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Accounting for space in intrametropolitan household location choicesOzturk, Erdogan 07 August 2003 (has links)
No description available.
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Diameter Distributions of Juvenile Stands of Loblolly Pine (Pinus taeda L.) with Different Planting DensitiesBullock, Bronson P. 13 March 2002 (has links)
Diameter distributions of juvenile loblolly pine (Pinus taeda L.) with different planting densities were characterized utilizing a two-parameter Weibull distribution. Trend analysis was employed to describe the effects of planting density, age, relative spacing, and rectangularity on the estimated diameter distributions for juvenile loblolly pine. A reparameterization of the two-parameter Weibull distribution was sought to reduce the dispersion of the estimated shape parameter.
Methods that quantify the amount of inter-tree spatial dependency in a particular stand were applied. Empirical semivariograms were derived for each plot over all ages to enable spatial trend recognition. Moran's I and Geary's C coefficients were estimated for ground-line diameters from ages 2 to 5, and for breast height diameters from ages 5 to 11. Though there was no discernable trend in the presence of significant spatial autocorrelation with planting density, an initial negative trend with age was present, but leveled off by age 5. A conditional autoregressive model was utilized to evaluate the amount of spatial influence stems in a stand have on one another. The occurrence of significant spatial influences was positively associated with age through age 8, the trend then leveled off; no recognizable trend was detected with planting density.
These indices help to describe stand dynamics that are influenced by the spatial distribution of stems. Models to predict the parameters of the two-parameter Weibull distribution were developed to aid in forecasting and simulation of juvenile loblolly pine. Simulations were conducted where a spatial dependency was imposed on the diameters within a stand. The spatial structure simulation enables accurate representations of stem characteristics when simulating forest stands that include spatially-explicit information. / Ph. D.
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Anisotropia da variabilidade espacial da emissão de co2 do solo sob cultivo de cana-de-açúcar e eucalipto /Veras, Ludhanna Marinho January 2019 (has links)
Orientador: Alan Rodrigo Panosso / Resumo: O dióxido de carbono (CO2) é um dos principais gases do efeito estufa adicional, sendo a agricultura uma grande contribuinte para a emissão do mesmo no Brasil. Para melhor modelar a perda de carbono do solo via CO2, deve-se considerar a variação espacial dessa variável, bem como dos atributos do solo, atento ao uso do solo agrícola e manejo. O presente estudo objetivou caracterizar a anisotropia espacial de FCO2 e atributos físicos e químicos do solo por meio da dimensão fractal (DF), na região do Cerrado no Mato Grosso do Sul. Para o estudo da anisotropia e geração de mapas de padrões espaciais foi utilizado uma malha regular amostral constituída de 102 pontos nas duas áreas. Para a FCO2 foram observados valores de DF 2,51 ± 0,41 para cana-de-açúcar e 2,61 ± 0,18 para eucalipto. A DF de FCO2 e dos atributos do solo estudadas por meio do gráfico de rosas mostrou que o fluxo de CO2 do solo apresenta variação espacial associada a diferentes atributos químicos e físicos do solo. Foram observados ganhos de precisão quando comparados os mapas de padrões espaciais isotrópico e anisotrópico para as variáveis FCO2, matéria orgânica do solo (MO) e a densidade do solo (Ds) nas duas áreas, indicados pela validação cruzada, com os valores de coeficiente de determinação entre 0,82 e 0,99 para área de cana-de-açúcar e 0,94 e 0,98 para áreas de eucalipto. FCO2 é um fenômeno de natureza complexa, sendo sua anisotropia espacial associada às variações espaciais dos demais atributos do solo e s... