MELO, Dayana Cristina Macedo de. Análise da tectônica rúptil associada a uma porção do lineamento transbrasiliano da Região Noroeste do Ceará integrando dados de campo, magnetométricos e de sensoriamento remoto. 2014. 62 f. Dissertação (Mestrado em geologia)- Universidade Federal do Ceará, Fortaleza-CE, 2014. / Submitted by Elineudson Ribeiro (elineudsonr@gmail.com) on 2016-06-03T19:48:15Z No. of bitstreams: 1 2014_dis_dcmmelo.pdf: 6286929 bytes, checksum: dc2ab250d7c685e3a24c96eecabd63c2 (MD5) / Approved for entry into archive by José Jairo Viana de Sousa (jairo@ufc.br) on 2016-07-21T19:11:30Z (GMT) No. of bitstreams: 1 2014_dis_dcmmelo.pdf: 6286929 bytes, checksum: dc2ab250d7c685e3a24c96eecabd63c2 (MD5) / Made available in DSpace on 2016-07-21T19:11:30Z (GMT). No. of bitstreams: 1 2014_dis_dcmmelo.pdf: 6286929 bytes, checksum: dc2ab250d7c685e3a24c96eecabd63c2 (MD5) Previous issue date: 2014 / The brittle tectonic analyzed in this work is referring to an area that represents a portion of the Transbrasiliano Lineament (TL), in northwest of Ceará State, comprising part of Cariré, Pacujá, Graça and Reriutaba’s county and the geological context is the basement (Ceará Complex-Canindé Unit) and Jaibaras and Parnaiba Basin (Jaibaras Group-Pacuja Formation and Serra Grande Group, respectively). This study aims to characterize the brittle structures associated to the TL, through integration of remote sensing (SRTM-Topodata and Landsat 7 ETM+), geophysics (Magnetometry) and field data information. From SRTM-Topodata images there were obtained drainage system and hillshade images in N, NE, E and NW directions. Color composition images RGB 743 and 431 derived from Landsat 7 ETM+. The combination of these products permitted the visualization of lineaments that were vectorized to compare to other data. The processed magnetometric data allowed to obtain the anomalous magnetic field and the elaboration of other products through application of variable filters, such as: horizontal and vertical Derived, analytic signal amplitude and analytic signal inclination. They were assets to identify lineaments and define magnetic domains. Anomalous magnetic their depth estimated by Euler deconvolution and matched filter application. The fracture planes’ rosette diagram elaborated from field measures composed parameters to compare the lineaments extracted from the products aforementioned. It’s evident, from the integration of all information, that the main direction of the TL (NE-SW) is compatible with the brittle structures observed in the area, as well as the N-S and NW-SE lineaments, that are potentially related with translative/extensional tectonic of TL. The E-W direction, which is late to TL and appears in the basement as the basins. The comparative analysis of the data suggests a tectonic control from TL over Jaibaras and Parnaiba Basins, through structures reactivation in NE and NW directions. / A tectônica rúptil analisada neste trabalho é referente a uma área que detém uma porção do Lineamento Transbrasiliano (LT), situada na região Noroeste do Estado do Ceará. Esta área abrange parte dos municípios de Cariré, Pacujá, Graça e Reriutaba. O contexto geológico abrange o embasamento (Complexo Ceará-Unidade Canindé) e as bacias Jaibaras (Grupo Jaibaras- Formação Pacujá) e Parnaíba (Grupo Serra Grande). Este estudo tem como objetivo caracterizar as estruturas rúpteis associadas ao LT, através da integração de informações oriundas de sensores remotos (SRTM-Topodata e Landsat 7 ETM+), geofísica (magnetometria) e dados de campo. A partir das imagens SRTM-Topodata obteveram-se o traço da rede de drenagem e as imagens com sombreamento de relevo nas direções N, NE, E, NW. As imagens Landsat 7 ETM+ as imagens foram analisadas em composições coloridas RGB 743 e 431. Estes produtos integrados permitiram a visualização de lineamentos que foram vetorizados para posterior comparação com outros dados. Os dados magnetométricos foram processados permitindo a obtenção do campo magnético anômalo na área de estudo, e a elaboração de produtos gráficos através da aplicação de diferentes filtros, tais como: Derivada horizontal e derivadas verticais, amplitude do sinal analítico, inclinação do sinal analítico, os quais permitiram identificar lineamentos e definir domínios magnéticos. As anomalias magnéticas tiveram suas profundidades estimadas através da deconvolução de Euler e da aplicação de filtro matched. Os diagramas de roseta elaborados a partir de medidas de campo de direções dos planos de fratura constituíram parâmetros para comparação com os lineamentos extraídos dos outros produtos. A integração das informações evidencia que a principal direção do LT (NE-SW) é compatível com as estruturas rúpteis observadas na área de estudo, assim como as direções N-S e NW-SE potencialmente relacionadas com a tectônica transtativa/extensional do LT. A direção E-W tardia ao LT aparece tanto no embasamento como nas bacias. A análise comparativa dos dados sugere um controle tectônico do LT nas bacias Jaibaras e Parnaíba, através da reativação de estruturas nas direções NE e NW.

