鑒於過去文獻可知，由於同一地區內的鄰近住宅擁有相同區位及市場特性，因而不動產價值存在高度相依性。空間相依性的產生往往是因為近鄰區域內的住宅有相似的建築結構（往往在同一個時間所興建），以及享有相同社會服務。由於建商在產品策略決策上會參考同一時間內鄰近競爭個案的產品策略，所以鄰近的新推個案會有相似的建築特徵以及相似的產品訂價。因此新推個案的訂價與鄰近的個案產生相關性，而新推個案訂價的相依性程度也會隨著時間距離遞減。 　　本文的目的在於將空間和時間的相依性最適地納入新推個案的訂價模型。採用582個台北市建商推案樣本進行實證。本研究分別以Moran’s I值和LISA值兩項指數來檢測空間自相關，並且比較傳統OLS迴歸模型、空間落遲模型，以及空間誤差模型三個模型的預測能力。此外，我們以不同的空間和時間的加權矩陣納入空間誤差模型中討論。 　　研究結果顯示，考量空間相依性之空間迴歸模型其解釋能力明顯優於一般傳統迴歸模型。而比起空間統計模型，時空迴歸模型更可以提高估計新推個案訂價的準確性。此外，研究結果亦顯示考慮時空交互影響的時空迴歸模型乃為新推個案訂價的最佳推估模式。 / It is well-known from the literature that the values of real estates are highly dependent on their locational and market characteristics of the buildings in adjacent areas. Spatial dependence mainly derives from factors that buildings at nearby properties have similar structural features (which were often developed at the same time) and often share the same social welfare. As developers in making decisions on product strategy will make reference to the strategy of nearby products of competitive cases which developed during the same time, therefore, within a certain period of time, the adjacent new construction will often have similar construction attributes as well as similar products pricing. Not only the pricing of a new construction is likely to be related to the pricing of adjacent new construction, but also the pricing of a new construction would be prone to autocorrelation decays in accordance with time distance. The aim of this paper is to analyze on how to take this temporal and spatial dependence into account in the pricing model of the new construction in the most appropriate way. We use a database of 582 asking prices of real estate developers in Taipei city. Two indices for measuring spatial autocorrelation are considered including (i) Moran’s I Index and (ii) LISA’s Index. We compared the predictive ability of three models including (i) OLS model, (ii) spatial lag model, and (iii) spatial error model. Moreover, we discussed the different temporal and spatial weight matrices in the spatial error model. According to our research results, we concluded that spatial statistical models obviously perform better than the traditional OLS model. Temporal and spatial statistical models would provide more accurate predictions on the pricing of a new construction than spatial statistical models do. The research result reveals that the best pricing model of the new construction is temporal and spatial statistical models which include temporal and spatial correlation.

La modélisation probabiliste des événements climatiques et environnementaux doit prendre en compte leur nature spatiale. Cette thèse porte sur l’étude de mesures de risque pour des processus spatiaux. Dans une première partie, nous introduisons des mesures de risque à même de prendre en compte la structure de dépendance des processus spatiaux sous-jacents pour traiter de données environnementales. Une deuxième partie est consacrée à l’estimation des paramètres de processus de type max-mélange. La première partie de la thèse est dédiée aux mesures de risque. Nous étendons les travaux réalisés dans [44] d’une part à des processus gaussiens, d’autre part à d’autres processus max-stables et à des processus max-mélange, d’autres structures de dépendance sont ainsi considérées. Les mesures de risque considérées sont basées sur la moyenne L(A,D) de pertes ou de dommages D sur une région d’intérêt A. Nous considérons alors l’espérance et la variance de ces dommages normalisés. Dans un premier temps, nous nous intéressons aux propriétés axiomatiques des mesures de risque, à leur calcul et à leur comportement asymptotique (lorsque la taille de la région A tend vers l’infini). Nous calculons les mesures de risque dans différents cas. Pour un processus gaussien, X, on considère la fonction d’excès : D+ X,u = (X−u)+ où u est un seuil fixé. Pour des processus max-stables et max-mélange X, on considère la fonction puissance : DνX = Xν. Dans certains cas, des formules semi-explicites pour les mesures de risque correspondantes sont données. Une étude sur simulations permet de tester le comportement des mesures de risque par rapport aux nombreux paramètres en jeu et aux différentes formes de noyau de corrélation. Nous évaluons aussi la performance calculatoire des différentes méthodes proposées. Celle-ci est satisfaisante. Enfin, nous avons utilisé une étude précédente sur des données de pollution dans le Piémont italien, celle-ci peuvent être considérées comme gaussiennes. Nous étudions la mesure de risque associée au seuil légal de pollution donnée par la directive européenne 2008/50/EC. Dans une deuxième partie, nous proposons une procédure d’estimation des paramètres d’un processus max-mélange, alternative à la méthode d’estimation par maximum de vraisemblance composite. Cette méthode plus classique d’estimation par maximum de vraisemblance composite est surtout performante pour estimer les paramètres de la partie max-stable du mélange (et moins performante pour estimer les paramètres de la partie asymptotiquement indépendante). Nous proposons une méthode de moindres carrés basée sur le F-madogramme : minimisation de l’écart quadratique entre le F-madogramme théorique et le F-madogramme empirique. Cette