Thesis (Ph. D.)--Virginia Commonwealth University, 2009. / Prepared for: Dept. of Biostatistics. Title from title-page of electronic thesis. Includes bibliographical references (p. 126-131).

Thesis (Ph. D.)--University of Washington, 1996. / Vita. Includes bibliographical references (leaves [106]-114).

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Social demands on soil information have grown dramatically, meanwhile the soil surveys are seldom carried out in the country. Digital soil mapping techniques can be applied to infer the spatial distribution of soil from existing soil maps or from reference areas, extrapolating this information to areas not mapped. The purpose of this study was to apply in a Geographic Information System the Multiple Logistic Regressions (MLR) using Principal Components (PC) as explanatory variables to predict soil classes spatial distribution. The study area was the region of municipality São Pedro do Sul / RS. For the development of predictive models a set of nine terrain attributes were used. Model training was executed on an existing soil map and with a survey carried out in a reference area, both in a 1:50.000 scale. The first three retained PC explained 65.57% of the data variability. The predictive models which used PC had lower values of kappa index. The most accurate predicted map reached a kappa value of 63.20% and was generated by using the nine attributes of land as predictive covariates. The mapping accuracy is sensitive to similarities between the mapped classes, and mapping in a more homogeneous categorical level reduces the accuracy of the predicted maps. Soil classes relatively not representative in the training maps are not properly spatialized. The use of MLR allows spatializing of soil classes to areas not mapped, although the use of PC needs to be tested with a larger number of covariates. / As demandas da sociedade pela informação solo têm crescido, porém levantamentos pedológicos praticamente não ocorrem mais no país. Técnicas de Mapeamento Digital do Solo podem ser empregadas para inferir a distribuição espacial de classes de solos a partir de mapas existentes e áreas de referência, extrapolando esta informação para áreas não mapeadas. O objetivo deste estudo foi empregar em um Sistema de Informações Geográficas as Regressões Logísticas Múltiplas (RLM) utilizando-se de Componentes Principais (CP) como variáveis explicativas para a predição espacial de classes de solos. A área de estudo foi na região do município de São Pedro do Sul / RS. Para o desenvolvimento dos modelos preditivos foram utilizados um conjunto de nove atributos do terreno. O treinamento dos modelos foi executado em um mapa de solos existente, e em um levantamento realizado em áreas de referência, ambos na escala 1:50.000. As três primeiras CP retidas explicaram 65,57% da variabilidade dos dados. Os modelos preditivos que empregaram CP obtiveram menores valores do índice kappa. O mapa predito mais acurado empregou os nove atributos do terreno e alcançou um valor de kappa de 63,20%. A acurácia do mapeamento é sensível a semelhança entre as classes mapeadas, e o mapeamento em níveis categóricos mais homogêneos reduz a precisão dos mapas preditos. Classes de solos relativamente pouco representativas não são corretamente espacializadas. O emprego de RLM permite espacializar classes de solos para áreas não mapeadas, embora o emprego de CP necessite ser testado com um maior número de covariáveis.

L’espace provençal du 3ème millénaire av. n. è. laisse entrevoir un certain nombre d’éléments qui mettent en scène la complexité archéologique de la transition Néolithique final / Âge du Bronze ancien. En Provence, si le travail de J. Cauliez a ouvert la voie à un cadre chrono-culturel plus robuste et tissé une trame plus diversifiée des composantes céramiques de la fin du Néolithique, il n’en demeure pas moins que l’imbrication de l’évènement Campaniforme avec les différentes traditions locales se pose toujours comme un problème majeur, notamment en termes stratigraphiques, dans la compréhension des gisements domestiques de cette période. L’analyse des différents types de vestiges archéologiques liés à ces contextes requiert à notre sens une étude complémentaire fondée sur les logiques d’implantation des sites d’habitat dans le paysage afin de mieux saisir l’ensemble des mécanismes socio-culturels émergeants à l’aube de l’Âge du Bronze. Grâce à la mise en place d’une base de données relationnelle couplée à un Système d’Information Géographique, il a été possible de générer de nouvelles informations spatiales sur les sites géo-référencés de notre corpus. Ainsi, après des analyses statistiques multivariées exploratoires sur les données archéologiques issues de la littérature et les nouvelles données spatiales, il a été possible de caractériser finement les implantations de chacun des gisements étudiés à l’échelle de la Provence (426 sites) puis à l’échelle du Luberon (analyse territoriale basée sur 70 sites) et de dégager des tendances principales dans les choix d’installation de ces populations au cours du 3ème millénaire av. n. è. / The archaeological complexity of the transition between Late Neolithic and Early Bronze Age can be characterized by a certain amount of elements found in the Provence area in the 3rd millennium BCE. Despite the fact that the work done by J. Cauliez in Provence provided a more structured chrono-cultural framework and a more diversified background concerning ceramic components in the Late Neolithic, the Bell Beaker event overlapping the various local traditions still appears as a crucial issue. It specifically relates to the understanding of domestic deposits in this period in terms of stratigraphic studies. Following the analysis of these different types of archaeological remains in these dwellings, we believed that an in-depth study on settlement patterns in the landscape must be carried out to better comprehend the emerging social and cultural mechanisms at the dawn of Bronze Age. Due to the set up of a relational database integrated with a Geographic Information System (GIS), new spatial items were generated on the georeferenced sites listed in our corpus. Finally, after the use of statistical multivariate and exploratory analysis based on archaeological data from bibliographic references and on new spatial data, a precise implantation’s characterization of each investigated deposits has been possible, first in Provence (426 establishments), then in Luberon (territorial analysis involving 70 sites) as well as an identification of significant trends regarding dwelling choices by the populations living in the 3rd millennium BCE.