MEIRELES, Marcos. Estimativa da evapotranspiração real pelo emprego do algoritmo SEBAL e imagem Landsat 5-TM na Bacia do Acaraú, CE. 2007. 88 f. Dissertação (Mestrado em engenharia agrícola)- Universidade Federal do Ceará, Fortaleza-CE, 2007. / Submitted by Elineudson Ribeiro (elineudsonr@gmail.com) on 2016-06-24T18:53:16Z No. of bitstreams: 1 2007_dis_mmeireles.pdf: 7960852 bytes, checksum: 2a3fe5af2b180274de52163c28b43e87 (MD5) / Approved for entry into archive by José Jairo Viana de Sousa (jairo@ufc.br) on 2016-07-21T20:19:38Z (GMT) No. of bitstreams: 1 2007_dis_mmeireles.pdf: 7960852 bytes, checksum: 2a3fe5af2b180274de52163c28b43e87 (MD5) / Made available in DSpace on 2016-07-21T20:19:38Z (GMT). No. of bitstreams: 1 2007_dis_mmeireles.pdf: 7960852 bytes, checksum: 2a3fe5af2b180274de52163c28b43e87 (MD5) Previous issue date: 2007 / Elaboration of natural resources mapping is difficult due to large spatial and temporal variability of them. In the least decay, remote sensing is widely used do make this because the lower survey costs. The main goal of this work is to estimate daily evapotranspiration of the Araras Norte Irrigated Perimeters and evaporation of four reservoirs (Jaibaras, Paulo Sarasate, Edson Queiroz and Forquilha) located in the middle part of the Acaraú basin. The actual evapotranspiration was quantified from spectral satellite data on the basis of the energy balance approach. The LANDSAT 5 Thematic Mapper 30 m, resolution satellite image taken on 01 september 2004, was obtained from Instituto Nacional de Pesquisas Espaciais (INPE). Satellite image was processed and piled up using Erdas Imagine 8.5 Demo. Hour and daily evapotranspiration was estimated using SEBAL (Surface Energy Balance Algorithm for Land) algorithm, which is based on energy balance between incoming and outgoing solar radiation. Among generated remote sensing maps are: temperature (ºC), Albedo (a), Normalized Difference Vegetation Index (NDVI), net radiation (Rn), sensible heat flux (H), latent heat flux (lET) and hour evapotranspiration (ETH). Based on ETH the evaporative fraction was estimated throughout the relationship of ET for pixel at the satellite image time (mm.h-1) and reference crop ET by Penman-Montheith method. Results showed that the lowest albedo and the highest evapotranspiration rates were registered in the reservoir (7.5 mm.dia-1); the spatial distribution of soil heat flux presented a similar distribution of soil predominant types in the studied region. Also, It was observed the influence of water flow in the repair zone soil humidity, once it was registered, in these areas, values of NDVI and daily evapotranspiration similar to those observed in irrigated areas. Irrigated District of Araras Norte showed an ETdiária around 6.5 mm.dia-1. It was clear that SEBAL approach has a high potential in study of desertification, changes in cover vegetation and land use at basin scales; since latent heat and evapotranspiration can be a good indication of changed cover vegetation change. / Tomando-se por base o emprego crescente do sensoriamento remoto na elaboração de mapas mais precisos e de menor custo dos recursos naturais, desenvolveu-se este estudo com o objetivo de se elaborar imagens que venham a identificar o balanço de energia na superfície, bem como estimar as taxas evaporimétricas horária e diária da região que abrange o Perímetro de Irrigação Araras Norte e os quatro principais reservatórios (Jaibaras, Paulo Sarasate, Edson Queiroz e Forquilha) da bacia do Acaraú. Para tanto, imagem do satélite Landsat 5, datada de 01 de setembro de 2004, foi obtida junto ao Instituto Nacional de Pesquisas Espaciais (INPE). Esta imagem foi submetida, processada e empilhada pelo software Erdas IMAGINE 8.5 Demo. Em seguida aplicou-se o algoritmo SEBAL (Surface Energy Balance Algorithm for Land), o qual se fundamenta no fluxo de calor entre a superfície do solo e a atmosfera, para se estimar a evapotranspiração horária e diária da área em estudo. Pelo emprego do referido algoritmo foram geradas cartas, dentre outras, da temperatura (ºC), albedo (a), Índice de Vegetação por Diferença Normalizada (NDVI), saldo de radiação (Rn), calor sensível (H), calor latente (lET) e evapotranspiração horária (EThorária). De posse da carta da EThorária, estimou-se a fração de evapotranspiração de referência horária (FET0_H), pela relação dos valores da evapotranspiração de cada pixel da imagem estimada pelo SEBAL e a evapotranspiração de referência horária (ET0_H), estimada pelo método de Penman-Montheith. Pelos resultados alcançados observou-se que os menores percentuais de energia refletida (albedo) e as maiores taxas de evaporação foram registrados nas superfícies liquidas dos açudes (7,5 mm.dia-1); que a distribuição espacial do fluxo de calor no solo apresentou uma repartição semelhante às manchas dos dois tipos de solo predominantes da área em estudo, Luvissolo e Neossolo Litólico. Pode-se, também, perceber a influência da perenização dos cursos d’água na umidade do solo das margens, encontrando-se para alguns trechos da mata ciliar valores de NDVI e de evapotranspiração diária bem próximos dos observados nas áreas irrigadas. As áreas do Distrito de Irrigação Araras Norte apresentaram ETdiária da ordem de 6,5mm.dia-1. Ficou evidenciado a alta potencialidade do emprego do SEBAL em estudos de desertificação, alterações na vegetação e uso da terra em escala de bacias hidrográficas, uma vez que a identificação em mudanças das espécies pode ocorrer pelo estudo das cartas de calor latente ou evapotranspiração.

