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Kubíček, Jan. „Statistická podpora procesu řízení firmy“. Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-443764.
Der volle Inhalt der QuelleMarklund, Per. „A 2D Electrical Resistivity Survey of Palsas in Tavvavuoma, sub-arctic Sweden“. Thesis, Uppsala universitet, Luft-, vatten och landskapslära, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-219932.
Der volle Inhalt der QuelleElektrisk resistivitetstomografi (ERT) är en geofysisk metod som har använts flitigt vid undersökningar av alpin permafrost, men få studier har hittills tillämpat denna teknik vid undersökningar av permafrost i myrmarker. Under detta examensarbete på masternivå mättes 5 ERT-profiler över 17 palsar samt torvplatåer i ett palsmyrkomplex med sporadisk permafrost i Tavvavuoma, norra Sverige, med det primära målet att undersöka permafrostens mäktighet under dessa. De beräknade permafrostdjupen används även för att uppskatta isöverskottsfraktionen (EIF), vilket ger en indikation på andelen segregationsis i den frusna kärnan under respektive pals/torvplatå. Palsarnas interna struktur och den rumsliga utbredningen av permafrost i myren diskuteras också kvalitativt utifrån resistivitetsmodellerna. Permafrostmäktigheten under palsar och torvplatåer bestämdes till mellan 5 – 17 meter, med den djupaste permafrosten i den västra delen av studieområdet. Isöverskottsfraktionen varierar mellan 0,04 – 0,58, med de lägsta värdena i samma del av studieområdet som den djupaste permafrosten fanns, här är även palshöjderna låga. Den djupa permafrosten i kombination med låga palshöjder föreslås tillskrivas förekomst av grovkorniga (glaciofluviala) sediment i denna del av studieområdet, där bildningen av segregationsis begränsas. I och med detta begränsas mängden frosthävning, med låga palshöjder som resultat. Djup permafrost kan finnas under minst två thermokarstsänkor i området, vilket kan hindra dränering av dessa. Ett oväntat resultat var att palshöjd minskar med ökat permafrostdjup bland de studerade objekten, vilket bäst kan förklaras med det varierade sedimentunderlaget, som ger mycket olika förutsättningar för segregationsisbildning. Denna masteruppsats visar på tillämpligheten av ERT i myrmarker med permafrost, men beaktar även metodens begränsningar för denna tillämpning.
Swan, Marc C. „Anisotropic self-inflating tissue expanders in reconstructive palstic surgery“. Thesis, University of Oxford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497105.
Der volle Inhalt der QuelleCummings, Craig E. „A geoecological investigation of palsas in the Schefferville area /“. Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=57008.
Der volle Inhalt der QuellePatrícia, Barbosa de Alencar Bruna. „Análise de áreas de sombras em imagens ALOS/PALSAR“. Universidade Federal de Pernambuco, 2013. https://repositorio.ufpe.br/handle/123456789/10466.
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As imagens de RADAR são uma alternativa para a realização de mapeamentos em áreas de grande cobertura de nuvens, inerentes às imagens de sensores passivos. Entretanto, devido à variação de declive dos terrenos, que influência o ângulo de incidência do feixe emitido pelo RADAR, alguns erros geométricos ocorrem nas imagens. Esses erros são o encurtamento de rampa, inversão do relevo e o sombreamento. O objeto de estudo desta dissertação é a análise da ocorrência da sombra nas imagens ALOS/PALSAR, por ser uma área que não tem sinal de retorno e por gerar confusão no mapeamento de áreas como, por exemplo, as de vegetação. O sombreamento pode ocorrer em regiões de terreno movimentado e onde a face do relevo está voltada perpendicularmente ao pulso enviado pela antena ALOS/PALSAR. Para analisar a geração da sombra, são estudadas duas áreas de terreno movimentado. As áreas estão nos municípios de Petrolândia em Pernambuco e Glória na Bahia. Elas apresentam relevo ondulado controlado por zonas de cisalhamento, dobramentos e falhas geológicas. Uma metodologia de detecção da sombra ALOS/PALSAR é realizada, através da binarização da imagem ALOS/PALSAR supondo que para a área de sombra o retorno de sinal é muito baixo. Curvas de nível, mapa de orientação de vertentes e mapa de declividade foram adquiridos do projeto TOPODATA para verificar as características do terreno que influenciam na ocorrência do sombreamento, a escala utilizada foi de 1:100000. As imagens LANDSAT5/TM permitiram localizar as feições e compará-las com as regiões de sombra localizadas nas imagens ALOS/PALSAR. A área de sombra foi identificada na região de declividade, predominantemente, maior que 75% e nas orientações Sudeste e Sul. Os dados de orientação de vertentes e declividade serviram como dados fundamentais na identificação das áreas de sombra, juntamente com a imagem binarizada para identificar o baixo retorno do sinal que ocorre nas imagens de RADAR.
An, Weidong. „Palsa formation, mathematical modelling and field information“. Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq26040.pdf.
Der volle Inhalt der QuelleWu, Meng-Che. „Wenchuan earthquake deformation 3D modelling based on ALOS/PALSAR data“. Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/10975.
Der volle Inhalt der QuelleMaciel, Luz Marilda de Moraes. „Processamento de imagens ALOS/PALSAR aplicado à regularização fundiária na Amazônia“. reponame:Repositório Institucional da UnB, 2012. http://repositorio.unb.br/handle/10482/12607.
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A regularização fundiária é uma das ações do Governo Federal no ordenamento fundiário e combate ao desmatamento. O Programa Terra Legal Amazônia foi criado em 2009 para conceder títulos de domínio de terra a posseiros ocupantes de terras públicas federais. Um dos quesitos para a concessão de títulos aos ocupantes é o cumprimento da legislação ambiental. O sensor PALSAR (radar) apresenta um grande potencial para o mapeamento da cobertura e uso da Terra e é ideal para a aquisição de dados na região amazônica, onde a cobertura de nuvens afeta o imageamento por sensores ópticos. O objetivo deste trabalho é avaliar métodos de processamento de imagem de radar para classificar a cobertura e uso da Terra na Gleba do Baixo Candeias Igarapé Três Casas (RO) e verificar o cumprimento da legislação ambiental nessas ocupações. A coleta de amostras de treinamento (utilizadas na classificação) e teste (utilizadas na validação) foi orientada pelas classes de cobertura e uso da Terra mapeadas pelo Projeto TerraClass (agricultura, pasto limpo, pasto sujo, regeneração com pasto, vegetação secundaria e floresta). Foram testados os filtros Enhanced Frost, Enhanced Lee e Gamma,janelas 3x3 e 5x5, nas imagens SAR de polarização HH e HV para a remoção de ruído. Os valores da razão sinal ruído para as classes de cobertura e uso foram muito semelhantes, ligeiramente superiores para o filtro Gamma, janela 5x5 da polarização HV. Foram também testadas diferentes composições univariadas e bivariadas para melhorar a qualidade das imagens antes da classificação pelos métodos MAXVER e ICM. Entre as composições univariadas, a melhor concordância com o Mapa Digital do TerraClass foi atribuída apolarização HV, filtro Gamma, janela 5x5, classificada pelo método ICM (índice Kappa 0,6661) e entre as bivariadas, a composição HH+HV/HV, filtro Gamma, janela 5x5, classificada pelo método ICM (índice Kappa 0,6735). Por fim foi utilizada uma nova abordagem que combina filtragem espectral e componentes de densidade de probabilidade (CDP) e classificação pelo método de Mínima Distância.A imagem de polarização HV resultante da classificação apresentou excelente concordância com o Mapa Digital TerraClass (índice Kappa 0,9816). As imagens PALSAR demonstraram ser boa fonte de dados para o mapeamento de áreas de floresta e não floresta na região de estudo. Apesar das classes intermediárias entre floresta e pasto limpo apresentarem certo grau de confusão, como sinalizado nas análises preliminares, isso não comprometeu a discriminação de áreas florestadas e áreas não florestadas, possibilitando a quantificação de áreas de Reserva Legal existentes e áreas de Reserva Legal previstas em lei, nas parcelas. _______________________________________________________________________________________ ABSTRACT
Land regularization is one of the actions of the Federal Government to territorial planning and to combat deforestation. The Programa Terra Legal Amazônia was created in 2009 to grant titles of domain to squatter occupants of public federal lands. One of the requirements for the granting of titles to occupants is the enforcement of environmental legislation. The sensor PALSAR (radar) presents a great potential for mapping land use cover and is ideal for data acquisition in the Amazon region where cloud cover affects imaging by optical sensors. The aim of this work is to evaluate image processing methods to classify land use cover at Gleba do Baixo Candeias Igarapé Três Casas (RO) and verify the enforcement of environmental legislation in these occupations. The collect of training samples (used in the classification)and test (used in the validation) was guided by land cover classes mapped by Projeto TerraClass (agriculture, clean pasture, dirty pasture, regeneration with pasture, secondary vegetation and forest). In order to remove noises, the filters Enhanced Frost, Enhanced Lee and Gamma, 3x3 and 5x5 windows, were applied on SAR images of HH and HV polarizations. Signal-to-noise ratio values were very close among land use classes, slightly superior for the Gamma filter, 5x5 window of the HV polarization. In order to improve image quality were tested different univaried and bivaried compositions before the classification by the MAXVER and ICM methods. Among univaried compositions the best agreement with the Mapa Digital do TerraClass was obtained by the HV polarization image, Gamma filter, 5x5 window classified by the ICM method (Kappa index of 0,6661) and among the bivaried, the composition HH+HV/HV, Gamma filter, 5x5 window classified by the ICM method (Kappa index of 0,6735). Lastly was used a new approach that combines spectral filtering and density of probability components (CDP) and classification by Mínima Distancia method. The HV image obtained as result of this procedure presented the best agreement with the Mapa Digital TerraClass (Kappa index of 0,9816). The PALSAR images were considered a good source of data to map forested and non-forested areas in the study site. In spite of the intermediate classes between forest and pasture presented a certain degree of confusion, as flagged in the preliminary analysis, this did not affected the discrimination of forested and deforested areas,enabling the quantification of the existing Reserva Legal areas and Reserva Legal areas provided by legislation in plots.
Carlson, David. „Dynamic process model of palsa genesis and development based on geomorphologic investigations at the Boundary Ridge Palsa Bog near Schefferville, Quebec“. Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=18192.
Der volle Inhalt der QuelleLa simulation numérique pour les procédés de formation est un instrument important pour le choix des matériaux, la conception d'outils et l'optimisation des procédés. Un des composants critiques de la simulation reste cependant un modèle constitutif de matériaux précis, pouvant décrire la réponse du matériau sous des modes de déformation possibles. Par ailleurs, l'exactitude est liée aux essais et aux techniques appliqués pour l'identification des modèles constitutifs: plus l'identification est raffinée, plus les paramètres du matériau sont fiables. Pour des composés textiles, des facteurs incontrôlables tels que le frottement de contact, la déviation d'alignement, le glissement, les variations de volume local des fibres, et le tassement des fibres sont des sources qui produisent un éparpillement considérable dans la réponse des tissus. Par conséquent, les méthodes de caractérisation souffrent occasionnellement de la non-répétabilité des données des essais même lorsque les conditions d'essais sont semblables. De plus, il est typique que différents ensembles de paramètres du matériau soient obtenus à partir des différents modes de déformation. Si la variance de la réponse du matériau dans les répliques d’essais et les modes de déformation est négligée, l'identification des paramètres du modèle peut alors être loin du véritable comportement du matériau. Afin de confronter les imperfections mentionnées ci-dessus, la présente étude est une tentative d'élaboration de la caractérisation des composés textiles en utilisant une nouvelle méthode inverse basée sur un schéma pondéré signal/bruit et deux modèles constitutifs par le biais d’une approche basée sur l’invariance des phénomènes. Une identification complète des modèles constitutifs développés est appliquée à un tissu typique en utilisant la méthode inverse proposée et un ensemble de données obtenus à partir des méthodes d'essais stand
Nicolas, Timothée. „Transport de particules induit par les Dents-de-Scie dans les palsmas de tokamak“. Phd thesis, Ecole Polytechnique X, 2013. http://pastel.archives-ouvertes.fr/pastel-00926428.