méthode est évaluée par simulation et comparée à la méthode par maximum de vraisemblance composite. Les simulations indiquent que la méthode par moindres carrés du F-madogramme est plus performante pour estimer les paramètres de la partie asymptotiquement indépendante / When dealing with environmental or climatic changes, a natural spatial dependence aspect appears. This thesis is dedicated to the study of risk measures in this spatial context. In the first part (Chapters 3 and 4), we study risk measures, which include the natural spatial dependence structure in order to assess the risks due to extreme environmental events and in the last part (Chapter 5), we propose estimation procedures for underlying processes, such as isotropic and stationary max-mixture processes. In the first part dedicated to risk measures, we extended the work in [44] in order to obtain spatial risk measures for various spatial processes and different dependence structures. We based these risk measures on the mean losses over a region A of interest. Risk measures are then defined as the expectation E[L(A,D)] and variance Var(L(A,D)) of the normalized loss. In the study of these measures, we focused on the axiomatic properties of asymptotic behavior (as the size of the region interest goes to infinity) and on computational aspects. We calculated two risk measures: risk measure for the gaussian process based on the damage function called access damage D+ X,u and risk measure for extreme processes based on the power damage function DνX . In simulation study and for each risk measure provided, we emphasized the theoretical results of asymptotic behavior by various parameters of a model and different Kernels for the correlation function. We also evaluated the performance of these risk measures. The results were encouraging. Finally, we implemented the risk measure corresponding to gaussian on the real data of pollution in Piemonte, Italy. We assessed the risks associated with this pollution when an excess of it was over the legal level determined by the European directive 2008/50/EC. With respect to estimation, we proposed a semi-parametric estimation procedure in order to estimate the parameters of a max-mixture model and also of a max-stable model ( inverse max-stable model) as an alternative to composite likelihood. A good estimation by the proposed estimator required the dependence measure to detect all dependence structures in the model, especially when dealing with the max-mixture model. We overcame this challenge by using the F-madogram. The semi-parametric estimation was then based on a quasi least square method, by minimizing the square difference between the theoretical F-madogram and an empirical one. We evaluated the performance of this estimator through a simulation study. It was shown that on a mean, the estimation is performed well, although in some cases, it encountered some difficulties

Orientador: Célia Regina Lopes Zimback / Banca: Hélio Grassi Filho / Banca: Carlos Alberto de Matos / Banca: Letícia Colares Vilela / Banca: Fátima Ahmad Rabah / Resumo: O presente trabalho teve como objetivo estudar a variabilidade de alguns atributos físicos e químicos do solo e de produtividade de alface (massa de matéria fresca da parte aérea total- F; massa de matéria fresca da parte aérea comercial - MFC; massa de matéria seca da parte aérea comercial - MSC e diâmetro de cabeça comercial - DCC), oferecendo subsídios ao mapeamento da estufa em diferentes zonas de manejo de água e nutrientes, almejando uma maior produtividade de alface e a irrigação de precisão, com a otimização do uso da água e de nutrientes. O experimento foi conduzido em uma estufa com alface irrigada por gotejamento e malha de amostragem com 152 pontos, na Fazenda Experimental São Manuel, da Faculdade de Ciências Agronômicas, Universidade Estadual Paulista, Câmpus de Botucatu, no município de São Manuel, Estado de São Paulo, Brasil. Todos os atributos estudados apresentaram dependência espacial forte; com exceção do atributo DCC que apresentou dependência moderada e do atributo MSC que não apresentou dependência espacial; os valores de umidade até 1,15 m apresentaram dependência espacial e valores de granulometria apresentaram dependência espacial variando de 1,35 m a 4,53 m; os valores de atributos químicos do solo nos períodos I e II apresentaram dependência espacial variando de 0,93 m a 10,52 m; os valores de atributos de produtividade de alface apresentaram alcance de dependência espacial de 0,41 m a 0,72 m; a krigagem mostrou-se um bom interpolador para a estimação de valores não amostrados; dos dados obtidos, apenas MF x MFC, MF x DCC e MFC x DCC apresentaram correlação; o mapa da aplicação de água 2 apresentou duas zonas distintas para o manejo da irrigação; a variabilidade espacial encontrada para a umidade influenciou no desenho do sistema de irrigação; considerando-se a necessidade da cultura em nutrientes, não foi... (Resumo completo, clicar acesso eletrônico abaixo). / Abstract: The objective of this work was to study the variability of some physical and chemical soil attributes and lettuce yield attributes (mass of total shoot fresh matter - MF; mass of commercial