Academic literature on the topic 'Urban Spatial analysis (Statistics)'

Fatal automobile crashes have claimed the lives of over 33,000 people each year in the United States since 1995. As in any point event, fatal crash events do not occur randomly in time or space. The objectives of this study were to identify spatial patterns and hot spots in FARS (Fatal Analysis Reporting System) fatal crash events based on temporal and demographic characteristics. The methods employed included 1) rate calculation using FARS points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and Warren County. Rate calculation analyses revealed that travel on roads with high speed limits and winding topography led to the highest number of crashes and highest rate of fatal crashesper 1,000 daily vehicles. Planar kernel density estimation results showed temporalpatterns, revealing that ‘hot spots’ and fatalities were highest in the summer, and typically occurred from 2pm-6pm on the weekends. Further, the 16 to 25 year age group was responsible for the most significant ‘hot spots’ and the most fatal accidents. Also showing that the most significant hot spots involving alcohol occurring in close proximity to meeting places such as bars and restaurants. Finally, results from the network kernel density estimation revealed that most hot spots were in high traffic areas of where majorr oads converged with secondary roads.

With increasing levels of motor vehicle ownership, automobile crashes have become a serious public issue in the U.S. and around the world. Knowing when, where, and how traffic accidents happen is critical in order to ensure road safety and to plan for adequate road infrastructure. There is a rich body of literature pertaining to time-related fatal crashes, most of which focuses on non-spatial factors such as a driver’s visibility at night, drinking and drug use, and road conditions. These studies provide a theoretical basis for understanding the causes of crashes from a non-spatial perspective, and a number of traffic laws and policies consequently have been enacted to minimize the impacts of non-spatial factors. Over the past few years, advances in Geographic Information Systems (GIS) have greatly enhanced our ability to analyze traffic accidents from a spatial perspective. This study aims to fill a void in traffic safety studies by comparing and analyzing the differences in the spatial distribution of fatal crashes based on temporal factors, specifically in three periods: 1) day and night; 2) A.M. rush hours and P.M. rush hours; and 3) weekdays and weekends. With the Nashville Metropolitan Area as the study area, the research utilized a number of spatial point-pattern analysis (SPPA) methods, including planar KDE, planar global auto K function, network global cross K functions, and network local cross K functions. All fatal crashes in the Nashville area were found to be clustered and generally follow the patterns of average daily traffic flow. All time-based subtypes of fatal crashes also were found to be concentrated within the central urban area of Nashville, mostly along major roads, and especially near major road intersections and highway interchanges. No notable spatial differences were detected among the subtypes of fatal crashes when applying network global cross K function. However, with the help of the network local cross K function, some localized spatial differences were identified. Some specific locations of hotspots of nighttime and P.M. rush hour fatal crashes were found not to be at the same locations as those at of daytime and A.M. rush hour fatal crashes, respectively. The approach adopted in this study not only provides a new way to analyze spatial distribution of spatial point events such as fatal crashes, but it also can be applied readily to real-world applications. A good understanding of where these spatial differences are should help various agencies practice effective measures and policies in order to improve road conditions, reduce traffic accidents, and ensure road safety.

