No Brasil, a área utilizada para pastagens é maior comparada com a área utilizada para as culturas agrícolas, com cerca de 158,6 milhões de hectares de pastagens. Sendo que as pastagens são extremamente importantes para a produção de carne bovina já que cerca do 95% é produzida para alimentar os rebanhos. O principal nutriente para a manutenção da produtividade em forrageiras é o nitrogênio (N), sendo um dos principais nutrientes que influencia diretamente as características morfofisiológicas, interferindo na produção e na qualidade da forragem. Nos últimos anos, o uso de técnicas de sensoriamento remoto tem se expandido nas áreas de ciências agrárias, mostrando-se uma ferramenta muito útil no monitoramento e gerenciamento da adubação nitrogenada nas culturas. Por tanto o objetivo do trabalho foi abordar o potencial de dados de sensoriamento remoto, mais especificamente para as forrageiras Panicum maximum cv. Mombaça e Urochloa brizantha cv. Marandú, obtidos por meio de sensor passivo e convertidos para diferentes índices de vegetação (IVs), na estimativa de parâmetros biofísicos, tais como: teor foliar de nitrogênio (TFN), produtividade, altura e índice de área foliar (IAF). Também foram simulados os dados para o satélite Sentinel-2 e testados, em áreas com plantio de Brachiaria brizantha cv. Piatã. Os IVs utilizados foram o NDVI (Índice de Vegetação por Diferença Normalizada), TBI (Three Band Index), DLH (Difference Line Height), NAOC (Normalized Area Over reflectance Curve) e TBDO (Three Band Dall ?Olmo). O experimento foi realizado na Escola Superior de Agricultura \"Luiz de Queiroz\" (ESALQ/USP), em Piracicaba, São Paulo. O delineamento experimental utilizado foi em blocos ao acaso, com quatro tratamentos e quatro repetições, sendo a ureia o fertilizante nitrogenado utilizado ao longo do experimento. As doses aplicadas para a cv. Mombaça foram três de 200, 400, 600 kg ha-1 e para a cv. Marandú foram aplicadas doses de 175, 350 e 525 kg ha-1, para ambas cultivares as parcelas testemunhas não receberam adubação nitrogenada (0 kg ha-1). Ao longo do ciclo da cultura, avaliou-se a sua altura, produtividade, IAF e o TFN e a sua resposta espectral de 400 até 920 nm. Os resultados demonstraram que as duas forrageiras foram responsivas à adubação nitrogenada, modificando a sua resposta espectral ao longo das aplicações, principalmente na região do visível (verde 550 nm) e do infravermelho próximo (a partir dos 700 nm). E também provaram que é possível predizer parâmetros biofísicos por meio de espectroscopia in situ e através do satélite Sentinel-2. / In Brazil, the area used for pasture is larger compared to the area used for agricultural crops, representing about 158,6 million hectares of pasture. Pastures are extremely important for beef production, as 95% is produced to feed the herds. The main nutrient for the maintenance of forage productivity is nitrogen (N), which influences directly the morphophysiological characteristics, interfering in the production and on the quality of the forage. In recent years, the use of remote sensing techniques has expanded in agricultural sciences, proving to be a very useful tool in the monitoring and management of nitrogen fertilization in crops. Therefore, the objective of this study was to address the potential of remote sensing data for the forages Panicum maximum cv. Mombasa and Urochloa brizantha cv. Marandú. Data were obtained by passive sensor and converted into different vegetation indices (IVs), in the estimation of biophysical parameters, such as: foliar nitrogen content (NTF), productivity, height and leaf area index (LAI). The data for the Sentinel-2 satellite were also simulated and tested in areas with Brachiaria brizantha cv. Piatã. The IVs used were NDVI (Normalized Difference Vegetation Index), TBI (Three Band Index), DLH (Difference Line Height), NAOC (Normalized Area Over Reflectance Curve) and TBDO (Three Band Dall\'Olmo). The experiment was carried out at the \"Luiz de Queiroz\" School of Agriculture (ESALQ/USP), in Piracicaba, São Paulo. The experimental design applied was a randomized block, with four treatments and four replicates, and with urea used throughout the experiment as a nitrogen fertilizer. The doses applied for cv. Mombaça were three of 200, 400 and 600 kg ha-1 and for cv. Marandú were applied 175, 350 and 525 kg ha-1 doses. For both cultivars the control plots did not receive nitrogen fertilization (0 kg ha-1). During the culture cycle, we evaluated its height, productivity, LAI and TFN, and its spectral response of 400 to 920 nm. The results showed that the two forages were responsive to nitrogen fertilization, modifying their spectral response along the applications, mainly in the region of visible (green 550 nm) and near infrared (from 700 nm). They also proved that it is possible to predict biophysical parameters using in situ spectroscopy and by using the Sentinel-2 satellite.

