High levels of toxic heavy metals in the environment are a major concern and our knowledge about their adverse impacts and distribution patterns is improving. To mitigate human exposure for large regions, understanding the spatial distribution of metals in soil is key. Several types of models are available to predict the concentration levels, but they are often complex and data-intensive. The objective of this research is to explore the application of a simple method that produces geographically referenced predictions of surface soil concentrations of heavy metals. The approach uses publicly-available Canadian soil sample data, Geographic Information Science, statistical correlation and regression analyses. Geographically Weighted Regression (GWR) was used to investigate the spatial variability of the relationship between surface and the subsurface soil metal concentrations. Correlation analysis (Pearson’s) between the log of concentration levels of the two layers shows relationships of 0.51 for arsenic (As), and 0.23 for lead (Pb). Although the correlation results showed levels in the two layers are related, GWR analysis illustrates that the degree of this relation varies geographically. This study suggests that factors (natural and anthropogenic) other than the subsurface concentration itself are contributing to the concentration surface levels for all of the studied metals in this dataset. Based on the above findings, two linear regression models were developed to predict As and Pb levels in surface soil. Independent variables in the models were developed using geographic data on factors hypothesized to influence surface levels, an approach that has been extensively used for modelling air pollution and known as Land Use Regression (LUR). For the LUR analysis, the results show that industrial activities account for more than 70% of the variation of Pb concentrations in surface soil. Interestingly, the LUR model for As suggests that the bedrock geology and the total length of road at a location are the main factors. Both variables account for more than 40% of the variations of the As levels in surface soil in BC. The LUR results suggest that regional scale modeling of As and Pb surface soil concentrations can provide information about their spatial patterns that may be useful for understanding potential human exposure and the conduct of environmental epidemiological studies. / Graduate / 768 / 573 / 481 / steeved@uvic.ca

Social disorganization and routine activity theories have been studied over the past 30 years. The subsequent research examines prior concepts that were constructed to measure these theories and recent attempts in combining these theories. It also examines how these concepts have been measured using a multitude of geographical scales. It suggests that one consistent set of geographical scales must be used and that these must be easily reproduced in order to test these concepts on a multitude of cities that have a wide variation in populations.

Walkability research has broadened in the past few years, being performed by researchers in different fields such as urban planning, public health, and transportation planning. Definitions of walkability and methods of operationalizing the concept vary widely. Since the results of studies that incorporate walkability may well have policy implications, it is important to consider the potential impacts of different definitions and methods of measurement. This thesis investigates to what extent walkability indices may differ when either the composition of the indices is changed or when different quantitative methods of standardization are used to summarize their component measures. The association of these different walkability indices with socio-demographic variables is also investigated to determine the variability in such associations. The thesis also investigates to what extent changing the spatial extent of a study area, in this case the definition of an urbanized area, may also lead to differences in how walkability measures may be associated with socio-demographic variables. In the analysis process, several methodological innovations were developed such as applying new detailed GIS analysis, developing two accessibility measures and two accessibility indices, creating a comprehensive walkability index, and applying the latest methods from spatial econometrics. The results from investigating the research questions showed that even though walkability scores across the study area are different based on index compositions or index standardization methods, their association with socio-demographics is fairly consistent. When investigated for areas with different extents, the association between walkability and socio-demographics differed more.