Der volle Inhalt der QuelleŞahin, Sedar Cihan. „Surface deformation analysis over a hydrocarbon reservoir using InSAR with ALOS-PALSAR data“. Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79299.
Der volle Inhalt der QuelleCataloged from PDF version of thesis.
Includes bibliographical references (p. 92-97).
InSAR has been developed to estimate the temporal change on the surface of Earth by combining multiple SAR images acquired over the same area at different times. In the last two decades, in addition to conventional InSAR, numerous multiple acquisition InSAR techniques have been introduced, including permanent scatterer (PS) (Ferretti et al., 2001) and small baseline subset (SBAS) (Berardino et al., 2002). Stanford method for persistent scatterers (StaMPS) (Hooper, 2006) is another multiple acquisition method that has been developed for estimating ground deformation and differs from the permanent scatterer technique through the method used for pixel selection. In this project, we used the SBAS method to detect the surface deformation over a hydrocarbon reservoir in Adiyaman Providence, Turkey. The SBAS technique is performed on combinations of SAR images that are characterized by small orbital distances with large time intervals. By applying singular value decomposition (SVD), the temporal sampling rate is increased and those subsets are connected. We applied the SBAS method to five ALOS-PALSAR fine-beam dual (FBD) mode images, and removed the topographic phase by using a 3 arc-sec SRTM digital elevation model (DEM). The atmospheric artifacts are determined and filtered out based on available spatial and temporal information on processed data. Our analysis has revealed that due to the effective mitigation measures taken by the oil company, the maximum observed LOS displacement velocity in the oil field is 5 mm/yr with a likely uncertainty of a similar magnitude in the period of 2007-2010. The high uncertainty estimate is due to the other spatially correlated signals of similar and larger magnitude seen in regions outside of the oil field.
by Sedar Cihan Sahin.
S.M.in Geophysics
Picoli, Michelle Cristina Araújo 1981. „Utilização de dados PALSAR/ALOS (banda L) no monitoramento da cana-de-açúcar“. [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256838.
Der volle Inhalt der QuelleTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola
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Resumo:A cana-de-açúcar (Saccharum spp.) exerce papel fundamental na economia na medida em que fornece matéria prima para a produção das comodities açúcar e álcool. Dentro deste contexto a necessidade de informações, as quais possibilitam o acompanhamento desta, é extremamente importante porque permite avaliar a disponibilidade da matéria prima e sua demanda. Para isto, é necessário o monitoramento constante da cultura e uma das formas de se fazer é com o uso de imagens de sensoriamento remoto. Porém, sabe-se que nem sempre isso é possível devido aos períodos chuvosos que ocorrem durante a safra e, portanto, dificultando a aquisição de imagens de satélite livre de nuvens. Para tentar minimizar este problema, a utilização de sensores ativos, como é o caso dos sensores radar de abertura sintética (SAR - Synthetic Aperture Radar), pode ajudar. Os sensores SAR podem coletar dados da superfície em áreas com freqüente cobertura de nuvens e névoa, operando inclusive à noite. Sendo assim, este trabalho teve como objetivo: analisar o potencial das imagens de radar PALSAR/ALOS, polarizações HH e HV, no monitoramento da cultura de cana-de-açúcar, determinar os efeitos das linhas de plantio em culturas de cana-de-açúcar nessas imagens de radar e estimar a produtividade agrícola em talhões de cana-de-açúcar, por meio de um modelo utilizando imagens de radar do sensor PALSAR/ALOS e dados agronômicos, nas safras: 2007/08, 2008/09, 2009/10 na região nordeste do Estado de São Paulo. Os resultados mostraram que foi capaz de detectar mudanças na estrutura (biomassa) da cana-de-açúcar. Os valores médios do coeficiente de retroespalhamento (?°), provenientes de talhões, com linhas de plantio perpendiculares, na polarização HH, foram mais altos que os dos talhões com linhas paralelas à linha de visada do sensor (0,7 a 2,3 dB mais altos, 1,2 dB em média). Para a polarização HV não houve diferença estatisticamente significativa. Já os modelos de estimativa de produtividade explicaram 79%, 12% e 74% da variação da produtividade agrícola observada nos talhões nos anos safra 2007/08, 2008/09 e 2009/10, respectivamente, e o modelo considerando as três safras juntas explicou 66%. Esses resultados podem ser usados para auxiliar e aprimorar a estimativa da produtividade feita in loco, e, principalmente, proporcionar uma alternativa ao monitoramento da cultura sob quaisquer condições climáticas
Abstract: The sugarcane (Saccharum spp.) plays important role in economy because it is source of raw material for sugar and alcohol production. In this context the information needs, which enables its monitoring is very important due to allows evaluate the availability of raw material and its demands. For this, it is need a crop systematical monitoring and one of the ways to do this is through the use of remote sensing images. However, it known that it is not always possible due to the rainy season that occurs in certain periods during the crop phenological phases, impeding the acquisition of optics satellite images free of clouds. To get around this problem the use of active sensors, such as sensors of synthetic aperture radar (SAR) can help. SAR sensors can collect data in areas with frequent cloud cover and fog and can operate even at night. Therefore, this study aimed to analyze the potential of radar PALSAR/ALOS, in HH and HV polarizations, for monitoring the sugarcane crop, to determine the effects of planting rows on the backscatter and estimate sugarcane yield by means of model using radar sensor PALSAR/ALOS and agronomic data, in crop seasons: 2007/08, 2008/09, 2009/10 in northeastern region of São Paulo. The results are promising because it was able to show changing in biomass enabling the monitoring. The mean values of the backscattering coefficient (?°) from fields with perpendicular rows, in HH polarization, were higher than those from parallel rows to the range direction of the satellite (0.7 to 2.3 dB over high, 1.2 dB on average). For HV polarization, there was no statistically significant difference. The yield model estimation, explained 79%, 12% and 74% of the variation in final yield, observed in the plots, in crop seasons 2007/08, 2008/09 and 2009/10, respectively, and the model built for the three crop seasons together explained 66% . These results can be used to assist and improve the prediction of yield performed in loco, and mainly to afford an alternative for crop monitoring in some weather conditions
Doutorado
Planejamento e Desenvolvimento Rural Sustentável
Doutora em Engenharia Agrícola
Neta, Sumaia Resegue Aboud. „Uso de imagens ALOS/PALSAR multipolarizadas para detecção de incremento de desflorestamento na Amazônia“. Instituto Nacional de Pesquisas Espaciais, 2009. http://urlib.net/sid.inpe.br/mtc-m19@80/2009/11.19.09.48.
Der volle Inhalt der QuelleThe Amazon forest is a region of rainforest, which has about 5,4 million square kilometers, and with great biodiversity of species on the planet. However, its traditional model of occupation has lead to significant levels of increase of deforestation in the brazilian Legal Amazon. Through remote sensing, these areas can be constantly monitored, offering rates of control and estimation of deforested areas. Due to the high rainfall rates, humidity and presence of clouds, which characterize the Amazon region climate during the year, there are limitations in optical imaging. The ability of Radar sensors to acquire images through the clouds allows the continuous imaging of areas regardless of weather conditions in the region. In this context, this study evaluated the potential of the full polarized amplitude PLR ALOS/PALSAR L band data to discriminate the deforestation increase over National Forest of Tapajos-PA. The radar image segmentations and classifications with no filter and Gamma 5x5 filter were performed. The MAXVER-ICM and Bhattacharyya (combined with SPRING and SEGSAR segmentations) classifiers were used for all combinations of the multipolarized images: HH, HV, VV, HH + HV, HV + VV, HH + VV and HH + HV + VV. The results were compared with the PRODES thematic map to detect the deforestation increment and the existence of significant information loss when all the polarized channels were not used, and to find the best polarization which characterizes the deforestation. The Bhattacharyya classifier had higher accuracy than MAXVERICM classifier. The best classifications were obtained when the HH + HV polarization (with and without filter, segmented by SPRING and SEGSAR) was used. The highest accuracy was obtained for the no filter SPRING (kappa of 0.5085). However, the HH + HV producer's accuracy was minor compared with other combinations of polarization because the error of omission (E.O.) has been higher. For the other channel combinations, the lower E.O. was obtained when the SEGSAR (in the image with filter and with no filter) and SPRING (in the image with filter) segmentations were used but the error of inclusion (E.I.) was higher in relation to classification of higher kappa in all these classifications. There was a detailed analysis of these four classifications. The results showed that the use of radar mapping in tropical regions is an additional powerful tool for the soil cover information acquisition throughout the year. The combined radar and optical data is recommended for the detection of new deforestation (due to water accumulation in the soil a few days before the imaging radar, and the incidence of biomass (stump) in the soil in the region of study), because the high E.I. and in some cases E.O. classifications has limited the use of radar.
Zuidhoff, Frieda S. „Palsa Growth and Decay in Northern Sweden : Climatic and Environmental Controls“. Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2003. http://publications.uu.se/theses/91-554-5546-8/.
Der volle Inhalt der QuelleGurney, Stephen D. „Investigations into the geomorphology and sedimentology of permafrost related pingos and palsas : ancient and modern“. Thesis, University of Reading, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239172.
Der volle Inhalt der QuelleBERNINI, Thiago Andrade. „Utiliza??o de imagens ALOS/PALSAR no mapeamento digital de atributos f?sicos dos solos“. Universidade Federal Rural do Rio de Janeiro, 2016. https://tede.ufrrj.br/jspui/handle/jspui/2317.
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The survey and analysis of the spatial distribution of soil attributes through geostatistics tools are essential for agricultural land use according to soil capability. The images of synthetic aperture radar (SAR) have great potential for soil moisture estimation and, thus, these sensors can assist in mapping the physical-hydric and physical properties of soils. The overall objective of this study was to evaluate the potential use of radar images (microwave) ALOS/PALSAR on the identification of soils in an area of the Botucatu formation, dominated by sandy and medium texture soils in the municipality of Mineiros, Goi?s State, Brazil. The area has approximately 946 hectares, with the relief of the region ranging from plain to low undulating hills and the geology of the area is composed basically by sandstones of the Botucatu formation. In the present study there were sampled 84 points for calibration and 25 points for validation, collected in the depths of 0-20 cm and 60-80 cm. The soil samples were analyzed for the determination of sand, silt, clay, field capacity (CC), permanent wilting point (PMP) and total water available (AD). For the development of the work were acquired ALOS/PALSAR radar images of five dates and different polarizations, totaling 14 images, which were processed for the geographic and radiometric corrections, using a DEM. Were also generated covariates of terrain attributes: high (ELEV), slope (DECLIV), relative position of the slope (PR-DECL), vertical distance of the drainage channel (DVCD), ls factor (FACTOR-LS) and Euclidean distance (D-EUCL). Prediction of soil attributes was performed using Random Forest methods (RF) and Random Forest Kriging (RFK), having as predictive covariates the radar imaging and terrain attributes. Image processing of the ALOS/PALSAR radar images enabled the geographical and radiometric corrections, transforming the data into backscatter coefficient (??) in units of dB, corrected by digital elevation model (MDE). The acquired images represented broad range of ?? between the different dates. The soils of the study area are predominantly sandy, with most of the sampled points classified as Neossolos Quartzar?nicos (Entisols), followed by Latossolos (Oxisols). The RF models employed for prediction of physical-hydric and physical attributes of soils provided an analysis of the contribution of these covariates in the predictive models. The landscape attributes that caused the largest impact in the prediction of the studied attributes are related to the altitude. The images of 5/3/2009 (HH1, VV1, HV1 and VH1) and 9/26/2010 (HH3 and HV3), obtained in drier periods, had best correlations with the soil attributes. The analysis of the semivariograms of the RF prediction models residues demonstrated greater spatial dependence in the 60 to 80 cm layer. The Kriging approach coupled with RF model contributed to the improvement of the prediction of sand, clay, CC and PMP. Using ALOS/PALSAR radar images and terrain attributes as covariates in RFK models showed potential to estimate the physical (sand and clay) and physical-hydric (CC and PMP) attributes, which can assist in mapping of soils associated with the Botucatu formation parent materials.