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Carbon dioxide (CO2) is one of principal greenhouse gases, being the agriculture one of the contributor major to emission specially in Brazil. To better understands this phenomenon, it is necessary to consider the spatial variation of this variable, as well as the attributes of the soil, considering the type of agricultural land use and management. The present study objective of characterizing the spatial anisotropy of FCO2 and other soil physical and chemical attributes, through the fractal dimension (DF), in Cerrado region, Mato Grosso do Sul. For the study of anisotropy and maps generation of spatial patterns, a regular sample consisting of 102 points in both areas was used. To FCO2 anisotropy values of DF were observed for 2.51 ± 0.41 for sugarcane and 2.61 ± 0.18 for eucalyptus areas. DF of FCO2 and other soil attributes studied through the rose graphics showed that the FCO2 presents spatial variation associated with different soil chemical and physical attributes. Precision and accuracy gains were observed when comparing spatial patterns generated from isotropic and anisotropic modeling for FCO2, soil organic matter (MO) and soil density (Ds) in the two study areas, as indicated by cross-validation, with values of determination coefficient varying between 0.82 and 0.99 for sugarcane and 0.94 and 0.98 for eucalyptus areas. The spatial pattern indicated that the spatial variability of FCO2, soil organic matter (MO) and soil density (Ds) that obtained gains in the two stud... (Complete abstract click electronic access below) / Mestre
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Spatial Methods in Econometrics. An Application to R&D Spillovers.Gumprecht, Daniela January 2005 (has links) (PDF)
In this paper I will give a brief and general overview of the characteristics of spatial data, why it is useful to use such data and how to use the information included in spatial data. The first question to be answered is: how to detect spatial dependency and spatial autocorrelation in data? Such effects can for instance be found by calculating Moran's I, which is a measure for spatial autocorrelation. The Moran's I is also the basis for a test for spatial autocorrelation (Moran's test). Once we found some spatial structure we can use special models and estimation techniques. There are two famous spatial processes, the SAR- (spatial autoregressive) and the SMA- (spatial moving average process) process, which are used to model spatial effects. For estimation of spatial regression models there are mainly two different possibilities, the first one is called spatial filtering, where the spatial effect is filtered out and standard techniques are used, the second one is spatial two stage least square estimation. Finally there are some results of a spatial analysis of R&D spillovers data (for a panel dataset with 22 countries and 20 years) shown. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics
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Análise espacial e temporal de parâmetros de qualidade das águas do Aquífero Bauru de 2010 a 2012 / Spatial and tempotal analysis of water quality parameters in Bauru Aquifer System, 2010 to 2012Marques, Sâmia Momesso 30 July 2018 (has links)
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Previous issue date: 2018-07-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A água exerce influência direta no desenvolvimento de sociedades. Por sua vez, as águas subterrâneas apresentam um papel fundamental para o abastecimento humano por constituírem aproximadamente dois terços da fonte de água doce no mundo. A Companhia Ambiental do Estado de São Paulo (CETESB) controla e monitora atividades que possam ser fontes de poluição e avalia periodicamente os parâmetros de qualidade das águas. Sua rede conta com 75 pontos de monitoramento até 2012, dificultando um panorama amplo da qualidade das águas no Sistema Aquífero Bauru. O objetivo do trabalho foi estudar a variabilidade espacial e temporal dos parâmetros de qualidade das águas subterrâneas do SAB no Estado de São Paulo. Foram avaliados os parâmetros: Alcalinidade Bicarbonato, Bário, Cálcio, Condutividade Elétrica, Dureza, Magnésio, Nitrato, Potássio, pH, Sódio, Sólidos Totais Dissolvidos e Temperatura. Para tanto foi realizada a análise descritiva, de correlação e a análise geoestatística por meio do cálculo de variogramas experimentais para avaliação da dependência espacial e interpolações por krigagem ordinária. Os resultados indicaram que à exceção do pH e da Temperatura, todos os parâmetros possuíam elevada variabilidade dos dados, com Coeficientes de Variação (CV) elevados, em sua maior parte. As correlações significativas do ponto de vista prático