Community health centers (CHCs) provide comprehensive primary care regardless of a patient’s ability to pay. Key policies in the last decade facilitated development of new CHC delivery sites, but the extent of change in geographic access to CHCs (CHC accessibility) is understudied. Furthermore, existing research on CHC accessibility relies on antiquated methods for measuring CHC accessibility despite the growing use of contemporary accessibility methods to study access to other types of health services. We conducted three studies that examined CHC accessibility using contemporary accessibility methods and publicly available data from the Health Resources and Services Administration, American Community Survey, Area Health Resources File, and the 500 Cities Project. The first study assessed CHC accessibility at the census tract level in 2008 and 2016, before and after implementation of policies that expanded CHCs, using the two-step floating catchment area method. It then investigated the association between indicators of CHC need and changes in CHC accessibility. The second study examined the association between CHC accessibility and primary care utilization. The third study investigated differential change in CHC accessibility for census tracts in a subset of Medicaid expansion states compared to census tracts in a subset of non-expansion states. We found that CHC accessibility substantially increased between 2008 and 2016, that spatial distribution of increases in CHC accessibility was not uniform, and that the two-step floating catchment area method could be successfully applied to reveal small area variation in CHC accessibility changes across states. We also found that CHC accessibility was positively related to primary care utilization, but moderated by extent of primary care provider supply and median household income in the surrounding area. Finally, we found that census tracts in Medicaid expansion and non-expansion states saw similar increases in CHC accessibility from 2008 to 2016. In the current health policy context, where gains in health coverage from the Affordable Care Act are in jeopardy of being scaled back, CHC accessibility is critically important. The findings of this work support the important role of CHC accessibility in primary care utilization and describe how CHC accessibility has changed in the last decade. / 2020-10-23T00:00:00Z

Is school accessibility a valued good, and do school closures affect house prices? This thesis applies two different methods of hedonic regression analysis, augmented by spatial regression methods, to a dataset of Hamilton real estate transactions (2005-2017) to investigate whether the closure of a school in an urban neighbourhood negatively affects house prices in that closed school catchment. Evidence is found that school accessibility is a valued good, and that the closure of a primary school will negatively affect house prices from the period of closure announcement through several subsequent quarters. The use of spatial analysis corrects for bias in coefficient estimates. / Thesis / Master of Arts (MA) / Do homebuyers pay a premium to be located closer to a school, and do school closures affect house prices? An analysis of Hamilton real estate transactions (2005-2017) finds evidence that houses closer to schools sell for more, and that a primary school closure has a negative impact on local house sale prices.

As técnicas de análise espacial constituem-se em um importante instrumento para o entendimento dos condicionantes que compõem o processo de transmissão da dengue, contribuindo com o fornecimento de subsídios para as ações de vigilância e controle da doença. O objetivo desse trabalho foi caracterizar a distribuição espacial da dengue por meio do mapeamento dos casos no município de Osasco no período de 2007 a 2013; identificar a distribuição espacial e espaço temporal do risco de ocorrência de dengue; avaliar a relação da incidência de dengue com os índices larvários; e avaliar a relação entre dengue e os fatores socioeconômicos. Foram utilizados dados secundários obtidos na base de dados do Sistema de Informação de Agravos de Notificação (SINAN). A incidência anual, as principais medidas de frequência da doença e a correlação dos índices de Breteau (IB) e os casos de dengues foram analisados. Os casos notificados de dengue no município foram geocodificados a partir do eixo de logradouros e agrupados de acordo com os 928 setores censitários considerados no estudo, o que permitiu a elaboração de mapas temáticos. Utilizando-se o modelo discreto de Poisson para a identificação de conglomerados de maior ou menor risco para ocorrência de dengue no espaço e no espaço-tempo. A dependência espacial dos casos de dengue foi medida pelo Índice de Moran. Por meio de técnicas de análise de regressão linear e espacial as variáveis socioeconômicas foram associadas aos casos de dengue, no sentido de buscar o melhor modelo que esclarecesse a associação dos casos de dengue com os fatores