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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
91

Sustainable knowledge systems and resource stewardship : in search of ethno-forestry paradigms for the indigenous peoples of Eastern Kham

Studley, John January 2005 (has links)
Policy-makers, project planners and development organisations are becoming convinced that the failure of the new socio-ecologically sensitive strategies co-opted by 'professional' forestry could be better addressed by indigenous forestry. They believe that indigenous forestry might assist with the development of successful forestry projects that are ecologically sustainable and socio-politically equitable. In order, however, to learn from indigenous forestry systems, the acculturation of foresters in the vernacular culture of the forest users appears to be an essential process for understanding and intervening in a local forest management complex. Acculturation entails not only more attention to the immaterial cultural realm, but an understanding of multiple resource stewardship, local ways of knowing and perceiving, local forest values and 'practices of care'. While acknowledging the significance of the politics of knowledge and political ecology this study examines resource stewardship from an alternative neglected angle that of knowledge sustainability and synergistic bridging. It will examine in general modes of knowing and bridging between 'formal' and indigenous forestry knowledge, and in particular the identification of forest value paradigms that are evidently exemplars of bio-cultural sustainability. The main outcomes of this study include the cognitive mapping of forest values among 'Tibetan minority nationalities' in Eastern Kham, their spatial distribution and the coincidence of changes in forest values with cultural or biophysical phenomena. Conceptually this study relies heavily on knowledge-system, hypertext, and paradigm theory and a critique of the narratives of John Locke. The former provide a platform to compare and contrast alternative knowledge systems and a means of synergistic bridging between them and the latter encapsulates a trajectory of western knowledge often known as modernity. The quantitative methods employed in this study included text analysis for forest value identification, multidimensional scaling for the cognitive mapping of forest values, spatial analysis and kriging for forest value distribution, and boundary or wombling analysis for changes in forest values and their coincidence with cultural or biophysical phenomena. The latter four methods are groundbreaking in that they have never been used to study forest values before. The study concludes that there is compelling evidence suggesting homogeneity in forest values with up to 5 geospatial paradigms and up to 12 cognitive paradigms. The findings, especially close correlation between forest values and ethnolinguistics, provide a potential template for foresters to develop multiple models of natural resource or biodiversity stewardship based on local forest values. In terms of the wider application, indigenous knowledge cannot seemingly be sustained if it is integrated with or into western knowledge systems due to the lack of conceptual frameworks for cross-cultural epistemological or psychological integration. Coalescing under the rubric of post-modernism, however, we do find a number of complimentary trajectories, which seemingly provide space for knowledge equity, sustainability and bridging. These trajectories include hypertext theory, paradigm theory, abductive logic, adaptive management, ecospiritual paradigms, and post-modern forestry paradigms. These trajectories and findings offer planners globally a means for synergistic bridging between local and non-local knowledge systems on the road to sustainable forestry and biodiversity stewardship.
92

A New Evolutionary Algorithm For Mining Noisy, Epistatic, Geospatial Survey Data Associated With Chagas Disease

Hanley, John P. 01 January 2017 (has links)
The scientific community is just beginning to understand some of the profound affects that feature interactions and heterogeneity have on natural systems. Despite the belief that these nonlinear and heterogeneous interactions exist across numerous real-world systems (e.g., from the development of personalized drug therapies to market predictions of consumer behaviors), the tools for analysis have not kept pace. This research was motivated by the desire to mine data from large socioeconomic surveys aimed at identifying the drivers of household infestation by a Triatomine insect that transmits the life-threatening Chagas disease. To decrease the risk of transmission, our colleagues at the laboratory of applied entomology and parasitology have implemented mitigation strategies (known as Ecohealth interventions); however, limited resources necessitate the search for better risk models. Mining these complex Chagas survey data for potential predictive features is challenging due to imbalanced class outcomes, missing data, heterogeneity, and the non-independence of some features. We develop an evolutionary algorithm (EA) to identify feature interactions in "Big Datasets" with desired categorical outcomes (e.g., disease or infestation). The method is non-parametric and uses the hypergeometric PMF as a fitness function to tackle challenges associated with using p-values in Big Data (e.g., p-values decrease inversely with the size of the dataset). To demonstrate the EA effectiveness, we first test the algorithm on three benchmark datasets. These include two classic Boolean classifier problems: (1) the "majority-on" problem and (2) the multiplexer problem, as well as (3) a simulated single nucleotide polymorphism (SNP) disease dataset. Next, we apply the EA to real-world Chagas Disease survey data and successfully archived numerous high-order feature interactions associated with infestation that would not have been discovered using traditional statistics. These feature interactions are also explored using network analysis. The spatial autocorrelation of the genetic data (SNPs of Triatoma dimidiata) was captured using geostatistics. Specifically, a modified semivariogram analysis was performed to characterize the SNP data and help elucidate the movement of the vector within two villages. For both villages, the SNP information showed strong spatial autocorrelation albeit with different geostatistical characteristics (sills, ranges, and nuggets). These metrics were leveraged to create risk maps that suggest the more forested village had a sylvatic source of infestation, while the other village had a domestic/peridomestic source. This initial exploration into using Big Data to analyze disease risk shows that novel and modified existing statistical tools can improve the assessment of risk on a fine-scale.
93