O levantamento e a an?lise da espacializa??o dos atributos do solo atrav?s de ferramentas de geoestat?stica s?o fundamentais para que cada hectare de terra seja cultivado segundo as suas reais aptid?es. As imagens de radar de abertura sint?tica (SAR) t?m um grande potencial para a estima??o de umidade do solo e, desta forma, estes sensores podem auxiliar no mapeamento de propriedades f?sicas e f?sico-h?dricas dos solos. O objetivo geral deste estudo foi avaliar o potencial de utiliza??o de imagens de radar (micro-ondas) ALOS/PALSAR na identifica??o de solos em uma ?rea da Forma??o Botucatu, dominada por solos de textura arenosa e m?dia no munic?pio de Mineiros - GO. A ?rea tem aproximadamente 946 ha, com o relevo da regi?o variando de plano a suave ondulado e geologia da ?rea ? composta basicamente, por Arenitos da Forma??o Botucatu. No presente estudo foram amostrados 84 pontos para calibra??o e 25 pontos para valida??o, coletados nas profundidades de 0-20 cm e 60-80 cm. As amostras de solo analisadas para a determina??o de areia, silte, argila, capacidade de campo (CC), ponto de murcha permanente (PMP) e ?gua total dispon?vel (AD). Para o desenvolvimento do trabalho foram adquiridas imagens de cinco datas e diferentes polariza??es, totalizando 14 imagens, que foram processadas para a corre??o geom?trica e corre??o radiom?trica, utilizando o MDE. Tamb?m foram gerados covari?veis dos atributos do terreno: eleva??o (ELEV), declividade (DECLIV), posi??o relativa da declividade (PR-DECL), dist?ncia vertical do canal de drenagem (DVCD), fator-ls (FATOR-LS) e dist?ncia euclidiana (D-EUCL). A predi??o dos atributos do solo foi realizada utilizando os m?todos Random Forest (RF) e Random Forest Krigagem (RFK), tendo como covari?veis preditoras as imagens de radar e os atributos do terreno. O processamento das imagens do radar ALOS/PALSAR possibilitou as corre??es geom?trica e radiom?trica, transformando os dados em unidades de coeficiente de retroespalhamento (??) corrigidos pelo modelo digital de eleva??o (MDE). As imagens adquiridas representaram de forma ampla as varia??es de ?? ocorridos em diferentes datas. Os solos da ?rea de estudo s?o predominantemente arenosos, com a maioria dos pontos amostrados classificados como NEOSSOLOS QUARTZAR?NICOS, seguidos dos LATOSSOLOS. Os modelos RF empregados para a predi??o dos atributos f?sicos e f?sico-h?dricos dos solos proporcionaram a an?lise da contribui??o das covari?veis preditoras. Os atributos do terreno que exerceram maior influ?ncia na predi??o dos atributos estudados est?o relacionados ? eleva??o. As imagens de 03/05/2009 (HH1, VV1, HV1 e VH1) e 26/09/2010 (HH3 e HV3), obtidas em per?odos mais secos, tiveram melhores correla??es com os atributos do solo. As an?lises dos semivariogramas dos res?duos da predi??o dos modelos RF demonstraram maior depend?ncia espacial na camada de 60 a 80 cm. A abordagem da Krigagem somada ao modelo RF contribu?ram para a melhoria da predi??o dos atributos areia, argila, CC e PMP. O uso de imagens de radar ALOS/PALSAR e atributos do terreno como covari?veis em modelos RFK mostrou potencial para estimar os atributos f?sicos (areia e argila) e f?sico-h?dricos (CC e PMP), que podem auxiliar no mapeamento de solos associados aos materiais de origem da Forma??o Botucatu.
Beneditti, Cristina Aparecida [UNESP]. „Imagens multitemporais ALOS/PALSAR baseada em orientação a objeto na discriminação da cobertura da terra“. Universidade Estadual Paulista (UNESP), 2010. http://hdl.handle.net/11449/86778.
Der volle Inhalt der QuelleConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Sensores ópticos são amplamente utilizados para mapeamento da cobertura da terra em escala local e pequenas regiões, com uma ampla variedade de aplicações, incluindo planejamento urbano, inventario agrícola e florestal, gerenciamento de bacias hidrográficas e monitoramento ambiental. Mapeamento de cobertura da terra com dados da banda L SAR tem focado primariamente em florestas e área úmidas de regiões tropical e boreal, com ênfase no monitoramento de desmatamento tropical e reflorestamento. No inicio de 2006, aquisições sistemáticas do ALOS PALSAR tem fornecido conjunto de dados multisazonais com alta resolução (12,5m), com potencial para substituir ou complementar os conjuntos de dados ópticos para mapeamento de cobertura da terra em regiões que a cobertura de nuvens é menos problemática, mas ainda um limitante para a variação sazonal da cobertura da terra. Este estudo avalia a utilização de dados PALSAR multitemporal, combinados com modelo digital de superfície (DSM) derivado do ALOS PRISM, para o mapeamento da cobertura da terra em uma região central do estado de São Paulo, Brasil. A área de estudo (22.5ºS 47.8 ºW) está situada na região oeste do reservatório de Barra Bonita, próximo a confluência dos rios Tietê e Piracicaba, com elevações variando entre 300 e 1000m. Os usos da terra dominante são agricultura ( cana de açúcar, cítricas e gramíneas) e florestal (eucaliptos). A vegetação natural é restrita a vegetação riparia, mata na front da cuesta e macrofitas aquáticas sazonais. Áreas urbanas presente na região são São Pedro e Aguas de São Pedro. Duas cenas PALSAR no modo Fine-Beam Single-polarization (FBS) (08 de abril de 2008 e 09 de janeiro de 2009...
Optical sensors are widely used for land cover mapping at local and small region scales, for a wide variety of applications including urban planning, forest and crop inventory, watershed management, and environmental monitoring. Land cover mapping with L-band SAR data has focused primarily on forest and wetland areas in tropical and boreal regions, with particular emphasis on monitoring tropical deforestation and regrowth. Beginning in 2006, systematic acquisitions of ALOS PALSAR have provided multi-season, near-global data sets at high (12.5 m) resolution, with the potential to substitute for or complement optical data sets for land cover mapping in regions where cloud cover is less problematic, but still limiting for seasonally varying land cover. This study evaluates the utility of multi-temporal PALSAR data, combined with a digital surface model (DSM) derived from ALOS PRISM, for land cover mapping at a site in central São Paulo state, Brazil. The study area (22.5ºS 47.8 ºW) is situated at the west end of the Barra Bonita Reservoir, at the entrance point of the Tietê River, with elevations ranging from about 300 to 1000 m. Dominant land uses are agriculture (sugar cane, citrus, pasture) and forestry (eucalyptus). Natural vegetation is largely restricted to riparian forest, forests on steep slopes, and seasonal aquatic macrophytes. Urban areas include the cities of São Pedro and Águas de São Pedro. Two PALSAR Fine-Beam Single-polarization (FBS) mode scenes (8 April 2008 and 9 January 2009... (Complete abstract click electronic access below)
Beneditti, Cristina Aparecida. „Imagens multitemporais ALOS/PALSAR baseada em orientação a objeto na discriminação da cobertura da terra /“. Presidente Prudente : [s.n.], 2010. http://hdl.handle.net/11449/86778.
Der volle Inhalt der QuelleAbstract: Optical sensors are widely used for land cover mapping at local and small region scales, for a wide variety of applications including urban planning, forest and crop inventory, watershed management, and environmental monitoring. Land cover mapping with L-band SAR data has focused primarily on forest and wetland areas in tropical and boreal regions, with particular emphasis on monitoring tropical deforestation and regrowth. Beginning in 2006, systematic acquisitions of ALOS PALSAR have provided multi-season, near-global data sets at high (12.5 m) resolution, with the potential to substitute for or complement optical data sets for land cover mapping in regions where cloud cover is less problematic, but still limiting for seasonally varying land cover. This study evaluates the utility of multi-temporal PALSAR data, combined with a digital surface model (DSM) derived from ALOS PRISM, for land cover mapping at a site in central São Paulo state, Brazil. The study area (22.5ºS 47.8 ºW) is situated at the west end of the Barra Bonita Reservoir, at the entrance point of the Tietê River, with elevations ranging from about 300 to 1000 m. Dominant land uses are agriculture (sugar cane, citrus, pasture) and forestry (eucalyptus). Natural vegetation is largely restricted to riparian forest, forests on steep slopes, and seasonal aquatic macrophytes. Urban areas include the cities of São Pedro and Águas de São Pedro. Two PALSAR Fine-Beam Single-polarization (FBS) mode scenes (8 April 2008 and 9 January 2009... (Complete abstract click electronic access below)
Orientador: Nilton Nobuhiro Imai
Coorientadora: Laura Hess
Banca: Maria de Lourdes Bueno Trindade Galo
Banca: Claudia Maria de Almeida
Banca: José Tadeu Garcia Tommaselli
Mestre
Elbialy, Samy Gamal Khedr. „Potential of Spaceborne X & L-Band SAR-Data for Soil Moisture Mapping Using GIS and its Application to Hydrological Modelling: the Example of Gottleuba Catchment, Saxony / Germany“. Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-66626.
Der volle Inhalt der QuelleSouza, Edivaldo Lima de. „Classificação semi-automatizada da cobertura da terra da Amazônia por meio de imagens multitemporais ALOS/PALSAR“. reponame:Repositório Institucional da UnB, 2011. http://repositorio.unb.br/handle/10482/9880.