socioeconômicos. Em todos os anos ocorreram casos de dengue e a incidência foi maior nos meses de março a maio. Os mapas gerados mostraram a distribuição espacial e espaço temporal da dengue no município. Não foi observado correlação estatística entre os casos de dengue e o IB. Na análise de espaço-temporal, foram identificados um aglomerado de alto risco, localizado na zona Norte, referente ao período de fevereiro a maio de 2007, e um outro aglomerado de baixo risco. O número de casos de dengue foi maior em áreas sem rede de abastecimento de água; com serviço de coleta do lixo; moradores de cor parda e renda domiciliar per capita de 1 a 2 salários mínimos. O modelo de regressão espacial se mostrou mais eficiente na tentativa de explicar a ocorrência da dengue em relação aos modelos lineares. As taxas de incidência de dengue em períodos epidêmicos e interepidêmicos sugerem que a transmissão de dengue é endêmica no município de Osasco. A ocorrência da dengue não apresenta padrão de distribuição uniforme. As análises espacial, espaço temporal e de modelagem por regressão apontam que a dengue atingiu diferentes estratos socioeconômicos, podendo ser atribuído a heterogeneidade espacial das condições de vida da população. Os resultados levantam a necessidade de estudos específicos dos métodos que estão sendo utilizados para medir infestações de Ae. aegypti no município. O método utilizado mostrou-se adequado para identificação de áreas de risco e por consequência direcionamento de ações e recursos do poder público / The spatial analysis techniques constitute an important tool for understanding the conditions that make up the process of dengue virus transmission, contributing to the provision of subsidies for the surveillance and control of the disease. The purpose of this study was to characterize the spatial distribution of dengue cases through mapping of cases in the city of Osasco in the period from 2007 to 2013; also, identify the spatial distribution and temporal space risk of dengue; evaluate the relationship between the incidence rates of dengue cases with the larval indices; as well evaluate the relationship between dengue and socioeconomic factors. Data were obtained from Sistema de Informação de Agravos de Notificação (SINAN Information System for Notifiable Diseases). The annual incidence, the main frequency measures of the disease and the correlation of the Breteau indexes (BI) and cases of dengue cases were analysed. Dengue cases registered in the city were geocoded by street names and grouped according to 928 census tracts, thus generating thematic maps. Incidence rates were calculated for the study period, as well as the identification of higher and lower-risk areas for spaceand space-time clusters of dengue. It was used the discrete Poisson model to identified the clusters of higher or lower risk for the occurrence of dengue cases in space and space-time. The spatial dependence of dengue cases was measured by Moran index. Through linear and spatial regression analysis techniques socioeconomic variables were associated with dengue cases, in order to seek the best model to clarify the association dengue cases with socioeconomic factors. In all the years there have been cases of dengue and the incidence was higher in the months from March to May. The maps showed the spatial and temporal distribution of dengue in the city space. However, there was no statistical correlation between cases of dengue and the IB. The spatio-temporal analysis, they identified a high risk cluster, located in the northern area for the period from February to May 2007, and another low-risk cluster. The number of cases of dengue was higher in areas without water supply system, garbage collection service, brown residents and per capita domiciliary income of 1 to 2 minimum wages. The spatial regression model was more efficient in trying to explain the occurrence of dengue cases in relation to linear models. In conclusion, the dengue incidence rates at epidemic and inter-epidemic periods suggest that dengue cases transmission is endemic in the city of Osasco. The occurrence of dengue has no uniform distribution pattern. The Spatial analysis, timeline and regression modeling indicate that dengue cases reached different socioeconomic strata, as a result, is attributing to spatial heterogeneity of living conditions of the population. Therefore, the results raise the need for specific studies of the methods being used to measure infestation of Ae. aegypti in the city. The method proved to be suitable for areas of risk identification and consequently direct actions and resources of government