Surface Gas Permeability of Porous Building Materials: Measurement, Analysis and Applications

Grover, David Klein Weibust 01 January 2014 (has links)
In many events affecting our civil infrastructure, such as contamination or weathering, it is likely that only the surfaces of the affected building materials will be available for non-destructive measurements. In this work, we describe and analyze surface gas permeability measurements on a variety of natural and engineered building materials using two types of relatively new, non-destructive surface permeameters. It is shown that the surface gas permeability measurements correlate well with each other and could provide rapid estimates of macroscopic gas permeability and degradation of materials due to weathering. It is hypothesized that surface permeability can be used to predict macroscopic wicking of water. The results indicated that macroscopic wicking correlated reasonably well with surface permeability measurements of uniform materials with low permeabilities such as sandstones and clay brick.
94

DEVELOPMENT AND DEPLOYMENT OF A FIELD BASED SOIL MAPPING TOOL USING A COMPARATIVE EVALUATION OF GEOSTATISTICS AND MACHINE LEARNING

Jeff Fiechter (7046756) 13 August 2019 (has links)
Soil property variability is a large component of the overall environmental variability that Precision Agriculture practices seek to address. Thus, the creation of accurate field soil maps from field soil samples is of utmost importance to practitioners of Precision Agriculture, as understanding and characterizing variability is the first step in addressing it. Today, growers often interpolate their soil maps in a “black-box” fashion, and there is a need for an easy to use, accurate method of interpolation. In this study, current interpolation practices are examined as a benchmark, a Random Forest (RF) based prediction framework utilizes public data to aid predictions, and the RF framework is exposed via a webtool. A high density (0.20 ha/sample) field soil sample dataset provides 28 training points and 82 validation points to be used as a case study. In the prediction of soil percent organic matter (OM), the grid and ordinary kriging interpolations both had higher Mean Absolute Error (MAE) scores than a field average prediction, though the difference was not statistically significant at a 5\% confidence level. A RF framework interpolation utilizing a high resolution (1.52 m) DEM and distances to known points as the feature set had a significantly lower MAE score than the field average, grid, and ordinary kriging interpolations. The results suggest that for the study site, RF framework performed better compared to a field average, a grid based, and an ordinary kriging interpolation methods.
95

[en] GEOLOGICAL AND GEOMECHANICS MODELLING 3D AND STABILITY ANALYSES 2D OF THE SLOPES OF THE MORRO DA MINA MINE, CONSELHEIRO LAFAIETE, MG, BRAZIL / [pt] MODELAGEM GEOLÓGICA E GEOMECÂNICA 3D E ANÁLISES DE ESTABILIDADE 2D DOS TALUDES DA MINA DE MORRO DA MINA, CONSELHEIRO LAFAIETE, MG, BRASIL

