Sociology at its core has always been interested in understanding how society works. Previous studies on social stratification have sought to outline who gets what, when, and why. This project introduces the where element to advance our understanding of how resource distribution affects life chances. The research question is: Does the percent of Latinos in the area of residence have an influence on Latino?s individual poverty over and above the influence on poverty of the person characteristics? The study ascertains how micro-level inequality is influenced by macro-level attributes and explores how spatial non-stationarity plays a role in these mechanics. This sociospatial inequality investigation will delineate how individual-level stratifying mechanisms are influenced by context-level structural attributes and how sociospatial non-stationary processes play a role in these mechanics. The dissertation is conceptually driven by Hubert M. Blalock's 1970 theory on minority relationships. Blalock posited the testable hypothesis that discrimination against oppressed groups increases when their population rises. Using theoretical propositions inspired by Blalock leads to the testing of the following two formal hypothesis: the multilevel hypothesis (H1) focuses on macro-level effects, I hypothesize that as the percent of Latinos/as in the area of residence increases, the odds of being in poverty will increase for Latinas/os; on the spatial hypothesis (H2), I hypothesize that the statistical association between percent Latina/o and percent poverty is spatially nonstationary. I find that H1 cannot be falsified. The models reveal, as Blalock predicted, that as the percent of Latinos/as in the area of residence increases, the odds of being in poverty increase for Latinas/os (even after controlling for various level-1, level-2, and GWR-level-2 factors). I also find that H2 could not be falsified. I find that the statistical association between percent Latina/o and percent poverty is spatially nonstationary. My multilevel and spatial modeling investigation was unable to falsify Blalock's minority group threat theory. Hierarchical models indicate that as the percent of Latino/a increases, the likelihood of being in poverty for Latinas/os increases. This statically significant relationship holds constant even after spatial nonstationarity level-2 control factors are introduced.

The topic of this thesis is to solve spatial heterogenity in forestry models by means of utilizing linear mixed-effects models (LMM) and geographically weighted regression (GWR) to model a height-diameter curve. Both of these methods were previously tested, and they have a high potential to reduce the minimal necessary amount of data needed, and at the same time, increase precision. The data come from VŠLP Křtiny, LÚ Borky, a complex of forests utilized for educational purposes by Mendel’s university in Brno. We choosed beech as the model species. We split the data into training and validation sets for fitting, and consequent prediction assessment. Resulting models were compared with OLS fitted global model. Local OLS models were unreliable, as only a very few measured trees were available for each plot. Results were different for GWR and LMM. GWR models failed at prediction, but had good results on training plots, especially considering the reduction of autocorrelation of model residuals. LMM provided the best results for both training and validation plots

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The purpose of this thesis is to analyse how bank branch closure has affected the formation of new firms and to explore the varying local relationships between the accessibility of bank branches and new firm formation in 290 Swedish municipalities. In the first paper, the effect of bank branch closure is examined through spatial econometric analysis, in particular, the fixed effects and the random effects spatial panel models. The findings of the first paper show that an increase in the weighted distance to the nearest bank branches due to bank branch closure negatively affects new firm formation, based on the random effects spatial panel model. The analysis also shows that spatial effects should be included in the analysis due to spill-over effects from neighbouring municipalities. In the second paper, the varying relationships between new firm formation and its determinants in 290 Swedish municipalities are examined through Geographically weighted regression (GWR). Mostly positive relationships with new firm formation are shown for firm density, human capital level, industry diversification level and percentage of immigrants living in the area. In contrast, mostly negative relationships are shown for weighted mean distance to the nearest bank branches, establishment size, unemployment rate, industry specialization. Spatially constrained multivariate clustering is also applied to group municipalities with similar conditions. Patterns in the industry composition and the location attributes are analysed for each cluster. / Syftet med denna avhandling är att analysera hur nedläggningen av bankkontorpåverkar frekvensen av nystartade företag och undersöker sambandet mellannystartsfrekvens och avståndet till närmaste bankkontor i Sveriges 290 kommuner.I avhandlingens första artikel studeras effekten av kontorsnedläggelse genom enrumslig ekonometrisk analys och rumsliga panel modeller. Resultaten visar att enökning av avståndet till närmaste bankkontor har en negativ påverkan pånyföretagandet. Vidare ger analysen vid handen att spatiala effekter bör inkluderasi analysen då det förekommer spill-over effekter från närliggande kommuner. Iavhandlingens andra artikel undersöks hur frekvensen av nystartade företag iSveriges 290 kommuner påverkas av ett antal olika faktorer, med hjälp av engeografiskt viktad regressionsmodell. Analysen visar att antalet befintliga företag,humankapital, näringslivets diversifiering, samt andelen invandrare, har ett positivtsamband med nystartsfrekvensen. Däremot finns det ett negativt samband mellannystartsfrekvens och avståndet till närmaste bankkontor, storleken bland debefintliga företagen, arbetslöshet och näringslivets specialisering. En multivariatklusteranalys har också genomförts där kommunerna fördelats över kluster medliknande egenskaper, där de ingående kommunerna har liknande förutsättningaroch strukturer. / <p>QC 20190923</p>

