Walkability is desirable for a variety of reasons. Sometimes, walkability is desirable because it is the only available or affordable transportation modal choice. Urban form and transportation infrastructure can be hostile to pedestrians because cars are prioritized first, and pedestrians often face unsafe situations and a lack of pedestrian facilities. This analysis explores a spatial distribution of pedestrian access to opportunities in Austin, TX, and examines the locations of households of different income levels relative to areas of high pedestrian access to opportunities. To achieve results that are equally precise across the study area, this analysis employs GIS analysis and U.S. Census 2000 data, and analyzes the study area using a ½ square-mile grid system. High pedestrian access areas are defined as locations where residential parcels have pedestrian network access to multiple types of opportunities and above average number of opportunities. This analysis finds that low income households are more associated with high pedestrian access areas in Austin, TX, than moderate and high income households. If lower income households are consistently shown to rely more on pedestrian infrastructure than moderate or high income households, it may be important to allocate funding to high pedestrian access areas with low income populations in such a way that is socially equitable, and that will result in more use of the pedestrian facilities. / text

Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2017-06-12T13:59:52Z No. of bitstreams: 1 J??lioCesarDaCunhaLopesDissertacao2016.pdf: 5954507 bytes, checksum: 3d54d8db00b8c7c9adb70d31efdca84d (MD5) / Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2017-06-12T14:00:28Z (GMT) No. of bitstreams: 1 J??lioCesarDaCunhaLopesDissertacao2016.pdf: 5954507 bytes, checksum: 3d54d8db00b8c7c9adb70d31efdca84d (MD5) / Made available in DSpace on 2017-06-12T14:00:28Z (GMT). No. of bitstreams: 1 J??lioCesarDaCunhaLopesDissertacao2016.pdf: 5954507 bytes, checksum: 3d54d8db00b8c7c9adb70d31efdca84d (MD5) Previous issue date: 2016-03-10 / Although there is a wide variety of measures to measure the levels of agglomeration and location of firms, the areal unit problem modifiable - MAUP - is always remembered in literature as a problem in regional science. The purpose of the research is to apply the newly developed tracing measures that surpass largely the MAUP problem. With unprecedented use in Brazil, these measures assess the level of sectoral location of manufacturing industry in the Greater S??o Paulo and the results show that the fabrication industries of automotive vehicles, trailers and bodies and clothing and accessories are more localized . On the other hand, the non-metallic minerals and pulp and paper segments have a higher dispersion in relation to the other. / Embora exista uma extensa variedade de medidas para se mensurar os n??veis de aglomera????o e localiza????o das firmas, o modifiable areal unit problem ??? MAUP ??? sempre ?? lembrado na literatura como um problema na ci??ncia regional. O prop??sito da pesquisa ?? aplicar as medidas de localiza????o recentemente desenvolvidas que superam, em boa parte, o problema do MAUP. Com utiliza????o in??dita no Brasil, tais medidas avaliam o n??vel de localiza????o setorial da ind??stria da transforma????o na Regi??o Metropolitana de S??o Paulo e os resultados mostram que as ind??strias de fabrica????o de ve??culos automotores, reboques e carrocerias e de artigos de vestu??rio e acess??rios s??o mais localizadas. Por outro lado, os segmentos de minerais n??o met??licos e celulose e papel apresentam maior dispers??o em rela????o aos demais.

The role of the spatial representation in the relation between chronic exposure to NO2 and respiratory health outcomes is studied through a spatial approach encompassing three conceptual components: the geography of susceptibility, the geography of exposure and the geography of risk. A spatially explicit methodology that defined natural neighbourhoods for the city of Ottawa is presented; it became the geography of analysis in this research. A LUR model for Ottawa is developed to study the geography of exposure. Model sensitivity to the spatial representation of population showed that dasymetric population mapping did not provide significant improvements to the LUR model over population at the dissemination block level. However, both the former were significantly better than population represented at the dissemination area. Spatial representation in the geography of exposure was also evaluated by comparing four kriging and cokriging interpolation models to the LUR. Geostatistically derived NO2 concentration maps were weakly correlated with LUR model results. The relationship between mean NO2 concentrations and respiratory health outcomes was assessed within the natural neighbourhoods. We find a statistically significant association between NO2 concentrations and respiratory health outcomes as measured by global bivariate Moran’s I. However, for regression model building, NO2 had to be forced into the model, demonstrating that NO2 is not one of the main contributing variables to respiratory health outcomes in Ottawa. The results point toward the importance of the socioeconomic status on the health condition of individuals. Finally, the role of spatial representation was assessed using three different spatial structures, which also permitted to better understand the role of the modifiable areal unit problem (MAUP) in the study of the relationship between exposure to NO2 and health. The results confirm that NO2 concentration is not a major contributing factor to the respiratory health in Ottawa but clearly demonstrate the implications that the use of opportunistic administrative boundaries can have on results of exposure studies. The effects of the MAUP, the scale effect and the zoning effect, were observed indicating that a spatial structure that embodies the scale of major social processes behind the health condition of individuals should be used when possible.

