Esta tese se concentra em aplicar os modelos de mistura de distribuições na segmentação de imagens SAR polarimétricas multi-look. Dentro deste contexto, utilizou-se o algoritmo SEM em conjunto com os estimadores obtidos pelo método dos momentos para calcular as estimativas dos parâmetros do modelo de mistura das distribuições Wishart, Kp ou G0p. Cada uma destas distribuições possui parâmetros específicos que as diferem no ajuste dos dados com graus de homogeneidade variados. A distribuição Wishart descreve bem regiões com características mais homogêneas, como cultivo. Esta distribuição é muito utilizada na análise de dados SAR polarimétricos multi-look. As distribuições Kp e G0p possuem um parâmetro de rugosidade que as permitem descrever tanto regiões mais heterogêneas, como vegetação e áreas urbanas, quanto regiões homogêneas. Além dos modelos de mistura de uma única família de distribuições, também foi analisado o caso de um dicionário contendo as três famílias. Há comparações do método SEM proposto para os diferentes modelos com os métodos da literatura k-médias e EM utilizando imagens reais da banda L. O método SEM com a mistura de distribuições G0p forneceu os melhores resultados quando os outliers da imagem são desconsiderados. A distribuição G0p foi a mais flexível ao ajuste dos diferentes tipos de alvo. A distribuição Wishart foi robusta às diferentes inicializações. O método k-médias com a distribuição Wishart é robusto à segmentação de imagens contendo outliers, mas não é muito flexível à variabilidade das regiões heterogêneas. O modelo de mistura do dicionário de famílias melhora a log-verossimilhança do método SEM, mas apresenta resultados parecidos com os do modelo de mistura G0p. Para todos os tipos de inicialização e grupos, a distribuição G0p predominou no processo de seleção das distribuições do dicionário de famílias. / The main focus of this thesis consists of the application of mixture models in multi-look polarimetric SAR image segmentation. Within this context, the SEM algorithm, together with the method of moments, were applied in the estimation of the Wishart, Kp and G0p mixture model parameters. Each one of these distributions has specific parameters that allows fitting data with different degrees of homogeneity. The Wishart distribution is suitable for modeling homogeneous regions, like crop fields for example. This distribution is widely used in multi-look polarimetric SAR data analysis. The distributions Kp and G0p have a roughness parameter that allows them to describe both heterogeneous regions, as vegetation and urban areas, and homogeneous regions. Besides adopting mixture models of a single family of distributions, the use of a dictionary with all the three family of distributions was proposed and analyzed. Also, a comparison between the performance of the proposed SEM method, considering the different models in real L-band images and two widely known techniques described in literature (k-means and EM algorithms), are shown and discussed. The proposed SEM method, considering a G0p mixture model combined with a outlier removal stage, provided the best classication results. The G0p distribution was the most flexible for fitting the different kinds of data. The Wishart distribution was robust for different initializations. The k-means algorithm with Wishart distribution is robust for segmentation of SAR images containing outliers, but it is not so flexible to variabilities in heterogeneous regions. The mixture model considering the dictionary of distributions improves the SEM method log-likelihood, but presents similar results to those of G0p mixture model. For all types of initializations and clusters, the G0p prevailed in the distribution selection process of the dictionary of distributions.

A manutenção dos ecossistemas florestais da Amazônia é, sem dúvida, de suma importância para preservação da biodiversidade do planeta. Utilizar e avaliar dados de última geração que forneçam informações sobre estes ecossistemas torna-se então fundamental para o gerenciamento dos mesmos. Projeto pioneiro realizado na década de 1970, o RADAM teve como objetivo levantar, a partir de imagens de RADAR obtidas na banda X, informações sobre os recursos naturais da Amazônia. O avanço dos sistemas sensores baseados nas tecnologias de RADAR (Radio Detection and Ranging), com a introdução de plataformas capazes de imagear a superfície em comprimentos de onda maiores e em mais de uma polarização, trouxe uma nova perspectiva no campo de estudo destes recursos. Este trabalho emergiu a partir da constatação da necessidade, e possibilidade, de se obter informações mais precisas e atualizadas sobre o ambiente amazônico, levando em conta, inclusive, a velocidade das transformações que recaem sobre essa região. O objetivo primário do estudo foi analisar o potencial das imagens produzidas pelos radares de abertura sintética (SAR) nas bandas L e nas polarizações HH, HV e VV, na avaliação de tipologias vegetais da porção leste da Ilha de Marajó. Entendemos que essa pequena parcela do ambiente amazônico nos cede uma chave de padrões de classificação que podem ser replicados em outras regiões da Amazônia Legal, ou mesmo, em novos projetos de mapeamento similares ao RADAM. Os resultados obtidos por meio de análises das imagens de radar e através do estudo de diversas propostas de classificação fitogeográfica, evidenciaram um alto potencial de utilização destes recursos, bem como a possibilidade de avançarmos na escala de análise, produzindo mapeamentos de maior detalhe e mais abrangentes do ponto de vista das classes vegetais. A tecnologia para incrementar o mapeamento da região amazônica, de forma mais criteriosa e precisa, já existe há algum tempo e está disponível às instituições nacionais. Dar esse salto, importantíssimo para o conhecimento, preservação e monitoramento daquele que é considerado hoje o bioma mais importante do mundo, só depende de uma mudança nos critérios e de uma atualização das ferramentas usadas até o momento. / The maintenance of forest ecosystems in the Amazon is undoubtedly of great importance to the preservation of the planets biodiversity. The utilization and analysis of last generation data about these ecosystems become fundamental for their management. A pioneer project in the 1970 decade, the