This dissertation is an empirical modeling investigation of the impact of forest harvesting, climate change and topography on stream nitrate fluxes in the Turkey Lakes Watershed (TLW), Ontario, Canada. Data used for this study include topography (DEM), climate (mean monthly temperature and total monthly precipitation), wet nitrogen deposition (total monthly nitrate-N and ammonium-N), nitrate water samples and streamflow in 13 headwater catchments within the TLW. First, a paired-watershed approach was used to examine the impact of forest harvesting intensity on stream water nitrate fluxes by developing transfer function noise (TFN) models that related monthly stream water nitrate fluxes of three treatment catchments to those of one control catchment. Second, TFN models were also developed to relate monthly stream nitrate fluxes in 13 catchments to the temperature, precipitation and wet nitrogen deposition to examine the spatially varying responses of stream nitrate fluxes to changes in climate and bulk deposition. Third, geographically weighted regression (GWR) was introduced to model the spatial and temporal relationships between topography and stream nitrate fluxes in 13 headwater catchments. The results showed that there existed a new phenomenon of clustered wave-up and wave-down of the stream nitrate increases caused by clearcut and selectioncut at the monthly scale, respectively. This phenomenon was never reported by previous studies because it was not possible to be identified with ordinary least squares (OLS) regression at an annual scale. There also existed significant responses of stream nitrate fluxes to wet nitrogen deposition in all catchments at the monthly scale over a long-term record between 1982 and 2003. These responses were previously thought to be lower and masked by the impact of climate variations. There further existed significant spatial and seasonal variability of the relationships between topography and stream nitrate fluxes across space and over time. This variability was largely ignored in previous studies with possibly misleading interpretation on the empirical relations. / Thesis (Ph.D, Geography) -- Queen's University, 2012-12-31 22:37:39.137

One of the key concerns in spatial analysis and modelling is to study and analyse similarities or dissimilarities between places over geographical space. However, ”global“ spatial models may fail to identify spatial variations of relationships (spatial heterogeneity) by assuming spatial stationarity of relationships. In many real-life situations spatial variation in relationships possibly exists and the assumption of global stationarity might be highly unrealistic leading to ignorance of a large amount of spatial information. In contrast, local spatial models emphasise differences or dissimilarity over space and focus on identifying spatial variations in relationships. These models allow the parameters of models to vary locally and can provide more useful information on the processes generating the data in different parts of the study area. In this study, a framework for localising spatial interaction models, based on geographically weighted (GW) techniques, has been developed. This framework can help in detecting, visualising and analysing spatial heterogeneity in spatial interaction systems. In order to apply the GW concept to spatial interaction models, we investigate several approaches differing mainly in the way calibration points (flows) are defined and spatial separation (distance) between flows is calculated. As a result, a series of localised geographically weighted spatial interaction (GWSI) models are developed. Using custom-built algorithms and computer code, we apply the GWSI models to a journey-to-work dataset in Switzerland for validation and comparison with the related global models. The results of the model calibrations are visualised using a series of conventional and flow maps along with some matrix visualisations. The comparison of the results indicates that in most cases local GWSI models exhibit an improvement over the global models both in providing more useful local information and also in model performance and goodness-of-fit.