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A floresta amazônica abriga uma das maiores biodiversidades do planeta e possui cerca de 5,4 milhões de km2. Esta floresta está sofrendo perdas significativas decorrente do desmatamento, principalmente na área da Amazônia Legal, acompanhado pelo aumento da ocupação humana. Por se tratar de uma região de muita umidade, a presença de nuvens durante a maior parte do ano impossibilita o uso de imagens de sensores que operam na região do visível. Desta forma a utilização de imagens de sensores RADAR é favorecida, devido ao fato das ondas eletromagnéticas microondas penetrarem pelas nuvens sem sofrer interferência. Neste contexto, este estudo avaliou a potencialidade do uso de imagens de RADAR para o mapeamento semi-automatizado de áreas desmatadas na Amazônia, utilizando dados multitemporais e multipolarimetricos (HH e HV) SAR em banda L, na região de Machadinho d‟ Oeste, em Rondônia e Confresa, em Mato Grosso, municípios que estão na área de influência do arco de desmatamento. Foram utilizadas imagens multitemporais do sensor ALOS/PALSAR dos meses de abril, junho e julho, relativas aos anos 2007, 2008 e 2009. A caracterização do comportamento do retroespalhamento multitemporalmente reduz a possibilidade de confusão entre alvos parecidos e, consequentemente, aumenta a separabilidade e a precisão de classes de uso do solo. Para confecção dos mapas de uso do solo, o método baseado em regras de decisão para duas variáveis foi aplicado neste trabalho. A primeira variável é resultado da média do retroespalhamento para toda a série temporal, e a segunda, o cálculo do índice de mudança temporal. Em Machadinho d`Oeste, o acerto foi de 86,4% e foram detectadas áreas desmatadas, representando 919 km2 e áreas não desmatadas 2.774 km2. O acerto para a área de Confresa foi de 84,4% com total de áreas desmatadas de 2.311 km2, e áreas não desmatadas 1.313 km2. ______________________________________________________________________________ ABSTRACT
The Amazon rainforest is home to one of the greatest biodiversities on the planet and comprises an area of approximately 5.4 million km2. This forest is suffering significant losses due to deforestation, mainly in the Legal Amazon region, accompanied by increased human occupation. Because it is a region of high humidity, the presence of clouds during most of the year prevents the use of images from sensors that operate in the visible range. Thus the use of RADAR images is favored due to the fact that microwave electromagnetic waves penetrate the clouds without interference. Within this context, this study evaluated the potential use of RADAR images for semi-automatic mapping deforested areas in Amazonia, using multitemporal data with multipolarimetric (HH and HV) SAR L band in the region of Machadinho d 'Oeste, in the State of Rondônia and Confresa, in the State of Mato Grosso. These municipalities are located within the „arc of deforestation‟. Multiple images from the ALOS / PALSAR RADAR for the months of April, June and July of the years 2007, 2008 and 2009 were used. The characterization of multitemporal backscatter reduces the possibility of confusion between similar targets and thus increases the accuracy and separability of classes of land use. The method based on decision rules for two variables was applied to obtain the land use maps. The first variable is the result of the average backscatter for the entire series, and the second variable is the result of the calculation of the temporal change index. In Machadinho d'Oeste, accuracy was 86.4%, were detected deforested areas, representing 919 km2 and 2,774 km2 deforested areas not. The hit to the area of Confresa was 84.4% with total deforested area of 2,311 km2 and 1,313 km2 not deforested areas. ______________________________________________________________________________ RESUMÉ
La forêt amazonienne est le foyer de l'une des plus grandes biodiversités de la planète et a environ 5,4 millions de km2. Cette forêt subit des pertes importantes dues à la déforestation, principalement en Amazonie, accompagné par l'occupation humaine a augmenté. Parce que c'est une région de forte humidité, la présence de nuages pendant la plus grande de l'année empêche l'utilisation d'images provenant de capteurs qui fonctionnent dans la région visible. Ainsi, l'utilisation du RADAR de détection des images est favorisée par le fait de micro-ondes des ondes électromagnétiques pénètrent à travers les nuages sans subir d'interférences. Dans ce contexte, cette étude a évalué la possibilité d'utiliser des images RADAR pour cartographier semi-automatique les zones déboisées en Amazonie, en utilisant des données et multitemporelles Multipolarimetric (HH et HV) SAR en bande L dans la région de Machadinho d 'Oeste dans le Rondônia et Confresa Mato Grosso, les municipalités qui se trouvent dans la zone d'influence de l'arc de déforestation. Nous avons utilisé des images à partir de capteurs multiples ALOS / PALSAR pour le mois d'avril, Juin et Juillet de l'année 2007, 2008 et 2009. La caractérisation de la rétrodiffusion multitemporelle réduit la possibilité de confusion entre des objectifs similaires et augmente ainsi la précision et la séparabilité des classes de l'utilisation des terres. Pour obtenir les cartes d'utilisation des terres, la méthode fondée sur des règles de décision pour les deux variables a été appliquée dans ce travail. La première variable est le résultat de la rétrodiffusion moyenne pour toute la série, et le second, le calcul de l'indice de changement temporel. En Machadinho d'Oeste, la précision était de 86,4%, ont été détectés les zones déboisées, ce qui représente 919 km2 et 2.774 km2 les zones déboisées pas. Le hit de la zone de Confresa était de 84,4% à surface déboisée totale de 2.311 km2 et 1.313 km2 les zones ne déboisées pas.
Negri, Rogério Galante. „Avaliação de dados polarimétricos do sensor ALOS PALSAR para classificação da cobertura da terra da Amazônia“. Instituto Nacional de Pesquisas Espaciais, 2009. http://urlib.net/sid.inpe.br/mtc-m18@80/2009/05.14.12.59.
Der volle Inhalt der QuelleAmazon Forest is considered the largest tropical forest of the planet. It keeps considerable part of the biodiversity and has great importance to the biogeochemistry cycles. The anthropic actions cause destructive processes such as deforestations and burnings, which can provoke unbalances on the ecosystem. This scenario highlights the importance of the monitoring on this area by Remote Sensing. Atmospheric factors over the Amazon region as the cloud cover could affect the quality of the optical remoto sensing. In this context, the use of the imaging radars in the tropics is important, because the atrnospheric conditIons do not flatly prejudice the data acquisition. Polarimetric radars are a recent technology capable to collect a large amount of information of the target characteristics, improving the discrimination capability of them. Recently, the L-band PALSAR sensor on ALOS was launched. The potential of PALSAR data in the discrimination of different targets was evaluated using Maximum Likelihood and the K-Means Wishart H/A/α SAR image classifiers. The results showed that Maximum Likelihood presented higher ability of the target discrimination. The use of Single-Polarization data (HH, HV or VV) is limited to separate different targets, unlike to Dual-, Multi- and Full-Polarization data. Primary forest and regeneration types were not satisfactorily discriminated. However, different agriculture types and pasture were well discriminated. The results showed that the discrimination capacity of targets with Multi- and Full-Polarization data does not provide considerable increase, when compared with results generated by HH+HV and HV+VV Dual-Polarization data. The HH+HV data, named ALOS PALSAR Operational Acquisition Mode, is designated to the study of the tropical forest monitoring using the L-band radars.
Sartori, Lauriana Rúbio [UNESP]. „Informação polarimétrica PALSAR/ALOS aplicada à discriminação de espécies e estimação de parâmetros morfológicos de macrófitas“. Universidade Estadual Paulista (UNESP), 2011. http://hdl.handle.net/11449/100252.
Der volle Inhalt der QuelleCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
O propósito deste trabalho foi avaliar o potencial dos dados PALSAR polarimétricos para discriminar e mapear espécies de macrófitas (vegetação aquática) de uma área alagável da Amazônia, a planície de inundação do Lago Grande de Monte Alegre, no estado do Pará. A coleta de dados foi realizada quase simultaneamente à aquisição dos dados de radar. Três principais espécies de macrófitas foram encontradas na área: Paspalum repens (PR), Hymenachne amplexicaulis (HA) e Paspalum elephantipes (PE). Variáveis morfológicas foram medidas em campo e usadas para derivar outras variáveis tais como a biomassa. Atributos foram gerados a partir da matriz de covariância [C] extraída da imagem ALOS/PALSAR em modo SLC (single look complex). Os atributos polarimétricos foram analisados para as três espécies e identificados aqueles capazes de discriminar as espécies. Foram aplicadas as seguintes abordagens de classificação: baseada em regras, baseada em modelos de decomposição (Decomposições de Freeman-Durden e Cloude-Pottier), baseada em estatística (Classificação supervisionada baseada na distância Wishart) e híbrida (Classificador Wishart com classes de entrada baseadas na decomposição de Cloude-Pottier). Finalmente, a variável morfológica “volume da haste” foi modelada por regressão múltipla em função de alguns atributos polarimétricos. Os resultados sugerem que a imagem polarimétrica banda L possui potencial para discriminar as espécies de macrófitas, sendo os principais atributos para isso sigma zero HH ( ), sigma zero HV ( ) e sigma zero VV ( ), índice de estrutura da copa...
The purpose of this work was to evaluate the potential of fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain, more specifically in the Monte Alegre Lake, in the state of Pará, Brazil. Fieldwork was carried out almost simultaneously to the radar acquisition. Three main species were found in the study area: Paspalum repens (PR), Hymenachne amplexicaulis (HA) and Paspalum elephantipes (PE). Macrophyte morphological variables were measured on the field and used to derive others variables, like the biomass. Attributes were calculated from the covariance matrix [C] derived from the SLC (single look complex) data. The polarimetric attributes were analyzed for the three species and it was identified that ones capable of discriminating them. The following classification approaches were applied: a rule-based classification, model-based classifications (Freeman-Durden and Cloude-Pottier), a statistical-based classification (supervised classification using Wishart distance measure) and a hybrid classification (Wishart classifier with the input classes based on the H/a plane). Finally, the morphological variable “stem volume” was modeled using multiple regression. The findings suggest that the fully polarimetric image has potential for discriminating plant species, being the main attributes sigma-nought HH ( ), sigma-nought HV ( ) and sigma-nought VV ( ), canopy structure index ( ), HH-VV polarimetric coherence ( ), helicity of the third scattering mechanism (τ ), orientation angle of the first scattering mechanism ( ) and scattering type phase of the first mechanism ( ); among the different classifications, only the supervised (Wishart) and the rule-based discriminated the species, with overall accuracy of 75,04% and 87,18%, respectively; the stem volume was modeled using the following attributes: biomass index ( ), volumetric scattering ... (Complete abstract click electronic access below)
Sartori, Lauriana Rúbio. „Informação polarimétrica PALSAR/ALOS aplicada à discriminação de espécies e estimação de parâmetros morfológicos de macrófitas /“. Presidente Prudente : [s.n.], 2011. http://hdl.handle.net/11449/100252.
Der volle Inhalt der QuelleAbstract: The purpose of this work was to evaluate the potential of fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain, more specifically in the Monte Alegre Lake, in the state of Pará, Brazil. Fieldwork was carried out almost simultaneously to the radar acquisition. Three main species were found in the study area: Paspalum repens (PR), Hymenachne amplexicaulis (HA) and Paspalum elephantipes (PE). Macrophyte morphological variables were measured on the field and used to derive others variables, like the biomass. Attributes were calculated from the covariance matrix [C] derived from the SLC (single look complex) data. The polarimetric attributes were analyzed for the three species and it was identified that ones capable of discriminating them. The following classification approaches were applied: a rule-based classification, model-based classifications (Freeman-Durden and Cloude-Pottier), a statistical-based classification (supervised classification using Wishart distance measure) and a hybrid classification (Wishart classifier with the input classes based on the H/a plane). Finally, the morphological variable "stem volume" was modeled using multiple regression. The findings suggest that the fully polarimetric image has potential for discriminating plant species, being the main attributes sigma-nought HH ( ), sigma-nought HV ( ) and sigma-nought VV ( ), canopy structure index ( ), HH-VV polarimetric coherence ( ), helicity of the third scattering mechanism (τ ), orientation angle of the first scattering mechanism ( ) and scattering type phase of the first mechanism ( ); among the different classifications, only the supervised (Wishart) and the rule-based discriminated the species, with overall accuracy of 75,04% and 87,18%, respectively; the stem volume was modeled using the following attributes: biomass index ( ), volumetric scattering ... (Complete abstract click electronic access below)
Orientador: Nilton Nobuhiro Imai
Coorientador: José Cláudio Mura
Banca: Evlyn Marcia Leão de Moraes Novo
Banca: Thiago Sanna Freire Silva
Banca: João Roberto dos Santos
Banca: Vilma Mayumi Tachibana
Doutor
Jackson, Sarah May. „An investigation of the combined stable isotopic composition of methane emissions from northern wetlands“. Thesis, Open University, 1998. http://oro.open.ac.uk/54555/.
Der volle Inhalt der QuellePatruno, Jolanda. „Polarimetric RADARSAT-2 and ALOS PALSAR multi-frequency analysis over the archaeological site of Gebel Barkal (Sudan)“. Phd thesis, Université Rennes 1, 2014. http://tel.archives-ouvertes.fr/tel-01061287.
Der volle Inhalt der QuelleCoultish, Tara L. „Long-term development of palsas and other permafrost-cored mounds in mountainous terrain, Wolf Creek, southern Yukon“. Thesis, University of Ottawa (Canada), 2002. http://hdl.handle.net/10393/6454.
Der volle Inhalt der QuelleMichelakis, Dimitrios. „Using satellite Earth observation & field measurements to assess the above ground woody biomass in the tropical savanna woodlands of Belize“. Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/17879.
Der volle Inhalt der QuelleMartins, Flora da Silva Ramos Vieira. „Caracterização e estimativa de biomassa aérea de florestas atingidas pelo fogo a partir de imagens polarimétricas ALOS/PALSAR“. Instituto Nacional de Pesquisas Espaciais, 2012. http://urlib.net/sid.inpe.br/mtc-m19/2012/03.08.13.38.