RADAM project had the objective of gathering information about Amazon natural resources from RADAR images obtained in the band X. The progress in sensor systems based on RADAR (Radio Detection and Ranging) technologies, with the introduction of platforms capable of imaging the surface in bigger wavelengths and in more than one polarization, brought a new perspective in the study area of these resources. This work emerged from the constatation of the need and possibility of obtaining more precise and updated information about the Amazon environment, inclusive considering the speed of the transformations that occur in this region. The primary objective of the study was to analyze the potential of the produced images by Synthetic Aperture Radars (SAR) in bands L and in polarizations HH, HV and VV, for the evaluation of vegetal typology of the east portion of Marajo Island. We understand that this little portion of the Amazon environment gives us a key of classification patterns that can be reapplied in other regions of Legal Amazon, or even in new mapping projects similar to RADAM. The results obtained from radar images analysis and through the study of several propositions for phytogeographic classification evidenced a high potential for the utilization of these resources, as well as the possibility of making progresses in the analysis scale, producing more detailed and comprehensive mappings from the point of view of vegetal classes. The technology to improve the mapping of Amazon region in a more criterious and precise manner has already existed for some time now and is available for national institutions. Making this leap, greatly important to knowledge, preservation and monitoring of what is considered the most important biome in the world only depends on a change in criteria and an updating of the tools that have been used up to this moment.

<p style="text-align: justify;">Reverzno-faznom tečnom hromatografijom pod visokim pritiskom primenom dva sistema<br />rastvarača ispitano je pona&scaron;anje i hromatografska lipofilnost prirodnih stiril laktona 7-(+)-<br />goniofufurona, 7-epi-(+)-goniofufurona, krasalaktona B i C i dvadeset njihovih<br />novosintetizovanih derivata i analoga. U ranijim ispitivanjima pokazalo se da ova jedinjenja<br />imaju veliki biolo&scaron;ki potencijal jer pokazuju zapaženu citotoksičnost prema vi&scaron;e humanih<br />tumorskih ćelijskih linija. Hromatografsko pona&scaron;anje jedinjenja uglavnom je u skladu sa<br />njihovom strukturom. Ustanovljene su linearne veze između hromatografskih retencionih<br />konstanti i većine in silico parametara lipofilnosti. Primenom hemometrijske QSRR analize<br />utvrđeni su veoma dobri multi linearni regresioni prediktivni modeli kvantitativne zavisnosti<br />između eksperimentalno dobijene hromatografske retencione konstante, koja defini&scaron;e<br />retenciju jedinjenja u čistoj vodi i in silico molekulskih deskriptora odnosno strukture<br />jedinjenja. Lipofilnost jedinjenja ima najveći uticaj na njihove farmakokinetičke, tj. ADME<br />(apsorpcija, distribucija, metabolizam, eliminacija) osobine. Definisani su i statistički<br />potvrđeni najbolji multi linearni regresioni modeli zavisnosti farmakokinetičkih parametara<br />stiril laktona i od drugih molekulskih deskriptora. In vitro citotoksična aktivnost jedinjenja<br />evaluirana je prema četiri nove humane maligne ćelijske linije: kancer prostate (PC3), kancer debelog creva (HT-29), melanom (Hs294T), adenokancer pluća (A549). Najaktivnije<br />novosintetizovano jedinjenje je triciklični 4-fluorocinamatni analog, koji ispoljava<br />nanomolarnu aktivnost (IC₅₀ 2,1 nM) prema ćelijama melanoma i aktivniji je preko 2250 puta od komercijalnog antitumorskog agensa doksorubicina (DOX). SAR analizom utvrđena je zavisnost između strukture i biolo&scaron;ke aktivnosti jedinjenja. Molekulskim dokingom ispitana je veza stiril laktona i ciljanog proteina značajnog za kancer prostate. Jedinjenja sa visokom inhibitornom aktivno&scaron;ću prema ćelijama kancera prostate imaju visok doking skor i mogu graditi koordinativno-kovalentnu vezu sa Fe²+jonom prisutnim u aktivnom centru enzima. 3D-QSAR analizom, koja je izvedena metodama komparativnih polja CoMFA i CoMSIA, formiran je značajan prediktivni model između hemijske strukture i biolo&scaron;ke aktivnosti stiril laktona.</p> / <p>The behavior and the chromatographic lipophilicity natural styryl lactone 7-(+)-<br />goniofufurone, 7-epi-(+)-goniofufurone, crassalactones B and C and twenty of their newly<br />synthesized derivatives and analogs were examined using reverse-phase high performance liquid chromatography in the two solvent systems. In previous studies it has been shown that these compounds have great biological potential toward several human tumor cell lines. Chromatographic behavior of the compounds is generally in accordance with their structure. The relationships between the chromatographic retention constants and the majority of their in silico lipophilicity parameters are linear. The application of chemometric QSRR analysis determined very good multiple linear regression predictive models of quantitative correlation between experimentally obtained chromatographic retention constant, which determines the retention of the compound in pure water and in silico molecular descriptors, i.e. the structure of the compound. The lipophilicity of the compounds has a major influence on their pharmacokinetics, i.e. ADME (absorption, distribution, metabolism, elimination) properties. The best multi-linear regression models depending on the pharmacokinetic parameters of styryl lactone and other molecular descriptors have been defined and statistically validated. In vitro cytotoxic activity of the compounds was evaluated according to four novel human malignant cell lines: prostate cancer (PC3), colon cancer (HT-29), melanoma (Hs294T), lung adenocarcinom (A549). The most active compound was tricyclic 4-fluorocinnamic analog, which exhibits a nanomolar activity (IC50 2,1 nM) toward melanoma cells. This compound is over 2250 times more active than commercial antitumor agent doxorubicin (DOX). SAR analysis has revealed a correlation between the structure and the biological activity of the compounds. Using the molecular docking the relationship of the styryl lactone and the target protein important for prostate cancer was examined. The compounds with high inhibitory activity against prostate cancer cells have a high docking score and are capable to form a coordinative-covalent bond with a Fe2+ ion present in the active centre of the enzyme. 3DQSAR analysis, which was performed by methods of comparative CoMFA and CoMSIA fields, has formed a good predictive model between chemical structure and biological activity of the styryl lactone.</p>