Made available in DSpace on 2014-06-12T16:00:25Z (GMT). No. of bitstreams: 2 arquivo6557_1.pdf: 4867823 bytes, checksum: 64578a5cde42f460f0745045ec1bb555 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2007 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / Neste trabalho apresentamos um novo modelo neural para segmentação de imagens, baseado nos Mapas Auto-organizáveis SOM (Mapa Auto-organizável - Self-organizing Map) e GWR (Crescer Quando Requerido - Grow When Required) chamado de LARFSOM (Mapa Auto-organizável com Campo Receptivo Adaptativo Local - Local Adaptive Receptive Field Self-organizing Map). As características principais do modelo são: número adaptativo de nodos, topologia variável, inserção de novos nodos baseada em uma medida de similaridade dos protótipos existentes em relação ao padrão de entrada aferida por meio de campo receptivo, remoção de nodos com informações não significativas ao final do treinamento, rápida convergência e baixo custo de processamento para o treinamento. A rede LARFSOM é capaz de segmentar imagens por cor ou por borda: a primeira, é feita através do agrupamento de informações ocorrido no treinamento da rede LAFRSOM seguido de um processo de quantização de cores; já a segunda, ocorre pelo acréscimo de dois nodos RBF (Função de Base Radial - Radial Basis Function) à rede LARFSOM, criando um modelo de dois estágios chamado LARFSOM-RBF. Adicionalmente, o modelo é capaz de salvar em um formato variante do BMP indexado tanto a rede treinada como as informações espaciais dos pixels da imagem. Acrescido de compactação tipo ZIP o arquivo a ser salvo torna-se bem reduzido. Comparações com outros modelos neurais como o SOM, FS-SOM (Mapa Auto-organizável Sensível à Freqüência - Frequency Sensitive Self-organizing Map) e GNG (Gás Neural Crescente - Growing Neural Gas) são feitas mediante segmentação de imagens do mundo real com diferentes níveis de complexidade. Técnicas de processamento de imagens e o formato JPEG são usados para fins de comparação. Os resultados mostram que a rede LARFSOM atinge maior variação de cores da paleta e melhor distribuição espacial 3D RGB das cores selecionadas que os demais modelos. A qualidade das imagens geradas também figura entre os melhores resultados obtidos

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This thesis presents a number of GIS based landscape analyses that together aim to explore aspects of the social development in Iron Age Västmanland, central Sweden. From a perspective where nature and culture are seen as integrated in the landscape, differences in the relations to the physical landscape are interpreted as reflecting social organisation. Thus, hydrological modelling of watersheds is used for understanding the development of territories and regions that are recognisable in the outlay of the medieval hundare districts. Statistical modelling of burial grounds together with variables describing their situation in the landscape is used to calculate an estimated chronology for sites that have not yet been excavated. This information is used to analyse differences in how the setting in the landscape can tell of different trends in claims to land and property rights. An extensive renegotiation of property rights is suggested to have taken place after climatic catastrophe in AD 536 and the years after. This is interpreted as having caused a substantial population decline in parts of Scandinavia. The social development after this includes an increasingly stratified social hierarchy in the Late Iron Age, which is reflected in the construction of grave monuments. New GIS methods for analysing how to interpret the perception of different locations of the landscape, in terms of local topography and soil are discussed in relation to this.   How to make the best use of large datasets of archaeological information in combination with other sources of geographical information is a central theme. Geographically Weighted Regression is used to predicting the representativity of the registry of graves for the whole landscape. It is suggested that the increasing availability of archaeological information in digital format, together with new analytical techniques has the potential to introduce fruitful new research perspectives. This will make it increasingly rewarding to work with the large amount of data produced from rescue archaeology, and it is important that this information is managed in a structured manner. / Appendices see http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-111310