shoot fresh matter - MFC; mass of commercial shoot dry matter - MSC and commercial diameter of the head - DCC); offering subsidies to the mapping of the greenhouse in different areas of water and nutrients management, longing for a larger yield lettuce and the precision irrigation, with the optimization of the use of the water and nutrients. The experiment was carried out in a greenhouse with lettuce irrigated by drip irrigation and sampling grid with 152 points, at São Manuel Experimental Farm, Agronomic Sciences College, São Paulo State University, Campus of Botucatu, in São Manuel city, São Paulo State, Brazil. All of the studied attributes presented strong spatial dependence; except for the DCC attribute that presented moderate dependence and the MSC attribute that didn't present spatial dependence; the soil moisture values up to 1.15 m presented spatial dependence and granulometric values presented spatial dependence varying from 1.35 m to 4.53 m; the soil chemical attributes values in the I and II periods presented spatial dependence varying from 0.93 m to 10.52 m; the lettuce yield attributes values presented the range of spatial dependence of 0.41 m to 0.72 m; the krigagem was shown a good interpolador for the estimate of no sampling values; of the obtained data, just MF x MFC, MF x DCC and MFC x DCC presented correlation; the water application map presented two different areas for the irrigation management; the spatial variability found for soil moisture influenced the irrigation system 4 drawing; considering the crop necessity in nutrients, it wasn't possible to establish two different areas from application of the elements P (phosphorus) and K (potassium) for the plantation fertilization... (Complete abstract. click electronic address below). / Doutor

Made available in DSpace on 2017-07-10T19:24:35Z (GMT). No. of bitstreams: 1 Samara Rodrigues[1].pdf: 1486003 bytes, checksum: 31d0e0cb1c9c341ca0e307d3684010b1 (MD5) Previous issue date: 2009-07-08 / Weeds can negatively affect the quantity and quality on orchards fruit yield. They usually occur in clusters in a given area, not evenly distributed throughout the entire field. Thus, the site-specific application of herbicides makes possible the use of control methods, decreasing the entire cost. In this work, both spatial and temporal variability of broad-leafed and narrow-leafed weeds were evaluated in an orchard of pear trees, using tools of precision agriculture. The experimental area has 1.24 ha, cultivated with 146 pear trees (variety ―Pêra D água‖), located in Nova Laranjeiras, Paraná State, Brazil. The orchard s productivity was through two distinct harvests, given the different reaping point of its fruits. Eighteen pear trees were selected as reference for the four samplings of broad-leafed and narrow-leafed weeds populations, performed per tree, using a 0.5 m x 0.5 m (0.25 m2) wooden frame. Data collected were then used to elaborate maps of mean incidence from both types of weeds. The methodology used was efficient to quantify both types of weeds, since it allows to build maps of the spatial and temporal incidence of both types of plants (broad and narrow). Pear yield showed little correlation with weed incidence. The weeds showed spatial and temporal dependence and such dependence was different due to the leaf type (broad or narrow) and of the position (under the tree canopy or between lines). The western region showed the highest incidence of weeds in the experimental area. / As plantas daninhas podem afetar negativamente a quantidade e a qualidade da produção de frutíferas. Normalmente ocorrem em agrupamentos em uma determinada área, não se distribuindo regularmente. Assim, a definição de unidades de manejo para controle de plantas daninhas viabiliza a aplicação de métodos de controle, diminuindo os custos. O objetivo deste trabalho foi avaliar a variabilidade espacial e temporal das plantas daninhas de folhas largas e estreitas, em um pomar de pereiras, visando definir unidades de manejo. A área experimental tem 1,24 ha, cultivada com 146 pereiras da variedade ―Pêra D'água‖, fica no município de Nova Laranjeiras, Paraná, Brasil. A produtividade do pomar foi obtida em duas colheitas distintas em função da maturação diferenciada dos frutos. Foram selecionadas dezoito árvores de pêra como referência para os quatro períodos de amostragens da população de plantas daninhas de folhas largas e estreitas, utilizando-se um quadro de madeira de 0,5 m x 0,5 m (0,25 m2). Os dados levantados foram usados então para elaborar mapas de incidência de ambos os tipos de plantas daninhas. A metodologia adotada para quantificação das plantas daninhas foi considerada eficiente, pois permitiu que se construísse mapas da incidência espacial e temporal de ambos os tipos de plantas (largas e estreitas). A produtividade de pêra apresentou fraca correlação linear com a incidência de plantas daninhas. As plantas daninhas apresentaram dependência espacial e temporal e esta dependência foi diferente em função do tipo de folha (larga ou estreita) e da posição (copa - linha de plantio ou nas entre-linhas). A região oeste apresentou a maior incidência de plantas daninhas na área experimental.