Orientador: Roberto Wagner Lourenço<br>Resumo: O controle dos vetores do mosquito Aedes aegypti apresenta como um dos principais problemas de saúde pública no mundo representado por duas vertentes importantes como o cuidado com o meio ambiente e pelo investimento em ciência. A preocupação com o meio ambiente é uma das maneiras mais eficazes de conter a reprodução do mosquito Aedes aegypti que, segundo Organização Mundial da Saúde, infecta cerca de 100 milhões de pessoas por ano. Esta pesquisa teve como objetivo principal analisar a distribuição espacial dos casos de dengue confirmados autóctones e importados, bem como dos recipientes de larvas do mosquito no município de Itu, São Paulo no período de 2005 a 2014. Para o desenvolvimento do trabalho foi realizada uma pesquisa junto à Vigilância Epidemiológico da área de estudo para obtenção dos dados, acompanhada de pesquisa bibliográfica e trabalho de campo. Os dados foram tratados por meio de técnicas de geoprocessamento e análise estatística exploratória. Os resultados obtidos demonstraram uma crescente alta de casos e de incidência ao longo dos anos estudados da faixa de 10 anos, sendo que os casos autóctones se sobrepõe em termos de ocorrência aos importados em 88 %. Além disso, foi possível verificar uma distribuição espacial com maiores ocorrências nas regiões centrais da área urbana do município estudado, apresentando as maiores concentrações nos anos de 2007, 2009, 20011 e 2013 do total analisado, com distribuição tendendo para a direção sudeste-noroeste da área de ... (Resumo completo, clicar acesso eletrônico abaixo)<br>Abstract: The control of the vectors of the mosquito Aedes aegypti presents as one of the main problems of public health in the world acted by two important slopes as the care with the environment and for the investment in science. The concern with the environment is one in the most effective ways of containing the reproduction of the mosquito Aedes aegypti that, second World Organization of the Health, infects about 100 million people a year. This research had as main objective to analyze the space distribution of the cases of primness confirmed autochthonous and mattered, as well as of the containers of larvas of the mosquito in the municipal district of Itu, São Paulo in the period of 2005 the 2014. For the development of the work a research was accomplished the Surveillance Epidemic of the study area close to for obtaining of the data, accompanied of bibliographical research and field work. The data were treated through geoprocessamento techniques and exploratory statistical analysis. The obtained results demonstrated a crescent high of cases and of incidence along the studied years of the 10 year-old strip, and the autochthonous cases are put upon in occurrence terms to the mattered in 88%. Besides, it was possible to verify a space distribution with larger occurrences in the central areas of the urban area of the studied municipal district, presenting the largest concentrations in the years of 2007, 2009, 20011 and 2013 of the analyzed total, with distribution tending for the sou... (Complete abstract click electronic access below)<br>Mestre

[ES] Esta tesis aborda el desarrollo y análisis de nuevas herramientas y métodos para monitorizar y caracterizar el crecimiento urbano utilizando datos geográficos y bases de datos de usos y coberturas del suelo (LULC), así como explorar sus relaciones con factores socioeconómicos, aportando nuevas evidencias sobre el uso de los datos LULC para la caracterización urbana en diferentes niveles mediante métodos espaciales y estadísticos. En primer lugar, se compilaron e implementaron las métricas espacio-temporales más comunes dentro de una herramienta software, IndiFrag. A continuación, se presenta una metodología basada en métricas espacio-temporales y se propone un nuevo índice que cuantifica la desigualdad entre el crecimiento de la población y las zonas edificadas, para analizar y comparar los patrones de crecimiento urbano en diferentes niveles. Esto permitió una distinción de los patrones de crecimiento, además el análisis a diversos niveles contribuyó a una mejor comprensión de los patrones. En segundo lugar, se cuantificaron relaciones bidireccionales entre la estructura urbana de las ciudades y su situación socioeconómica a partir de métricas espaciales extraídas de mapas de zonas climáticas locales en 31 ciudades en Renania del Norte-Westfalia (Alemania). A partir de estos datos se cuantificaron relaciones con indicadores socioeconómicos mediante modelos de regresión lineal múltiple, explicando gran parte de su variabilidad. El método propuesto es transferible a otros conjuntos de datos, niveles y regiones. En tercer lugar, se evaluó el uso de las métricas espacio-temporales