The role of the spatial representation in the relation between chronic exposure to NO2 and respiratory health outcomes is studied through a spatial approach encompassing three conceptual components: the geography of susceptibility, the geography of exposure and the geography of risk. A spatially explicit methodology that defined natural neighbourhoods for the city of Ottawa is presented; it became the geography of analysis in this research. A LUR model for Ottawa is developed to study the geography of exposure. Model sensitivity to the spatial representation of population showed that dasymetric population mapping did not provide significant improvements to the LUR model over population at the dissemination block level. However, both the former were significantly better than population represented at the dissemination area. Spatial representation in the geography of exposure was also evaluated by comparing four kriging and cokriging interpolation models to the LUR. Geostatistically derived NO2 concentration maps were weakly correlated with LUR model results. The relationship between mean NO2 concentrations and respiratory health outcomes was assessed within the natural neighbourhoods. We find a statistically significant association between NO2 concentrations and respiratory health outcomes as measured by global bivariate Moran’s I. However, for regression model building, NO2 had to be forced into the model, demonstrating that NO2 is not one of the main contributing variables to respiratory health outcomes in Ottawa. The results point toward the importance of the socioeconomic status on the health condition of individuals. Finally, the role of spatial representation was assessed using three different spatial structures, which also permitted to better understand the role of the modifiable areal unit problem (MAUP) in the study of the relationship between exposure to NO2 and health. The results confirm that NO2 concentration is not a major contributing factor to the respiratory health in Ottawa but clearly demonstrate the implications that the use of opportunistic administrative boundaries can have on results of exposure studies. The effects of the MAUP, the scale effect and the zoning effect, were observed indicating that a spatial structure that embodies the scale of major social processes behind the health condition of individuals should be used when possible.

The role of the spatial representation in the relation between chronic exposure to NO2 and respiratory health outcomes is studied through a spatial approach encompassing three conceptual components: the geography of susceptibility, the geography of exposure and the geography of risk. A spatially explicit methodology that defined natural neighbourhoods for the city of Ottawa is presented; it became the geography of analysis in this research. A LUR model for Ottawa is developed to study the geography of exposure. Model sensitivity to the spatial representation of population showed that dasymetric population mapping did not provide significant improvements to the LUR model over population at the dissemination block level. However, both the former were significantly better than population represented at the dissemination area. Spatial representation in the geography of exposure was also evaluated by comparing four kriging and cokriging interpolation models to the LUR. Geostatistically derived NO2 concentration maps were weakly correlated with LUR model results. The relationship between mean NO2 concentrations and respiratory health outcomes was assessed within the natural neighbourhoods. We find a statistically significant association between NO2 concentrations and respiratory health outcomes as measured by global bivariate Moran’s I. However, for regression model building, NO2 had to be forced into the model, demonstrating that NO2 is not one of the main contributing variables to respiratory health outcomes in Ottawa. The results point toward the importance of the socioeconomic status on the health condition of individuals. Finally, the role of spatial representation was assessed using three different spatial structures, which also permitted to better understand the role of the modifiable areal unit problem (MAUP) in the study of the relationship between exposure to NO2 and health. The results confirm that NO2 concentration is not a major contributing factor to the respiratory health in Ottawa but clearly demonstrate the implications that the use of opportunistic administrative boundaries can have on results of exposure studies. The effects of the MAUP, the scale effect and the zoning effect, were observed indicating that a spatial structure that embodies the scale of major social processes behind the health condition of individuals should be used when possible.