Der volle Inhalt der QuelleFire is one of the main factors leading to forest degradation in the Amazon by changing species composition, biomass and structure. Considering the (potential) geographical scale of forest fires, remote sensing provides essential data for mapping, monitoring and even modeling. Despite radar sensors gather information on forest structure, no study based on such data mainly focused on fire affected areas in the Brazilian Amazon. The study area was situated in the \textquotedblleft{Are of F ire}\textquotedblright, in the State of Roraima (Northem Amazonia), where 50 plots (0.25 ha each) were set out. We aimed to model the aboveground biomass (AGB) as a function of polarimetric attributes and to characterize the forest degradation from these attributes. The impacts of understory fires on species composition, stand structure and AGB were also assessed. Field and polarimetric data analyses provided concordant results, revealing that frequent fires promoted a ´secondarization´ of primary forests. Tree species diversity was significantly reduced after recurrent fires. Even after a 12 years post-fire of a single fire, some units were still dominated by Cecropia spp. Significant differences were found on stand structure (density, height, basal area) between fire degradation levels, particularly in thrice bumed forests. The AGB stocks were reduced by 60\% and similar to values previously reported for secondary forests in the same region. Forests that experimented frequent fire showed lower entropy and the presence of surface scattering was emphasized in the H/ plane. The polarimetric responses indicated the dominance of the VV polarization scattering in primary and lightly bumed forests, whereas a dominance of the scattering in HH polarization was noted in heavily and frequent bumed forests. The results suggests that polarimetric coherent and incoherent attributes ($\psi$2, A, Pd, VSI) are both important in modeling AGB in forests characterized by a fire history (R$^{2}$=0.76; RMSE=32.l Mg.ha-l or 27.8\% ofthe mean). No saturation point was detected for the estimates as the AGB values were predicted up to 300 Mg.ha-1. This was attributed to the inclusion of coherent parameters in the model. The model cross-validation (leave-one-out) showed a RMSE equal to 36.6 Mg.ha-1 (31\% of the mean). We found an adjusted R$^{2}$ of 0.7 and a RMSE of 32.45 Mg.ha-1 (23\% of the mean) in the model validation from independent set of samples (hold-out). We thus confirmed that the fullpolarimetric data used in biomass studies are sensitive to the fire degradation level. The high vulnerability of Northem Amazonia tropical forests to fire was also verified. Finally, we underlined the importance of field data collection and analyze as they provide valuable insights to understand the target itself and how it interacts with the radar microwaves.
Horvath, Celesa Lyra. „An evaluation of ground penetrating radar for investigation of palsa evolution, Macmillan Pass, Northwest Territories“. Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0003/MQ28946.pdf.
Der volle Inhalt der QuelleBispo, Polyanna da Conceição. „Efeitos da geomorfometria na caracterização florístico-estrutural da Floresta Tropical na região de Tapajós com dados SRTM e PALSAR“. Instituto Nacional de Pesquisas Espaciais, 2012. http://urlib.net/sid.inpe.br/mtc-m19/2012/06.03.13.58.
Der volle Inhalt der QuelleThe present study aimed to analyze SRTM and ALOS PALSAR data as inputs for floristic and structural study of vegetation as conditioned by relief variations expressed in geomorphometric variables in the TapajósNational Forest. Floristic and structural data were collected on field survey, in plots distributed according to phyto-ecological classes and to geomorphometric conditions. Geomorphometric data derived from SRTM and polarimetric data calculated from PALSAR were extracted in the survey points for analyses together with vegetations data. A species ordination through Detrended Correspondence Analysis (DCA) was accomplished to identify the species distribution groups. Floristic composition variables (abundance, richness and floristic) and geomorphometric data were evaluated through regression analysis. Logistic regression was applied to study the relationships between the occurrences of selected species. In the development of forest structural variables, geomorphometric variables were applied in canonical correlation analysis followed by regression between each structural variable and the geomorphometric variables. For biomass estimates, geomorphometric data were evaluated though multiple regression. SAR data were submitted to exploratory analysis of the polarimetric responses of plots stratified into three terrain types (flat, gentle and steep). An approach to free polarimetric data from relief effects for improvement in biomass estimates by compensating topographic illumination factor was proposed, but did not succeed in the experimented conditions. Finally, SAR and selected geomorphometric data were applied together in multiple regression analyses for a broader statistic model for biomass estimates. This model resulted in a more correlated estimate of biomass than the models accounting for polarimetric variables alone.
Filho, Clódis de Oliveira Andrades. „Análise morfoestrutural da porção central da Bacia Paraíba (PB) a partir de dados MDE-SRTM e ALOS-PALSAR FBD“. Instituto Nacional de Pesquisas Espaciais (INPE), 2010. http://urlib.net/sid.inpe.br/mtc-m19@80/2010/04.08.17.10.
Der volle Inhalt der QuelleThe present study aimed the morphostructural analysis of the central portion of the Paraíba Basin (PB) through integration of qualitative (i.e., density and direction of morphostructural lineaments; drainage patterns and anomalies) and quantitative morphometric indices) information in order to test if drainage and relief evolved under the influence of tectonics. The investigation included remote sensing data derived from both DEM (digital elevation model)-SRTM (Shuttle Radar Topography Mission) and ALOS (Advanced Land Observing Satellite)-PALSAR (Phased Array type L-band Synthetic Aperture) radar system, as well as digital drainage data extracted from DSG (Department of Geographical Service) topographic maps. In addition to help extracting the morphostructural lineaments, the DEM-SRTM also provided the basis to analyse the drainage network and to apply the morphometric indexes. The results revealed that the DEM-SRTM was more efficient to enhance the morphostructural lineaments than the PALSAR. Geometric characteristics during acquisition of PALSAR data and land cover interference contributed to obliterate or mask the morphostructures in this product. The morphostructural lineaments derived from the DEM-SRTM had good correspondence with tectonic structures recorded in the study area. Other evidence of tectonic influence include: high frequency of trellis drainage patterns (and their variations); occurrence of angular-rectangular pattern; and abundance of drainage anomalies, mainly in areas dominated by sedimentary cover. Additionally, the morphometric indexes showed, in general, values consistent with tectonic influence. The indexes also indicated that the northeast area with dominance of sedimentary cover and the northern sector of the area with dominance of crystalline basement were the ones with the greatest intensity in tectonic activity in more recent geological times. The qualitative and quantitative information derived from the DEM-SRTM provided evidence in support of tectonic influence in the study area. Both brittle and ductile deformations related to reactivation of Precambrian tectonic faults during the Mesozoic and the Cenozoic, added to creation of new features during these periods, were crucial to define the landscape and to control sedimentation patterns in the central Paraíba Basin.
Silva, Fabio Fernandes da. „Avaliação temática de imagens ALOS/PALSAR no mapeamento do uso e cobertura da terra na região semi-árida brasileira“. Instituto Nacional de Pesquisas Espaciais, 2010. http://urlib.net/sid.inpe.br/mtc-m19/2010/08.24.15.05.
Der volle Inhalt der QuelleThe objective of this study was to analyze the potential use of ALOS/PALSAR images at acquisition mode dual FDB 1.1 (L-band), to characterize and map the vegetation cover in the Brazilian semi-arid region. In this study the MAXVER-ICM and Wishart classifiers were used, which involved single, pairs and/or three components of the co-variance matrix [A$_{HH}$, A$_{HV}$ e A$_{HH*HV}$]. After the classification, using the above mentioned algorithms, the thematic accuracy was evaluated using Kappa statistics. Field survey data related to the physiognomic-structural parameters of the "Caatinga" (steppe savanna) vegetation types as well as observation points of land use/land cover classes, duly georeferenced, were as training and test samples for the thematic classification and its calibration. In the methodological procedure, the best result was found when the three components [A$_{HH}$, A$_{HV}$ e A$_{HH*HV}$] were used and classified by the MAXVER-ICM algorithm, presenting an overall accuracy of 66\% (\textit{Kappa} = 0.58) for the class separability. Additionally, we also evaluated the posicional planimetric quality of the ALOS/ PALSAR orthorectified product, generated with the use of ephemeris data platform and SRTM DEM. The check points using GPS in the field allowed the characterization based on the Brazilian Standard for Cartographic Accuracy for 1:100.000-map (Class A).
Santos, Elaine Marra dos. „Análise de imagens do satélite ALOS PALSAR (Banda L, modo polarimétrico) para discriminação de coberturas de terras no Distrito Federal“. reponame:Repositório Institucional da UnB, 2009. http://repositorio.unb.br/handle/10482/4132.
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Mapas de cobertura de terras são importantes fontes de dados para monitoramentos ambientais, preservação da biodiversidade, zoneamentos sócio-econômico e ambiental e monitoramento de mudanças climáticas locais e globais, dentre outras atividades. No Distrito Federal (DF), os mapeamentos de cobertura de terras têm sido realizados com base em imagens ópticas. No entanto, imagens de radar constituem-se em uma alternativa viável às imagens ópticas, pois independem das condições de iluminação solar, podem atravessar nuvens e fumaças e podem detectar diferenças nas estruturas da vegetação. O objetivo deste estudo é analisar o potencial das imagens de radar adquiridas pelo satélite ALOS PALSAR para o mapeamento de cobertura de terras. Uma imagem de 25 de abril de 2007 (banda L, polarizações HH, HV e VV, final da estação chuvosa) de parte do DF foi convertida para coeficientes de retroespalhamento (s°) e processada por meio da técnica de segmentação por crescimento de regiões. Valores de s° foram analisados estatisticamente por meio de cluster analysis. Os segmentos foram convertidos para o formato shape e mapeados visualmente na tela do monitor de computador, com suporte de um pacote de programas de sistema de informações geográficas, em uma escala de mapeamento compatível com 1:100.000. As seguintes classes temáticas foram consideradas: Áreas Urbanas consolidadas, Áreas Urbanas em consolidação, Culturas Agrícolas, Pastagens Cultivadas, Reflorestamento, Campos, Cerrado Típico, Matas de Galeria, Matas Indiscriminadas e Reservatórios. A exatidão de mapeamento, fornecido pelo índice kappa e calculado a partir da verificação de 86 pontos em campo, foi de 0,69. _______________________________________________________________________________ ABSTRACT
Land cover maps are important source of data for environmental monitoring, biodiversity conservation, social, economic and environmental zonning, and local and global climatic changes, among other activities. In the Federal District of Brazil (FD), land cover mappings have been obtained from optical images. However, radar data are valuable alternative for the optical remote sensing since they are independent of solar illumination, can penetrate clouds and smokes and can depict differences in canopy structures. The goal of this study is to analyze the potential of ALOS PALSAR radar data for land cover mapping. A scene covering part of FD, obtained in April 25th, 2007 (L-band, HH, HV and VV polarizations, end of wet season) was converted into backscattering coefficients (s°) and processed through the image segmentation technique by growing region. Values of s° were analyzed with the support of cluster analysis. The segments were converted into shape format and mapped visually in the computer screen using a geographical information system software package, in a 1:100,000 mapping scale. The following thematic classes were considered: consolidated urban areas, urban areas in consolidation, croplands, planted pasturelands, reforestations, grasslands, shrub Cerrado, gallery forests, indiscriminated forests and reservoirs. The accuracy of the final map, provided by the kappa index and obtained from 86 field checking points, was 0.69.
Alves, Fabio Corrêa. „Análise morfoestrutural das bacias dos rios Paraíba e Mamanguape (PB), com base em MDE-SRTM e imagem PALSAR/ALOS-1“. Instituto Nacional de Pesquisas Espaciais (INPE), 2015. http://urlib.net/sid.inpe.br/mtc-m19/2015/02.26.13.32.