Made available in DSpace on 2017-05-12T14:47:10Z (GMT). No. of bitstreams: 1 Ademir Natal Correa.pdf: 1505539 bytes, checksum: fd8e294f5766bf4043789d75eba28f1f (MD5) Previous issue date: 2007-07-16 / The objective of this study was to assess the relationship among soil physical attributes and their influences on wheat yield. For this purpose an estimating method, called State-Space Model or dynamic linear regression model, was used and compared to simple and multiple regression models of classical statistics. Experimental data were obtained at a Rhodic Ferralsol, originated from UNIOESTE Agricultural Engineering Experimental Nucleus Cascavel Campus, in an area where wheat was grown. In this area, 3 equally spaced transects, with 97 sampling points, 3.0 meters away from each other, were delimited. The State-Space approach was used to assess wheat yield estimate on position i, influenced by wheat yield, bulk density, soil compaction degree and soil resistance to penetration on position i-1 in different combination between data series of these variables. Applying the State-Space approach, all the response variables presented significant correlation with the dependent variable: soil resistance to penetration was the attribute with the best correlation, presenting R2 coefficient equal to 0.849. The other attributes had R2 coefficient of around 0.800. Comparing to conventional static models, soil resistance to penetration attribute had R2 coefficient equal to 0.102. The other attributes had R2 coefficient equal or less than 0.087, in conventional regression. Utilizing the State-Space approach, the two combinations that indicated the best results were: 1) between wheat yield and soil resistance to penetration that showed the best estimate to wheat yield with R2 coefficient equal to 0.849, while the same combination in conventional regression presented R2 equal to 0.102; 2) between wheat yield, soil compaction degree and soil resistance to penetration, with R2 coefficient equal to 0.836, while the same combination in classical regression presented R2 equal to 0.217. Thus, it is possible to show the advantage of the State-Space approach in relation to other more conventional regression methods for estimating and forecasting in soil-plant system relationship. / Este trabalho foi realizado com o objetivo de estudar o relacionamento entre os atributos físicos do solo e a influência destes na produtividade de trigo. Para isso, utilizou-se o método de estimação chamado de Modelo de Espaço de Estados ou modelo de regressão linear dinâmico, comparando-o aos modelos de regressão simples e múltipla da estatística clássica. Os dados experimentais foram obtidos em um Latossolo Vermelho-Escuro pertencente ao Núcleo Experimental de Engenharia Agrícola da Universidade Estadual do Oeste do Paraná Campus de Cascavel, em uma área cultivada com trigo. Foram demarcadas 3 transeções com 97 pontos de amostragem espaçados de 3 m entre si. A abordagem de Espaço de Estados foi usada para avaliar a estimativa da produtividade do trigo na posição i, influenciada por medidas da produtividade do trigo, da densidade do solo, do grau de compactação do solo e da resistência do solo à penetração na posição i-1, em diferentes combinações entre as séries de dados dessas variáveis. Com a aplicação da abordagem de Espaço de Estados, todas as variáveis explicativas utilizadas apresentaram correlação significativa com a variável dependente: a resistência do solo à penetração foi o atributo com a melhor correlação, apresentando o coeficiente de ajuste R2 igual a 0,849. Os demais atributos tiveram os coeficientes R2 em torno de 0,800. Comparando-se com os modelos estáticos convencionais, o atributo resistência do solo à penetração teve o coeficiente de ajuste R2 igual a 0,102 e os demais atributos tiveram os seus coeficientes R2 abaixo de 0,087, na regressão convencional. Utilizando a metodologia de Espaço de Estados, as duas combinações que indicaram os melhores resultados foram a combinação entre produtividade do trigo e resistência do solo à penetração, que apresentou a melhor estimativa para produtividade do trigo, com coeficiente R2 igual a 0,849. A mesma combinação na regressão convencional resultou em R2 igual a 0,102. A segunda melhor combinação ocorreu entre os atributos: produtividade do trigo, grau de compactação do solo e resistência do solo à penetração, com R2 igual a 0,836, sendo que a mesma combinação na regressão clássica teve o coeficiente R2 igual a 0,217. Com isso é possível mostrar-se a vantagem da abordagem de Espaço de Estados em relação a outros métodos de estimativa e previsão para o relacionamento no sistema solo-planta.