Dentro da região litorânea central do Estado de Santa Catarina, compreendida entre as praias do Ouvidor e dos Ingleses, foram delimitadase estudadas cinco áreas que abrigam tanto campos de dunas ativos quanto estabilizados. Com base em dados meteorológicos obtidos de 1962 a 2010, como registros diários de precipitação e deintensidade e rumo de vento, inferiu-se que a tendência de estabilização recente, observada nos campos de dunas atuais por comparação de fotografias aéreas de diferentes datas, resulta da combinação de aumento da precipitação com redução da intensidade do vento. Este dois fatores inibem o transporte eólico de sedimentos para o campo de dunas, seja pelo efeito de aumento de coesão da areia exercido pela umidade seja pelo favorecimento da colonização vegetal nas zonas de deflação. Persistentes nas últimas três décadas, estes fatores têm reduzido gradualmente as áreas deareia expostas ao retrabalhamento eólico, o que diminui cada vez mais a deriva eólica efetiva, culminando na fixação dos campos de dunas. Os depósitos sedimentares de dunas e paleodunas eólicas foram agrupados, por critérios morfológicos, estratigráficos, granulométricos e mineralógicos, em quatro gerações (G1 a G4), correlatas às reconhecidas previamente na literatura. A geração mais antiga (G1) possui, todavia, distribuição de idades mais ampla do que se pensava, podendo portanto, por critérios geocronológicos, vir a ser subdividida. Os resultados sedimentológicos apontam para tendências de engrossamento, melhora de seleção granulométrica e assimetria mais positiva, da geração mais antiga para a mais nova, o que é atribuído a influência de sucessiva reciclagem de sedimentos entre as gerações, sem descartar o efeito, em paralelo, de mudanças de energia e/ou morfodinâmica costeira. As idades obtidas para as gerações antigas pelo método da luminescência opticamente estimulada (LOE) permitem observar certa coincidência com contextos de linha de costa estável e de clima em transição de menos úmido para mais úmido. A relação observada entre as idades LOE obtidas e as curvas de variação do nível relativo do mar (NRM) e de paleopluviosidade, associadas ao modelo de estabilização de dunas recentes por aumento de umidade e queda de energia eólica, permite sugerir que a iniciação dos campos de dunas costeiros da região, em suas diferentes gerações, seja favorecida por situações de NRM estável e/ou em inversão de tendência, e por clima menos úmido e mais ventoso. A estabilização dos campos de dunas, em contrapartida, seria favorecida pela subida de NRM, pelo aumento da chuva e pela diminuição da intensidade dos ventos. Do ponto de vista do controle climático, a condição de iniciação de campos de dunas mencionadacoincidiria com momentos de enfraquecimento do Sistema de Monções da América doSul (SMAS), correlatos a períodos mais quentes no hemisfério norte. E a condição favorávelà estabilização de campos de dunas ocorreria nos momentos de intensificação do SMAS, correlatos a períodos mais frios no hemisfério norte. / This master dissertation refers to five areas withactive and stabilized eolian dune fields in the central coast of the Santa Catarina State, southernBrazil. In this region, a recent tendency to stabilization of active dune fields is inferred from the comparison between aerial photographs of different years. Meteorological data obtained between 1962 and 2010, including daily records of rainfall, wind intensity and wind direction, indicate increasing precipitation and weakening wind to this period. The combination of these two factors inhibits the eolian sediment transport to the dune field, as effect of increasing sand cohesion by wetting and vegetal colonization in deflation zones. Being persistent in the last three decades, these factorshave reduced gradually the sand areas exposed to eolian reworking and decreased more and more the effective eolian drift, culminating in the stabilization of dune fields. The sedimentary deposits of eolian dunes and paleodunes were grouped, by morphological, stratigraphic, granulometric and mineralogical criteria in four generations (G1 to G4), analogous to that previously recognized in the literature. The older generation (G1) has a wider age distribution than previously thought and can be subdivided regarding the geochronological aspect. The grain-size analysis data indicate trends of sediment coarsening, better sorting and more positive skewness, from the older to the younger generation,what is attributed to the influence of successive reworking of sediments between generations, withoutdiscarding the effect of changes in the transport energy and/or beach morphodynamics. The ages of the three older generations obtained by optically stimulated luminescence (OSL) method show coincidence with contexts of stable coastline and with climate in transition from less to more wet. The observed relationship between the OSL ages andthe relative sea level (RSL) and paleoprecipitation curves, besides the model of recent dune stabilization by the wet increasing and wind energy decreasing, allow us to suggest that the initiation of the dune fields in their different generations, in this coastal region, can be favoredby moments of stable and / or in reversal trend RSL, as well by less humid and more windy weather. In other hand, the stabilization of the dune fields would be favored by higher RSL, increasing rain and decreasing wind intensity. From the perspective of climate control, the mentioned condition to initiation of dune fields agree with moments of weakening of the South America Summer Monsoon System (SASM), related to warmer periods in the northern hemisphere. Analogously, the favorablecondition for the stabilization of dune fields would coincide with moments of intensification of the SASM, related to colder periods in the northern hemisphere.