de determinação laboratorial foram de Sólido Total Dissolvido com Cálcio (r = 0,770) e com Magnésio (r = 0,700), além da Dureza com Cálcio (r = 0,910). Do ponto de vista espacial, à exceção da Temperatura no primeiro semestre de 2012, os demais parâmetros apresentaram dependência espacial com apreciáveis ajustes variográficos e mapas de krigagens bem definidos. Os valores de pH estiveram dentro do permitido para consumo humano, à exceção de alguns dados pontuais. Em relação ao NO3-, algumas amostras superaram o Valor Máximo Permitido de 10 mg/L, indicando toxicidade para consumo humano. A influência da variação sazonal foi sutil, em períodos de cheia alguns parâmetros apresentam concentrações ligeiramente inferiores devido ao maior volume de água. As aproximações espaciais e temporais mostraram-se funcionais para extensas áreas e os parâmetros apresentam elevada correlação entre si. / Water is essential for the life maintenance. It influences directly the society development over the centuries. Currently, groundwater resources have a crucial role for supply. These resources constitute around two thirds of the global freshwater sources. The Sao Paulo Environmental Company (CETESB) is responsible for manage activities which can be source of contamination and periodically assess water parameters. However, the CETESB system had 75 monitoring points until 2012, hindering area overview. This study aims evaluate variability and temporal-spatial dependency of water parameters for groundwater quality in the Bauru Aquifer System (BAS), in the State of Sao Paulo, using geostatistical techniques. The parameters were: Bicarbonate Alkalinity, Barium, Hardness, Calcium, Magnesium, Nitrate, Potassium, pH, Sodium, Total Dissolved Solids and Temperature. It has been done at first descriptive analysis and then spatial dependency for which parameter by semivariogram analyzes. The results showed that the parameters have a high variability, except by pH and Temperature, the coefficient variation were very high for the parameters. The significant correlations were Total Dissolved Solids with Calcium (r = 0.770) and Magnesium (r = 0.700) on a laboratorial practice. Besides Hardness and Calcium with r = 0.910. All parameters showed spatial dependency with appreciable semivariographic adjustments and kriging maps defined. The pH values were allowed for human consumption, except by some punctual wells. The pH averages point to neutral waters. The NO3- had some samples values over the maximum permitted (10 mg/L), toxic water for consumption. Existing correlation between parameters and realizing spatial and temporal approaches to find values of not sampled points is possible. It works well even for large areas with non-uniform distribution of the sampling points as Bauru Aquifer System.
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Temporal and Spatial Models for Temperature Estimation Using Vehicle DataEriksson, Lisa January 2019 (has links)
Safe driving is a topic of multiple factors where the road surface condition is one. Knowledge about the road status can for instance indicate whether it is risk for low friction and thereby help increase the safety in traffic. The ambient temperature is an important factor when determining the road surface condition and is therefore in focus. This work evaluates different methods of data fusion to estimate the ambient temperature at road segments. Data from vehicles are used during the temperature estimation process while measurements from weather stations are used for evaluation. Both temporal and spatial dependencies are examined through different models to predict how the temperature will evolve over time. The proposed Kalman filters are able to both interpolate in road segments where many observations are available and to extrapolate to road segments with no or only a few observations. The results show that interpolation leads to an average error of 0.5 degrees during winter when the temperature varies around five degrees day to night. Furthermore, the average error increases to two degrees during springtime when the temperature instead varies about fifteen degrees per day. It is shown that the risk of large estimation error is high when there are no observations from vehicles. As a separate result, it has been noted that the weather stations have a bias compared to the measurements from the cars.