Medidas complementares ao monitoramento in situ da qualidade da água podem ser obtidas por meio de sensoriamento remoto, sendo clorofila-a e sólidos suspensos alguns dos parâmetros que podem ser estimados. Este trabalho teve como objetivo explorar técnicas de processamento de imagens, análises estatísticas e de inteligência artificial com o objetivo de predizer e modelar as concentrações de clorofila-a e sólidos suspensos totais na Represa do Lobo/SP. Metodologicamente, foram realizadas coletas em campo, em três diferentes datas, para amostragem de água e posterior análise laboratorial. Os resultados limnológicos foram analisados, modelados e comparados com imagens processadas do satélite Sentinel-2. Análises de regressão e redes neurais artificiais (RNA) foram exploradas para gerar modelos de predição para a área de estudo. Os resultados indicam que métodos de regressão podem não ser adequados para capturar as relações lineares e/ou não-lineares entre os compostos de interesse e as respostas espectrais da água recebidas pelo satélite, indicando a capacidade das redes neurais em modelar relações mais complexas. Através da integração da resposta que o sensor MSI do satélite Sentinel-2 coletou nas regiões do visível ao infravermelho médio e de RNAs foi possível modelar a concentração de clorofila-a, com valores de R² superiores a 0,65 e de RMSE inferiores a 2,5 μg/L, e gerar mapas que permitam seu monitoramento temporal e análise espacial na área de estudo. Os resultados para SST não foram satisfatórios devido à complexidade óptica do ambiente analisado, bem como as baixas concentrações de SST na represa. Portanto, a integração de dados de sensoriamento remoto no mapeamento de corpos d\'água com a aplicação de redes neurais na análise de dados é uma abordagem promissora para prever clorofila-a e sólidos suspensos, bem como suas variações temporais e espaciais. / Complementary measures to in situ monitoring of water quality can be obtained through remote sensing, with chlorophyll-a and suspended solids being some of the parameters that can be estimated. The objective of this work was to explore techniques for image processing, statistical analysis and artificial intelligence with the objective of predicting and modeling the concentrations of chlorophyll-a and total suspended solids in the Lobo Reservoir/SP. Methodologically, field samples were collected in three different dates for water sampling and laboratory analysis. The limnological results were analyzed, modeled and compared with processed images of the Sentinel-2 satellite. Regression analysis and artificial neural networks (ANNs) were explored to generate prediction models for the study area. The results indicate that regression methods may not be adequate to capture linear and/or nonlinear relationships between the compounds of interest and the spectral responses of water received by the satellite, indicating the ability of neural networks to model more complex relationships. Through of the integration of response wich the MSI sensor of Sentinel satellite collected in the visible and near-infrared regions and of the ANN analysis was possible modeling the chlorophyll-a concentration, wich R² values highers of 0.65 and RMSE less 2.5, and create predict maps wich allow your temporal monitoring and spatial analysis in the study area. The TSS results were unsatisfactory because of the optic complexity of analysed ambient, as well as your small TSS concentrations in the Lobo Reservoir. Therefore, the integration of remote sensing data in the mapping of water bodies with the application of neural networks in the data analysis is a promising approach to predict chlorophyll-a and suspended solids as well as their temporal and spatial variations.

Diss. (sammanfattning) Uppsala : Uppsala universitet, 2007. / Härtill 4 uppsatser.