Climate change has posed significant challenges for the world's sustainable development, and the water cycle is highly dependent on the climate system. In particular, the arid zone fragile ecosystems in northwest China are highly vulnerable to the sophisticated hydrological variations. While ground-based measurements are less capable for large scale hydrological modelling, remote sensing techniques offer enhanced and effective alternatives for various hydrological states/fluxes. With the advancement of the Gravity Recovery and Climate Experiment (GRACE) satellites, the Terrestrial Water Storage (TWS), an integrative measurement of regional hydro-climatic environment, can now be measured as well for examining the overall hydrological response to recent climate change. TWS is an essential element of the water cycle and a key state variable for land surface-atmosphere interaction. Investigating the TWS change is important for understanding the response of the water cycle to climate change. In this study, the intra-annual and inter-annual spatio-temporal change pattern of TWS in Xinjiang Uyghur Autonomous Region of China during 2003-2015 are characterized from Gravity Recovery and Climate Experiment (GRACE) Tellus data products. Sub-regional re-analysis reveals that the increasing/decreasing rate in sub-regions, namely, Altay Mountains (ATM), Junggar Basin (JGB), Tianshan Mountains (TSM), Tarim Basin (TRB) and Kunlun Mountains (KLM), are - 3.41mm, -5.82mm, -6.76mm, -2.59mm and +3.05mm per year in unit of equivalent water height (EWH), respectively. The results suggest that TWS variation presents certain spatio-temporal patterns with spatial heterogeneity. The uncertainties from different GRACE products are also assessed. In conjunction with gridded meteorological data products and land surface model simulations of hydrological variables, the heterogeneous mechanisms of seasonal TWS change are analyzed. The correlation relationship among various hydrologic states/fluxes variables (e.g. snow water, soil water, snow amount) and climatic variables (e.g. temperature and precipitation) with GRACE-derived TWS variation in different sub-regions are investigated. The findings appear to indicate that 1) temperature month-over-month change and temperature anomaly with 4- month time lag, rather than precipitation, are more capable to explain the intra- annual TWS variation; 2) In most part of the study area, the TWS intra-annual change can be primarily attributed to the snow accumulation in winter and melt in spring. On the other hand, the glacier mass variation, which is particularly sensitive to recent climate change, could be a substantial contributor to inter-annual TWS change. The elevation trends over glaciers are estimated based on ICESat altimetry measurements. Correlation analysis results suggest that, during 2003- 2009, the inter-annual TWS loss in Tianshan Mountains (TSM) was tightly associated with glacier mass variation induced by temperature change, particularly in summer. In contrast, TWS gain in Kunlun Mountains (KLM) can be attributed to glacier mass increase. By utilizing remote sensing observation techniques/products, this study has characterized the spatio-temporal change pattern of TWS in northwest arid zone of China, as well as the underlying mechanism. It suggests that TWS is an effective indicator of regional climate change. This study contributes to a better understanding of the hydrologic and climatic processes in arid zone water cycle, and could be beneficial for regional water resources management and climate change adaptation effort.

Lava flows are common at volcanoes around the world and on other terrestrial planets, but their behavior is not fully understood. In Hawai`i, advances in remote sensing are offering new insights into lava flow emplacement. In this dissertation, I develop new techniques using satellite-based synthetic aperature radar, aerial photographs, and airborne lidar to produce three-dimensional high-resolution maps of lava flows from data collected before, during, and after emplacement. These new datasets highlight complex lava channel networks within these flows, which are not incorporated into current predictive or probabilistic lava flow models yet may affect flow behavior. I investigate the origin and influence of these channel networks through morphologic analysis of underlying topography, network topology, and flow morphology and volume. Channel network geometries range from distributary systems dominated by flow branching around local obstacles to tributary systems constricted by topography. I find that flow branching occurs where the flow thins over steeper slopes and that the degree of flow branching, network connectivity, and longevity of flow segments all influence the final flow morphology. Furthermore, because channel networks govern the distribution of lava supply within a flow, changes in the channel topology can dramatically alter the effective volumetric flux in any one branch, which affects both flow length and advance rate. Specifically, branching will slow and shorten flows, while merging can accelerate and lengthen them. To test these observations from historic eruptions and morphologic analysis, I use analogue experiments to simulate the interaction of a lava flow with a topographic obstacle and determine the conditions under which the flow branches and the effects of the bifurcation on flow advance rate. These experiments support the earlier results but also demonstrate the importance of flow dynamics and obstacle morphology on governing when flows may overtop obstacles. Consideration of channel networks is thus important for predicting lava flow behavior and mitigating flow hazards with diversion barriers. One video of Kilauea lava flow activity from 2003-2010 accompanies this dissertation as a supplemental file. This dissertation includes both previously published and unpublished co-authored material.