This dissertation takes a sociological look at the relationship between urbanization and environmental change. While sociological studies on urbanization have long addressed the social dimensions of the built environment, the natural environment has not been treated as a primary concept in urban sociology. Based on an analysis of local land use change across the United States at the beginning of the 21st century, this dissertation brings the built and natural environments together, recognizing both as important dimensions of urbanization. The expansion of the built environment, through deforestation and the covering up of fertile agricultural land, represents a modern form of land use change with direct and indirect impacts on the natural environment, the most severe effects of which are seen in biodiversity loss, disruption of the nitrogen cycle, and climate change. Drawing on literatures and theories in environmental, rural, and urban sociology as well as demography and human ecology, the bulk of the dissertation involves empirical analyses of overall changes in forest cover as well as the loss of forest cover and agricultural land to the built environment (i.e., the impervious structures and surfaces that cover the land), a process I refer to as land use intensification. My dissertation project uses quantitative methods to examine the demographic, economic, and social forces behind this process in contemporary America. Hypotheses are derived from the various literatures mentioned above; to test these hypotheses, I integrate county-level data from US governmental sources with satellite imagery on land cover change from the National Land Cover Database (NLCD). For the years 2001-2006, I use the NLCD data to quantify three dependent variables at the county-level: overall change in the area of forest cover as well as the area of forest cover and agricultural land lost to the built environment. Results from regression analyses demonstrate that urbanization is a multidimensional process that differentially transforms the American landscape. With a focus on land use intensification, this study advances a sociological framework to address connections between urbanization and changes in both the built and natural environments.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-04-08T12:50:39Z No. of bitstreams: 1 Camila Flores Orth.pdf: 2246948 bytes, checksum: 8066e9a1d139e4e2b3ecd4e2ff6d1e61 (MD5) / Made available in DSpace on 2015-04-08T12:50:39Z (GMT). No. of bitstreams: 1 Camila Flores Orth.pdf: 2246948 bytes, checksum: 8066e9a1d139e4e2b3ecd4e2ff6d1e61 (MD5) Previous issue date: 2012-08-24 / Nenhuma / A análise regional dos determinantes da corrupção faz com que elementos histórico-culturais e políticos sejam mais homogêneos, tornando os fatores socioeconômicos mais importantes. Assim, esta dissertação procurou determinar e analisar os fatores socioeconômicos da corrupção em nível municipal no Brasil. Para isso, utilizaram-se dados do Programa de Fiscalização de Recursos Federais a partir de Sorteios Públicos da Controladoria Geral da União (CGU) de municípios auditados entre 2006 e 2010. Para esta análise utiliza-se a avaliação por um modelo de regressão espacial. Os resultados obtidos através do estudo apontam para uma alta dependência espacial nos dados, indicando que, neste caso, o modelo de regressão espacial é o mais correto. Além disso, as variáveis mais significativas como determinantes da corrupção foram o número de beneficiários do Programa Bolsa Família (utilizada como proxy para pobreza), a taxa de analfabetismo de pessoas entre 7 e 14 anos e o valor do PIB da agricultura municipal, que apresentaram correlação positiva com o nível de irregularidades. Ainda, outras duas variáveis socioeconômicas apresentaram significância estatística em pelo menos um dos modelos testados, as despesas de investimento, com correlação negativa, e a parcela de mulheres entre 10 e 14 anos que tiveram filhos, com sinal positivo. / Regional analysis of the determinants of corruption makes historical, cultural and political factors more homogeneous, making socioeconomic factors as the most important. This dissertation aimed to determine and analyze the socioeconomic factors of corruption at the municipal level in Brazil. For this, it was used data from a anti-corruption program based on the random auditing of municipal government’s expenditure, called in portuguese Programa de Fiscalização de Recursos Federais a partir de Sorteios Públicos, implemented by the Controladoria Geral da União (CGU) of municipalities audited between 2006 and 2010. For this analysis we use the evaluation by a spatial regression model. The results obtained from the study show a high spatial dependence in the data, indicating that in this case, the spatial regression model is more indicated. Moreover, the most significant variables as determinants of corruption is poverty (measured by the number of beneficiaries of the Program Bolsa Família), the illiteracy rate of people between 7 and 14 years and the value of GDP of agriculture, which correlated positively with the level of corruption. Still, two other socioeconomic variables showed statistical significance in at least one of the models tested, the investment expenditure, with negative correlation, and the share of women between 10 and 14 years who had children, with a positive sign.

