Urbanization has considerably altered natural hydrology of urban watersheds by increasing runoff volume, producing higher and faster peak flows, and reducing water quality. Efforts to minimize or avoid these impacts, for example by implementing low impact development (LID) practices, are gaining momentum. Designing effective and economical stormwater management practices at a watershed scale is challenging; LIDs are commonly designed at site scales, considering local hydrologic conditions (i.e., one LID at a time). A number of empirical studies have documented hydrologic and water quality improvements achieved by LIDs. However, watershed scale effectiveness of LIDs has not been well studied. Considering cost, effort, and practicality, computer modeling is the only viable approach to assess LID performance at a watershed scale. As such, the United States Environmental Protection Agency’s Stormwater Management Model (SWMM) was selected for this study. It is well recognized that model predictions are plagued by uncertainties that arise from the lack of quality data and inadequacy of the model to accurately simulate the watershed. To scrutinize sensitivity of prediction accuracies to spatial resolution, four SWMM models of different spatial detail were developed for the Ballona Creek watershed, a highly urbanized watershed in the Los Angeles Basin, as a case study. Detailed uncertainty analyses were carried out for each model to quantify their prediction uncertainties and to examine if a detailed model improves prediction accuracy. Results show that there is a limit to the prediction accuracy achieved by using detailed models. Three of the four models (i.e., all but the least detailed model) produced comparable prediction accuracy. This implies that devoting substantial resources on collecting very detailed data and building fine resolution watershed models may not be necessary, as models of moderate detail could suffice. If confirmed using other urban watersheds, this result could benefit stormwater managers and modelers. All four SWMM models were then used to evaluate hydrologic effectiveness of implementing bioretention cells at a watershed scale. Event based analyses, 1-year, 2-year, 5-year and 10-year storms of 24-hours were considered, as well as data from October 2005 to March 2010 for a continuous simulation. The runoff volume reductions achieved by implementing bioretention cells were not substantial for the event storms. For the continuous simulation analysis, however, about twenty percent reductions in runoff volume were predicted. These results are in-line with previous studies that have reported ineffectiveness of LIDs to reduce runoff volume and peak for less frequent but high intensity storm events.

Spatio-temporal data analysis involves modeling a variable observed at different locations over time. A key component of space-time modeling is determining the spatial scale of the data. This dissertation addresses the following three questions: 1) How does spatial aggregation impact the properties of the variable and its model? 2) What spatial scale of the data produces more accurate forecasts of the aggregate variable? 3) What properties lead to the smallest information loss due to spatial aggregation? Answers to these questions involve a thorough examination of two common space-time models: the STARMA and GSTARMA models. These results are helpful to researchers seeking to understand the impact of spatial aggregation on temporal and spatial correlation as well as to modelers interested in determining a spatial scale for the data. Two data examples are included to illustrate the findings, and they concern states' annual labor force totals and monthly burglary counts for police districts in the city of Philadelphia. / Statistics

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the statistical learning process, yielding regional model features whose construction is driven by model prediction performance rather than prior assumptions. Our results demonstrate that Genetic Programming is particularly well suited to this type of feature construction because it can automatically synthesize appropriate aggregations, as well as better incorporate them into predictive models compared to other regression methods we tested. In our experiments we consider a specific problem instance and real-world dataset relevant to predicting snow properties in high-mountain Asia.

No description available.

