The inspection of power lines is an important process to maintain a stable electrical infrastructure. Simultaneously it is very time consuming task considering there are 164 000 km of power lines in Sweden alone. A cheaper and more sustainable approach is an automatic inspection with drones. But for a successful inspection with drones, exact power line coordinates is needed, which is not always available. To identify power lines in satellite images a machine learning approach was implemented. In machine learning, semantic segmentation is the process of pixel-wise classification of an image. Where you not only label the entire image, but every pixel individually. This way not only the existence of a power line will be identified, but their position inside the image. This thesis aims to investigate if semantic segmentation is an effective approach to locate power lines in satellite images. And what methods can be used on the segmented output data to extract linestring coordinates representing the power line. Linear regression and a polygon centerline extraction method was implemented on the segmented output data to define a line that represents the true location of the power line. The semantic segmentation model could find power lines where they were clearly visible, but struggled where they were not very visible. From good output data from the segmentation model, the linear regression and the polygon centerline extraction methods could successfully extract linestring coordinates that represented the true location of the power line. In the best case around 67% of power lines was correctly identified. But still, with good output data from the model, complex shapes such as intersections might still get bad results. Even if the approach needs further work, and cannot reliably identify all power lines in the current state, it has proven that this could be a promising method to identify power lines in satellite images.

The Sun is of fundamental importance to life on earth and is studied by scientists from many disciplines. It exhibits phenomena on a wide range of observable scales, timescales and wavelengths and due to technological developments there is a continuing increase in the rate at which solar data is becoming available for study which presents both opportunities and challenges. Two satellites recently launched to observe the sun are STEREO (Solar TErrestrial RElations Observatory), providing simultaneous views of the SUN from two different viewpoints and SDO (Solar Dynamics Observatory) which aims to study the solar atmosphere on small scales and times and in many wavelengths. The STEREO and SDO missions are providing huge volumes of data at rates of about 15 GB per day (initially it was 30 GB per day) and 1.5 terabytes per day respectively. Accessing these huge data volumes efficiently at both high spatial and high time resolutions is important to support scientific discovery but requires increasingly efficient tools to browse, locate and process specific data sets. This thesis investigates the development of new technologies for processing information contained in multiple and overlapping images of the same scene to produce images of improved quality. This area in general is titled Super Resolution (SR), and offers a technique for reducing artefacts and increasing the spatial resolution. Another challenge is to generate 3D images such as Anaglyphs from uncalibrated pairs of SR images. An automated method to generate SR images is presented here. The SR technique consists of three stages: image registration, interpolation and filtration. Then a method to produce enhanced, near real-time, 3D solar images from uncalibrated pairs of images is introduced. Image registration is an essential enabling step in SR and Anaglyph processing. An accurate point-to-point mapping between views is estimated, with multiple images registered using only information contained within the images themselves. The performances of the proposed methods are evaluated using benchmark evaluation techniques. A software application called the SOLARSTUDIO has been developed to integrate and run all the methods introduced in this thesis. SOLARSTUDIO offers a number of useful image processing tools associated with activities highly focused on solar images including: Active Region (AR) segmentation, anaglyph creation, solar limb extraction, solar events tracking and video creation.

Yes / In this paper, we introduce two novel models for processing real-life satellite images to quantify and then visualise their magnetic structures in 3D. We believe this multidisciplinary work is a real convergence between image processing, 3D visualization and solar physics. The first model aims to calculate the value of the magnetic complexity in active regions and the solar disk. A series of experiments are carried out using this model and a relationship has been indentified between the calculated magnetic complexity values and solar flare events. The second model aims to visualise the calculated magnetic complexities in 3D colour maps in order to identify the locations of eruptive regions on the Sun. Both models demonstrate promising results and they can be potentially used in the fields of solar imaging, space weather and solar flare prediction and forecasting.