Submitted by Fabricia Fialho Reginato (fabriciar) on 2015-07-22T22:53:48Z No. of bitstreams: 1 LuisBragaEconomia.pdf: 6108813 bytes, checksum: bf186fda5918d6000c0c2500d6ea514c (MD5) / Made available in DSpace on 2015-07-22T22:53:48Z (GMT). No. of bitstreams: 1 LuisBragaEconomia.pdf: 6108813 bytes, checksum: bf186fda5918d6000c0c2500d6ea514c (MD5) Previous issue date: 2010 / Nenhuma / Este trabalho visa determinar a influência que os fatores sócio-econômicos, em conjunto com as variáveis construtivas usuais, provocam na valoração de imóveis no Estado do Rio Grande do Sul. Sendo o imóvel um bem com características distintas das demais, muitos pesquisadores buscam elementos diferentes para explicar esse comportamento distinto. Neste contexto, sobressai um dos fatores com grande relevância, a vizinhança. Os métodos inferenciais tradicionais dificultam a modelagem adequada pela multiplicidade dos fatores que influenciam o valor dos imóveis de uma determinada região. Sendo assim, os modelos de regressão espacial foram utilizados na estimação do valor unitário dos mesmos (VU). Já o modelo de regressão LAG foi utilizado para uniformizar a amostra de dados dos imóveis que se mostrou heterogênea. Não obstante, a krigagem demonstrou a estimativa do valor de um imóvel para determinada região. A aplicação dos métodos foi realizada para uma base de dados obtida junto a Caixa Econômica Federal, contendo imóveis transacionados no Estado do Rio Grande do Sul, no período de 2006 a 2008. Ademais, os métodos de regressão aplicados confirmaram índices fortemente significativos nos modelos obtidos para todos os imóveis de uma região. Com isso, a estrutura espacial dos índices estimados minimizou a autocorrelação existente nos resíduos do modelo de regressão, melhorando a confiabilidade da avaliação. / This work aims to determine the influence that the social economic factors together with the usual variable constructive cause in the valuation of property, in Rio Grande do Sul State. Property is a material good with distinct characteristics from the other goods. Many researchers seek different elements to explain this situation. In this context one factor stands out with great relevance, the neighborhood. The traditional inferential methods difficult the adequate modeling because of the multiplicity of the factors that influence the value of the properties in a given region. Spatial regression models were used to estimate their unit value (UV). The regression model LAG was used to standardize the data sample of the properties, it was heterogeneous. Kriging showed the estimated value of a property for a given region. The application of the methods was performed for a database obtained from Caixa Econômica Federal, containing properties transacted in Rio Grande do Sul State, from 2006 to 2008. The applied regression methods confirmed strongly significant indices on the obtained models for all the properties in the region. The spatial structure of the estimated indices minimized the autocorrelation existing in the residuals of the regression models, improving the reliability of assessment.

As técnicas de análise espacial constituem-se em um importante instrumento para o entendimento dos condicionantes que compõem o processo de transmissão da dengue, contribuindo com o fornecimento de subsídios para as ações de vigilância e controle da doença. O objetivo desse trabalho foi caracterizar a distribuição espacial da dengue por meio do mapeamento dos casos no município de Osasco no período de 2007 a 2013; identificar a distribuição espacial e espaço temporal do risco de ocorrência de dengue; avaliar a relação da incidência de dengue com os índices larvários; e avaliar a relação entre dengue e os fatores socioeconômicos. Foram utilizados dados secundários obtidos na base de dados do Sistema de Informação de Agravos de Notificação (SINAN). A incidência anual, as principais medidas de frequência da doença e a correlação dos índices de Breteau (IB) e os casos de dengues foram analisados. Os casos notificados de dengue no município foram geocodificados a partir do eixo de logradouros e agrupados de acordo com os 928 setores censitários considerados no estudo, o que permitiu a elaboração de mapas temáticos. Utilizando-se o modelo discreto de Poisson para a identificação de conglomerados de maior ou menor risco para ocorrência de dengue no espaço e no espaço-tempo. A dependência espacial dos casos de dengue foi medida pelo Índice de Moran. Por meio de técnicas de análise de regressão linear e espacial as variáveis socioeconômicas foram associadas aos casos de dengue, no sentido de buscar o melhor modelo que esclarecesse a associação