A quantificação da precipitação é dificultada pela extrema aleatoriedade do fenômeno na natureza. Os métodos convencionais para mensuração da precipitação atuam no sentido de espacializar a precipitação mensurada pontualmente em postos pluviométricos para toda a área de interesse e, desta forma, uma rede com elevado número de postos bem distribuídos em toda a área de interesse é necessária para um resultado satisfatório. No entanto, é notória a escassez de postos pluviométricos e a má distribuição espacial dos poucos existentes, não somente no Brasil, mas em vastas áreas do globo. Neste contexto, as estimativas da precipitação com técnicas de sensoriamento remoto e geoprocessamento pretendem potencializar a utilização dos postos pluviométricos existentes através de uma espacialização baseada em critérios físicos. Além disto, o sensoriamento remoto é a ferramenta mais capaz para gerar estimativas de precipitação nos oceanos e nas vastas áreas continentais desprovidas de qualquer tipo de informação pluviométrica. Neste trabalho investigou-se o emprego de técnicas de sensoriamento remoto e geoprocessamento para estimativas de precipitação no sul do Brasil. Três algoritmos computadorizados foram testados, sendo utilizadas as imagens dos canais 1, 3 e 4 (visível, vapor d’água e infravermelho) do satélite GOES 8 (Geostacionary Operational Environmental Satellite – 8) fornecidas pelo Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais. A área de estudo compreendeu todo o estado do Rio Grande do Sul, onde se utilizaram os dados pluviométricos diários derivados de 142 postos no ano de 1998. Os algoritmos citados buscam identificar as nuvens precipitáveis para construir modelos estatísticos que correlacionem as precipitações diária e decendial observadas em solo com determinadas características físicas das nuvens acumuladas durante o mesmo período de tempo e na mesma posição geográfica de cada pluviômetro considerado. Os critérios de decisão que norteiam os algoritmos foram baseados na temperatura do topo das nuvens (através do infravermelho termal), reflectância no canal visível, características de vizinhança e no plano de temperatura x gradiente de temperatura Os resultados obtidos pelos modelos estatísticos são expressos na forma de mapas de precipitação por intervalo de tempo que podem ser comparados com mapas de precipitação obtidas por meios convencionais. / The quantification of precipitation is made difficult due mainly to the extreme variance of the phenomenom in nature. The usual methods work in the sense of spacializing the precipitation, which is measured punctually in pluviometric stations, for the entire area of interest and, hence, a net containing a big amount of stations well distributed along the whole area of interest is needed to reach a satisfactory result. Nevertheless, the scarcity of pluviometric stations and the bad distribution of the few existents is evident, not only in Brazil, but also in vast regions of the planet. In this context, the precipitation estimations using remote sensing techniques and geoprocessing intend to potencialize the utilization of existent pluviomteric stations through a spacialization based on physics criteria. Moreover, the remote sensing is the more capable tool to generate rainfall estimation for the oceans and the large continental areas that are unprovided of any type of pluviometric informations. At this work, the application of remote sensing and geoprocessing techniques for precipitation estimation at the south of Brazil was investigated. Three computerized algorithms were tested, based on the imagens of channels 1, 3 and 4 (visible, water steam and infrared) of the GOES 8 satellite, provided by Centro de Previsão de Tempo e Estudos Climáticos of the Instituto Nacional de Pesquisas Espaciais. The studyng area is the Rio Grande do Sul state, where the 1998’s daily precipitation data of 142 raingauges were used. The related algorithms try to identify precipitables clouds to build a mathematical model (through the minimum square process) which correlates the daily precipitation observed in ground with fisical features of the clouds acumulated during the same period and in the same geographic position of the raingauge. These algorithms tested decision criteria based on the temperature of the cloud tops (through thermal infrared), albedo in the visible channel, texture in the infrared channel and in the plane temperature versus temperature gradient. The results obtained by mathematical models are expressed as daily precipitation maps which can be compared with isohyetal maps obtained by conventional methods.