With advances in modern technology, satellite-based data is rapidly becoming a viable option for geotechnical site characterization. Commercial satellite data offers high resolution (~25-200 cm), increased spatial coverage on the order of kilometers, short revisit times leading to high temporal coverage, and allows for data to be analyzed rapidly and remotely without the need for physical site access. These advantages are particularly attractive for characterizing coastal sites, where both the strength properties and moisture content can change rapidly in response to tidal stages, wave runup, and storm events. To date, there have been limited investigations into the use of satellite-based data for characterizing geotechnical properties of sandy beach sediments. Furthermore, the use of these moisture contents to estimate the soil strength of beaches has been limited. The goal of this research was to develop pathways to estimate the moisture content of sandy beach sites utilizing satellite-based data. For this study, both optical and synthetic aperture radar (SAR) images were collected at two sites: the Atlantic beach near the US Army Corps of Engineers Field Research Facility in Duck, North Carolina and three distinct sites located near Yakutat, Alaska (Cannon Beach, Ocean Cape, and Point Carrew). During satellite overflight, ground measurements of moisture content, grain size, unit weight, porosity, and bearing capacity were collected. Using the field measurements, this research (1) developed a framework to estimate the moisture content of sandy beach sediments from satellite-based optical images; (2) investigated the necessary collection parameters to estimate the moisture content from SAR images; and (3) developed a framework to estimate the bearing capacity of sandy beaches using moisture contents derived from satellite-based images. The results of this study demonstrated that optical images can produce reasonable estimates of the moisture content when compared to field measurements and are strongly influenced by local morphology. Additionally, SAR images with incidence angles of 30°-50° produced the best results when compared to field measurements. Finally, using the spatial estimates moisture content produced from satellite data and standard sediment, maps of bearing capacity can be developed to predict beach trafficability. / Doctor of Philosophy / The strength of sandy beaches is impacted by the density, particle size and shape, distribution of grain sizes, mineralogy, and moisture content. For coastal sites, which typically have a dominant mineralogy and a limited range of grain sizes, a main factor changing is the moisture content. This varying moisture content can result in the increase or decrease in soil strength, and impacts modelling for coastal challenges such as erosion or beach trafficability (i.e., the ability to drive on the beach) on large scales. It is common to measure moisture content through sampling or moisture probes, but these represent point measurements and may not accurately capture the spatial and temporal moisture contents at a beach. Recently, satellite-based images have become popular for assessing processes and environmental changes over large areas. However, their use for mapping moisture content at sandy beaches has been limited, and the proper models are unknown. As such, the goal of this research is to investigate the use of satellite images to map moisture content over large areas. For this study, measurements were conducted at two sites: an Atlantic beach located near the US Army Corps of Engineers Field Research Facility in Duck, North Carolina and three distinct sites located near Yakutat, Alaska (Cannon Beach, Ocean Cape, and Point Carrew). Simultaneously with ground measurements, two different types of images were collected. The first, optical data, collects data over the visible (400-700 nm) and near infrared (700-1300 nm) regions of the electromagnetic spectrum. These satellites use the sun to light the scene and the amount of energy reflected back to the satellite is used to estimate the moisture content. The second, X-band synthetic aperture radar (SAR) data (wavelengths of 3.1 cm), sends its own energy source to the ground and uses the returned energy to estimate the moisture content. Both optical and SAR are able to produce reasonable estimates of moisture content when compared to field measurements. These estimated values of moisture content are then tested in a model to estimate the sand strength, with those estimated values also following the expected trends. Ultimately, this work can be used to contribute to understanding how moisture content varies at sandy beaches and improve trafficability predictions in sandy beach environments.