A aplicação de ar quente em videiras foi primeiramente realizada na fazenda do Sr. Florenzo Lazo, localizada no Chile, onde havia a necessidade de combater os efeitos negativos das freqüentes geadas que resultava em severos danos à lavoura. Por este motivo o Sr. Florenzo inventou uma máquina que aplicava ar quente com baixa umidade e tinha por objetivo dispersar o ar frio proveniente das geadas. Após certo tempo, foi observado pelo produtor que no local onde a máquina havia operado com maior frequência as plantas apresentavam-se com uma coloração mais escura e com sinais de maior vitalidade. Seguindo estas observações, relacionamos estes efeitos a um possível aumento nos fito-hormônios relacionados ao estresse vegetal e à SAR (Systemic Resistence Adquired), como o ácido salicílico (AS), ácido jasmônico (AJ) e ácido abscísico (ABA), além de fazer uma correlação com alguns resultados de pós-colheita importantes para a comercialização, como: Sólidos solúveis, firmeza e coloração. Para isso foi montado um experimento que foi conduzido em duas parcelas, sendo uma com tratamento TPC e outra apenas com o tratamento convencional com distância padronizada em 3,2 metros entre linhas por 2,0 metros entre planta. As amostras eram coletadas diariamente e devidamente acondicionadas. Ao final da safra, as amostras foram transportadas para o laboratório de estresse e neurofisiologia da universidade de São Paulo (LEPSE), onde foram novamente armazenadas em um Ultra-freezer - 86ºC. As analises fisiológicas de pós-colheita foram realizadas no departamento de pós-colheita da universidade de São Paulo onde foram analisados os teores de sólidos solúveis, coloração e firmeza das bagas de uva. As amostras de folhas foram maceradas e uniformizadas no LEPSE e enviadas para o laboratório de ecotoxicologia do Centro de Energia Nuclear na Agricultura (CENA) onde foram mensurados os teores dos fito-hormônios pelo método de espectrometria de massa. Para ambas as analises foram feitos testes estatísticos utilizando o programa SAS®. Não houve alteração de SS e firmeza entre os dois tratamentos para as características fisiológicas de póscolheita. Entretanto foi notado uma redução na coloração avermelhada para os cachos tratados com TPC seguindo o sistema de colorimetria proposto pelo CIE. Não houve alterações significantes para as variáveis ABA, AJ e AS para o efeito tratamento e para a analise de correlação. Entretanto notou-se significância entre o efeito dias para as variáveis ABA e AJ. Não foi notada significância para o efeito dias para a variável AS. Por se tratar de um estresse rápido, a TPC parece não causar estresse imediato nas plantas, entretanto notou-se indução de estresse ao longo do tempo, possivelmente devido à resposta lenta de ABA que aparentemente está envolvida com RNA e à síntese de proteínas S e R- ABA que são igualmente efetivas. Já para o AJ sugere-se que houve a produção de H2O2 por derivados de oligogalacturonideos, liberados por ação da enzima poligalacturonase, e um segundo mensageiro que ativam genes defensivos (genes tardios). O aumento na biossíntese do ABA e do AJ parece ter suprimido genes envolvidos na biossíntese do AS. / The application of hot air in grapevines was first held on the farm of Mr. Florenzo Lazo, located in Chile, to combat the negative effects of frequent frosts that resulted in severe damage to the crop. For this reason Mr. Florenzo invented a machine that applied hot air with low humidity and aimed to disperse the cold air from the frost. After a while, it was observed by the producer that where the machine had operated more frequently plants showed up with a darker and more signs of vitality. Following these observations, these effects relate to a possible increase in phytohormones related to plant stress and SAR (Systemic Resistance Adquired), such as salicylic acid (AS), jasmonic acid (AJ) and abscisic acid (ABA), besides making a correlation with results of some important postharvest for marketing, such as soluble solids, firmness and color. For this experiment was created that was conducted in two installments, the first one was treated with TPC and second one was applied only conventional treatment with standardized distance of 3.2 meters between lines by 2.0 meters between plant . The samples were collected daily and properly packed. At the end of the season, samples were transported to the laboratory stress and neurophysiology from the University of São Paulo (LEPSE), where they were again stored in an Ultra-freezer - 86 degrees. The physiological analyses of post-harvest were performed at the Department of Postharvest in University of Sao Paulo where we analyzed the levels of soluble solids, firmness and color in grape berries. The leaf samples were uniform macerated at LEPSE and sent to the laboratory of ecotoxicology in the Center for Nuclear Energy in Agriculture (CENA) where we measured the levels of the phytohormones by the method of mass spectrometry. For both analyzes were performed statistical tests using SAS ® program. There wasn`t change between the two treatments on physiological post-harvest characteristics. There was no change of SS and firmly between the two treatments for the physiological of post-harvest characteristics. However it was noted a reduction in red color for bunches treated with TPC following the colorimetry system by CIE. There were no significant changes to the variables ABA, AJ and AS for the treatment effect and to analyze the correlation. However significance was noted between the effect variables ABA days and AJ. No significant effect was noted for days variable for AS. Since it is a stress fast TPC does not seem to cause immediate stress in plants but it was noticed induction of stress over time, possibly due to slow response to ABA which apparently is involved in the synthesis of RNA and proteins S and R-ABA that are equally effective. As for AJ suggests that there was the production of H2O2 by derivatives of oligogalacturonides, released by action of the enzyme polygalacturonase, and a second messenger that activates defensive genes (late genes). The increase in ABA biosynthesis and AJ appears to have deleted genes involved in the biosynthesis of AS.