Depuis les années 1970, la télédétection a permis d’améliorer l’analyse de la surface de la Terre grâce aux images satellites produites sous format numérique. En comparaison avec les images aéroportées, les images satellites apportent plus d’information car elles ont une couverture spatiale plus importante et une période de revisite courte. L’essor de la télédétection a été accompagné de l’émergence des technologies de traitement qui ont permis aux utilisateurs de la communauté d’analyser les images satellites avec l’aide de chaînes de traitement de plus en plus automatiques. Depuis les années 1970, les différentes missions d’observation de la Terre ont permis d’accumuler une quantité d’information importante dans le temps. Ceci est dû notamment à l’amélioration du temps de revisite des satellites pour une même région, au raffinement de la résolution spatiale et à l’augmentation de la fauchée (couverture spatiale d’une acquisition). La télédétection, autrefois cantonnée à l’étude d’une seule image, s’est progressivement tournée et se tourne de plus en plus vers l’analyse de longues séries d’images multispectrales acquises à différentes dates. Le flux annuel d’images satellite est supposé atteindre plusieurs Péta octets prochainement. La disponibilité d’une si grande quantité de données représente un atout pour développer de chaines de traitement avancées. Les techniques d’apprentissage automatique beaucoup utilisées en télédétection se sont beaucoup améliorées. Les performances de robustesse des approches classiques d’apprentissage automatique étaient souvent limitées par la quantité de données disponibles. Des nouvelles techniques ont été développées pour utiliser efficacement ce nouveau flux important de données. Cependant, la quantité de données et la complexité des algorithmes mis en place nécessitent une grande puissance de calcul pour ces nouvelles chaînes de traitement. En parallèle, la puissance de calcul accessible pour le traitement d’images s’est aussi accrue. Les GPUs («Graphic Processing Unit ») sont de plus en plus utilisés et l’utilisation de cloud public ou privé est de plus en plus répandue. Désormais, pour le traitement d’images, toute la puissance nécessaire pour les chaînes de traitements automatiques est disponible à coût raisonnable. La conception des nouvelles chaînes de traitement doit prendre en compte ce nouveau facteur. En télédétection, l’augmentation du volume de données à exploiter est devenue une problématique due à la contrainte de la puissance de calcul nécessaire pour l’analyse. Les algorithmes de télédétection traditionnels ont été conçus pour des données pouvant être stockées en mémoire interne tout au long des traitements. Cette condition est de moins en moins respectée avec la quantité d’images et leur résolution. Les algorithmes de télédétection traditionnels nécessitent d’être revus et adaptés pour le traitement de données à grande échelle. Ce besoin n’est pas propre à la télédétection et se retrouve dans d’autres secteurs comme le web, la médecine, la reconnaissance vocale,… qui ont déjà résolu une partie de ces problèmes. Une partie des techniques et technologies développées par les autres domaines doivent encore être adaptées pour être appliquée aux images satellites. Cette thèse se focalise sur les algorithmes de télédétection pour le traitement de volumes de données massifs. En particulier, un premier algorithme existant d’apprentissage automatique est étudié et adapté pour une implantation distribuée. L’objectif de l’implantation est le passage à l’échelle c’est-à-dire que l’algorithme puisse traiter une grande quantité de données moyennant une puissance de calcul adapté. Enfin, la deuxième méthodologie proposée est basée sur des algorithmes récents d’apprentissage automatique les réseaux de neurones convolutionnels et propose une méthodologie pour les appliquer à nos cas d’utilisation sur des images satellites. / Since the 1970s, remote sensing has been a great tool to study the Earth in particular thanks to satellite images produced in digital format. Compared to airborne images, satellite images provide more information with a greater spatial coverage and a short revisit period. The rise of remote sensing was followed by the development of processing technologies enabling users to analyze satellite images with the help of automatic processing chains. Since the 1970s, the various Earth observation missions have gathered an important amount of information over time. This is caused in particular by the frequent revisiting time for the same region, the improvement of spatial resolution and the increase of the swath (spatial coverage of an acquisition). Remote sensing, which was once confined to the study of a single image, has gradually turned into the analysis of long time series of multispectral images acquired at different dates. The annual flow of satellite images is expected to reach several Petabytes in the near future. The availability of such a large amount of data is an asset to develop advanced processing chains. The machine learning techniques used in remote sensing have greatly improved. The robustness of traditional machine learning approaches was often limited by the amount of available data. New techniques have been developed to effectively use this new and important data flow. However, the amount of data and the complexity of the algorithms embedded in the new processing pipelines require a high computing power. In parallel, the computing power available for image processing has also increased. Graphic Processing Units (GPUs) are increasingly being used and the use of public or private clouds is becoming more widespread. Now, all the power required for image processing is available at a reasonable cost. The design of the new processing lines must take this new factor into account. In remote sensing, the volume of data currently available for exploitation has become a problem due to the constraint of the computing power required for the analysis. Traditional remote sensing algorithms have often been designed for data that can be stored in internal memory throughout processing. This condition is violated with the quantity of images and their resolution taken into account. Traditional remote sensing algorithms need to be reviewed and adapted for large-scale data processing. This need is not specific to remote sensing and is found in other sectors such as the web, medicine, speech recognition ... which have already solved some of these problems. Some of the techniques and technologies developed by the other domains still need to be adapted to be applied to satellite images. This thesis focuses on remote sensing algorithms for processing massive data volumes. In particular, a first algorithm of machine learning is studied and adapted for a distributed implementation. The aim of the implementation is the scalability, i.e. the algorithm can process a large quantity of data with a suitable computing power. Finally, the second proposed methodology is based on recent algorithms of learning convolutional neural networks and proposes a methodology to apply them to our cases of use on satellite images.