The role of the spatial representation in the relation between chronic exposure to NO2 and respiratory health outcomes is studied through a spatial approach encompassing three conceptual components: the geography of susceptibility, the geography of exposure and the geography of risk. A spatially explicit methodology that defined natural neighbourhoods for the city of Ottawa is presented; it became the geography of analysis in this research. A LUR model for Ottawa is developed to study the geography of exposure. Model sensitivity to the spatial representation of population showed that dasymetric population mapping did not provide significant improvements to the LUR model over population at the dissemination block level. However, both the former were significantly better than population represented at the dissemination area. Spatial representation in the geography of exposure was also evaluated by comparing four kriging and cokriging interpolation models to the LUR. Geostatistically derived NO2 concentration maps were weakly correlated with LUR model results. The relationship between mean NO2 concentrations and respiratory health outcomes was assessed within the natural neighbourhoods. We find a statistically significant association between NO2 concentrations and respiratory health outcomes as measured by global bivariate Moran’s I. However, for regression model building, NO2 had to be forced into the model, demonstrating that NO2 is not one of the main contributing variables to respiratory health outcomes in Ottawa. The results point toward the importance of the socioeconomic status on the health condition of individuals. Finally, the role of spatial representation was assessed using three different spatial structures, which also permitted to better understand the role of the modifiable areal unit problem (MAUP) in the study of the relationship between exposure to NO2 and health. The results confirm that NO2 concentration is not a major contributing factor to the respiratory health in Ottawa but clearly demonstrate the implications that the use of opportunistic administrative boundaries can have on results of exposure studies. The effects of the MAUP, the scale effect and the zoning effect, were observed indicating that a spatial structure that embodies the scale of major social processes behind the health condition of individuals should be used when possible.

I den här uppsatsen undersöks fem olika boendesegregationsindex som används för att beräkna och skildra graden av boendesegregation i samhället. Syftet är att studera hur index påverkas av slumpmässigt genererade befolkningssammansättningar av inrikes och utrikes födda, samt hur tre olika geografiska indelningar av ett område påverkar utfallet av utvalda index. Uppsatsen utförs med kvantitativ metod och deduktiv slutledning. Det data som samtliga index beräknas på är syntetiskt framtagen baserad på information om hur andelarna inrikes och utrikes födda ser ut i Sveriges tre största kommuner. Mätområdet utgörs av en hypotetisk stad som delas in på tre olika sätt varpå samtliga index testas. Beräkningar och analyser görs på stickprov för respektive index och geografisk indelning. Stickproven består alla av ett hundra element och är framtagna genom ett obundet slumpmässigt urval ur en teoretisk oändlig population simulerade befolkningssammansättningar. Den geografiska effekten undersöks genom MAUPs två delproblem, Scale Effect och Zoning Effect. Utifrån studiens resultat har följande slutsatser dragits. (1) Den slumpmässiga sammansättningen av befolkningen i den hypotetiska staden påverkade generellt index väldigt lite och låg spridning av resulterade indexvärden uppmättes för många av stickproven. De undantag som påvisades var för The Entropy Index och The Dissimilarity Index. (2) Scale Effect har stor påverkan på hur samtliga index uttrycker sig samtidigt som Zoning Effect uteblir för respektive index som testas. (3) Lägre grad av segregation uppvisas då upplösningen av den geografiska informationen är lägre.