Made available in DSpace on 2017-05-12T14:47:58Z (GMT). No. of bitstreams: 1 Samara Rodrigues[1].pdf: 1486003 bytes, checksum: 31d0e0cb1c9c341ca0e307d3684010b1 (MD5) Previous issue date: 2009-07-08 / Weeds can negatively affect the quantity and quality on orchards fruit yield. They usually occur in clusters in a given area, not evenly distributed throughout the entire field. Thus, the site-specific application of herbicides makes possible the use of control methods, decreasing the entire cost. In this work, both spatial and temporal variability of broad-leafed and narrow-leafed weeds were evaluated in an orchard of pear trees, using tools of precision agriculture. The experimental area has 1.24 ha, cultivated with 146 pear trees (variety ―Pêra D água‖), located in Nova Laranjeiras, Paraná State, Brazil. The orchard s productivity was through two distinct harvests, given the different reaping point of its fruits. Eighteen pear trees were selected as reference for the four samplings of broad-leafed and narrow-leafed weeds populations, performed per tree, using a 0.5 m x 0.5 m (0.25 m2) wooden frame. Data collected were then used to elaborate maps of mean incidence from both types of weeds. The methodology used was efficient to quantify both types of weeds, since it allows to build maps of the spatial and temporal incidence of both types of plants (broad and narrow). Pear yield showed little correlation with weed incidence. The weeds showed spatial and temporal dependence and such dependence was different due to the leaf type (broad or narrow) and of the position (under the tree canopy or between lines). The western region showed the highest incidence of weeds in the experimental area. / As plantas daninhas podem afetar negativamente a quantidade e a qualidade da produção de frutíferas. Normalmente ocorrem em agrupamentos em uma determinada área, não se distribuindo regularmente. Assim, a definição de unidades de manejo para controle de plantas daninhas viabiliza a aplicação de métodos de controle, diminuindo os custos. O objetivo deste trabalho foi avaliar a variabilidade espacial e temporal das plantas daninhas de folhas largas e estreitas, em um pomar de pereiras, visando definir unidades de manejo. A área experimental tem 1,24 ha, cultivada com 146 pereiras da variedade ―Pêra D'água‖, fica no município de Nova Laranjeiras, Paraná, Brasil. A produtividade do pomar foi obtida em duas colheitas distintas em função da maturação diferenciada dos frutos. Foram selecionadas dezoito árvores de pêra como referência para os quatro períodos de amostragens da população de plantas daninhas de folhas largas e estreitas, utilizando-se um quadro de madeira de 0,5 m x 0,5 m (0,25 m2). Os dados levantados foram usados então para elaborar mapas de incidência de ambos os tipos de plantas daninhas. A metodologia adotada para quantificação das plantas daninhas foi considerada eficiente, pois permitiu que se construísse mapas da incidência espacial e temporal de ambos os tipos de plantas (largas e estreitas). A produtividade de pêra apresentou fraca correlação linear com a incidência de plantas daninhas. As plantas daninhas apresentaram dependência espacial e temporal e esta dependência foi diferente em função do tipo de folha (larga ou estreita) e da posição (copa - linha de plantio ou nas entre-linhas). A região oeste apresentou a maior incidência de plantas daninhas na área experimental.

This thesis consists of three papers on econometric modeling of spatial dependence. The awareness of interactions between actors is fundamental for understanding property markets as well as the growth of regions. In both cases, neighbors and neighboring markets may stimulate or hamper growth of values. From a modeling point of view, these interdependencies calls for spatial econometric models. In the thesis we introduce such methods in the analysis of regional property markets as well as in a comparative regional growth analysis. In the first paper, we estimate hedonic prices in the market for co-operative flats in the city of Umeå, Sweden, during 1998 and 1999. Structural, neighborhood, and accessibility characteristics are used as attributes in the hedonic price function. Important attributes were the rent, floor space, age, and population density. Two attractive nodes, although with different characteristics, were found. Thus there are signs supporting the view that Umeå has developed into a multi-nodal structure for property values. SAR-GM estimation was used due to signs of spatial error dependence. In the second paper, hedonic prices for single-family homes in two Swedish counties are estimated for two years. Parameter estimates are compared and changes in space and time analyzed. Spatial lag dependence is found to influence the results. Hence, four independent variables are lagged with a spatial weights matrix. Additional spatial error dependence is treated by SAR-GM estimation. Structural, neighborhood, and accessibility characteristics are used as attributes. The regional price pattern and its changes over time, is illustrated and identified with GIS maps. Proximity to the two county capitals, as well as the other municipality centers, influence property prices positively. This is also noticable over time, where values have risen for homes located near major population centers and those which have water provided by the municipality. Values are in addition largely a function of the quality of each home. The third paper examines the provincial pattern of growth in China during the period 1985-2000, testing the hypothesis that provinces with similar growth rates are more spatially clustered than would be expected by chance. The provincial economic growth is explained by the distribution of industrial enterprises, foreign direct investment, infrastructure, and governmental preferential policies. The neoclassical hypothesis of convergence is also tested. Indications of unconditional convergence does occur during the periods 1985-2000 and 1985-1990. In addition, conditional convergence is found during the sub-period 1990-1995. Evidence of spatial dependence between adjacent provinces has also been established, and in the econometric part, solved by a spatial lag, or alternatively a spatial error term, in the growth equation.