Doctor of Philosophy / Department of Geography / Douglas Goodin / Quantitative remote sensing provides an effective way of estimating and mapping vegetation characteristics over an extensive area. The spatially explicit distribution of canopy vegetative properties from remote sensing imagery can be further used for studies of spatial patterns and processes in grassland systems. My research focused on remote sensing of grassland vegetation characteristics and its applications to spatial analysis of grassland dynamics involving interactions between pyric herbivory and vegetation heterogeneity. In remote sensing of vegetation characteristics, (1) I estimated the foliar pigments and nutritional elements at the leaf level using hyperspectral data. The foliar pigments, chlorophylls and carotenoids, were retrieved by inverting the physical radiative transfer model, PROSPECT. The nutritional elements were modeled empirically using partial least squares (PLS) regression. Correlations were found between the leaf pigments and nutritional elements. This provided insight into the use of pigment-related vegetation indices as a proxy of the plant nutritional quality. (2) At the canopy level, I assessed the use of the broadband vegetation indices, normalized difference vegetation index (NDVI) and green-red vegetation index (GRVI), in detecting vegetation quantity (LAI) and quality (leaf and canopy chlorophyll concentrations). The relationships between vegetation indices and vegetation characteristics were examined in the physical model, PROSAIL, and validated by a field dataset collected from a tallgrass prairie. NDVI showed high correlations with LAI and canopy chlorophylls. GRVI performed even better than NDVI in estimating LAI. A new index GNVI (green-red normalized vegetation index) that combined NDVI and GRVI was proposed to extract leaf chlorophyll concentration. These findings showed the potential of using broadband vegetation indices from multispectral remote sensors to monitor vegetation quantity and quality over a wide spatial extent. In the spatial analysis, I examined interactions between pyric herbivory and grassland heterogeneity at multiple scales from the remote sensing imagery. (3) At a coarse, watershed level, I evaluated effects of fire and large herbivores on the spatial distribution of canopy nitrogen. It was found that the interactive effects of fire and ungulate grazing were present in the watersheds burnt in spring, where a high level of ungulate grazing reduced vegetation density, but promoted canopy heterogeneity. Two grazer species, bison and cattle, were compared. Differences in the vegetation canopy between sites with bison and cattle were observed, which may be related to differences in the grazing intensity, forage behavior and habitat selection between the two grazer species. (4) At a fine, patch level (30 m), bison forage pattern was examined associated with canopy nitrogen heterogeneity. Bison preference for patches with high canopy nitrogen was evident in May. Later in June – September, bison tended to avoid sites with high canopy nitrogen. Vegetation heterogeneity showed significant influences on bison habitat selection in June. Bison preferred sites with low variance in canopy nitrogen, where the patch types were highly aggregated and equitably proportioned.

A Temperatura de Superfície de Lago (TSL) consiste em um importante parâmetro limnológico na definição da qualidade de um corpo de água. Por meio da variação da TSL, uma série de parâmetros biológicos, físicos e químicos são modificados, no entanto, afetam, diretamente a sociedade, por meio dos diversos usos da água, do consumo doméstico ao agrícola e industrial. Os corpos de água estão diretamente relacionados a parâmetros meteorológicos e climáticos, dessa forma sofrem os efeitos das mudanças climáticas em escala global, mas, por outro lado, influenciam no ambiente local como amenizador climático, contribuindo com uma atmosfera local mais úmida. Dessa forma, o objetivo principal é analisar o comportamento da dinâmica da TSL do Guaíba, levando em consideração períodos de normalidade e anormalidade climáticas e as relações com agentes meteorológicos locais. Por meio da construção de perfis de temperatura e análises espaciais feitas sobre um arcabouço temporal de imagens termais dos satélites: Landsat 5 e 8/ e Terra (sensor MODIS) e suas respectivas relações com os fatores externos à massa de água do Guaíba (dados de meteorológicos, climáticos e topográficos locais). Dessa forma construiu-se um conjunto de dados detalhando a dinâmica da circulação e o comportamento espacial das temperaturas. Destaca-se que o Guaíba possui uma complexa dinâmica correlacionada com fatores atmosféricos globais e locais, mas de modo mais intenso com as variações meteorológicas locais em função da posição geográfica e da presença de uma sazonalidade bem definida, que propicia a entrada de frentes frias causando oscilações de temperatura e pluviosidade de modo muito marcante. Quanto aos períodos de normalidade e anormalidade climática, observase que durante os períodos de El Niño e La Niña há um aquecimento maior da TSL quando comparado com períodos de normalidade climática, sendo que o primeiro está mais relacionado ao aquecimento global da atmosfera; já, a segunda está relacionada à maior insolação em função do resfriamento da atmosfera, condicionando um céu limpo, ficando mais propício ao aquecimento por radiação solar. / The lake surface water temperature (LSWT) consists in an important limnological parameter in the quality definition of a body of water. Through the LSWT variation, a series of biological, physical and chemical parameters are modified, however they affect directly the society through the various water usage, from the domestic consumption to the agricultural and industrial. The bodies of water are directly related to the climatic and metereological parameters, this way they suffer the climatic change in a global scale, but, on the other hand, they influence in the local ambient as a