Det som ofta faller bort i den offentliga debatten är att segregationens innebörd anspelar på åtskillnader av olika grupper, inte enbart de ”utsatta” utan även de socioekonomiskt starkare grupperna. Denna studie kommer att undersöka hur segregationen ser ut inom Sundsvalls tätortsområden och vilka faktorerna är som har störst påverkan till de skillnader som finns. Studien baseras på att urskilja den relativa segregationen, d.v.s. fördelningen av segregationspåverkande faktorer, i positiv och negativ riktning. Syftet i studien är sedan att jämföra två olika geografiska indelningssystem. Det ena är det kommunala nyckelkodssystemet (NYKO) och det andra är Statistiska centralbyråns regionala indelningssystem, demografiska statistikområden (DeSO). I metoden har två olika index använts för att mäta fördelningen av segregationsfaktorer genom en multikriterieanalys (MKA). Den första mätningen har skett genom en nyutvecklad segregationsindex och den andra mätningen genom index of dissimilarity. Studien har visat att det finns svårigheter kring att använda ett indelningssystem som kan verka funktionellt i alla avseenden. Beroende på vad studien syftar till att mäta så spelar olika zon- och skalindelningar en stor roll i hur resultatet framställs. Resultatet visar att segregationen utspelar sig inom både de socioekonomiskt svaga och starka områdena. Det finns däremot svårigheter med att bedöma vilken områdesindelning som är mest användbar då de verkar på olika grunder. Genom att jämföra DeSO och NYKO har resultaten av studien visat att befolkningsantalet och storleken på den geografiska områdesindelningen har en stor betydelse för hur pålitlig en studie kan bli. / What often falls away in the public debate is that the meaning of the segregation alludes to the separation of different groups, not just the "vulnerable" but also the socio-economically stronger groups. This study will investigate how the segregation plays out within Sundsvall's urban areas and which factors have the greatest impact on the differences that exist. The study is based on distinguishing the relative segregation, i. e. the distribution of factors affecting segregation, in a positive and negative direction. The purpose of the study is then to compare two different geographical area systems. One is the municipal key code system (NYKO) and the other is the state regional area system, demographic statistics areas (DeSO). In the method, two different indexes have been used to measure the distribution of segregation factors through a multi-criteria decision analysis (MKA). The first measurement has been made by a newly developed segregation index and the second measurement by the index of dissimilarity. The study has shown that there are difficulties in finding an area system that can function efficiently for all purposes. Depending on what the study aims to measure, the different zone and scale configurations play a major role in how the result is produced. The result of the study shows that the segregation takes place in both the socio-economically weak and strong areas. There are, on the other hand, difficulties in assessing which of the two area systems that is the most practical since they both operate on different grounds. By comparing DeSO and NYKO, the results of the study have shown that the population and size of the geographical area unit are of great importance for how reliable a study can be.

Segregation refers to the uneven spatial distribution of social groups over space. Segregation can be perceived as the spatial representation of social, cultural, and economic exclusion. There is no accepted standard way segregation is measured; instead, studies have used a wide range of methods, measurements, and indices to estimate levels of segregation. Existing studies are seldomly longitudinal in character, mostly because of lack of data, and have only been conducted until 2010 for Stockholm. The aim of this thesis is to investigate trends of residential poverty segregation in Stockholm County for the period 1991-2016. This study has utilized the isolation index, the dissimilarity index, percentile plots and location quotients on data aggregated to both administrative units and individualized neighborhoods on multiple scales to assess how these common techniques influence results. Results show that segregation patterns vary depending on technique, but most results indicate increasing levels of segregation of individuals at risk of poverty for the period 1991-2011, in line with previous research. On the other hand, the results indicate stagnating or decreasing levels of poverty segregation in recent years. Poverty segregation varies substantially by scale level, and therefore this thesis recommends multiscalar methods in segregation studies.