Der volle Inhalt der QuelleAn increasing number of publications have shown the influence of Cenozoic tectonic activities in northeastern Brazil, despite its localization in a passive margin of the Sulamerican plate. Tectonic influence in the current landscape configuration of the Paraíba Basin has been suggested by morphostructural characteristics derived from relief and drainage systems. However, detailed studies to confirm the presence of tectonic structures in various areas in this basin are lacking. The goal of this work was to analyze the tectonic influence in the development of the Paraíba and Mamanguape river basins, northern of Paraíba Basin (PB), from techniques and remote sensing products. The research was undertaken through the analysis of drainage basin and of morphostructural characteristics based on digital elevation model (DEM) acquired by the Shuttle Radar Topography Mission (SRTM), geomorphometric variables derived from this product, and multi-polarized radar image from the PALSAR/ALOS-1 sensor. The results showed that the topographic coherence was more efficient than the DEM-SRTM to extract the drainage network of the study area. In addition to help the extraction of morphostructural lineaments, the DEM-SRTM was also useful for the calculation of morphometric indices, such as the Transverse Topographic Symmetry Factor (TTSF), which was useful to suggest tectonic influence in various sub-basins of the study area. This index revealed rivers with high asymmetry which mainly include those located in areas with sedimentary cover, in addition to highlight two sets of sub-basins with different tilting patterns. The integrated analysis of morphostructural elements of the analyzed drainage basins allowed provide evidence to support tectonic deformation in study area. This was manifested in the late Quaternary and is due to the reactivation of extensional and compressive efforts already recorded in the crystalline basement during sedimentary deposition. This was evidenced by the good correspondence between the morphostructural lineaments from the areas with sedimentary cover and those from the Precambrian crystalline basement. In addition to these results, the present work also contributed to the morphological characterization of residual deposits related to a delta located at the Paraíba River´s mouth. Arithmetic operations using PALSAR/ALOS-1 images were essential for generating a data set that allowed the best characterization of the studied deltaic feature. Spatial filtering techniques (i.e., mean and directional filtering) allowed highlight this paleomorphology, in addition to help discriminating details of morphologies corresponding to its sedimentary sub-environments. The cuspate morphology and the presence of curvilinear features attributed to beach ridges and paleoshoreline validated the hypothesis that the investigated paleomorphology corresponds to residual deposits of a wave-influenced paleodelta. The combination of morphological and chronological data suggest that this delta was formed during the past 2.140 $\pm$ 144 years, i.e., after the mid-Holocene sea-level fall. However, the interpretation obtained from the morphostructural analysis led to propose that its genesis might have also been driven by tectonic factor.
Silva, Camila Valeria de Jesus. „Caracterização florístico-estrutural e modelagem de biomassa na Floresta Amazônica a partir de dados alos/palsar e TERRASAR/TANDEM-X“. Instituto Nacional de Pesquisas Espaciais (INPE), 2014. http://urlib.net/sid.inpe.br/mtc-m21b/2014/04.17.19.53.
Der volle Inhalt der QuelleThe role of the Amazon rainforest in the stock of terrestrial carbon is a topic of high relevance in the discussions on climate change. Reliable and practical methods for the quantification of aboveground biomass (AGB) in this region are enhanced by the radar sensor technology. In this work, polarimetric L-band attributes (ALOS/PALSAR) and the interferometric coherence (HH polarization) in X-band (TerraSAR/TanDEM-X) were analyzed with support of forest inventory data and multiple linear regressions, allowing modeling the biomass stock. The study was conducted in the area of Flona do Tapajós - PA, where the classes considered were: primary forest (PF), with forest logging (FPEM); and secondary succession stages: advanced (SSA), intermediate (SSInt) and initial (SSI). Floristic and structural analysis procedures were applied to better description of thematic classes. The PolSAR attributes and InSAR coherence were analyzed and showed sensitivity to structural differences between primary forest (PF and FPEM) and secondary succession (SSA, SSInt and SSI). The modeling involved two types of models : (1) PolSAR , adjusted for all "general" data involving all types , and the ${"}$specific${"}$ data set of primary forest (PF) and secondary succession (SS); (2) PolSAR+ InSAR ${"}$general${"}$ involving all data types and ${"}$specific${"}$ set to the data set SS. The mainly results obtained were: a) the attributes PolSAR that showed stronger correlations with AGB in primary forest were Ps and $\sigma$$^{°}$$_{HH}$ , while in secondary succession were $\Upsilon$i, $\sigma$$^{°}$$_{HV}$, H and $\alpha$; b ) the specific PolSAR model for FP showed superior performance ($R^{²}$adj = 0.74, RMSE = 65.69 $t.ha^{-1}$), compared to those PolSAR general models (FP+SS) and specific PolSAR SS; c) compared to the general model PolSAR+InSAR, general model which the information derived from PolSAR, had similar performance, with slight superiority ($R^{²}$adj = 0.59, RMSE = 69.19 $t.ha^{-1}$); d) the specific model PolSAR+InSAR, containing the interferometric coherence in secondary succession, compared to PolSAR model had statistically similar performance with small superiority ($R^{²}$adj = 0.86, RMSE = 17.02 $t.ha^{-1}$). Given the results, it is considered that the specific modeling of biomass in tropical forest produces best estimates, and that the use of InSAR coherence is a strategy of great potential in the biomass modeling in secondary succession.
Dore, Nicole. „Polarimetric multi-incidence angle analysis over the archaeological site of Samarra by means of RADARSAT-2 and ALOS PALSAR satellites datasets“. Phd thesis, Université Rennes 1, 2014. http://tel.archives-ouvertes.fr/tel-01060848.
Der volle Inhalt der QuelleCassol, Henrique Luis Godinho. „Aplicação dos dados polarimétricos ALOS/PALSAR-2 para modelagem de biomassa em florestas secundárias da Amazônia considerando o histórico de uso“. Instituto Nacional de Pesquisas Espaciais (INPE), 2017. http://urlib.net/sid.inpe.br/mtc-m21b/2017/11.08.17.08.
Der volle Inhalt der QuelleSecondary forests (SF) play an important role in the Brazilian Amazon, because it maintains biodiversity and ecosystem services, in addition to partially counterbalance carbon emissions from deforestation, forest degradation and other anthropogenic sources, accumulating carbon in biomass. In this context, the main objective of this work is to evaluate the use of polarimetric data from the Radar system (ALOS/PALSAR-2) to characterize and modeling growth of biomass in SF from two regions of the Brazilian Amazon regarding land-use history prior to abandonment. Forest inventories were conducted in two study areas: 1) North of Manaus, on both sides of the BR-174 and 2) South of Santarém, next to the Tapajos National Forest and the BR-163. Land-use history was obtained through the analysis of classification of Landsat historical series of images, containing the period of active land-use (PALU), the frequency of cuts (FC) and the age of each SF patches. The methodology consisted in the extraction of several polarimetric attributes derived from Radar images to characterize the SF of Manaus and Santarém, as well as to define intensity classes (IC) of land use in such areas: 1 - PALU and/or FC$\leq$ 2 or 2 - PALU ou FC > 2. Four methods of regression analysis were tested to model above-ground biomass (AGB) through the use of polarimetric attributes in each study area: i) multiple linear, ii) non-linear, iii) Non-Linear Mixed Effects (NLME) and iv) non linear semiempirical Extended Water Cloud Model (EWCM). The structural and floristic differences observed in Manaus and Santarem SF resulted in the importance of different attributes to characterize the ICs. In Manaus, the polarimetric attributes that allowed separating the SF by IC were the cross-polarization term of the coherence matrix from the Cloude decomposition (T$_{33_C}$) and the mean ellipticity angle of Touzi (TVSM$_{τ_s}$). In Santarém, several polarimetric attributes were able to separate the ICs, with emphasis on the real term of the covariance matrix between the HH and VV channels (C$_{12_real}$) and the second term of the diagonal of the coherence matrix from Cloude decomposition (T$_{22_C}$). The multiple linear models presented the best performance, i.e., lower standard error of the prediction (RMSEP), lower bias of the prediction and higher R$^{²}$ value by the cross validation. The most important attributes for AGB modeling, however, were distinct in each study area due to their structural variations. The performance of the multiple linear model for estimation the AGB in the Santarém SF was R$^{²}$ = 0.37 and RMSEP = 13.19 Mg.ha$^{-1}$ (8,9\%) and in Manaus was R$^{²}$ = 0.70, RMSEP = 8.2 Mg.ha$^{-1}$ (7,6\%) when information about the land-use history were included in the model. It was concluded that the models adjusted for one study area is not recommended to estimate the AGB from another study area without the relative loss of accuracy and the information about land-use history contributed to improving the AGB estimates of the SF in the Brazilian Amazon.
Oksanen, P. O. (Pirita O. ). „Development of palsa mires on the northern European continent in relation to Holocene climatic and environmental changes“. Doctoral thesis, University of Oulu, 2005. http://urn.fi/urn:isbn:9514278895.
Der volle Inhalt der QuelleViana, Silvia Nascimento. „Análise de imagens do satélite ALOS PALSAR para discriminar fitofisionomias do bioma Cerrado : estudo de caso no Parque Nacional da Chapada dos Veadeiros“. reponame:Repositório Institucional da UnB, 2012. http://repositorio.unb.br/handle/10482/12211.
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Cerrado é o termo brasileiro para as formações vegetais savânicas encontradas no Planalto Central brasileiro e é o segundo maior bioma do Brasil. A exploração dos recursos naturais desse bioma tem sido feita por meio de lavouras mecanizadas e criações extensivas de gado bovino. Em 2002, 40% da cobertura vegetal natural desse bioma já haviam sido removidas por alguma atividade antrópica Em 2010, essa porcentagem aumentou para aproximadamente 49%. O Cerrado é considerado um hotspot para conservação da biodiversidade. Mesmo assim, pouco mais de 2% do bioma é protegido em termos de unidades de conservação federal. Uma dessas unidades é o Parque Nacional Chapada dos Veadeiros (PNCV), localizado no nordeste do estado de Goiás. Nesse parque, estudos de reconhecimento e discriminação de classes de cobertura vegetal têm sido realizados com dados obtidos por sensoriamento remoto, mais especificamente os satélites Landsat ETM+ e Terra MODIS. Os sensores ópticos são bastante úteis no mapeamento de alvos na superfície terrestre, contudo é importante reconhecer algumas de suas limitações, como a dependência das condições atmosféricas (cobertura de nuvens). Uma alternativa é o uso de sensores de radar de abertura sintética (SAR), que possuem fonte própria de REM e operam na faixa espectral das microondas. Nesse sentido, o objetivo desse trabalho é analisar o potencial das imagens do ALOS PALSAR para discriminar as principais fitofisionomias do bioma Cerrado, tendo como estudo de caso, o PNCV. Para tanto, três métodos de classificação de imagens foram utilizados: segmentação e ISOSEG, MAXVER-ICM (máxima verossimilhança - iterated conditional mode) e SVM (support vector machine). A acurácia dos resultados dessas três classificações foi analisada por meio de exatidão global, erros de omissão e comissão e índice Tau ( ). Embora o classificador MAXVER-ICM tenha apresentado acurácia mais alta, os três classificadores tiveram desempenhos parecidos: exatidões globais variando entre 75% a 78% e índices variando de 0,71 a 0,76. Esses valores estão no intervalo de concordância denominado “muito boa”, apenas um nível abaixo da categoria mais alta. ______________________________________________________________________________ ABSTRACT
Cerrado is the Brazilian term for savanna vegetation found in the Brazilian Central Plateau and is the second largest biome in Brazil. The exploitation of natural resources of this biome has been made through extensive mechanized crops and livestock cattle. In 2002, 40% of the natural vegetation of this biome had been removed by human activities. In 2010, this percentage increased to approximately 49%. The Cerrado is considered a hotspot for biodiversity conservation. Even so, just over 2% of the biome is protected in terms of federal conservation units. One of these units is the Chapada dos Veadeiros National Park (PNCV), located in the northeastern State of Goiás. In this park, studies of recognition and discrimination of vegetation classes have been conducted with data obtained by remote sensing, especifically Landsat ETM + and Terra MODIS. Optical sensors are useful in mapping the Earth's surface targets, but it is important to recognize some of its limitations, such as dependence on atmospheric conditions (cloud cover). An alternative is the use of sensors with synthetic aperture radar (SAR), which have their own source of electromagnetic radiation and operating in the microwave spectral range. In this sense, the objective of this dissertation is to analyze the potential of ALOS PALSAR images to discriminate the main physiognomies of the Cerrado biome, taking as case study, the PNCV. For this purpose, three methods of image classification were used: segmentation plus ISOSEG, MAXVER-ICM (maximum likelihood-iterated conditional mode) and SVM (support vector machine). The accuracy of results from these three classifications was evaluated by global accuracy, errors of omission and commission and Tau ( ) index. Although the MAXVER-ICM classifier presented highest accuracy, the three classifiers had similar performance: overall accuracies ranging from 75% to 78% and index ranging from 0.71 to 0.76. These values are in the range of concordance called "very good", just one level below the highest category.