The Sun is of fundamental importance to life on earth and is studied by scientists from many disciplines. It exhibits phenomena on a wide range of observable scales, timescales and wavelengths and due to technological developments there is a continuing increase in the rate at which solar data is becoming available for study which presents both opportunities and challenges. Two satellites recently launched to observe the sun are STEREO (Solar TErrestrial RElations Observatory), providing simultaneous views of the SUN from two different viewpoints and SDO (Solar Dynamics Observatory) which aims to study the solar atmosphere on small scales and times and in many wavelengths. The STEREO and SDO missions are providing huge volumes of data at rates of about 15 GB per day (initially it was 30 GB per day) and 1.5 terabytes per day respectively. Accessing these huge data volumes efficiently at both high spatial and high time resolutions is important to support scientific discovery but requires increasingly efficient tools to browse, locate and process specific data sets. This thesis investigates the development of new technologies for processing information contained in multiple and overlapping images of the same scene to produce images of improved quality. This area in general is titled Super Resolution (SR), and offers a technique for reducing artefacts and increasing the spatial resolution. Another challenge is to generate 3D images such as Anaglyphs from uncalibrated pairs of SR images. An automated method to generate SR images is presented here. The SR technique consists of three stages: image registration, interpolation and filtration. Then a method to produce enhanced, near real-time, 3D solar images from uncalibrated pairs of images is introduced. Image registration is an essential enabling step in SR and Anaglyph processing. An accurate point-to-point mapping between views is estimated, with multiple images registered using only information contained within the images themselves. The performances of the proposed methods are evaluated using benchmark evaluation techniques. A software application called the SOLARSTUDIO has been developed to integrate and run all the methods introduced in this thesis. SOLARSTUDIO offers a number of useful image processing tools associated with activities highly focused on solar images including: Active Region (AR) segmentation, anaglyph creation, solar limb extraction, solar events tracking and video creation.

Dust storms are one of the natural hazards, which have increased in frequency in the recent years over Sahara desert, Australia, the Arabian Desert, Turkmenistan and northern China, which have worsened during the last decade. Dust storms increase air pollution, impact on urban areas and farms as well as affecting ground and air traffic. They cause damage to human health, reduce the temperature, cause damage to communication facilities, reduce visibility which delays both road and air traffic and impact on both urban and rural areas. Thus, it is important to know the causation, movement and radiation effects of dust storms. The monitoring and forecasting of dust storms is increasing in order to help governments reduce the negative impact of these storms. Satellite remote sensing is the most common method but its use over sandy ground is still limited as the two share similar characteristics. However, satellite remote sensing using true-colour images or estimates of aerosol optical thickness (AOT) and algorithms such as the deep blue algorithm have limitations for identifying dust storms. Many researchers have studied the detection of dust storms during daytime in a number of different regions of the world including China, Australia, America, and North Africa using a variety of satellite data but fewer studies have focused on detecting dust storms at night. The key elements of this present study are to use data from the Moderate Resolution Imaging Spectroradiometers on the Terra and Aqua satellites to develop more effective automated method for detecting dust storms during both day and night and generate a MODIS dust storm database.