derivadas de los mapas LULC para identificar patrones espaciales de crecimiento urbano. Se utilizaron modelos de cambio de usos del suelo para simular diferentes escenarios de crecimiento urbano a largo plazo siguiendo varios patrones espaciales en diversas formas urbanas de partida. A continuación, se calcularon las métricas espacio-temporales para los escenarios simulados, se seleccionaron las más explicativas aplicando análisis discriminante y se clasificaron los patrones de crecimiento utilizando métodos estadísticos de agrupación. Por último, se identificaron relaciones empíricas entre indicadores socioeconómicos y su evolución a lo largo del tiempo con la estructura espacial de los elementos construidos y naturales en hasta 600 áreas urbanas de 32 países. Se aplicaron modelos de regresión random forest y las métricas espacio-temporales fueron capaces de explicar considerablemente la variabilidad de los indicadores socioeconómicos, confirmando que los patrones espaciales y sus cambios están vinculados a los indicadores socioeconómicos. Este trabajo contribuye a una mayor comprensión de los patrones de crecimiento urbano y amplía el conocimiento sobre las relaciones entre la estructura espacial urbana y los factores socioeconómicos. Se describen nuevos métodos para monitorizar y evaluar la sostenibilidad urbana a partir de bases de datos LULC, que podrían ser utilizadas por los investigadores, planificadores urbanos y responsables políticos para garantizar un futuro sostenible en los entornos urbanos.<br>[CAT] Aquesta tesi aborda el desenvolupament i l'anàlisi de noves ferramentes i mètodes per a monitorar i caracteritzar el creixement urbà utilitzant dades geogràfiques i bases de dades d'usos i cobertures del sòl (LULC), així com explorar les seues relacions amb factors socioeconòmics, i aportar noves evidències sobre la utilització de les dades LULC per a la caracterització urbana en diferents nivells mitjançant mètodes espacials i estadístics. En primer lloc, es van compilar i implementar mètriques espaciotemporals dins d'un programari, IndiFrag. A continuació, es presenta una metodologia basada en mètriques espaciotemporals i es proposa un nou índex que quantifica la desigualtat entre el creixement de la població i les zones edificades, i serveix per a analitzar i comparar els patrons de creixement urbà a diferents nivells. Això va permetre una distinció dels patrons de creixement, a més l'anàlisi a diversos nivells va contribuir a una millor comprensió dels patrons. En segon lloc, es van quantificar relacions bidireccionals entre l'estructura urbana de les ciutats i la seua situació socioeconòmica a partir de mètriques espacials extretes de mapes de zones climàtiques locals en 31 ciutats a Renània del Nord-Westfàlia (Alemanya). A partir d'aquestes dades es van quantificar relacions amb indicadors socioeconòmics mitjançant models de regressió lineal múltiple, explicant gran part de la seua variabilitat. El mètode proposat és transferible a altres conjunts de dades, nivells i regions. Seguidament, es va avaluar l'ús de les mètriques espaciotemporals derivades dels mapes LULC per a identificar patrons espacials de creixement urbà. Es van utilitzar models de canvi d'usos del sòl per a simular diferents escenaris de creixement urbà a llarg termini seguint diversos patrons espacials en diverses formes urbanes de partida. A continuació, es van calcular les mètriques espaciotemporals per als escenaris simulats, es van seleccionar les més explicatives aplicant anàlisi discriminant i es van classificar els patrons de creixement utilitzant mètodes estadístics d'agrupació. Finalment, es van identificar relacions empíriques entre indicadors socioeconòmics i la seua evolució al llarg del temps, amb l'estructura espacial dels elements construïts i naturals en fins a 600 àrees urbanes de 32 països. Es van aplicar models de regressió random forest i les mètriques van ser capaces d'explicar considerablement la variabilitat dels indicadors socioeconòmics, això confirma que els patrons espacials i els seus canvis estan vinculats als indicadors socioeconòmics. Aquest treball contribueix a una major comprensió dels patrons de creixement urbà i amplia el coneixement sobre les relacions entre l'estructura espacial urbana i els factors socioeconòmics. Es descriuen nous mètodes per a monitorar i avaluar la sostenibilitat urbana a partir de bases de dades LULC, que podrien ser utilitzades pels investigadors, planificadors urbans i responsables polítics per a garantir un futur sostenible en els entorns urbans.