dos casos de dengue com os fatores socioeconômicos. Em todos os anos ocorreram casos de dengue e a incidência foi maior nos meses de março a maio. Os mapas gerados mostraram a distribuição espacial e espaço temporal da dengue no município. Não foi observado correlação estatística entre os casos de dengue e o IB. Na análise de espaço-temporal, foram identificados um aglomerado de alto risco, localizado na zona Norte, referente ao período de fevereiro a maio de 2007, e um outro aglomerado de baixo risco. O número de casos de dengue foi maior em áreas sem rede de abastecimento de água; com serviço de coleta do lixo; moradores de cor parda e renda domiciliar per capita de 1 a 2 salários mínimos. O modelo de regressão espacial se mostrou mais eficiente na tentativa de explicar a ocorrência da dengue em relação aos modelos lineares. As taxas de incidência de dengue em períodos epidêmicos e interepidêmicos sugerem que a transmissão de dengue é endêmica no município de Osasco. A ocorrência da dengue não apresenta padrão de distribuição uniforme. As análises espacial, espaço temporal e de modelagem por regressão apontam que a dengue atingiu diferentes estratos socioeconômicos, podendo ser atribuído a heterogeneidade espacial das condições de vida da população. Os resultados levantam a necessidade de estudos específicos dos métodos que estão sendo utilizados para medir infestações de Ae. aegypti no município. O método utilizado mostrou-se adequado para identificação de áreas de risco e por consequência direcionamento de ações e recursos do poder público / The spatial analysis techniques constitute an important tool for understanding the conditions that make up the process of dengue virus transmission, contributing to the provision of subsidies for the surveillance and control of the disease. The purpose of this study was to characterize the spatial distribution of dengue cases through mapping of cases in the city of Osasco in the period from 2007 to 2013; also, identify the spatial distribution and temporal space risk of dengue; evaluate the relationship between the incidence rates of dengue cases with the larval indices; as well evaluate the relationship between dengue and socioeconomic factors. Data were obtained from Sistema de Informação de Agravos de Notificação (SINAN Information System for Notifiable Diseases). The annual incidence, the main frequency measures of the disease and the correlation of the Breteau indexes (BI) and cases of dengue cases were analysed. Dengue cases registered in the city were geocoded by street names and grouped according to 928 census tracts, thus generating thematic maps. Incidence rates were calculated for the study period, as well as the identification of higher and lower-risk areas for spaceand space-time clusters of dengue. It was used the discrete Poisson model to identified the clusters of higher or lower risk for the occurrence of dengue cases in space and space-time. The spatial dependence of dengue cases was measured by Moran index. Through linear and spatial regression analysis techniques socioeconomic variables were associated with dengue cases, in order to seek the best model to clarify the association dengue cases with socioeconomic factors. In all the years there have been cases of dengue and the incidence was higher in the months from March to May. The maps showed the spatial and temporal distribution of dengue in the city space. However, there was no statistical correlation between cases of dengue and the IB. The spatio-temporal analysis, they identified a high risk cluster, located in the northern area for the period from February to May 2007, and another low-risk cluster. The number of cases of dengue was higher in areas without water supply system, garbage collection service, brown residents and per capita domiciliary income of 1 to 2 minimum wages. The spatial regression model was more efficient in trying to explain the occurrence of dengue cases in relation to linear models. In conclusion, the dengue incidence rates at epidemic and inter-epidemic periods suggest that dengue cases transmission is endemic in the city of Osasco. The occurrence of dengue has no uniform distribution pattern. The Spatial analysis, timeline and regression modeling indicate that dengue cases reached different socioeconomic strata, as a result, is attributing to spatial heterogeneity of living conditions of the population. Therefore, the results raise the need for specific studies of the methods being used to measure infestation of Ae. aegypti in the city. The method proved to be suitable for areas of risk identification and consequently direct actions and resources of government