Hydrological modelling is a powerful tool for hydrologists and engineers involved in the planning and development of integrated approach for the management of water resources. With the recent advent of computational power and the growing availability of spatial data, RS and GIS technologies can augment to a great extent the conventional methods used in rainfall runoff studies; it is possible to accurately describe watershed characteristics in particularly when determining runoff response to rainfall input. The main objective of this study is to apply the potential of spaceborne SAR data for soil moisture retrieval in order to improve the spatial input parameters required for hydrological modelling. For the spatial database creation, high resolution 2 m aerial laser scanning Digital Terrain Model (DTM), soil map, and landuse map were used. Rainfall records were transformed into a runoff through hydrological parameterisation of the watershed and the river network using HEC-HMS software for rainfall runoff simulation. The Soil Conservation Services Curve Number (SCS-CN) and Soil Moisture Accounting (SMA) loss methods were selected to calculate the infiltration losses. In microwave remote sensing, the study of how the microwave interacts with the earth terrain has always been interesting in interpreting the satellite SAR images. In this research soil moisture was derived from two different types of Spaceborne SAR data; TerraSAR-X and ALOS PALSAR (L band). The developed integrated hydrological model was applied to the test site of the Gottleuba Catchment area which covers approximately 400 sqkm, located south of Pirna (Saxony, Germany). To validate the model historical precipitation data of the past ten years were performed. The validated model was further optimized using the extracted soil moisture from SAR data. The simulation results showed a reasonable match between the simulated and the observed hydrographs. Quantitatively the study concluded that based on SAR data, the model could be used as an expeditious tool of soil moisture mapping which required for hydrological modelling.

Η χρήση των δεδομένων Ραντάρ Συνθετικού Ανοίγματος (SAR) σε εφαρμογές απομακρυσμένης παρακολούθησης της Γης έχει ήδη αρχίσει να πρωταγωνιστεί τις τελευταίες δεκαετίες. Τα συστήματα SAR με δυνατότητες μεταξύ άλλων συνεχούς λειτουργίας παντός καιρού, ημέρα και νύχτα, προσφέροντας μεγάλη κάλυψη εδάφους και με δυνατότητα λήψης απεικονίσεων πολλαπλών πολώσεων, έχουν αποτελέσει πηγή πολύτιμων πληροφοριών τηλεπισκόπησης. Έτσι, η χρήση των SAR δεδομένων για την ταξινόμηση κάλυψης γης προσελκύει όλο και περισσότερο την προσοχή των ερευνητών και φαίνεται να είναι πολλά υποσχόμενη. Η παρούσα ειδική επιστημονική εργασία έχει στόχο τη μελέτη και ερμηνεία των δεδομένων SAR μέσω επιβλεπόμενης ταξινόμησης, με τη χρήση νευρωνικών δικτύων (Neural Networks). Αφού πρώτα γίνεται εκτενής αναφορά στη τεχνολογία και τα συστήματα SAR, παρουσιάζεται αναλυτικά η πειραματική διαδικασία ταξινόμησης τριών βασικών δομών κάλυψης γης. Τα δεδομένα προέρχονται από το Προηγμένο Ραντάρ Συνθετικού Ανοίγματος (ASAR) του δορυφόρου ENVISAT από τον Ευρωπαϊκό Οργανισμό Διαστήματος και αφορούν στην ευρύτερη περιοχή του Άμστερνταμ. Πριν την διεξαγωγή της ταξινόμησης, τα δεδομένα δέχθηκαν τις απαραίτητες διαδικασίες προ-επεξεργασίας (ραδιομετρική βαθμονόμηση, γεωαναφορά, φιλτράρισμα θορύβου, συμπροσαρμογή). Όσον αφορά τη διαδικασία της ταξινόμησης, εξετάζεται η συμπεριφορά του ταξινομητή του νευρωνικού δικτύου για μεταβολές ποικίλων παραμέτρων, όπως η επιλογή δεδομένων διαφόρων πολώσεων, το πλήθος των νευρώνων κ.α. και ήδη από τα πρώτα πειράματα λαμβάνονται ικανοποιητικά αποτελέσματα. Στη συνέχεια εφαρμόζονται τεχνικές σύνθεσης πληροφορίας (average rule, majority rule) βελτιώνοντας τις επιδόσεις ταξινόμησης. Τέλος, ένα σημαντικό βήμα που εφαρμόζεται στη διαδικασία ταξινόμησης αποτελεί η εξαγωγή χαρακτηριστικών υφής από τις μήτρες συνεμφάνισης φωτεινοτήτων (Gray Level Co-occurrence Matrix-GLCM) και μήκους διαδρομής φωτεινότητας (Gray Level Run Length Matrix-GLRLM). Η χρήση των χαρακτηριστικών αυτών βελτιστοποιεί το σύστημα ταξινόμησης, δίνοντας εξαιρετικά αποτελέσματα. / The use of Synthetic Aperture Radar (SAR) data in remote sensing applications has become a cutting edge technology during the past few decades. The SAR systems have several capabilities, like day & night and all weather operation and they offer large ground coverage with the ability of multi-polarized imagery; therefore, they have proved to be a valuable source of remote sensing data. As a result, the use of SAR data for land cover classification increasingly attracts the attention of researchers and seems to be highly promising. Goal of this master thesis is the study and interpretation of SAR data through supervised classification, with the use of Neural Networks method. First, there is an extensive presentation of SAR systems and technology and then follows the detailed presentation of the experimental classification process