LAU, SIN WAI. „Comparison and Fusion of space borne L-, C- and X- Band SAR Images for Damage Identification in the 2008 Sichuan Earthquake“. Thesis, KTH, Geoinformatik och Geodesi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-37005.
Der volle Inhalt der QuelleSilva, Daniel Luís Andrade e. „Geração e avaliação de produtos interferométricos dos dados ALOS/PALSAR FDB e PLR para fins de classificação da cobertura da terra na região Amazônia“. Instituto Nacional de Pesquisas Espaciais, 2009. http://urlib.net/sid.inpe.br/mtc-m18@80/2009/06.01.20.48.
Der volle Inhalt der QuelleImagery radars are options of Remote Sensing in the research of natural resources and monitoring of the planet. Among these radars is the ALOS/PALSAR which belongs to the family of japanese satellites for observing the continents. One application of this radar is repeat pass interferometry. Employing this technique can be generated products as interferograms and interferometric coherence images, whose applications are, respectively, generation of digital elevation models and land cover classification. In this context, the purpose of this work is to generate and evaluate the quality of interferometrics products from ALOS/ PALSAR SLC images in different polarizations of Tapajos National Forest, acquired in the time interval of forty-six days. For the development of this work, were initially performed interferometrics processing to generate the desired products, whose evaluations of quality consisted of test their potential in land cover classifications. The evaluation of interferograms was made visually based on the interferometric coherence images while these images were used singly and combined with Amplitude images in land cover classifications using two different methods of supervised classification (maximum likelihood added by ICM algorithm and support vectors machine). Before the classifications, exploratory analysis were made for observing the behavior of interferometric coherence in each of the classes of land cover and verification of the separability among them based on JM (Jeffreys-Matusita) statistics distance. The results of classifications were compared using as parameter the Kappa coefficient, that enabled statistical tests to verify the equality of accuracy in classifications by the significance level 0,05. The results of the tests and comparisons showed that interferometric coherence images produces good results for classification (k > 0,4) only when combinated with Amplitude images. From the conclusions of results, it was also possible establish a comparison between the interferometric potentiality of ALOS/PALSAR and other imagery radars with different polarimetric capabilities, revisits time and frequency. It is hoped that this work can represent a contribution to current studies and researches involving imagery polarimetrics radars, especially those operating in L band.
Pôssa, Évelyn Márcia. „Discriminação de uso e cobertura da Terra na região Amazônica a partir de informação polarimétrica ALOS/PALSAR e coerência interferométrica da missão TanDEM-X“. Instituto Nacional de Pesquisas Espaciais (INPE), 2016. http://urlib.net/sid.inpe.br/mtc-m21b/2016/02.10.18.10.
Der volle Inhalt der QuelleThe indiscriminate conversion of the tropical forests into other kind of land cover has an impact on the climate dynamics, hydrological and biogeochemical cycles. In the Brazilian scenario, the Amazon deforestation motivates researchers to use new remote sensing products and to develop new information extraction methodologies, to improve the identification of anthropogenic forcings of environmental changes. In this context, this work aimed to access the integration of PALSAR polarimetric data and TANDEM-X interferometric coherence images for land use and land cover classes discrimination in a Brazilian Amazon region. Fieldwork data samples were used as a reference samples for training of the classification algorithm and for validation of the results. Polarimetric attributes derived from radar backscattering (sigma zero and Pope indexes) and phase-derived information (Cloude-Pottier, Touzi, Freeman-Durden and Yamaguchi target decomposition theorems) resulted in six groups of attributes, which were individually classified, and associated with interferometric coherence using MAXVER-ICM algorithm. A seventh group of attributes was formed by feature selection procedures including: exploratory analysis of sensitivity front of the thematic classes; order (ranking) according to their importance in relation to the classes; correlation analysis; and better combinations of attributes. The exploratory analysis pointed out that the greatest potential attributes for discrimination of forest succession and other thematic classes discussed were those related to the volumetric interaction process. Regarding the classifications, the highest kappa value (0.72) was obtained from Cloude-Pottier decomposition attribute group associated with interferometric coherence. However, without the interferometric coherence association this group obtained 0.70 kappa value, thereforeno significant statistical difference. The group of polarimetric attributes with the highest significant improvement when combined with interferometric coherence was that composed by Pope indexes, resulting in improved discriminatory performance of classes related to ${"}$water bodies${"}$, ${"}$primary forest${"}$ and ${"}$secondary succession stages${"}$. The results of the classifications of the attributes groups arising from the targets decomposition of Cloude-Pottier, Freeman-Durden and Yamaguchi showed superior performance, statistically significant, when compared to results of the group classification of the of the backscatter coefficients (sigma zero), indicating the potential of these theorems of targets decomposition for studies of land use and land cover in the study area.
Ndikumana, Emile. „Etude de la végétation à partir de nouveaux capteurs satellitaires radar“. Electronic Thesis or Diss., Paris, AgroParisTech, 2018. http://www.theses.fr/2018AGPT0010.
Der volle Inhalt der QuelleIn this thesis, we focus on how SAR images can be used to study vegetation. Vegetation lies at the core of human lives by providing both food and economic resources as well as participating in regulating climate. Traditionally, vegetation is classified into three categories: fields, flooded pastures, and forests. We follow this classification in our study. To tackle the first two, we chose to explore rice (in Camargue, France) since rice fields are initially flooded pastures and turn to fields when more mature. We illustrate the last category with forests in Madagascar.The aim of the first part is to provide a better understanding of the capabilities of Sentinel-1 radar images for agricultural land cover mapping through the use of deep learning techniques. We revealed that even with classical machine learning approaches (K nearest neighbors, random forest and support vector machines), good performance classification could be achieved with F-measure/Accuracy greater than 86% and Kappa coefficient better than 0.82. We found that the results of the two deep recurrent neural network (RNN)-based classifiers clearly outperformed the classical approaches.In the second part, the objective is to study the capabilities of multitemporal radar images for rice height and dry biomass retrievals using Sentinel-1 data. To do this, we train Sentinel-1 data against ground measurements with classical machine learning techniques (Multiple Linear Regression (MLR), Support Vector Regression (SVR) and Random Forest (RF)) to estimate rice height and dry biomass. The study is carried out on the same multitemporal Sentinel-1 dataset in the first part. The error of rice height estimation was 16% (7.9 cm), whereas the biomass was 18% (162 g¢m¡2) (both with Random Forest method). Such results indicate that the highly qualified Sentinel-1 radar data could be well exploited for rice biomass and height retrieval and they could be used for operational tasks.Finally, reducing carbon emissions from deforestation and degradation (REDD) requires detailed insight into how the forest biomass is measured and distributed. Studies so far haveestimated forest biomass stocks using rough assumptions and unreliable data. We aim to improve on previous approaches by using radar satellite ALOS PALSAR (25-m resolution) and optical Landsat-derived tree cover (30-m resolution) observations to estimate forest biomass stocks in Madagascar, for the years 2007-2010. The radar signal and in situ biomass were highly correlated (R2 = 0.71) and the root mean square error was 30% (for biomass ranging from 0 to 500 t/ha). Combining radar signal with optical tree cover data appears to be a promising approach for using by L-band SAR to map forest biomass (and hence carbon) over broad geographical scales
Prėskienis, Vilmantas. „Holocene development and permafrost history of two mires in Tavvavuoma, Northern Sweden“. Thesis, Stockholms universitet, Institutionen för naturgeografi och kvartärgeologi (INK), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-92709.
Der volle Inhalt der QuelleDubovtsev, Denis. „Application of the self-consistent method of moments to the investigation of dynamic and optical characteristics of plasmas“. Doctoral thesis, Universitat Politècnica de València, 2019. http://hdl.handle.net/10251/125711.
Der volle Inhalt der Quelle[CAT] El mètode dels moments ocupa un lloc especial entre els mètodes teòrics dedicats a l'estudi dels sistemes amb interacció de Coulomb entre partícules. El més important i característic és el fet que la funció de resposta lineal del sistema està parametritzada a semblança d'una transformació lineal fraccionària d'una funció de Nevanlinna (NPF, Nevanlinna Parameter Function) sota certes propietats matemàtiques. L'aproximació de freqüència zero s'aplica per a determinar l'última que va permetre relacionar-la amb el seu moment, tenint en compte aspectes físics que ho justifiquen. Es mostra que aquesta aproximació estàtica NPF és consistent amb el mètode de maximització d'entropia de Shannon. El present treball constitueix una versió autoconsistente del mètode dels moments per a la seua aplicació a la investigació de la correcció dinàmica de camp local, entre altres característiques dinàmiques, dels sistemes clàssics fortament acoblats d'un component, com són els plasmes densos de Coulomb i Yukawa. El model és autoconsistent ja que les propietats dinàmiques s'obtenen sense cap introducció de dades obtingudes en les simulacions, de manera que la funció dielèctrica satisfà les primeres cinc regles de suma automàticament. A més, tant el factor d'estructura dinàmic, com la dispersió i la correcció dinàmica del camp local, es determinen utilitzant exclusivament el factor d'estructura estàtic calculat a partir de l'aproximació de la cadena hiper enllaçada. Es mostra que s'aconsegueix un bon ajust quantitatiu amb les dades de simulacions de dinàmica molecular. D'igual manera, s'observa poca discrepància entre les característiques dinàmiques del plasma calculades a través dels factors d'estructura estàtica, enfront dels obtinguts per altres mètodes de càlcul d'aqueix factor d'estructura estàtica, com són l'aproximació de cadena hiper enllaçada (HNC, Hiper-NettedChain), la HNC modificada (MHNC, Modified Hiper-Netted Chain) i la HNC modificada variacionalmente (VMHNC, Variational Modified Hiper-Netted Chain). Aquesta estabilitat implica la robustesa de l'enfocament que es presenta. Així mateix, s'analitzen les possibilitats d'abandonar l'aproximació estàtica NPF.
[EN] The method of moments occupies a special place among the theoretical methods dedicated to the study of systems with Coulomb interaction between particles. Its essence lies in the fact that the system linear response function is parameterized as a fractional-linear transformation of a (Nevanlinna) parameter function (NPF) with certain mathematical properties. The zero-frequency approximation is applied to determine the latter which permitted to relate it, on the basis of justified physical considerations, to the moments themselves. This NPF static approximation is shown to be consistent within the Shannon entropy maximization method. In the present work, the self-consistent version of the method of moments is applied to the investigation of the dynamic local field correction and other dynamic characteristics of classical strongly coupled one-component systems, such as dense Coulomb and Yukawa plasmas. The self-consistency of the approach means that the dynamic properties are obtained without any data input from simulations so that the dielectric function satisfies the first five sum rules automatically. Moreover, the dynamic structure factor, dispersion and the dynamic local-field correction are determined using exclusively the static structure factor calculated from the hypernetted chain approximation. A good quantitative agreement with molecular dynamics simulation data is achieved. In addition, little discrepancy is observed in the plasma dynamic characteristics calculated with the static structure factors, obtained within various methods of calculation of the static structure factor, namely, the hyper-netted chain approximation (HNC), the modified HNC (MHNC) and the variational modified HNC (VMHNC). This stability implies the robustness of the present approach. Possibilities to abandon the NPF static approximation are analyzed as well.
Dubovtsev, D. (2019). Application of the self-consistent method of moments to the investigation of dynamic and optical characteristics of plasmas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/125711
TESIS
Arantes, Leticia Tondato. „Limiares topográficos de processos erosivos na bacia do Rio Bonito (SP) obtidos a partir de modelo digital de elevação de dados de radar (PALSAR/ALOS) /“. Ilha Solteira, 2019. http://hdl.handle.net/11449/183328.