Les villes sont des systèmes complexes que les modèles urbains peuvent aider à comprendre. Des modèles les plus simplistes aux modèles les plus sophistiqués, la modélisation urbaine a permis de mieux comprendre la question urbaine et ses implications sociétales. Dans ce contexte, les modèles peuvent avoir une valeur-ajoutée appréciable dans le processus de décision publique. Encore faut-il que ces modèles deviennent pratiques et répondent aux contraintes opérationnelles de la chaîne de décision. Dans ce sens, peu de recherches s’est intéressée à la question de praticité des modèles urbains et leur utilisation en situation opérationnelle. À ce jour, les modèles urbains standard qui reposent sur une description agrégée de l’espace sont parmi les approches de modélisation les plus opérationnelles et aussi les plus répandues. De par sa relative praticité, cette approche standard est attractive et simple à mettre en oeuvre. Toutefois, l’agrégation spatiale peut aussi être une source de biais statistiques préjudiciables à la qualité de la modélisation. C’est en particulier, le cas des modèles intégrés Transport-Urbanisme ou des modèles de transport à quatre étapes.La présente thèse a pour objectif d’étudier la question de l’agrégation spatiale dans les modèles transport et plus particulièrement dans les modèles d’affectation des déplacements. Les modèles d’affectation servent à calculer les temps de parcours et les conditions de déplacement sous congestion, présents et futurs, des personnes et des marchandises. Ils servent aussi à calculer les accessibilités nécessaires aux modèles d’usage des sols dont les modèles de choix de localisation des ménages et des entreprises. Toute erreur ou biais dans l’affectation des déplacements peut compromettre la validité et la qualité globales de la modélisation. Dans ce cadre, une attention particulière doit être allouée au problème d’agrégation spatiale dans les modèles d’affectation. Dans ces modèles, l’agrégation spatiale consiste à regrouper les observations individuelles enutilisant une description agrégée de l’espace, i.e. des zones. Par nature, l’utilisation d’une description agrégée à la place d’une représentation continue engendre une omission de l’information et de sa variabilité et donc un biais statistique dans la modélisation. C’est le cas par exemple avec l’utilisation des connecteurs de zones ou avec l’omission des trafics intrazones dans les modèles d’affectation.En reposant sur les zones comme unité spatiale de base, les modèles de transport recourent à l’utilisation des connecteurs de zones pour relier les centroïdes de zones au réseau de transport. Les connecteurs sont des liens fictifs qui modélisent les conditions moyennes d’entrée et de sortie du réseau de transport. Pour ce faire, la majorité des modèles de transport reposent sur une méthode simpliste sujette au problème d’agrégation spatiale. La présente thèse examine en détail l’impact de cette description simpliste sur les résultats et la qualité d’un modèle d’affectation des déplacements en transports en commun. Cette thèse propose aussi une nouvelle méthode de modélisation des connecteurs de zones afin de s’affranchir partiellement du biaisd’agrégation spatiale dans la modélisation des conditions d’accès au réseau des transports en commun.L’utilisation des zones comme unité spatiale de base a aussi pour conséquence l’omission des trafics intrazones de l’affectation des déplacements. Les trafics intrazones ont pour origine et pour destination la même zone et de ce fait ne sont pas pris en compte par les modèles standard d’affectation. Cette omission a souvent été ignorée et son impact sur la qualité de la modélisation demeure non évalué. Cette thèse développe une méthode stochastique pour l’évaluation de cet impact... / Cities are complex systems that urban models can help to comprehend. From simplistic models to more sophisticated ones, urban models have pushed forward our understanding the urban phenomenon and its intricacies. In this context, models can be of great value to policy makers providing that these tools become practical. In this regard, research has put little emphasis on the practicality of urban models and their use under operational conditions.To date, urban models which rely on spatial aggregation are the closest possibility to come to practical models. For this reason, the spatially aggregated modeling framework is widely used. This framework is relatively practical when compared to other modeling frameworks like microsimulation. Nevertheless, spatial aggregation is a serious source of bias in these models. This is especially the case of Land-Use and Transport Interaction (LUTI) models and more particularly of Four Step Models.The current PhD is committed to the study of spatial aggregation issues in traffic assignment models. Traffic assignment is responsable for the computation of travel times and travel conditions of present and future travel demand. Accessibility measurement, which is at the core of LUTI models, is tightly dependent on traffic assignment modeling and outcomes. Any bias in traffic assignment is likely to corrupt the overall modeling framework. In this context, a special attention is to be paid to spatial aggregation in traffic assignment models.In traffic assignment, spatial aggregation consists in grouping observations using zones or traffic analysis zones instead of using a continuous representation of space. By design, aggregation bears an implicit omission in data variability and thus a potential bias if this omission is not random. This is the case with the definition of centroid connectors and the omission of intrazonal demand in traffic assignment. With the use of zones as the basic spatial units, transport models require the use of centroid connectors to attach zones to the transportation network. Centroid connectors are introduced to model average access and egress conditions to and from the network. Nevertheless, average accessibility conditions are found to be too crude to render accurately accessibility conditions as encountered by trip makers. The current PhD explores the extent of the impact of this spatial aggregation bias in the case of transit models and suggests a new modeling strategy to overcome such modeling errors.The use of zones as spatial units induces a loss of intrazonal data. The omission of intrazonal trips in traffic assignment models is an example of such omission. This research introduces an uncertainty framework to study the statistical impact of ignoring intrazonal trips in traffic assignment models. Findings from this research are used to design new assignment strategies that are more robust towards the omission bias and more generally towards the spatial aggregation bias.