climatic softener, contributing with a more humid local atmosphere. Thus, the aim of this paper is to analyze the dynamical behavior of Guaíba LSWT, whereas climatic normality and abnormality periods and their relations with local metereological agents. Through the profile of temperature and spatial analysis made over a temporal framework of the satellite thermal images: Landsat 5 and 8 and Terra (MODIS sensor) and their respective relations with the external factors in water mass of Guaíba (local topographic, climatic and metereological data). In this way a set of data were built detailing the circulation dynamic and the spatial behavior of the temperatures. Guaíba has a dynamic complex correlated with local and global atmospheric factors more intensely with the local metereological variation according to the geographical position and the presence of a huge seasonality, which allows the entrance of cold fronts causing rainfall and temperature oscilation in a remarkable way. In the normality and abnormality climatic periods, during El Niño and La Niña periods, there is a bigger LSWT warming if compared to normality climatic periods, being that the first one is more related with the atmosphere global warming, and the second one is related with the greater insolation due to the cooling of the atmosphere, conditioning a clean sky, becoming more conducive to solar radiation heating.

O tema desta tese envolve a avaliação de dados de sensoriamento remoto e de campo como preditores de estimativa de biomassa em áreas de silvicultura, no sudeste do Estado do Rio Grande do Sul. Tem como objetivo geral avaliar modelos de variação temporal de biomassa vegetal acima do solo para povoamentos de eucalipto, utilizando variáveis dendrométricas e índices espectrais. A metodologia consistiu inicialmente, na organização de um banco de dados no aplicativo Spring. Foram elaborados mapas temáticos da evolução da silvicultura a partir da interpretação visual das imagens Landsat 5 TM e em seguida, extraídas as médias dos índices espectrais (NDVI, EVI e GPP) das imagens MODIS, a partir das quais se elaborou os perfis temporais da vegetação em hortos de eucalipto, oriundos de mudas de semente e mudas clonais, em diferentes idades (3, 5 e 7 anos). Estes perfis foram correlacionados com dados de precipitação do TRMM. Em uma terceira etapa foram associados os dados adquiridos em campo (IAF, DAP e H) quando se estimou a biomassa do eucalipto por meio de equações alométricas. Por último foram correlacionados os dados MODIS, IAF e a biomassa estimada, avaliando os modelos de predição de biomassa para o eucalipto. Os resultados observados nos mapas de evolução da silvicultura demonstraram que a região apresenta um crescente desenvolvimento neste setor. Os perfis temporais dos índices espectrais comprovaram a capacidade dos produtos MODIS para a avaliação dos ciclos fenológicos e da produtividade em diferentes plantios de eucalipto, no entanto, a correlação com os dados de precipitação (TRMM) não apresentou resultados satisfatórios. Os dados de IAF permitiram diferenciar os plantios clonais e por semente, além da idade do eucalipto. Os dados de inventário (DAP e H) proporcionaram bons resultados da estimativa de biomassa acima do solo para os plantios de eucalipto estudados. A correlação dos dados (de campo e espectrais) demonstrou pequena possibilidade na estimativa de biomassa em áreas de plantios arbóreos, com destaque para os dados de IAF e GPP. Conclui-se que a utilização conjunta de dados de campo e orbital, possibilita análises confiáveis para povoamentos de eucalipto. Assim, este trabalho demonstra a relação entre dados de satélite e de campo, e contribui com novas informações, alternativas e sugestões para o estudo de povoamentos arbóreos na região estudada. / This thesis involves the evaluation of remote sensing data and field as predictors of estimated biomass in forestry areas in the southeastern state of Rio Grande do Sul. We evaluate models of temporal variation of above ground biomass for eucalyptus stands, using dendrometric variables and spectral indices. The methodology consisted of organization of a database application Spring. Thematic maps with the evolution of forestry were developed from visual interpretation of Landsat 5 Thematic Mapper images and then extracted averages of spectral indexes (NDVI, EVI and GPP) derived from MODIS images from which elaborated the temporal profiles of vegetation in eucalyptus plantations, from seedlings of seed and clonal considered at different ages (3, 5 and 7 years old). These profiles were correlated with precipitation data from TRMM (Tropical Rainfall Measuring Mission). Following that, these profiles were associated with field data (IAF, DAP and H) and biomass of eucalyptus estimated through allometric equations. Finally, data were correlated with the MODIS data, IAF and the estimated biomass, evaluating prediction models of biomass for eucalyptus. The results observed for the evolution of forestry, showed that the region presents a growing development in forestry sector. The temporal profiles of spectral indices proved the ability of MODIS products for evaluation of phenological cycles and productivity in different eucalyptus plantations. However, the correlation with precipitation data (TRMM) did not provide satisfactory results. The IAF data allowed to differentiate between clonal and seed stands, and also the age of eucalyptus stands. The inventory data (DAP and H) have provided good results for eucalyptus plantations above-ground biomass estimation. The correlation of the data (spectral and field) demonstrated small possibility for estimating biomass in eucalyptus plantations, with emphasis on the data of IAF and GPP. It is concluded that the joint use of data from field and orbital, enables reliable analyses for stands of eucalyptus. This work demonstrates the relationship between satellite and field data, and contributes with new information, alternatives and suggestions for studying arboreal settlements in the region studied.

