Dissertação - Daniela de Oliveira Albanez - 2017.pdf: 10127114 bytes, checksum: 4c037243629d84539257a8febc621fa8 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-02-24T13:59:39Z (GMT) No. of bitstreams: 2 Dissertação - Daniela de Oliveira Albanez - 2017.pdf: 10127114 bytes, checksum: 4c037243629d84539257a8febc621fa8 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-02-24T13:59:39Z (GMT). No. of bitstreams: 2 Dissertação - Daniela de Oliveira Albanez - 2017.pdf: 10127114 bytes, checksum: 4c037243629d84539257a8febc621fa8 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-02-15 / Image segmentation is one of image processing that problems that deserve special interest of the scientific community, given its real utility and application in various areas as medicine, geography, engineering, mathematics and computing, just to name a few. Much of the recent interest in segmentation has been motivated by the availability of satellite images on the Earth’s surface, which can be transformed into concrete knowledge, aiming at land use monitoring and data mining. This work proposes a new segmentation method, using Arficial Intelligence techniques, more specifically Artificial Neural Networks (ANNs), and compare its results of segmentation of satellite images with the original method. The binarized results are compared with the ground truth for the validation of the proposed segmentation method. Experimental results, quantative analysis of segmentation results, indicating that the proposed segmentation method generates better results and a decaying of 36.60% in the total average computacional time when compared with the original method. / Segmentação de Imagens é um dos problemas de processamento de imagens que mercê especial interesse da comunidade científica, tendo em vista sua real utilidade e aplicação em várias áreas do conhecimento como a medicina, geografia, engenharia, matemática e computação, só para citar algumas. Grande parte do interesse recente sobre segmentação foi motivado pela disponibilidade de imagens de satélite sobre a superfície da Terra, que podem ser transformadas em conhecimento concreto, visando o monitoramento e a mineração do uso da terra. Este trabalho propõe um novo método de segmentação, através de técnicas de Inteligência Artificial, mais especificamente pelas Redes Neurais Artificiais (RNA’s), e compara seus resultados de segmentação de imagens de satélite com o método original descrito na literatura. Os resultados binarizados são comparados com o ground truth para a validação do método de segmentação proposto. Resultados experimentais, realizados através da analise quantitativa dos resultados de segmentação, indicam que o método de segmentação proposto produz melhores resultados e uma redução média total do desempenho computacional de 36.60% em relação ao método original.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A reservoir presents different environmental traits as a function of the flooded area, water circulation pattern, residence time and nutrients entrance. This situation define the aquatic compartments. The objective was use limnological parameter dynamic and spectral data to identify aquatic compartments in the Rodolfo Costa e Silva reservoir, located on central region of the State of Rio Grande do Sul, on southern region of Brazil. The methodology was based on the measure of water transparence with Secchi disc, Total of Suspended Solids (TSS) and chlorophyll a, b and c. These data were monthly collected in 21 sampling points, distributed over the reservoir during hydrologic year (Oct. 2005 to Sept. 2006). However, chlorophyll samples were collected only two times in autumn season. Satellites images from China-Brazil Earth Resources Satellite 2 (CBERS 2 CCD) and Landsat 5 (TM) were used to make a comparison with limnological and field spectral data. The spatial distribution of limnological parameters was done after data interpolation (weighted average) and its analyses allowed the discrimination of aquatic compartments. During the hydrologic year the transparence changed between 100 and 315 cm and could be divided in two periods: a period with low transparences, from August to November (marked by land tillage for summer crop) and; period with high transparence, from December to June. Based on this variable, the reservoir presented three compartments: a) upstream, with lower transparence; b) downstream, with higher transparence; c) central region, even with high transparence. The TSS ranged from 0.17 to 14.16 mg/L in the hydrologic year. Its behavior was inversely to the water transparence but presented the same three compartments than transparence. The chlorophyll concentration varied from 0.63 to 24.19 μg/L and defined two compartments: upstream and downstream. A larger input of nutrients in upstream let the development of phytoplankton (chlorophylls). Results from CCD and TM images were better when TSS concentration was greater and transparence smaller, associated to the highest data variance. Concentrations of TSS up to 4 mg/L periods with low transparence allowed identify aquatic compartments with blue band (centered on 450 nm) and the red band (centered on 661 nm). The chlorophylls a and c showed absorption bands on the field spectrum of reflectance, making possible establish correlations with limnological parameters (TSS and transparence). Finally, the aquatic compartments that were found out are specially related to the entrance of organic and inorganic matter from terrestrial environment. TSS and chlorophyll decreases into downstream. / Normalmente, um reservatório apresenta diferentes características ambientais em função das áreas alagadas, dos diferentes padrões de circulação, do tempo de residência e entrada de nutrientes, que definem diferentes compartimentos aquáticos. A caracterização limnológica e espectral, com a identificação da dinâmica dos compartimentos aquáticos, foram realizadas no reservatório Rodolfo Costa e Silva RS (Brasil). A metodologia baseou-se na coleta de dados de transparência da água medida pelo disco de Secchi, Totais de Sólidos em Suspensão (TSS) e clorofila a, b e c em 21 pontos amostrais, distribuídos em todo o reservatório e obtidos mensalmente para compor um ano hidrológico (Out. 2005 a Set. 2006); com exceção da clorofila, que foi medida em duas datas durante o outono. Imagens dos satélites CBERS 2 CCD e Landsat 5 TM foram utilizadas para relacionar com os dados limnológicos de campo. A distribuição espacial desses dados limnológicos foi identificada por interpolação por média ponderada, para posterior discriminação dos compartimentos aquáticos. A transparência da água apresentou uma variação no ano hidrológico de 100 a 315 cm e pode ser dividida em dois períodos: das baixas transparências, compreendendo o período de agosto a novembro (período de preparo de solo para a safra agrícola de verão); e de altas transparências, compreendendo o período de dezembro a junho. Essa variável forma três compartimentos: a) o de montante, com menor transparência; b) o de jusante, com maior transparência; c) junto ao dique, de elevada transparência. O TSS apresentou uma amplitude de 0,17 a 14,16 mg/L no ano hidrológico, com comportamento inversamente proporcional ao da transparência definindo compartimentos aquáticos semelhantes. As clorofilas com variação de 0,53 a 24,19 μg/L apresentaram os dois compartimentos aquáticos: o de montante e o de jusante. O maior aporte de nutrientes, à montante do reservatório, proporcionaram o desenvolvimento do fitoplâncton (clorofilas). Os resultados obtidos com imagens CCD e TM foram melhores, quando as concentrações de TSS foram maiores e as transparências foram menores, acompanhados de maior variância. As baixas transparências e as concentrações de TSS maiores que 4 mg/L permitiram identificar compartimentos aquáticos nas bandas azul (450 nm) e vermelha (661 nm). As clorofilas a e c apresentaram bandas de absorção nos espectros de reflectância, permitindo estabelecer correlações. Por fim, os compartimentos aquáticos encontrados estão relacionados, principalmente, ao fornecimento de matéria orgânica e inorgânica oriundas do ambiente terrestre para o sistema aquático, verificado no setor montante, e sua concentração diminui no sentido jusante do reservatório.