Submitted by Milena Rubi (milenarubi@ufscar.br) on 2017-08-08T16:42:10Z No. of bitstreams: 1 VALENTIM_Larissa_2016.pdf: 20751032 bytes, checksum: 336fa4890bc316b64ca91fd78a58df8b (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2017-08-08T16:42:18Z (GMT) No. of bitstreams: 1 VALENTIM_Larissa_2016.pdf: 20751032 bytes, checksum: 336fa4890bc316b64ca91fd78a58df8b (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2017-08-08T16:42:24Z (GMT) No. of bitstreams: 1 VALENTIM_Larissa_2016.pdf: 20751032 bytes, checksum: 336fa4890bc316b64ca91fd78a58df8b (MD5) / Made available in DSpace on 2017-08-08T16:42:30Z (GMT). No. of bitstreams: 1 VALENTIM_Larissa_2016.pdf: 20751032 bytes, checksum: 336fa4890bc316b64ca91fd78a58df8b (MD5) Previous issue date: 2016-05-24 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / The execution of this work aimed at the use of geostatistics to predict the spatial pattern of variation of moisture content in piles of eucalyptus wood chips intended for energy production to generate subsidies to adequate sampling and handling of the material. For this, piles wood chips were installed for evaluation in three different storage periods, these rings being made by the newly cut material in seven, thirty and sixty days of storage. Sampling occurred in both axial positions (top, middle and base) side, so that all samples were georeferenced in relation to the distance from the ground and the center of the pile. The moisture content of the wood chips in each sample point was determined by gravimetric method recommended by NBR 14929 (ABNT, 2003). In addition, samples were subjected to analysis bulk density, particle size distribution, chemical analysis and determination of its calorific value, aiming at energy material characterization. The humidity values were submitted to geostatistical analysis and kriging. Our results confirmed the spatial dependence of the moisture content over the piles stored at seven and thirty days, confirming that the use of geostatistics is a useful tool to support the creation of sampling protocols and assist moisture content distribution studies over the pile. The effect of rain was crucial to reduce the spatial dependence on pile sixty days of storage, indicating that the wood chips stored in the form of piles are subject to wetting even in inner parts of the pile. In general, Eucalyptus grandis wood chips showed satisfactory technological characteristics for energy production. / A execução deste trabalho teve como objetivo o uso da geoestatística para a predição do padrão espacial da variação do teor de umidade em pilhas de cavacos de madeira de eucalipto destinadas a produção de energia, visando gerar subsídios à adequada amostragem e manejo do material. Para isso, foram instaladas pilhas de cavacos para a avaliação em três diferentes períodos de estocagem, sendo estes ciclos constituídos pelo material recém cortado em sete, trinta e sessenta dias de armazenamento. A amostragem ocorreu nas posições axial (topo, meio e base) e lateral, de forma que todas as amostras foram georreferenciadas em relação à distância do solo e do centro da pilha. A umidade dos cavacos em cada ponto amostral foi determinada pelo método gravimétrico preconizado pela norma NBR 14929 (ABNT, 2003). Adicionalmente, as amostras, foram submetidas a análise de densidade a granel, distribuição granulométrica, análise química imediata e a determinação de seu poder calorífico, visando a caracterização energética do material. Os valores de umidade foram submetidos à análise geoestatística e interpolação por krigagem. Os resultados do trabalho comprovaram a dependência espacial do teor de umidade ao longo das pilhas armazenadas pelo período de sete e trinta dias, confirmando que o uso da geoestatística é uma ferramenta útil para a subsidiar a criação de protocolos de amostragem e auxiliar estudos da distribuição do teor de umidade ao longo da pilha armazenada. O efeito da chuva foi determinante para a redução da dependência espacial na pilha com sessenta dias de estocagem, indicando que os cavacos armazenados na forma de pilhas estão sujeitos ao umedecimento mesmo nas partes mais internas da estrutura. Em geral, os cavacos de Eucalyptus grandis apresentaram características tecnológicas satisfatórias para produção de energia