A valorização e preservação do meio-ambiente tem sido bastante discutida, e cada vez mais tem sido parte integrante de projetos de diferentes grupos de interesse que buscam um desenvolvimento sustentável. Dentro deste contexto da busca pelo desenvolvimento sustentável e de políticas ambientais eficazes, surge outro termo que irá englobar uma série de ações preventivas e de gerenciamento do meio ambiente: o planejamento ambiental. Levantamentos ambientais, inerentes ao planejamento ambiental são realizados de diferentes maneiras, e neste contexto, inclui-se a utilização de novas tecnologias como o uso de produtos do Sensoriamento Remoto e Sistema de Informação Geográfica (SIG), que têm auxiliado na otimização do processamento e da precisão de resultados devido à ampliação na velocidade de obtenção de dados e na capacidade de armazenamento de informações, bem como o uso de imagens de sensores orbitais que tem apresentado diversas utilidades no âmbito dos estudos da Terra, nos mais variados tipos de avaliação ambiental. A partir de tais considerações foi possível elaborar uma linha de atuação a partir da análise espaço-temporal com a utilização do sensoriamento remoto aplicado em uma porção do território que vem passando por transformações significativas nas últimas décadas. Dessa maneira, pensou-se em realizar a análise de uma área que apresenta uma grande potencialidade para a atividade turística e um crescimento industrial importante e que tem alterado sua paisagem nas duas últimas décadas. O trecho em questão é o que liga os municípios de Angra dos Reis e Parati, no litoral Sul do Estado do Rio de Janeiro. Nos dois casos têm-se como importante fonte de renda, o turismo ecológico, que têm atraído empreendimentos imobiliários de grande porte para a região, além do turismo cultural. O objetivo deste trabalho é analisar o grau de transformação do uso e cobertura da terra no entorno da Rodovia Rio-Santos neste trecho, nos últimos vinte anos, dando ênfase a três datas: 1984, 1994 e 2002. Parte-se da hipótese que tais transformações têm-se intensificado, estimulando maiores investimentos voltados ao turismo, pressionando os remanescentes de Mata Atlântica.. Através da análise espaço-temporal do uso e cobertura da terra no período e sua estruturação em um banco de dados, obteremos um retrato atual da região que pode servir como ponto de partida para o planejamento de uso e ocupação da terra, avaliando a forma atual da ocupação, evitando assim que seus recursos naturais sejam usufruídos de forma errônea podendo promover a degradação ou mesmo a extinção dos mesmos. / The environmental valuation and preservation has been sufficiently discussed, and it has been part of projects of different groups of interest that search for a sustainable development. Inside of this context of searching for a sustainable development and for efficient environmental politics, another term appears that involves a series of actions and management of the environment: the environmental planning. Environmental surveys are realized in different ways, and in this context it is common the use of new technologies such as Remote Sensing products and Geographic Information Systems (SIG). These technologies, which allow digital image processing and produce results with better precision as well as the use of images from orbital sensors, have presented diverse utilities in the scope of land use studies, in varied types of environmental evaluations. From such consideration it was possible to elaborate a research that begun with a time-space analysis using remote sensing products in a portion of the territory that is passing through significant transformations in the last decades. In this way, one thought about carrying through the analysis of an area that presents a great potentiality for tourism activity and also important industrial growth and that it has modified its landscape in the two last decades. The issue stretch in question is what it binds to the cove cities Angra dos Reis and Parati, in the South coast of the state of Rio de Janeiro. In these two cases they are had as important source of income, the ecological tourism, that have attracted real estate enterprises of great transport for the region, beyond the cultural tourism. The objective of the present work was to analyze the dynamic of the landscape produced by human transformations in tree different buffers from the Rio-Santos highway in the last twenty years and in three different years: 1984, 1994 and 2002. The hypothesis was that such transformations have been intensified, stimulated by the tourism, threatening the Atlantic forest fragments remnants. Through a time-space analysis of land use it was possible to present the landscape dynamic between two decades as a starting point for an environmental planning of the land use, evaluating the current form of occupation, thus preventing that the local natural resources will be usufructed of error form being able to promote the same degradation or the extinguishing of the same ones.