for three basic land cover structures. The available data are from the Advanced SAR (ASAR) radar of the ESA ENVISAT satellite and correspond to the Amsterdam city and suburbs. Prior to the classification process, the data have been appropriately pre-processed (radiometric calibration, geocoding, speckle filtering, co-registration). Regarding the classification process, the response of the neural network classifier with the variation of several parameters (e.g. data polarization and number of neurons) is studied and from the initial test already the results were quite satisfactory. Further on, ensemble classifying methods (average rule, majority rule) are applied to improve the classification performance. Finally, as an essential step applied in the classification process is the textural feature extraction from Gray Level Co-occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM). The use of these texture features optimizes the classification system, resulting to an exceptional performance.

Multitemporal SAR images have been increasingly used for the detection of different types of environmental changes. The detection of urban changes using SAR images is complicated due to the complex mixture of the urban environment and the special characteristics of SAR images, for example, the existence of speckle. This thesis investigates urban change detection using multitemporal SAR images with the following specific objectives: (1) to investigate unsupervised change detection, (2) to investigate effective methods for reduction of the speckle effect in change detection, (3) to investigate spatio-contextual change detection, (4) to investigate object-based unsupervised change detection, and (5) to investigate a new technique for object-based change image generation. Beijing and Shanghai, the largest cities in China, were selected as study areas. Multitemporal SAR images acquired by ERS-2 SAR and ENVISAT ASAR sensors were used for pixel-based change detection. For the object-based approaches, TerraSAR-X images were used. In Paper I, the unsupervised detection of urban change was investigated using the Kittler-Illingworth algorithm. A modified ratio operator that combines positive and negative changes was used to construct the change image. Four density function models were tested and compared. Among them, the log-normal and Nakagami ratio models achieved the best results. Despite the good performance of the algorithm, the obtained results suffer from the loss of fine geometric detail in general. This was a consequence of the use of local adaptive filters for speckle suppression. Paper II addresses this problem using the nonlocal means (NLM) denoising algorithm for speckle suppression and detail preservation. In this algorithm, denoising was achieved through a moving weighted average. The weights are a function of the similarity of small image patches defined around each pixel in the image. To decrease the computational complexity, principle component analysis (PCA) was used to reduce the dimensionality of the neighbourhood feature vectors. Simple methods to estimate the number of significant PCA components to be retained for weights computation and the required noise variance were proposed. The experimental results showed that the NLM algorithm successfully suppressed speckle effects, while preserving fine geometric detail in the scene. The analysis also indicates that filtering the change image instead of the individual SAR images was effective in terms of the quality of the results and the time needed to carry out the computation. The Markov random field (MRF) change detection algorithm showed limited capacity to simultaneously maintain fine geometric detail in urban areas and combat the effect of speckle. To overcome this problem, Paper III utilizes the NLM theory to define a nonlocal constraint on pixels class-labels. The iterated conditional mode (ICM) scheme for the optimization of the MRF criterion function is extended to include a new step that maximizes the nonlocal probability model. Compared with the traditional MRF algorithm, the experimental results showed that the proposed algorithm was superior in preserving fine structural detail, effective in reducing the effect of speckle, less sensitive to the value of the contextual parameter, and less affected by the quality of the initial change map. Paper IV investigates object-based unsupervised change detection using very high resolution TerraSAR-X images over urban areas. Three algorithms, i.e., Kittler-Illingworth, Otsu, and outlier detection, were tested and compared. The multitemporal images were segmented using multidate segmentation strategy. The analysis reveals that the three algorithms achieved similar accuracies. The achieved accuracies were very close to the maximum possible, given the modified ratio image as an input. This maximum, however, was not very high. This was attributed, partially, to the low capacity of the modified ratio image to accentuate the difference between changed and unchanged areas. Consequently, Paper V proposes a new object-based change image generation technique. The strong intensity variations associated with high resolution and speckle effects render object mean intensity unreliable feature. The modified ratio image is, therefore, less efficient in emphasizing the contrast between the classes. An alternative representation of the change data was proposed. To measure the intensity of change at the object in isolation of disturbances caused by strong intensity variations and speckle effects, two techniques based on the Fourier transform and the Wavelet transform of the change signal were developed. Qualitative and quantitative analyses of the result show that improved change detection accuracies can be obtained by classifying the proposed change variables. / <p>QC 20150529</p>