CRISTIANE SILVA ROCHA DAMASCENO 14 August 2008 (has links)
[pt] O trabalho propõe uma metodologia para elaboração de modelos geológicos e geomecânicos (3D) e realização de análises de estabilidade (2D)de taludes rochosos de minas a céu aberto, com base nos dados da mina de Morro da Mina, fornecidos pela empresa VALE, a qual esta pertence. A metodologia está dividida em duas etapas: modelagem e análises de estabilidade. Para a modelagem, foi utilizado o software Petrel 2004, que oferece ferramentas geoestatísticas, possibilitando a extrapolação das informações geotécnicas pontuais c`, fi, RQD, Q e RMR, obtidas por meio de testemunhos de sondagem, para o maciço inteiro. Utilizou-se a técnica de Krigagem Ordinária. O modelo gerado representou bem a distribuição destas propriedades no espaço. Na etapa de análise de estabilidade, foram utilizadas seções resultantes da modelagem geomecânica. Dois tipos de análises foram realizados: análises cinemáticas, com utilização do software Dips, da Rocscience, e análises por equilíbrio limite dos taludes globais e das bancadas, utilizando-se o software Slide 5.0, também da Rocscience. No primeiro tipo, realizado com dois conjuntos de mapeamentos diferentes, foi constatado que as bancadas devem receber bastante atenção nesta mina, e no segundo tipo, foi verificada a segurança quanto à ruptura circular das bancadas e taludes globais, porém recentemente ocorreu uma ruptura em um dos locais analisados. Os programas RocData 4.0 e RocProp, ambos da Rocscience, foram utilizados para estimar os parâmetros de resistência de Mohr-Coulomb, e os softwares AutoCAD 2004 e Microsoft Office Excel auxiliaram na preparação dos arquivos de entrada no Petrel 2004 e no Slide 5.0. / [en] This work presents a methodology to develop geological and geomechanic models (3D) and to carry out stability analyses (2D) of rock slopes of open pit mine, based on data of Morro da Mina mine, provided by the mining company VALE. The methodology is divided in two stages: modelling and stability analyses. For the modelling, the software Petrel 2004, which allows the use of geostatistical tools, was used, being possible the spatial distribution of geotechnical information, obtained from borehole cores, for the whole rock mass. The technique of Ordinary Kriging was used. The modeled properties were the following: c`, fi, RQD, Q e RMR. The generated model represented well the spatial distribution of these properties. The stability analyses were carried out using 2D sections and the necessary rock mass parameters were obtained from the geomechanical model. Two types of analyses were carried out: kinematic analyses, with use of the software Dips, from Rocscience, and limit equilibrium analyses of the global slopes and the benches, where the software Slide 5.0, also from Rocscience was used. The Kinematic analyses, carried out considering two sets of joint orientations, suggested that the benches have to receive enough attention in this mine, and the limit equilibrium analyses for circular failure of the benches and global slopes indicated high factors of safety. However, before this work initiating a failure already had happened in one of the sections analyzed. The programs RocData 4.0 and RocProp, both from Rocscience, were used to estimate the Mohr-Coulomb strength parameters, and the programs AutoCAD 2004 and Microsoft Office Excel helped at the development of the input files in the Petrel 2004 and Slide 5.0.
96

Geração de mapas de ambiente de rádio em sistemas de comunicações sem fio com incerteza de localização. / Generation of radio environment maps in wireless communications systems with location uncertainly.