O sistema estuarino-lagunar do Rio São Francisco, litoral norte da zona costeira de Sergipe, é uma região que apresenta vastas áreas de manguezal, apesar da incidência de tensores antrópicos. O presente estudo realizou um diagnóstico ambiental dos manguezais dessa zona costeira, considerando-se os níveis hierárquicos setting (paisagem), stand (unidade de paisagem) e site (parcela ou árvore), adaptado da proposta de Schaeffer-Novelli et al. (2000; 2005). Imagens de satélites e fotografias aéreas coloridas da área de estudo foram processadas em SIG e foi gerado um mapa de uso e cobertura da terra para 2008. Verdade de campo foi realizada e características qualitativas da composição da vegetação e da estrutura de bosques de mangue foram registradas. Atualmente 93% (179 km2) da zona costeira em estudo é ocupada por áreas de vegetação natural: manguezal (30 Km2, 16%), apicum (1,4 Km2,0,7%) e formações pioneiras de influência marinha (14 Km2, 77%); enquanto que 7% (13,56 km2) é ocupada por áreas antrópicas: aquicultura (4,6 Km2, 2,4%) e culturas de coco e arroz (9 Km2, 4,7%). Manguezais vêm a pelo menos 40 anos sendo pressionados por diferentes formas de uso da terra, destacando-se atualmente a carcinocultura e culturas de coco e arroz, que ocupam 25% da área total dessa vegetação, o que pode indicar que ¼ dos manguezais foram alterados ou convertidos para usos antrópicos. Esses resultados indicam que estado de conservação dos manguezais do sistema estuarino-lagunar do Rio São Francisco encontra-se bastante vulnerável demandando plano de gestão costeira que considere como prioridade a conservação dos mesmos diante da expansão da carcinocultura, o manejo das atividades locais de forma a considerar a capacidade de suporte do ecossistema manguezal e dos corpos dágua e a segurança das populações locais frente às alterações geradas pelos intensos processos erosivos na região da foz. / The estuarine system of the São Francisco River, the coastal zone of Sergipe State, Northeast Brazil is a region with large areas of mangrove despite they are strongly pressured by human activities. This study performed an environmental assessment of mangrove areas of the São Francisco River Estuary, considering the hierarchical levels: setting (landscape), stand (landscape unit) and site (plot or tree), adapted from the framework proposed by Schaeffer-Novelli et al. (2000, 2005). Satellite images and digital colour aerial photographs of the study area were processed in GIS and a land use and cover map was produced for 2008. Ground-truth was performed and characteristics of vegetation composition and structure were recorded. Currently 93% (179 km2) of the coastal zone in question is occupied by natural vegetation: mangrove (30 km2, 16%), apicum (1.4 km2, 0.7%) and sand coast plain (14 Km2 , 77%), while 7% (13.56 km2) is occupied by disturbed areas: aquaculture (4.6 km2, 2.4%) and coconut and rice plantations (9 km2, 4.7%). Mangroves have been pressured by different land uses for at least 40 years. Now the land use for aquaculture (mainly shrimp farms) and coconut and rice plantations occupy 25% of the total area of mangrove, which may indicate that ¼ of mangroves have been changed or converted to man-made uses. These results show that the conservation status of mangroves in the study area is vulnerable, requiring a coastal management plan which considers as priority the preservation of mangroves before the expansion of aquaculture, management of local activities to consider the carrying capacity of the mangrove ecosystem and water bodies and the security of local populations in the face of changes generated by intense erosion in the region of the mouth of the São Francisco River.

Made available in DSpace on 2016-04-27T18:15:44Z (GMT). No. of bitstreams: 1 Thiago Souza Vale.pdf: 3481122 bytes, checksum: 3870ff16b1d0a8120dd5019f7b9aec9b (MD5) Previous issue date: 2014-03-11 / Secretaria da Educação do Estado de São Paulo / This thesis discusses the use of Google Earth as methodological procedure in the teaching and learning of geographical education to the students of Escola Estadual Caetano de Campo, held in the 1st half of 2013. The popularization and dissemination of geographical information targeted to the geographical information are increasingly present in brazilian public schools, and demand more skills of both teachers and students consequently. Therefore, the objectives of this research are articulated to the computer role, through the mosaic of satellite images of different landscapes at various scales and temporalities presented in the Google Earth software, as a teaching media resource in the learning of geography. This research shows the experimental-inductive methodological procedure being evaluated quantitatively and qualitatively. The content used for this experimental were: Cartography, Europe and Globalization according to the curriculum proposal of the São Paulo State. The results presented that the students challenged themselves to study new technologies, improving performance in activities and events, however they had difficulties in procedural actions inherent geographical reasoning, such as orientation and localization of the geographical phenomenas. These difficulties are the fact of students do not initially dominate the software language and academic needs undelveloped throughtout their