Agricultural production is becoming increasingly important as the world demand increases. On the other hand, there are several factors threatening that production such as the climate change. Therefore, monitoring and management of different parameters affecting the production are important. The current study is dedicated to two key parameters, namely agricultural land cover and soil-moisture mapping using X- and L-Band Synthetic Aperture Radar (SAR) data. Land-cover mapping plays an essential role in various applications like irrigation management, yield estimation and subsidy control. A model of multi-direction/multi-distance texture analysis on SAR data and its use for agricultural land cover classification was developed. The model is built and implemented in ESRI ArcGIS software and integrated with “R Environment”. Sets of texture measures can be calculated on a plot basis and stored in an attribute table for further classification. The classification module provides various classification approaches such as support vector machine and artificial neural network, in addition to different feature-selection methods. The model has been tested for a typical Mid-European agricultural and horticultural land use pattern south to the town of Pirna (Saxony/Germany), where the high-resolution SAR data, TerraSAR-X and ALOS/PALSAR (HH/HV) imagery, were used for land-cover mapping. The results indicate that an integrated classification using textural information of SAR data has a high potential for land-cover mapping. Moreover, the multi-dimensional SAR data approach improved the overall accuracy. Soil moisture (SM) is important for various applications such as crop-water management and hydrological modelling. The above-mentioned TerraSAR-X data were utilised for soil-moisture mapping verified by synchronous field measurements. Different speckle-reduction techniques were applied and the most representative filtered image was determined. Then the soil moisture was calculated for the mapped area using the obtained linear regression equations for each corresponding land-cover type. The results proved the efficiency of SAR data in soil-moisture mapping for bare soils and at the early growing stage of fieldcrops. / Landwirtschaftliche Produktion erlangt mit weltweit steigender Nahrungsmittelnachfrage zunehmende Bedeutung. Zahlreiche Faktoren bedrohen die landwirtschaftliche Produktion wie beispielsweise die globale Klimaveränderung einschließlich ihrer indirekten Nebenwirkungen. Somit ist das Monitoring der Produktion selbst und der wesentlichen Produktionsparameter eine zweifelsfrei wichtige Aufgabe. Die vorliegende Studie widmet sich in diesem Kontext zwei Schlüsselinformationen, der Aufnahme landwirtschaftlicher Kulturen und den Bodenfeuchteverhältnissen, jeweils unter Nutzung von Satellitenbilddaten von Radarsensoren mit Synthetischer Apertur, die im X- und L-Band operieren. Landnutzungskartierung spielt eine essentielle Rolle für zahlreiche agrarische Anwendungen; genannt seien hier nur Bewässerungsmaßnahmen, Ernteschätzung und Fördermittelkontrolle. In der vorliegenden Arbeit wurde ein Modell entwickelt, welches auf Grundlage einer Texturanalyse der genannten SAR-Daten für variable Richtungen und Distanzen eine Klassifikation landwirtschaftlicher Nutzungsformen ermöglicht. Das Modell wurde als zusätzliche Funktionalität für die ArcGIS-Software implementiert. Es bindet dabei Klassifikationsverfahren ein, die aus dem Funktionsschatz der Sprache „R“ entnommen sind. Zum Konzept: Ein Bündel von Texturparametern wird durch das vorliegende Programm auf Schlagbasis berechnet und in einer Polygonattributtabelle der landwirtschaftlichen Schläge abgelegt. Auf diese Attributtabelle greift das nachfolgend einzusetzende Klassifikationsmodul zu. Die Software erlaubt nun die Suche nach „aussagekräftigen“ Teilmengen innerhalb des umfangreichen Texturmerkmalsraumes. Im Klassifikationsprozess kann aus verschiedenen Ansätzen gewählt werden. Genannt seien „Support Vector Machine“ und künstliche neuronale Netze. Das Modell wurde für einen typischen mitteleuropäischen Untersuchungsraum mit landwirtschaftlicher und gartenbaulicher Nutzung getestet. Er liegt südlich von Pirna im Freistaat Sachsen. Zum Test lagen für den Untersuchungsraum Daten von TerraSAR-X und ALOS/PALSAR (HH/HV) aus identischen Aufnahmetagen vor. Die Untersuchungen beweisen ein hohes Potenzial der Texturinformation aus hoch aufgelösten SAR-Daten für die landwirtschaftliche Nutzungserkennung. Auch die erhöhte Dimensionalität durch die Kombination von zwei Sensoren erbrachte eine Verbesserung der Klassifikationsgüte. Kenntnisse der Bodenfeuchteverteilung sind u.a. bedeutsam für Bewässerungsanwendungen und hydrologische Modellierung. Die oben genannten SAR-Datensätze wurden auch zur Bodenfeuchteermittlung genutzt. Eine Verifikation wurde durch synchrone Feldmessungen ermöglicht. Initial musste der Radar-typische „Speckle“ in den Bildern durch Filterung verringert werden. Verschiedene Filtertechniken wurden getestet und das beste Resultat genutzt. Die Bodenfeuchtebestimmung erfolgte in Abhängigkeit vom Nutzungstyp über Regressionsanalyse. Auch die Resultate für die Bodenfeuchtebestimmung bewiesen das Nutzpotenzial der genutzten SAR-Daten für offene Ackerböden und Stadien, in denen die Kulturpflanzen noch einen geringen Bedeckungsgrad aufweisen.