Silva Junior, Ricardo Augusto da 17 December 2018 (has links)
A geração e o uso dos mapas de ambiente de rádio (REM - Radio Environment Map) em sistemas de comunicações sem fio vêm sendo alvo de pesquisas recentes na literatura científica. Dentre as possíveis aplicações, o REM fornece informações importantes para os processos de predição e otimização de cobertura em sistemas de comunicações sem fio, pois é baseado em medidas coletadas diretamente da rede. Neste contexto, a geração do REM depende do processamento das medidas e suas localizações para a construção dos mapas, por meio de predições espaciais. Entretanto, a incerteza de localização das medidas coletadas pode degradar a acurácia das predições de forma significativa e, consequentemente, impactar as posteriores decições baseadas no REM. Este trabalho aborda o problema de geração do REM de forma mais realística, formulando um modelo de predição espacial que introduz erros de localização no ambiente de rádio de um sistema de comunicação sem fio. As investigações mostram que os impactos provocados pela incerteza de localização na geração do REM são significativos, especialmente nas técnicas de estimação utilizadas para a aprendizagem de parâmetros do modelo de predição espacial. Com isso, uma técnica de predição espacial é proposta e utiliza ferramentas da área geoestatística para superar os efeitos negativos causados pela incerteza de localização nas medidas. Simulações computacionais são desenvolvidas para a avaliação de desempenho das principais técnicas de predição no contexto de geração do REM, considerando o problema da incerteza de localização. Os resultados de simulação da técnica proposta são promissores e mostram que levar em conta a distribuição estatística dos erros de localização pode resultar em predições com maior acurácia para a geração do REM. A influência de diferentes aspectos da modelagem do ambiente de rádio também é analisada e reforçam a ideia de que a aprendizagem de parâmetros do ambiente de rádio tem um papel importante na acurácia das predições espaciais, que são fundamentais para a geração confiável do REM. Finalmente, um estudo experimental do REM é realizado por meio de uma campanha de medidas, permitindo explorar o desempenho dos algoritmos de aprendizagem de parâmetros e predições desenvolvidos neste trabalho. / The generation and use of radio environment maps (REM) in wireless systems has been the subject of recent research in the scientific literature. Among the possible applications, the REM provides important information for the coverage predicfition and optimization processes in wireless systems, since it is based on measurements collected directly on the network. In this context, the REM generation process depends on the processing of the measurements and their locations for the construction of the maps through spatial predictions. However, the location uncertainty related to the measurements collected can signicantly degrade the accuracy of the spatial predictions and, consequently, impact the decisions based on REM. This work addresses the problem of the REM generation in a more realistic way, through the formulation of a spatial prediction model that introduces location errors in the radio environment of a wireless communication system. The investigations show that the impacts of the location uncertainty on the REM generation are significant, especially in the estimation techniques used to learn the parameters of the spatial prediction model. Thus, a spatial prediction technique is proposed, based on geostatistical tools, to overcome the negative effects caused by the location uncertainty of the REM measurements. Computational simulations are developed for the performance evaluation of the main prediction techniques in the context of REM generation, considering the problem of location uncertainty. The simulation results of the proposed technique are promising and show that taking into account the statistical distribution of location errors can result in more accurate predictions for the REM generation process. The influence of different aspects of the radio environment modeling is also analyzed and reinforce the idea that the learning of radio environment parameters plays an important role in the accuracy of spatial predictions, which are fundamental for the reliable REM generation. Finally, an experimental study is carried out through a measurement campaign with the purpose of generating the REM in practice and to explore the performance of the learning and prediction algorithms developed in this work.
97

Análise de incertezas do modelo de teores associado aos investimentos de pesquisa de longo prazo / Uncertainty analyses of grade models related with long term resources

Ferreira, Talita Cristina de Oliveira 31 March 2016 (has links)
Os empreendimentos de mineração comumente demandam grande quantidade de investimentos financeiros e, na maioria das vezes, longos períodos de implantação, o que os torna altamente sujeitos a diversas fontes de incertezas. Tais incertezas comumente tendem a diminuir conforme a evolução do projeto. O objetivo deste estudo é correlacionar as incertezas associadas ao modelo de teores de cobre do depósito Sequeirinho com o volume de investimentos realizados ao longo de distintas fases da pesquisa geológica. Este depósito insere-se no contexto do Complexo de Mineração Sossego, localizado no município de Canaã dos Carajás (PA). Primeiramente, foram realizadas 100 simulações para cada domínio litológico em cada campanha de sondagem (pré-1998, 1999, 2000, 2002 e 2003) a partir do método de simulação sequencial gaussiana condicionada aos dados amostrais, totalizando 1.400 possíveis cenários. Para a avaliação das incertezas foram calculados três índices: variância condicional, coeficiente de variação condicional e intervalo interquartil. Por fim, a avaliação dos investimentos foi elaborada a partir dos custos estimados para o desenvolvimento de sondagens e análises químicas. Desde a campanha pré-1998, houve uma tendência de os teores médios do depósito aproximarem-se dos prováveis valores reais observados nas fases finais da pesquisa. No ano de 2000 ocorreu o maior investimento (cerca de 28 milhões de Reais) e a redução das incertezas atingiu o patamar de 15%. Os investimentos desenvolvidos em sondagens posteriores à campanha de 2000 foram da ordem de 9 milhões de Reais (cerca de 12 mil metros de sondagem), porém, não foram constatadas reduções significativas das incertezas. Este investimento seria melhor aproveitado caso fosse redirecionado a novas áreas de prospecção. Além do montante financeiro necessário para a redução das incertezas, foco deste estudo, as variações na interpretação geológica e a locação dos furos de sondagem são variáveis importantes na análise de incertezas associadas aos investimentos em pesquisa geológica. / Mining projects require large amount of capital investment and most cases spend long periods of implementation, which make them extremely susceptible to several sources of uncertainty. Such uncertainties commonly tend to decrease along the project development. The present study aims to correlate the uncertainties associated to the grade model of the Sequeirinho copper mine with the amount of capital investment that has been spent along different geological surveys. Sequeirinho site is included in the context of Sossego Mine Complex, located in Canaã dos Carajás (PA, Brazil). Initially, 100 simulations were carried out for each lithologic domain in each drilling campaign (pre-1998, 1999, 2000, 2002 and 2003) using sequential Gaussian simulation conditioned to the sample, resulting in 1,400 possible scenarios. Three indexes were calculated for the uncertainty analysis: conditional variance, conditional coefficient variance and interquartile range. Finally, the evaluation of capital investment was elaborated from the costs estimated for drilling and chemical analysis. Since pre-1998 drilling campaign, deposit average grades have showed a trend to get closer to the possible real values observed in the final research surveys. In 2000, there was the biggest capital investment (about R$ 28 millions) and the uncertainty reduction has reached the maximum level of 15%. Investments performed in drilling programs after 2000 were around R$ 9 million (around 12,000 meters of drill holes), but the uncertainty reduction was not significant. Therefore, such investments might be used to discover new targets. Besides the correlation of uncertainty reduction and amount of capital investment, the main focus of this study, the uncertainty of geological model and the drillhole locations are important variables to be considered in investment analysis of geological survey.
98