Der volle Inhalt der QuelleResumo: A erosão é um fenômeno complexo, uma vez que envolve a ação direta ou indireta de diversos fatores, tais como tipos de solos, clima, vegetação, declividade e ações antrópicas. O estudo acerca da dinâmica, agentes desencadeadores e fatores condicionantes é uma importante ferramenta para uma tomada de decisão. A proposição de índices que indicam o limiar crítico para determinar a ocorrência de processos erosivos, é uma das vertentes dos estudos acerca de processos erosivos, cuja pressupõe-se uma relação entre a declividade (S) e área de contribuição (A), que condiciona os processos de erosão. Considerando os avanços na geração dos produtos de Sensoriamento Remoto, este trabalho objetivou realizar um estudo sobre o desencadeamento das erosões lineares, no qual propõe a avaliação da empregabilidade do Modelo Digital de Elevação (MDE) gerado por meio de imagem de radar interferométrico (ALOS/Palsar) para obtenção dos parâmetros topográficos da Bacia Hidrográfica do Rio Bonito, inserida no município de Descalvado e Porto Ferreira no estado de São Paulo. Com isso o MDE, o mapa de declividades e direção de fluxo foram elaborados em ambiente SIG, com pixels de saída de 2m, possibilitando obter os valores de A versus S, utilizando o algoritmo D-Infinity para o processamento dos dados hidrológicos. Os valores obtidos forma representados em um gráfico, permitindo identificar a declividade mínima para a ocorrência de um processo erosivo, bem como estabelecer de forma empírica o limiar top... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: Erosion is a complex phenomenon as it involves the direct or indirect action of various factors such as soil types, climate, vegetation, slope and anthropic actions. The study about dynamics, triggering agents and conditioning factors is an important tool for decision making. The proposition of indices that indicate the critical threshold to determine the occurrence of erosive processes is one of the strands of studies on erosive processes, whose assumption is a relationship between slope (S) and contribution area (A), which conditions the erosion processes. Considering the advances in the generation of Remote Sensing products, this work aimed to conduct a study on the triggering of linear erosions, which proposes the evaluation of the employability of the Digital Elevation Model (MDE) generated by interferometric radar imaging (ALOS / Palsar) to obtain the topographic parameters of the Bonito River Watershed, inserted in the municipality of Descalvado and Porto Ferreira in the state of São Paulo. With this the MDE, the slope map and flow direction were elaborated in GIS environment, with 2m output pixels, allowing to obtain the values of A versus S, using the D-Infinity algorithm for the hydrological data processing. The values obtained were represented in a graph, allowing to identify the minimum slope for the occurrence of an erosive process, as well as to establish empirically the topographic threshold. The index obtained in this work from the analysis was S = 0.0333A-0.0... (Complete abstract click electronic access below)
Mestre
Freitas, Daniel Moraes de. „Potencial das imagens multipolarizadas do satélite ALOS/PALSAR na discriminação de cobertura vegetal do bioma pantanal : estudo de caso na região do Médio Taquari, MS“. reponame:Repositório Institucional da UnB, 2012. http://repositorio.unb.br/handle/10482/11531.
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A região do Médio Taquari, MS, corresponde a uma região situada em áreas de terra firme do bioma Pantanal, apresenta fitofisionomias típicas do bioma Cerrado e possui importantes tributários que contribuem para o alagamento periódico do Pantanal propriamente dito. O objetivo do presente trabalho é analisar o potencial das imagens ALOS/PALSAR para discriminar as diferentes classes de cobertura de terras representativas da região do Médio Taquari. Foram analisadas imagens do sensor PALSAR (banda L, polarizações HH, HV e VV) de 11 de junho de 2009. Essas imagens foram convertidas para coeficiente de retroespalhamento e analisadas por meio dos seguintes tratamentos estatísticos: análise multivariada discriminante, teste de Kruskal-Wallis, teste ad hoc de distância e análise de correlação de Spearman. As seguintes classes de cobertura vegetal natural e antrópica foram consideradas: Floresta Estacional Semidecidual Aluvial (Fa); Savana Florestada (Sd); Savana Arborizada (Sa); Savana Gramíneo-Lenhosa (Sg); e Pastagens Cultivadas (Ap). Os resultados mostraram o grande potencial das três polarizações na discriminação das classes Floresta Estacional Semidecidual Aluvial, Savana Florestada e Savana Arborizada, não sendo possível diferenciar as classes Savana Gramíneo- Lenhosa e Pastagem. O teste estatístico discriminante indicou a polarização VV com o melhor resultado para a discriminação. As classes florestadas mostraram valores de restroespalhamento muito mais altos que as classes arbustivas/gramíneas. ______________________________________________________________________________ ABSTRACT
The region of Médio Taquari, State of Mato Grosso do Sul, corresponds to a region located in highlands of Pantanal biome, presents typical phytophisiognomies of Cerrado biome, and hás important tributaries that contribute to the periodic flooding of pantanal itself. The objectives of this study is to analyze the potential of ALOS/PALSAR imageries to discriminate representative land cover classes of the Médio Taquari. We analyzed PALSAR images (L-band, HH, HV and VV polarizations; overpass: june 11, 2009). These imagens were converted to backscattering coefficientes and analyzed by the following statistical treatments: multivariated, discriminant analysis; Kruskal-Wallis test; ad hod distance test; and Spearman correlation. The following land use and land cover classes were considered: Floresta Estacional Semidecidual Aluvial (Fa); Savana Florestada (Sd); Savana Arborizada (As); Savana Gramíneo-Lenhosa (Sg); and Cultivated Pastures (Ap). Statistical results showed that VV polarization presented Best performance and all land use and land cover classes were discriminated, with the exception of Sg and Ap. The statistical test indicated that the VV polarization had the best results regarding the discrimination. The forested ranges presented higher backscattering values than the grassy/bushes ranges.
Prado, Bruno Rodrigues do. „Análise dos dados ALOS/PALSAR (modo de imageamento FBD) para identificação dos tipos de cobertura da terra na região norte do estado do Mato Grosso“. Instituto Nacional de Pesquisas Espaciais, 2009. http://urlib.net/sid.inpe.br/mtc-m19@80/2009/11.25.12.50.
Der volle Inhalt der QuelleThe Amazon forest is the largest rainforest of the planet and concentrates great biodiversity and natural resources. The continuous human impacts are occurring due to the occupation and exploitation of the region, then becoming essential to understand and to monitor the land cover changes. The intense cloud coverage in this region makes the use of optical images limited, requiring the use of radar images, since the images acquired in the microwave range do notsuffer atmospheric interference. The work analyses the potential of ALOS/PALSAR images, in the FBD (level 1.5 imaging) mode, to discriminate the following land cover classes: primary forest, secondary forest, degraded forest and agriculture, in two study areas located in the north region of Mato Grosso State. Different filters were tested for speckle noise, and the best result in terms of signal noise-ratio was achieved by Gamma 5x5 filter. For the filtered images, it was performed segmentation with the software Multiseg following the classification using Bhattacharyya and Maxver-ICM algorithms, employing the Polarimetric SAR Classifier 0.7 software. The classifications were subsequently validated using data from PRODES, DETER and DEGRAD projects, supported by visual interpretation of Landsat 5/TM, SPOT 2/HRV images, and soil, shade and vegetation fraction images. The analysis was performed using the single polarization (HH and HV) and the combination of polarizations (HH and HV). In general, the Bhattacharyya classifier showed better classification performance when compared to the Maxver-ICM classifier. The best result obtained by the Bhattacharyya classifier was related to the HH polarization (Kappa = 0.58), and the best result obtained by the Maxver-ICM classifier used the combination of HH and HV polarizations (Kappa = 0.51). In some cases there was an increment of information through the combination of polarizations. The results of the exploratory analysis and classifications showed a clear identification of the agriculture class, but a great confusion for discriminating forest classes, mainly between secondary forest and degraded forest classes. With this techniques the agriculture classes were sufficiently discriminated, but the forest classes were not sufficiently discriminated independently of data or algorithm used, showing a limitation of ALOS/PALSAR (mode FBD) data for identification of land cover classes defined in this work.
Rollin-Martinet, Sabrina. „Développement de nouvelles biocéramiques par consolidation à basse température d'apatites nanocristallines bionimétiques“. Limoges, 2011. https://aurore.unilim.fr/theses/nxfile/default/4a55024a-307c-4fe3-ad5e-19fb73487d7f/blobholder:0/2011LIMO4047.pdf.
Der volle Inhalt der QuelleBiomimetic nanocrystalline apatites (BNA) Ca10-x-Z(PO4)6-x(HPO4)x(OH)2-x-2Z, (H2O)n were synthesized by precipitation in aqueous medium, then consolidated by Spark Plasma Sintering (or SPS). They are constituted of nanocrystals involving an apatitic core and a surface phospho-calcic hydrated layer containing “non-apatitic” phosphate, hydrogenphosphate and calcium ions, highly “labile” (easily exchangeable), responsible for their high reactivity. The chemical composition, structure and morphology of the nanocrystals of BNA evolve upon maturation in solution, and they tend toward greater thermodynamic stability. Although the amount of non-apatitic chemical species decreases upon maturation, their presence is still significant after a long maturation. Low temperature (150°C) SPS sintering of maturated BNA allowed us to obtain highly-cohesive, porous ceramics. The sintering phenomenon observed in such conditions suggests a “crystal fusion” consolidation process, involving the high surface reactivity of the nanocrystals by way of their hydrated layer. The mechanical properties (elastic modulus between 12 and 35 GPa, flexure strength close to 10 MPa) of the ceramics obtained are close to those of bone mineral. Moreover, the nanometer-scale dimensions of the crystals, beneficial to bioresorption after implantation in osseous site, as well as the presence of labile non-apatitic ionic species, favorable to bioactivity, are preserved after SPS. These properties confer to BNA ceramics a particularly promising potential in view of applications in the field of bone tissue engineering
Wiederkehr, Natalia Cristina. „Mudanca de uso e cobertura da terra a partir dos dados polarimétricos ALOS/PALSAR-2 em uma porção da Floresta Nacional do Tapajós e áreas adjacentes“. Instituto Nacional de Pesquisas Espaciais (INPE), 2018. http://urlib.net/sid.inpe.br/mtc-m21b/2018/01.23.15.57.
Der volle Inhalt der QuelleThe Amazon rainforest presents a great biodiversity being considered one of the largest and most important tropical forests in the world. However, has been subjected to several pressures that impact climate dynamics and hydrological and biogeochemical cycles. Such forcing factors, especially anthropogenic ones, can cause modifications and even complete conversions of the forest in other land use and land cover classes. The orbital remote sensing data applied to the dimensions of the Amazonian forest becomes a suitable tool to monitor how land use and land cover changes. In this context, this work aimed to evaluate the ALOS/PALSAR-2 full polarimetric images for the thematic stratification of changes in land use and land cover in a portion of the Tapajós National Forest and adjacent areas between 2015 and 2016. Polarimetric attributes derived from radar backscatter (Cross-Polarized Ratio, Parallel-Polarized Ratio and Radar Forest Degradation Index) and phase information (Cloude-Pottier, Freeman-Durden and Yamaguchi target decomposition techniques) resulted in six groups of attributes. A seventh group of attributes, called the optimal subset, was formed from attribute selection procedures. Field data samples were used as a reference samples for training the Classification algorithm and for validation of the results. The seven groups were classified by the MAXVER-ICM algorithm, and the classification results showed that the groups formed by the Cloude-Pottier decomposition and the optimal subset (H, A, α e Pv) showed the highest Kappa values of 0.78 and 0.75, respectively, for the year 2015 and 0.75 and 0.74, respectively for the year 2016. From the optimum subsets 2015 and 2016, we elaborated the maps and performed the technique of subtraction of maps from the qualifying result of 2015 by the result of 2016. As a result of the validity of the detections, a Kappa value of 0.60 was obtained. The classification results for the groups of the Cloude-Pottier, Freeman-Durden and Yamaguchi decompositions showed superior performance, when compared to the classification results of the backscatter coefficients groups, indicating the potential of these techniques of targets decomposition for studies of land use and land cover in the research area. In relation to changes of occurrence in the analyzed period (2015/2016), there was a decrease of the forest cover in relation to the areas in process of production. The greatest losses of the forest areas were associated mainly with forest degradation from the fires that occurred in the region. Agricultural, forestry and pasture areas continue increasing, suppressing mainly the forest area.