Η παρούσα διατριβή είχε σαν κύριο στόχο την ανάλυση και επεξεργασία των δεδομένων SAR υπό το πρίσμα του περιεχομένου υφής για την ανίχνευση περιοχών με περιβαλλοντικές αλλοιώσεις όπως είναι οι παράνομες εναποθέσεις απορριμμάτων. Τα δεδομένα που χρησιμοποιήθηκαν προέρχονταν από τον δορυφόρο ENVISAT και το όργανο ASAR του Ευρωπαϊκού Οργανισμού Διαστήματος με διακριτική ικανότητα 12.5m και 30m για τις λειτουργίες μονής και διπλής πολικότητας αντίστοιχα καθώς και από τον δορυφόρο Terra-SAR με διακριτική ικανότητα 3m και HH πολικότητα. Χρησιμοποιήθηκαν κλασσικές τεχνικές ανάλυσης και ταξινόμησης υφής όπως GLCM, Markov Random Fields, Gabor Filters και Neural Networks. Η μελέτη προσανατολίστηκε στην ανάπτυξη νέων μεθόδων ταξινόμησης υφής για αυξημένη αποτελεσματικότητα. Χρησιμοποιήθηκαν δεδομένα πολυφασματικά και SAR. Για τα πολυφασματικά δεδομένα προτάθηκε η χρήση της spectral co-occurrence ως χαρακτηριστικό υφής που χρησιμοποιεί πληροφορία φασματικού περιεχομένου. Για τα δεδομένα SAR αναπτύχθηκε μία νέα μέθοδος ταξινόμησης η οποία βασίζεται σε συνήθεις περιγραφείς υφής (GLCM, Gabor, MRF) οι οποίοι μελετώνται για την ικανότητά τους να διαχωρίζουν ζεύγη μεταξύ τάξεων. Για κάθε ζεύγος τάξεων προκύπτουν χαρακτηριστικά υφής που βασίζονται στις στατιστικές ιδιότητες της cumulative καθώς και της πρώτης και δεύτερης τάξης αυτής. Η μέθοδος leave one out χρησιμοποιείται για τον εντοπισμό των χαρακτηριστικών που μπορούν να διαχωρίσουν τα δείγματα ανά ζεύγη τάξεων στα οποία αντιστοιχίζεται και ένας ξεχωριστός και ανεξάρτητος γραμμικός ταξινομητής. Η τελική ταξινόμηση γίνεται με τη μέθοδο της πλειοψηφίας η οποία εφαρμόζεται στο πρόβλημα των δύο τάξεων και τριών τάξεων αλλά επεκτείνεται και στο πρόβλημα των N-τάξεων δεδομένης της ύπαρξης κατάλληλων χαρακτηριστικών. / Texture characteristics of MERIS data based on the Gray-Level Co-occurrence Matrices (GLCM) are explored as far as their classification capabilities are concerned. Classification is employed in order to reveal four different land cover types, namely: water, forest, field and urban areas. The classification performance for each cover type is studied separately on each spectral band, while the combined performance of the most promising spectral bands is explored. In addition to GLCM, spectral co-occurrence matrices (SCM) formed by measuring the transition from band-to-band are employed for improving classification results. Conventional classifiers and voting techniques are used for the classification stage. Furthermore, the properties of texture characteristics are explored on various types of grayscale or RGB representations of the multispectral data, obtained by means of principal components analysis (PCA), non-negative matrix factorization (NMF) and information theory. Finally, the accuracy of the proposed classification approach is compared with that of the minimum distance classifier. A simple and effective classification method is furthermore proposed for remote sensed data that is based on a majority voting schema. We propose a feature selection procedure for exhaustive search of occurrence measures resulting from fundamental textural descriptors such as Co-occurrence matrices, Gabor filters and Markov Random Fields. In the proposed method occurrence measures, that are named texture densities, are reduced to the local cumulative function of the texture representation and only those that can linearly separate pairs of classes are used in the classification stage, thus ensuring high classification accuracy and reliability. Experiments performed on SAR data of high resolution and on a Brodatz texture database have given more than 90% classification accuracy with reliability above 95%.