<br>[EN] This thesis addresses the development and analysis of new tools and methods for monitoring and characterizing urban growth using geo-data and land-use/land-cover (LULC) databases, as well as exploring their relationships with socio-economic factors, providing new evidences regarding the use of LULC data for urban characterization at different levels by means of spatial and statistical methods. First, the most common spatio-temporal metrics were compiled and implemented within a software tool, IndiFrag. Then, we present a methodology based on spatio-temporal metrics and propose a new index that quantifies the inequality of growth between population and built-up areas to analyze and compare urban growth patterns at different levels. This allowed for a differentiation of growing patterns, besides, the analysis at various levels contributed to a better understanding of such patterns. Second, we quantified the two-way relationship between the urban structure in cities and their socio-economic status by means of spatial metrics issued from a local climate zone map for 31 cities in North Rhine-Westphalia, Germany. Based on these data, we quantified their relationship with socio-economic indicators by means of multiple linear regression models, explaining a significant part of their variability. The proposed method is transferable to other datasets, levels, and regions. Third, we assessed the use of spatio-temporal metrics derived from LULC maps to identify urban growth spatial patterns. We applied LULC change models to simulate different long-term scenarios of urban growth following various spatial patterns on diverse baseline urban forms. Then, we computed spatio-temporal metrics for the simulated scenarios, selected the most explanatory by applying a discriminant analysis and classified the growth patterns using clustering methods. Finally, we identified empirical relationships between socio-economic indicators and their change over time with the spatial structure of the built and natural elements in up to 600 urban areas from 32 countries. We employed random forest regression models and the spatio-temporal metrics were able to explain substantially the variability of socio-economic variables. This confirms that spatial patterns and their change are linked to socio-economic indicators. This work contributes to a better understanding of urban growth patterns and improves knowledge about the relationships between urban spatial structure and socio-economic factors, providing new methods for monitoring and assessing urban sustainability by means of LULC databases, which could be used by researchers, urban planners and decision-makers to ensure the sustainable future of urban environments.<br>Sapena Moll, M. (2020). Development and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158626<br>TESIS

O objetivo deste estudo é explorar uma metodologia para análises de autocorrelação em redes utilizando um atributo de fenômenos cuja ocorrência esteja de alguma forma vinculada ou que seja dependente de uma rede. Para isso foram utilizados dados de acidentes de trânsito em um estudo de caso para a cidade de São Carlos, referentes aos anos de 2001, 2002 e 2003. Foram considerados inicialmente os dados totais dos acidentes e, em seguida, separados por tipos (atropelamentos, acidentes com danos materiais e acidentes com vítimas). A próxima etapa considerou os valores dos acidentes totais majorados pela UPS (Unidade Padrão de Severidade). A última etapa do estudo levou ainda em consideração a localização dos acidentes nos arcos ou interseções, que permitiu concluir que esta forma de caracterização espacial dos acidentes pode interferir significativamente nos resultados da análise. Outra conclusão relevante foi a identificação de autocorrelação espacial elevada e positiva no caso estudado. Finalmente a comparação com análise semelhante realizada por áreas demonstra vantagens para a análise por redes.<br>The objective of this study is to explore a methodology for network spatial autocorrelation analysis by applying it to an attribute of phenomena that are somehow connected to or dependent of a network. In other to do so, traffic accident data recorded in the years 2001, 2002, and 2003 in the city of São Carlos were selected for a case study. A first analysis considered all data, followed by analyses per accident type. In another phase of the study, the total accidents were weighted according to their severity. The last part of the study included in the analysis information about the location of each accident, either at a link or at an intersection. A conclusion drawn from the later analysis indicated that the consideration of the accidents locations can produce significant changes in the results. Another relevant conclusion was the identification of high and positive spatial autocorrelation in the case studied. Finally, the comparison with a similar analysis carried out with areas shows advantages for the network analysis.