Le suivi de l’évolution du manteau neigeux est directement lié à des enjeux socio-économiques majeurs en zone de montagne. Parmi ces enjeux figure la prévision du risque d’avalanche qui s’appuie principalement sur des observations et sur la connaissance de l’état du manteau neigeux et de son évolution dans le temps. Dans cette thèse, co-financée par le CNES et par Météo- France, nous avons évalué l’apport d’observations de télédétection spatiale active micro-ondes issues du radar à synthèse d’ouverture (SAR) de Sentinel-1, pour suivre l’évolution de certaines propriétés du manteau neigeux. Dans un premier temps, nous avons évalué la chaîne de modélisation SAFRAN-ISBA/Crocus-MEMLS par rapport aux données Sentinel-1 pré-traitées sur 3 saisons hivernales de 2014 à 2017, sur une zone de 2310 km2 à 20 m de résolution dans les Alpes du Nord françaises. Nous avons montré que les données SAR étaient pertinentes pour suivre l’évolution du manteau neigeux et, avons démontré la capacité de la chaîne de modélisation à reproduire les variations du signal observé dans le temps malgré de forts biais négatifs en cas de neige humide. Nous nous sommes intéressés à la valeur ajoutée des observations SAR de Sentinel-1 pour cartographier la neige humide, c’est-à-dire, la neige avec un taux élevé d’eau liquide. Des comparaisons ont été effectuées entre les produits neige humide obtenus par Sentinel-1 et les produits neige de Sentinel-2 distribués par Theia. Cette étude a été menée sur la saison hivernale 2017-2018, qui a connu un enneigement exceptionnel. Ces travaux ouvrent la voie à l’assimilation de données de télédétection SAR dans le modèle de neige Crocus ainsi qu’à une plus grande exploitation de ces données dans le cadre du suivi de l’enneigement pour de multiples applications. / Monitoring snowpack properties in moutainous areas is directly related to major socio-economic issues. Among these issues, avalanche prediction works through a range of tools based on meteorological and snow observations and modeling. In this thesis, co-funded by the CNES and Météo-France, we evaluated the contribution of Sentinel-1 synthetic aperture radar (SAR) remote sensing observations to study the snowpack properties and the quality of the simulations for assimilation in a snowpack model. As a first step, we evaluated the SAFRAN-ISBA/Crocus- MEMLS modeling chain against pre-processed Sentinel-1 data for 3 winter seasons from 2014 to 2017 over an area of 2310 km2 in the Northern French Alps. We have shown that SAR data are relevant for monitoring snowpack evolution and demonstrated the ability of the modeling chain to reproduce observed signal variations despite strong negative bias in wet snow conditions. We focused on wet snow products derived from Sentinel-1 SAR observations in synergy with snow absence/presence products derived from visible Sentinel-2 observations. This study was conducted on the winter season 2017-2018, which was remarkable for its snow and avalanche conditions. Such combined products make it possible to follow the spatio-temporal variability of mountain wet snow and dry snow at high elevation. This work opens the way for the assimilation of SAR remote sensing data into the Crocus snowpack model as well as greater exploitation of this data in the context of avalanche snow monitoring and prediction for a variety of purposes.

Orientador: Antônio José Maria Cataneo / Resumo: Introdução: No melanoma primário, a aplicabilidade da biópsia de linfonodo sentinela (BLS), seguida ou não de esvazimento linfonodal (EL) é conhecida. Na recidiva locorregional (RL) de melanoma, alguns serviços tendem a indicá-la, buscando estadiamento mais acurado para embasar condutas individualizadas aos pacientes, ainda que as evidências sejam insuficientes. Objetivo: Avaliar o sucesso da BLS no encontro do linfonodo sentinela (LNS) e sua positividade na RL. Comparar a sobrevida entre os pacientes com LNS positivo e negativo. Verificar diferença na sobrevida pós EL. Métodos: Revisão sistemática, através das bases MEDLINE via PUBMED, LILACS, SCOPUS, EMBASE e CENTRAL, buscando estudos experimentais e observacionais sobre BLS na RL de melanoma. Desfechos avaliados: sucesso na BLS pelo encontro do LNS, positividade para melanoma no LNS; sobrevida no subgrupo LNS positivo comparado com o negativo; sobrevida livre de doença no subgrupo LNS positivo comparada com o negativo; sobrevida dos pacientes submetidos ao EL. Para metanálises, utilizaram-se RevMan 5.3 e StatsDirect 3.0.121. Resultados: Foram identificados 1872 estudos, destes, seis estudos observacionais foram incluídos, totalizando 449 pacientes. O LNS foi encontrado em 98% das BLS (IC 95-100%, I2=53,7% - seis estudos). LNS com 32% de positividade para melanoma (IC 19-47%, I2= 84,6% - seis estudos). A chance de sobrevida global em cinco anos foi 2,49 vezes maior no subgrupo com LNS negativo (IC 95% 1,41-4,38, I2=0% - qua... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Background: In primary melanoma, the applicability of sentinel lymph node biopsy (SLB), followed or not by complete lymph node dissection (CLND) is known. In locoregional recurrence (LR) of melanoma, some groups may indicate it for more accurate staging to support individualized management, even with scarce evidence. Objective: To evaluate success in SLB and its positivity in LR. Compare survival between patients with positive and negative sentinel lymph node (SLN). Check for survival modification after CLND. Methods: Systematic review through databases such as MEDLINE via PUBMED, LILACS, SCOPUS, EMBASE and CENTRAL, searching for experimental and observational studies on SLB in melanoma LR. Outcomes assessed: success in SLB by finding the SLN, positivity for melanoma in the SLN; survival in the positive SLN subgroup compared to the negative one; disease-free survival in the positive versus negative SLN subgroup; survival of patients undergoing CLND. For meta-analyzes, RevMan 5.3 and StatsDirect 3.0.121 were used. Results: The total number of patients in six observational studies was 449, over 1872 studies indentified. The SNL was found in 98% of SLB (95-100% CI, I2 = 53.7%, 6 studies). SLB detected 32% positivity for melanoma on SNL (CI 19-47%, I2 = 84.6%, 6 studies). The chance of five year overall survival was 2,49 higher in the negative SNL subgroup (95% CI 1.41-4.38, I2 = 0%, 4 studies). Meta-analyzes were not performed due to lack of objective data for disease-free survi... (Complete abstract click electronic access below) / Doutor

Monitoring carbon stock has emerged as a critical environmental problem among several worldwide organizations and collaborations in the context of global warming and climate change. This study seeks to provide a remote sensing solution based on three types of data, to explore the feasibility and reliability of estimating aboveground biomass (AGB) in order to improve the efficiency of monitoring carbon stock. The study attempted to investigate the potential of using Google Earth Engine (GEE), and the combinations of different datasets from Sentinel-1 (SAR), Sentinel-2 multispectral imagery, and LiDAR data to estimate AGB, by using the random forest algorithm (RF). Two models were proposed: the first one (Model 1) detected the AGB temporal changes from 2016 to 2021 in Southern Sweden; while the second one (Model 2) focused on Hultsfred municipality and studied the influence of different variables including the canopy height. Besides, six experimental groups of variables were tested to determine the performance of using different types of remote sensing data. We validated these two models with the observed AGB, and the findings showed that the combination of SAR polarization, multisprectral bands, vegetation indices able to estimate AGB for Model 1. In addition, Model 2 showed that further using the canopy height data can further improve the estimation.  We also found out that the spectral bands from Sentinel-2 contributed the most to AGB estimation for Model 1 in terms of: bands B3 (Green), B4 (Red), B5 (Red edge), B11 (SWIR), B12 (SWIR); and, vegetation indices of RVI, DVI, and EVI. On the other hand, for Model 2, B1(Ultra blue), B4 (Red), EVI, SAVI, and the canopy height are the most crucial variables for estimating AGB. Besides, the radar backscatter values using VV and VH modes from Sentienl-1 were both important for Models 1 and 2. For Model 1, the experimental group with the best accuracy was the group that used all variable combinations from Sentinel-1 and 2, and its   was 0.33~0.74. For Model 2, the group that used all the variables, in addition to the canopy height performed the best, where its   is 0.91. These therefore showed the benefit of integrating different remote sensing data sources.  In conclusion, this study showed the potential of using RF and GEE to estimate AGB in Southern Sweden. Furthermore, this study also shows the possibility of handling large dataset for a large scale area, at the resolution of 10 m, and producing time series AGB maps from 2016 to 2021. This can help enhance our understanding of AGB temporal changes and carbon stock detection in Southern Sweden, that can provide valuable insights for forest management and carbon monitoring.

Soil moisture estimation using Sentinel-1 radar data The main aim of this diploma thesis was to find and quantify the relationship between the intensity of backscatter from the Sentinel-1 radar data and the volume soil moisture at the level of agricultural fields. The research was conducted in three areas, in the first part there were two vegetation-free fields near the Thessaloniki (Greece), and information about soil moisture was obtained from own measurements using a thermogravimetric method. The second part drew data from the freely available ISMN database and the research was carried out on agricultural fields during the vegetation season in northwest Germany. The third part used soil moisture data from the Czech Hydrometeorological Institute (ČHMÚ) and the area of interest was two grassed areas of the airport and one agricultural field. Correlation was measured by calculating the determination coefficient and by using the linear regression an equation for calculating the soil moisture from the radar backscatter was compiled. High dependence has been confirmed when VV polarization with constant surface roughness were examined. In the case of surfaces with varying roughness and vegetation cover, only low correlation was found, similarly with using VH polarization. Key words: radar, SAR, Sentinel-1, soil...