Identificação de padrões de uso do solo urbano em São Paulo/SP utilizando parâmetros de variogramas. / Urban land use pattern identification using variograms on image.

Barros, Daniele Lima 17 April 2015 (has links)
As imagens de alta resolução espacial impulsionaram os estudos de Sensoriamento Remoto em ambientes urbanos, já que elas permitem uma melhor distinção dos elementos que compõem esse ambiente tão heterogêneo. Técnicas de Geoestatística são cada vez mais utilizadas em estudos de Sensoriamento Remoto e o variograma é uma importante ferramenta de análise geoestatística, pois permitem entender o comportamento espacial de uma variável regionalizada, neste caso, os níveis de cinza de uma imagem de satélite. O presente trabalho pretende avaliar a proposta metodológica que consiste em identificar padrões residenciais urbanos de três classes de uso e ocupação do solo por meio da análise dos valores apresentados pelos parâmetros, alcance, patamar e efeito pepita de um variograma. A hipótese é que os valores correspondentes a esses parâmetros representem o comportamento espectral padrão de cada classe e, portando, indicam que há um padrão na organização espacial de cada uma das classes. Para a presente pesquisa foram utilizadas imagem IKONOS 2002, e a classificação de uso e ocupação do solo da sub-bacia do córrego Bananal na bacia do Rio Cabuçu de Baixo em São Paulo SP. Amostras das imagens de cada classe foram extraídas e os valores de nível de cinza em cada pixel foram utilizados para calcular os variogramas. Após análise dos resultados obtidos, apenas o parâmetro alcance foi levado em consideração, pois é através desse parâmetro que se observa o grau de homogeneidade de cada amostra. Os valores de alcance obtidos nos cálculos dos variogramas identificaram com melhor precisão a classe Conjuntos Residenciais que é uma classe com padrões e características singulares, já a identificação das classes Ocupação Densa Regular e Ocupação Densa Irregular não obteve uma precisão boa, sendo que essas classes são similares em diversos aspectos. / The images of high spatial resolution studies of leveraged Remote Sensing in urban environments, as they enable better distinction of the elements that make up this very heterogeneous environment. Geostatistical techniques are increasingly used in studies of Remote Sensing, the variogram is an important tool geostatiscal analysis, because it allows to understand the spatial behavior of a regionalized variable, in this case, the gray levels of a satellite image. This study aims to assess the methodological proposal is to identify urban residential patterns of three classes of use and occupation of land by the analysis of the figures presented by the parameters, scope, and level of a nugget effect variogram. The hypothesis is that the values corresponding to these parameters represent the standard of each class spectral behavior and bearing indicate that there is a pattern in the spatial organization of each class. IKONOS 2002 image were used for this research, and the classification of the use and occupation of the stream Banana plantation sub-basin in the Rio Cabuçu Low Bowl in Sao Paulo - SP. Samples of stock were taken from each class and the values of gray level in each pixel are used to calculate the variogram. After analyzing the results, only the parameter range was taken into account , because it is through this parameter is observed the degree of homogeneity of each sample. The range of values obtained in the calculation of variograms identified with better accuracy class \"Multiple Dwelling Unit\" which is a class with unique patterns and characteristics, since the identification of classes \"Regulated Dense Occupation\" and \"Irregular Dense Occupation\" did not get a good precision since the classes are similar in several respects.
99