Les extrêmes neigeux sont parmi les risques naturels les plus dangereux dans les régions montagneuses. Les processus max-stables, qui relient statistique des valeurs extrêmes et géostatistique, offrent un cadre approprié pour les étudier. Deux questions importantes concernant la dépendance spatiale des extrêmes sont traitées dans cette thèse à travers les cas des chutes et des hauteurs de neige dans les Alpes françaises : la sélection de modèle et la non-stationnarité temporelle. Nous utilisons pour cela deux jeux de données de maxima hivernaux de chutes de neige (90 stations de 1958 à 2013) et de hauteurs de neige (82 stations de 1970 à 2013). Nous décrivons d'abord une procédure de validation-croisée appropriée pour évaluer les capacités des processus max-stables à capturer la structure de dépendance des extrêmes spatiaux. Nous mettons en exergue trois processus max-stables pour leur aptitude à modéliser la dépendance spatiale des chutes de neige extrêmes : les processus de Brown-Resnick, géométrique gaussien et extrémal-t. Les performances de ces trois modèles sont extrêmement similaires, quel que soit le nombre de stations ou d'années. Ensuite, nous présentons une approche par fenêtre glissante pour évaluer l'évolution temporelle de la dépendance des extrêmes spatiaux. Nous montrons ainsi que les chutes de neige extrêmes ont tendance à être de moins en moins dépendantes spatialement. Nous montrons que cela est dû à une augmentation de la température provoquant une baisse du ratio neige/pluie. Il existe aussi un effet d'intensité avec des extrêmes moins dépendants à cause d'une baisse du cumul hivernal de chutes de neige. Enfin, nous présentons la première utilisation de processus max-stables avec des tendances temporelles dans la structure de dépendance spatiale. Cette approche est appliquée aux maxima de hauteurs de neige modélisés par un processus de Brown-Resnick. Nous montrons que leur dépendance spatiale est impactée par le changement climatique d'une manière similaire que celle des chutes de neige extrêmes. / Extreme snowfall and extreme snow depths are among the most dangerous hazards in the mountainous regions. Max-stable processes, which connect extreme value statistics and geostatistics by modeling the spatial dependence of extremes, offer a suitable framework to deal with. Two challenging issues concerning spatial dependence of extremes are broached in this thesis through the examples of snowfall and snow depths in the French Alps: model selection and temporal nonstationarity. We process two winter maxima data sets of 3-day snowfall (90 stations from 1958 to 2013) and snow depths (82 stations from 1970 to 2013). First, we introduce a leave-two-out cross-validation procedure appropriate for evaluating the predictive ability of max-stable processes to model the dependence structure of spatial extremes. We compare five of the most commonly used max-stable processes, using as a case study the snowfall maxima data set. This approach allows us to show that the extremal-t, geometric Gaussian and Brown-Resnick processes are able to represent as well the structure of dependence of the data, regardless of the number of stations or years. Then, we show, using a data-based approach allowing to make minimal modeling assumptions, that snowfall extremes tended to become less spatially dependent over time, with the dependence range reduced roughly by half during the study period. We demonstrate that this is attributable at first to the increase in temperature and its major control on the snow/rain partitioning. A magnitude effect, with less dependent extremes due to a decrease in winter cumulated snowfall, also exists. Finally, we tackle the first-ever use of max-stable processes with temporal trends in the spatial dependence structure. This approach is applied to snow depth winter maxima modeled by a Brown-Resnick process. We show that the spatial dependence of extreme snow depths is impacted by climate change in a similar way to that has been observed for extreme snowfall.