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Análise espacial e temporal de parâmetros de qualidade das águas do Aquífero Bauru de 2010 a 2012 /Marques, Sâmia Momesso. January 2018 (has links)
Orientador: César Gustavo da Rocha Lima / Resumo: A água exerce influência direta no desenvolvimento de sociedades. Por sua vez, as águas subterrâneas apresentam um papel fundamental para o abastecimento humano por constituírem aproximadamente dois terços da fonte de água doce no mundo. A Companhia Ambiental do Estado de São Paulo (CETESB) controla e monitora atividades que possam ser fontes de poluição e avalia periodicamente os parâmetros de qualidade das águas. Sua rede conta com 75 pontos de monitoramento até 2012, dificultando um panorama amplo da qualidade das águas no Sistema Aquífero Bauru. O objetivo do trabalho foi estudar a variabilidade espacial e temporal dos parâmetros de qualidade das águas subterrâneas do SAB no Estado de São Paulo. Foram avaliados os parâmetros: Alcalinidade Bicarbonato, Bário, Cálcio, Condutividade Elétrica, Dureza, Magnésio, Nitrato, Potássio, pH, Sódio, Sólidos Totais Dissolvidos e Temperatura. Para tanto foi realizada a análise descritiva, de correlação e a análise geoestatística por meio do cálculo de variogramas experimentais para avaliação da dependência espacial e interpolações por krigagem ordinária. Os resultados indicaram que à exceção do pH e da Temperatura, todos os parâmetros possuíam elevada variabilidade dos dados, com Coeficientes de Variação (CV) elevados, em sua maior parte. As correlações significativas do ponto de vista prático de determinação laboratorial foram de Sólido Total Dissolvido com Cálcio (r = 0,770) e com Magnésio (r = 0,700), além da Dureza com Cálcio (r = 0... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Water is essential for the life maintenance. It influences directly the society development over the centuries. Currently, groundwater resources have a crucial role for supply. These resources constitute around two thirds of the global freshwater sources. The Sao Paulo Environmental Company (CETESB) is responsible for manage activities which can be source of contamination and periodically assess water parameters. However, the CETESB system had 75 monitoring points until 2012, hindering area overview. This study aims evaluate variability and temporal-spatial dependency of water parameters for groundwater quality in the Bauru Aquifer System (BAS), in the State of Sao Paulo, using geostatistical techniques. The parameters were: Bicarbonate Alkalinity, Barium, Hardness, Calcium, Magnesium, Nitrate, Potassium, pH, Sodium, Total Dissolved Solids and Temperature. It has been done at first descriptive analysis and then spatial dependency for which parameter by semivariogram analyzes. The results showed that the parameters have a high variability, except by pH and Temperature, the coefficient variation were very high for the parameters. The significant correlations were Total Dissolved Solids with Calcium (r = 0.770) and Magnesium (r = 0.700) on a laboratorial practice. Besides Hardness and Calcium with r = 0.910. All parameters showed spatial dependency with appreciable semivariographic adjustments and kriging maps defined. The pH values were allowed for human consumption, except by ... (Complete abstract click electronic access below) / Mestre
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Accommodating flexible spatial and social dependency structures in discrete choice models of activity-based travel demand modelingSener, Ipek N. 09 November 2010 (has links)
Spatial and social dependence shape human activity-travel pattern decisions and their antecedent choices. Although the transportation literature has long recognized the importance of considering spatial and social dependencies in modeling individuals’ choice behavior, there has been less research on techniques to accommodate these dependencies in discrete choice models, mainly because of the modeling complexities introduced by such interdependencies. The main goal of this dissertation, therefore, is to propose new modeling approaches for accommodating flexible spatial and social dependency structures in discrete choice models within the broader context of activity-based travel demand modeling. The primary objectives of this dissertation research are three-fold. The first objective is to develop a discrete choice modeling methodology that explicitly incorporates spatial dependency (or correlation) across location choice alternatives (whether the choice alternatives are contiguous or non-contiguous). This is achieved by incorporating flexible spatial correlations and patterns using a closed-form Generalized Extreme Value (GEV) structure. The second objective is to propose new approaches to accommodate spatial dependency (or correlation) across observational units for different aspatial discrete choice models, including binary choice and ordered-response choice models. This is achieved by adopting different copula-based methodologies, which offer flexible dependency structures to test for different forms of dependencies. Further, simple and practical approaches are proposed, obviating the need for any kind of simulation machinery and methods for estimation. Finally, the third objective is to formulate an enhanced methodology to capture the social dependency (or correlation) across observational units. In particular, a clustered copula-based approach is formulated to recognize the potential dependence due to cluster effects (such as family-related effects) in an ordered-response context. The proposed approaches are empirically applied in the context of both spatial and aspatial choice situations, including residential location and activity participation choices. In particular, the results show that ignoring spatial and social dependencies, when present, can lead to inconsistent and inefficient parameter estimates that, in turn, can result in misinformed policy actions and recommendations. The approaches proposed in this research are simple, flexible and easy-to-implement, applicable to data sets of any size, do not require any simulation machinery, and do not impose any restrictive assumptions on the dependency structure. / text
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