Abordagens para análise de dados composicionais / Approaches to compositional data analysis

Prado, Naimara Vieira do 03 April 2017 (has links)
Dados composicionais são vetores, chamados de composições, cujos componentes são todos positivos, satisfazem a soma igual a 1 e possuem um espaço amostral próprio chamado Simplex. A restrição da soma induz a correlação entre os componentes. Isso exige que os métodos estatísticos para análise desses conjuntos de dados considerem esse fato. A teoria para dados composicionais foi desenvolvida inicialmente por Aitchison na década de 80. Desde então, várias técnicas e métodos têm sido desenvolvidos para a modelagem dos dados composicionais. Este trabalho apresenta as principais abordagens para a análise estatística de dados composicionais independentes. Sendo, regressão Dirichlet (distribuição natural aos dados composicionais) ou o uso de transformações em razões logarítmicas que saem do espaço simplex para o espaço real. Também descreve os métodos para os casos em que a suposição de independência não pode ser atendida. Por exemplo, dados composionais com dependência espacial. Para esses casos, há na literatura métodos baseados nas teorias desenvolvidas para análise geoestatística de dados univariados; ou, no uso de transformações em razões logarítmicas com a inclusão da dependência espacial. Além de revisitar os métodos já difundidos, propõe-se o uso do método de Equações de Estimação Generalizadas (EEG) como alternativa para a análise de dados composicionais independentes e com dependência espacial. A principal vantagem é que as equações de estimação necessitam apenas da especificação de funções que descrevam a média e a estrutura de covariância. Assim, não é necessário atribuir uma distribuição de probabilidade aos dados ou fazer o uso de transformações. A aplicação do método EEG para dados composicionais independentes apresentou resultados tão eficientes quanto a regressão Dirichlet ou transformação em razões logarítmicas. Para os dados composicionais com dependência espacial, o método baseado em verossimilhança foi o que apresentou valores preditos mais próximos aos valores reais. O método EEG foi mais eficaz do que a abordagem geoestatística dos componentes individuais, porém, comparado com os demais métodos, foi o que apresentou maior valor residual. / C ompositional data are vectors, called compositions, whose components are all positive, it satisfies the sum equal one and has a Simplex space. The sum constraint induces the correlation between the components and this requires that the statistical methods for the analysis of datasets consider this fact. The theory for compositional data was developed mainly by Aitchison in the 1980s, and since then, several techniques and methods have been developed for compositional data modelling. This work presents the main approaches for the statistical analysis of independent compositional data, such as Dirichlet regression (natural distribution to compositional data) or the use of transformations log-ratios that aim to leave the simplex space for to Euclidean space. Also describes the methods for cases where the assumption of independence cannot be satisfied, for example, spatial dependence compositional data. For these cases, there are in the literature methods of analysis based on the theories developed for univariate geostatistics analysis or use of logratios transformations with the inclusion of the spatial dependence generated by the distance between the points. In addition, to revisiting the already diffused methods, this work propose the use of the Generalized Estimation Equation (GEE) method as an alternative for the analysis of independent compositional data and with spatial dependence. The GEE only requires the specification of functions that describe the mean and correlation matrix (covariance structure, therefore, it is not necessary to assign a probability distribution to the data or transformations. The application of the GEE method for independent compositional data presented results as efficient as Dirichlet regression or log-ratios transformation. Compositional data with spatial dependence, log-ratios transformations presented predicted values close to the real values. GEE method was more effective than the traditional geostatistical approach, however, compared with the other methods, It was the one that presented the high residual values.
100

Nova abordagem para a interpretação da Reserva Legal com auxílio da geoestatística. / New approach to the interpretation of the Legal Reserve with the aid of geostatistics.