Viticulture in Rio Grande do Sul state occupies a prominent position in the national scenario, the sector accounts for about 60.2 % of the total cultivated area in the country. Vine cultivation has very important economic and social, as well as a production chain organized in the different producing regions. The aim of this study was to quantify the spatial variability of the chemical attributes of the grape must, chemical soil properties, vegetation indices and verify possible correlations between variables. The study area consisted of a vineyard with 3.09 ha of farming Bordô (Ives) grafted onto the rootstock Paulsen, located in the trough line, in the municipality of Sarandi - RS. In a mesh composed of 34 sampling points soil samples were collected in a depth range from 0 to 20 cm. Analyses were performed in the laboratory of soil analysis at the Federal University of Santa Maria (UFSM), the chemical attributes analyzed were: clay; pH in H2O; SMP, P; K; organic matter; al; Here; mg; H + Al; CTC effective; CTC pH7; Base saturation; relationship between Ca and Mg; Zn; Cu; S and B. The analysis of grape must was held in the chemistry laboratory of the Federal Institute Farroupilha campus Panambi studied enological parameters were: total soluble solids; titratable acidity and pH in organic acid. The determination of vegetation indices was carried out in situ in the 34 sampling points with use of spectroradiometer. The data were submitted to descriptive statistical analysis and Geostatistics, using the computer program for such Geoestatistics for the Environmental Sciences (GS +), Pearson correlation coefficients were determined with the aid of Excel. Analysis of the spatial variability of the data was based on the experimental semivariogram and from adjusted models interpolation was performed by ordinary Kriging, Stochastic Simulation and map algebra. Only the figures for the amount of total soluble solids showed low values other chemical attributes must show proper values. The results of soil analysis identified low concentrations of B and organic matter and high for the other attributes. From the overall analysis of the statistical dependence between variables, there was no significant correlations between the chemical properties of grape must and the other variables, unlike the segmented analysis according to the different harvest dates. The spatial dependence index of most chemical properties of soil studied was considered strong, only the attributes, Cu, Effective CTC CTC in pH7 and Clay did not present spatial dependence structure. Vegetation indices, except TVI2 showed strong spatial dependency ratio. Chemical attributes of the grape must, the concentration of soluble solids did not present spatial dependence structure, while others showed strong spatial dependence. In the result of map algebra the middle class of titratable acidity in organic acid added to middle class NDVI was representing the highest. / A viticultura no estado do Rio Grande do Sul ocupa uma posição de destaque no cenário nacional, o setor responde por aproximadamente 60,2% do total da área cultivada no país. O cultivo da videira tem grande importância econômica e social, além de uma cadeia produtiva organizada nas diversas regiões produtoras. O objetivo desse estudo foi realizar a quantificação da variabilidade espacial dos atributos químicos do mosto da uva, dos atributos químicos do solo, dos índices de vegetação e verificar as possíveis correlações entre as variáveis estudadas. A área de estudo foi composta por um vinhedo com 3,09 ha da cultivar Bordô (Ives) enxertada sobre o porta enxerto Paulsen, situado na linha Cocho, no município de Sarandi - RS. Em uma malha constituída por 34 pontos amostrais foram coletadas amostras de solo numa faixa de profundidade de 0 a 20 cm. As análises foram realizadas no laboratório de análises de solo da Universidade Federal de Santa Maria (UFSM), os atributos químicos analisados foram: argila; pH em H2O; Índice SMP; P; K; matéria orgânica; Al; Ca; Mg; H+Al; CTC efetiva; CTC em pH7; Saturação por bases; relação entre Ca e Mg; Zn; Cu; S e B. A análise do mosto da uva foi realizado no laboratório de química do Instituto Federal Farroupilha campus Panambi, os parâmetros enológicos estudados foram: sólidos solúveis totais; acidez total titulável em ácido orgânico e pH. A determinação dos índices de vegetação foi realizada in situ nos 34 pontos amostrais com uso de espectrorradiômetro. Os dados foram submetidos à análise estatística descritiva e Geostatística, utilizando-se para tal o programa computacional Geoestatistics for the Environmental Sciences (GS+), os coeficientes de correlação de Pearson foram determinados com auxílio do programa Excel. A análise da variabilidade espacial dos dados foi realizada com base nos semivariogramas experimentais e a partir dos modelos ajustados foi realizada interpolação por Krigagem ordinária, Simulação Estocástica e álgebra de mapas. Apenas os valores referentes a quantidade de sólidos solúveis totais apresentaram valores baixos os demais atributos químicos do mosto apresentaram valores adequados. Os resultados das análises de solo identificaram baixas concentrações para B e matéria orgânica e altas para os demais atributos. A partir da análise global da dependência estatística entre as variáveis estudadas, observou-se não haver correlações significativas entre os atributos químicos do mosto da uva e as demais variáveis, diferentemente da análise segmentada de acordo com as diferentes datas de colheita. O índice de dependência espacial da maioria dos atributos químicos de solo estudados foi considerado forte, apenas os atributos, Cu, CTC Efetiva, CTC em pH7 e Argila não apresentaram estrutura de dependência espacial. Os índices de vegetação, com exceção do TVI2, apresentaram índice de dependência espacial forte. Dos atributos químicos do mosto da uva, a concentração de sólidos solúveis totais não apresentou estrutura de dependência espacial, enquanto os demais apresentaram forte dependência espacial. No resultado da álgebra de mapas a classe média da acidez titulável em ácido orgânico, somada a classe média do NDVI foi a que representou o maior percentual da área.