In order to reduce their predation risk, species have evolved a range of anti-predator behaviours. One co-ordinated anti-predator behaviour present in some group-living species is sentinel behaviour. In this behaviour individuals take up an elevated position and scan for threats, providing an alarm when one is spotted. However, this behaviour can lead to social conflict. Sentinel behaviour is a public good, i.e. the benefits are felt by all group members, but the costs only accrue to the actor. Thus it may be open to free loading, requiring individuals to monitor collaborators to prevent cheats. Additionally, individuals may vary in their alarm call reliability, which may select individuals to alter their behaviour based on caller ID. Monitoring others requires individuals to be closely associated, yet individuals may be spread out. For instance, foraging groups may be some distance from their nest, yet nestlings are particularly vulnerable. Adults should reduce their number of nest visits if a threat is nearby, so individuals returning from the nest may be selected to communicate about any perceived threats. Additionally, when perceiving threats, species need not use only conspecific information, because heterospecifics can also provide relevant information. In this thesis, I test these ideas in the Southern Pied Babbler (Turdoides bicolor), and I show that a) pied babblers monitor the quantity and quality of group-mates’ anti-predator behaviour; b) babblers accompany naïve sentinels and I investigate whether this may be related to anti-predator teaching; c) babblers do not appear to actively communicate about perceived nest threats because they do not alter their provisioning rate based on heterospecific derived anti-predator information; while d) avian heterospecifics are more prevalent in the presence of pied babblers, and can be attracted to areas by playback of pied babbler calls. These results show that species monitor both conspecifics and heterospecifics, and alter their behaviour based on the information they collect.

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Traditional disease surveillance systems are instrumental in guiding policy-makers' decisions and understanding disease dynamics. The first study in this dissertation looks at sentinel surveillance network design. We consider three location-allocation models: two based on the maximal coverage model (MCM) and one based on the K-median model. The MCM selects sites that maximize the total number of people within a specified distance to the site. The K-median model minimizes the sum of the distances from each individual to the individual's nearest site. Using a ground truth dataset consisting of two million de-identified Medicaid billing records representing eight complete influenza seasons and an evaluation function based on the Huff spatial interaction model, we empirically compare networks against the existing volunteer-based Iowa Department of Public Health influenza-like illness network by simulating the spread of influenza across the state of Iowa. We compare networks on two metrics: outbreak intensity (i.e., disease burden) and outbreak timing (i.e., the start, peak, and end of the epidemic). We show that it is possible to design a network that achieves outbreak intensity performance identical to the status quo network using two fewer sites. We also show that if outbreak timing detection is of primary interest, it is actually possible to create a network that matches the existing network's performance using 42% fewer sites. Finally, in an effort to demonstrate the generic usefulness of these location-allocation models, we examine primary stroke center selection. We describe the ineffectiveness of the current self-initiated approach and argue for a more organized primary stroke center system. While these traditional disease surveillance systems are important, they have several downsides. First, due to a complex reporting hierarchy, there is generally a reporting lag; for example, most diseases in the United States experience a reporting lag of approximately 1-2 weeks. Second, many regions of the world lack trustworthy or reliable data. As a result, there has been a surge of research looking at using publicly available data on the internet for disease surveillance purposes. The second and third studies in this dissertation analyze Wikipedia's viability in this sphere. The first of these two studies looks at Wikipedia access logs. Hourly access logs dating back to December 2007 are available for anyone to download completely free of charge. These logs contain, among other things, the total number of accesses for every article in Wikipedia. Using a linear model and a simple article selection procedure, we show that it is possible to nowcast and, in some cases, forecast up to the 28 days tested in 8 of the 14 disease-location contexts considered. We also demonstrate that it may be possible in some cases to train a model in one context and use the same model to nowcast or forecast in another context with poor surveillance data. The second of the Wikipedia studies looked at disease-relevant data found in the article content. A number of disease outbreaks are meticulously tracked on Wikipedia. Case counts, death counts, and hospitalization counts are often provided in the article narrative. Using a dataset created from 14 Wikipedia articles, we trained a named-entity recognizer (NER) to recognize and tag these phrases. The NER achieved an F1 score of 0.753. In addition to these counts in the narrative, we tested the accuracy of tabular data using the 2014 West African Ebola virus disease epidemic. This article, like a number of other disease articles on Wikipedia, contains granular case counts and deaths counts per country affected by the disease. By computing the root-mean-square error between the Wikipedia time series and a ground truth time series, we show that the Wikipedia time series are both timely and accurate.