Okumura, Miriam Harumi 17 February 2014 (has links)
A Floresta Amazônica é palco de um grande número de atividades de desflorestamento, como a mineração artesanal, agropecuária e comércio de madeira. A fim de se ter uma diminuição dos impactos ambientais, os órgãos fiscalizadores têm tentado regular estas atividades e orientá-las para métodos de operação mais responsável. Este trabalho descreve a iniciativa por meio do monitoramento dessas áreas de floresta localizadas perto dessas regiões de desmatamento, porque os elementos fundamentais, tais como a biomassa e acúmulo de carbono das árvores podem ser adequadamente monitorados contra distúrbios ocasionais trazidos por essas atividades. A atual abordagem padrão na Amazônia é monitorar todas as árvores da floresta dentro de uma área chamada de transecto, também designado como inventário florestal, mantendo um registro rigoroso de seu comportamento e crescimento. No entanto, essas atividades são restritas às áreas de controle que estão localizados em regiões estratégicas e não representam toda a área a ser monitorada. Esta pesquisa explora uma nova metodologia baseada na geoestatística e destinada a otimização da amostragem, estendendo-se para o estudo de áreas florestais muito maiores, mantendo a utilização dos recursos humanos unitária inalterada, e, ao mesmo tempo, aumentar a superfície das áreas de estudo e a manter a confiança nos resultados. A metodologia proposta permite a seleção da Reserva Legal - RL, a ser feita de acordo com a distribuição real de acumulação de carbono da floresta, em vez de confiar na utilização de área percentual proposta por lei e no senso comum de proprietários / órgãos fiscalizadores. Esta metodologia foi aplicada na Floresta Nacional de Tapajós (FLONA Tapajós), no Estado do Pará, Brasil, utilizou-se de conjunto de dados disponíveis, para otimizar as amostras e monitorar a capacidade da floresta de armazenar carbono. A presente metodologia pretende contribuir para uma diminuição do custo das atividades de monitoramento por unidade de área, aumento da precisão para localização RL, e simplificação dos procedimentos através da aplicação de um conjunto de ferramentas de fácil utilização. Os resultados mostraram que a aplicação de estudos geoestatísticos para determinação de RL é um procedimento viável, pois a estrutura do variograma se mantém mesmo com a amostragem sofrendo uma diminuição randômica de até 50% da área de cobertura vegetal, conseguindo manter o mesmo resultado da amostragem na totalidade da cobertura vegetal. / The Amazon Rainforest is the scene of a large number of deforestation activities such as artisanal mining, agriculture and timber trade. For the purpose of have reduced environmental impacts, regulatory agencies have attempted to regulate these activities and direct them towards more responsible methods of operation. This paper describes the initiative by monitoring these forest areas located near these regions of deforestation, because the core elements, such as biomass and carbon accumulation of the trees can be adequately monitored against occasional disturbances brought by these activities. The current standard approach in the Amazon is to monitor all the trees of the forest within an area called the transect, also designated as forest inventory, keeping a strict record of their behavior and growth. However, these activities are restricted to control areas that are located in strategic regions and do not represent the whole area to be monitored. This research explores a new methodology based on geostatistics and designed to optimize the sampling, extending the study of much larger forest areas, keeping unchanged the use of human resources unit, and at the same time increase the surface areas of study and to maintain confidence in the results. The proposed methodology allows the selection of the Legal Reserve - RL, to be made according to the actual distribution of carbon accumulation in the forest, instead relying in using area percentage proposed by law and common sense of proprietary / regulatory agencies. This methodology was applied in the Tapajós National Forest (FLONA Tapajós), State of Pará, Brazil, we used the data set available, to optimize the sample and monitor the forest\'s ability to store carbon. This methodology intends to contribute to reducing the cost of monitoring activities per unit area, increased precision for location RL, and simplifying procedures by applying a set of easy to use tools. The results showed that application of geostatistical studies for determination of RL is a viable procedure, because the structure of the variogram is maintained even with a random sampling suffering decreased to 50% of the area of vegetation, even managing to keep the sampling result the total vegetation cover.

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