basic training. Then, we consider that the use of Google Earth, as a didacting resource, in fact enhances the teaching and learning, and further reaserches should be required to investigate and propose adaptations of the software to be used as a teaching resource applied to geography education / A presente dissertação discute o uso do Google Earth como procedimento metodológico no processo de ensino e aprendizagem da educação geográfica com os alunos do Ensino Fundamental II da Escola Estadual Caetano de Campo, sendo realizada no 1º semestre de 2013. A popularização e difusão de softwares que abordam informações geográficas são realidades cada vez mais presentes nas escolas públicas brasileiras, e consequentemente demandam novas habilidades tanto dos docentes quanto dos alunos. Dessa maneira os objetivos dessa pesquisa estão articulados ao papel do computador, através do mosaico de imagens de satélites de diferentes paisagens em diversas escalas e temporalidades presentes no software Google Earth, como recurso didático-mediático no processo de ensino aprendizagem em geografia. Esta pesquisa apresenta procedimento metodológico experimental-indutivo sendo avaliada de forma quantitativa e qualitativa. Os conteúdos escolhidos para a realização deste experimento foram: Cartografia, Europa e Globalização estando de acordo com a proposta curricular do estado de São Paulo. Dessa forma os resultados demonstraram que os educandos se motivaram para o desafio de se estudar como novas tecnologias, melhorando o desempenho em atividades e provas, entretanto os alunos apresentaram dificuldades nas ações procedimentais inerentes ao raciocínio geográfico como a orientação e localização dos fenômenos geográficos. Estas dificuldades se devem ao fato dos alunos não dominarem inicialmente a linguagem do software e de carências acadêmicas não desenvolvidas ao longo de sua formação básica. Portanto consideramos que o uso do Google Earth como recurso didático, de fato potencializa o processo de ensino e aprendizagem, e que novos estudos devem ser feitos para investigar e propor adaptações desse software como recurso pedagógico aplicado a educação geográfica

L’exploitation de l’énergie solaire soulève des défis liés à la nature variable de la res- source concernée : le rayonnement solaire. Son comportement intermittent est un problème pour la gestion des centrales photovoltaïques et du réseau électrique. L'une des solutions largement envisagées est la prévision de la production photovoltaïque à différents horizons.L'objectif de cette thèse est d'explorer de nouvelles voies pour améliorer les prévisions existantes du rayonnement solaire, pour des horizons allant de quelques minutes à quelques heures, en exploitant les synergies possibles entre les mesures pyranométriques, les images hémisphériques du ciel prises depuis le sol et les images acquises par les satellites météorologiques géostationnaires. Ces deux types d’images ont des couvertures spatiales, des résolutions spatio-temporelles et des points de vue très différents.L’approche proposée dans cette thèse exploite cette différence de points de vue afin d’affiner la géolocalisation des nuages en 3D par stéréoscopie, dont l’évolution des ombres peut alors être estimée et prévue. Un simulateur géométrique de la méthode a été développé et permet d’en identifier certains avantages et limitations. La géolocalisation des nuages appliquée à des données réelles a permis d’élaborer des schémas d’estimations et de prévisions prometteurs du rayonnement solaire incident. Enfin, pour compléter l’analyse usuelle de ces performances de prévision, deux nouvelles métriques ont été proposées dans l’optique de quantifier deux notions essentielles : le respect du suivi des rampes et l’alignement temporel de la prévision par rapport à la mesure. / The exploitation of solar energy raises challenges related to the variable nature of the resources involved: the incident solar irradiance. Its intermittent behavior is an is- sue for photovoltaic power plants and grid management. One of the solutions that have been widely considered is the forecast of photovoltaic production at different time horizon.The aim of this thesis is to explore new ways for improving the existing solar irradiance forecasts, for horizons ranging from the present moment to few hours, by exploiting possible synergies between pyranometric measurements, hemispherical images of the sky taken from the ground and images acquired by geostationary meteorological satellites. These two types of images have completely different spatial coverage, spatio-temporal resolutions and are taken from two different locations.The proposed approach in this thesis exploits this difference in points of view in order to geolocate the clouds in 3D by stereoscopy, which shadows’ location and motion can then be estimated and forecasted. A geometric simulator of the method has been developed to identify some of the advantages and limitations of this approach. The geolocation of clouds applied to real data made it possible to develop promising estimates and forecasts of incident solar irradiance. Finally, to complete the usual analysis of forecasting performances, two new metrics have been proposed in order to quantify two essential notions: the ability to monitor the ramps and the temporal alignment of the forecast with the measurements.

O sistema estuarino-lagunar do Rio São Francisco, litoral norte da zona costeira de Sergipe, é uma região que apresenta vastas áreas de manguezal, apesar da incidência de tensores antrópicos. O presente estudo realizou um diagnóstico ambiental dos manguezais dessa zona costeira, considerando-se os níveis hierárquicos setting (paisagem), stand (unidade de paisagem) e site (parcela ou árvore), adaptado da proposta de Schaeffer-Novelli et al. (2000; 2005). Imagens de satélites e fotografias aéreas coloridas da área de estudo foram processadas em SIG e foi gerado um mapa de uso e cobertura da terra para 2008. Verdade de campo foi realizada e características qualitativas da composição da vegetação e da estrutura de bosques de mangue foram registradas. Atualmente 93% (179 km2) da zona costeira em estudo é ocupada por áreas de vegetação natural: manguezal (30 Km2, 16%), apicum (1,4 Km2,0,7%) e formações pioneiras de influência marinha (14 Km2, 77%); enquanto que 7% (13,56 km2) é ocupada por áreas antrópicas: aquicultura (4,6 Km2, 2,4%) e culturas de coco e arroz (9 Km2, 4,7%). Manguezais vêm a pelo menos 40 anos sendo pressionados por diferentes formas de uso da terra, destacando-se atualmente a carcinocultura e culturas de coco e arroz, que ocupam 25% da área total dessa vegetação, o que pode indicar que ¼ dos manguezais foram alterados ou convertidos para usos antrópicos. Esses resultados indicam que estado de conservação dos manguezais do sistema estuarino-lagunar do Rio São Francisco encontra-se bastante vulnerável demandando plano de gestão costeira que considere como prioridade a conservação dos mesmos diante da expansão da carcinocultura, o manejo das atividades locais de forma a considerar a capacidade de suporte do ecossistema manguezal e dos corpos dágua e a segurança das populações locais frente às alterações geradas pelos intensos processos erosivos na região da foz. / The estuarine system of the São Francisco River, the coastal zone of Sergipe State, Northeast Brazil is a region with large areas of mangrove despite they are strongly pressured by human activities. This study performed an environmental assessment of mangrove areas of the São Francisco River Estuary, considering the hierarchical levels: setting (landscape), stand (landscape unit) and site (plot or tree), adapted from the framework proposed by Schaeffer-Novelli et al. (2000, 2005). Satellite images and digital colour aerial photographs of the study area were processed in GIS and a land use and cover map was produced for 2008. Ground-truth was performed and characteristics of vegetation composition and structure were recorded. Currently 93% (179 km2) of the coastal zone in question is occupied by natural vegetation: mangrove (30 km2, 16%), apicum (1.4 km2, 0.7%) and sand coast plain (14 Km2 , 77%), while 7% (13.56 km2) is occupied by disturbed areas: aquaculture (4.6 km2, 2.4%) and coconut and rice plantations (9 km2, 4.7%). Mangroves have been pressured by different land uses for at least 40 years. Now the land use for aquaculture (mainly shrimp farms) and coconut and rice plantations occupy 25% of the total area of mangrove, which may indicate that ¼ of mangroves have been changed or converted to man-made uses. These results show that the conservation status of mangroves in the study area is vulnerable, requiring a coastal management plan which considers as priority the preservation of mangroves before the expansion of aquaculture, management of local activities to consider the carrying capacity of the mangrove ecosystem and water bodies and the security of local populations in the face of changes generated by intense erosion in the region of the mouth of the São Francisco River.