Orientador: Marco Antonio de Assis / Banca: Leonor Patricia Cerdeira Morellato / Banca: Marcia Cristina Mendes Marques / Resumo: Estudos abrangendo aspectos da ecologia populacional de plantas fornecem informações importantes sobre os processos de regeneração, ocorrência de perturbações e os meios pelos quais as espécies exploram seus ambientes. Estudos dessa natureza em Florestas de Restinga, feições marcantes no litoral brasileiro, ainda são escassos. Assim, no presente trabalho foram investigados alguns aspectos da ecologia populacional de Calophyllum brasiliense Cambess. (Clusiaceae), uma espécie de ampla ocorrência em ambienteis sujeitos à inundação nas florestas Neotropicais, em 0,5 ha de Floresta de Restinga, localizada no Parque Estadual da Serra do Mar, Núcleo Picinguaba, Ubatuba, SP. Foi realizada uma análise temporal da estrutura de tamanho e do padrão de distribuição espacial da população, visando compreender como a heterogeneidade ambiental, relacionada às variações na microtopografia (mosaico de regiões sobre e entre cordões arenosos), na abertura do dossel da floresta e nas condições de drenagem do solo, afeta os parâmetros da estrutura populacional analisados. Observou-se que a população apresenta estrutura com predomínio de indivíduos nas menores classes de tamanho e distribuição agregada em todas as classes (plântulas, jovens, imaturos e adultos). A saturação hídrica do solo e as diferenças na microtopografia dos cordões arenosos influenciaram o padrão encontrado e afetaram os parâmetros demográficos, entretanto, não foram encontradas correlações entre a abertura de dossel e os parâmetros analisados. Além disso, a análise da estrutura de tamanho em subclasses de altura revelou ausência de indivíduos com alturas entre três e 15 metros, o que pode ser um indicativo de que apesar da população apresentar representantes em todas as classes de tamanho, o acesso dos indivíduos à classe reprodutiva está comprometido... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Studies concerning plant population ecology provide important information about status of regeneration, occurrence of disturbances and the means by which the species exploit the environment. Studies like these, in the "Restingas" forests, striking features in the Brazilian coast, are still scarce. Therefore, we investigated some aspects of population ecology of Calophyllum brasiliense Cambess. (Clusiaceae), in 0.5 ha of the Restinga Forest, in the "Parque Estadual da Serra do Mar", "Núcleo Picinguaba", Municipality of Ubatuba, São Paulo State. We performed a temporal analysis of size structure and spatial pattern, to understand how the environmental heterogeneity, such as microtopography variations, light availability and soil drainage conditions can affect the population structure. Population structure presented dominance of individuals in lower size classes as well as aggregated distribution. These patterns result of both drainage and microtopography conditions, however, no correlations were found between canopy openness and the parameters analyzed. In addition, the size structure analysis, performed into different height classes, showed no individuals with heights between 3 and 15 m, which can suggest that the access to reproductive class seems to be compromised, even though there were individuals within all size classes. It was also observed a high frequency of herbivory damage; however, such damage did not contribute to increase the mortality rate of the population. In general, it could be concluded that environmental heterogeneity has a major influence on the size structure and spatial distribution, mainly in smaller size classes, and that the population seems to have trouble reaching the reproductive stage, which can lead, as a long term, to its disappearance in the area. / Mestre

Over the past several decades conservation easements have seen immense growth in their popularity. There are now over 40 million acres of easement land in the United States, up from only 1.4 million in 1998. A significant body of research exists on easements, factors that lead to their adoption, their consequences and effectiveness, and problems that arise from their use, among other topics. Our study contributes to this literature by exploring community and system-level effects on easement adoption, using Virginia as a case study, and applying a novel approach that incorporates spatial analysis and the insights of conservation professionals. The purpose of our research was to explore whether community-level factors affect easement adoption decisions, and what those factors are. Previously established variables were investigated to gauge their relationship to easement occurrence when scaled up to the community level, as well as to test our ability to make predictions about where easements should be most likely to occur. Spatial market segmentation data was also incorporated into this analysis to determine whether it could augment our understanding of community-level factors and predictive ability. Statistical models produced were reasonably predictive. However, we suspect that this was the case for different reasons at our community scale of analysis than at the individual landowner level examined in previous research. We used surveys and interviews with easement professionals to further explore additional variables that might explain adoption patterns. Results indicate the importance of system-level factors including change agents, opinion leaders, and local government and land-use planning. / Master of Science

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.

Made available in DSpace on 2014-06-11T19:23:03Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-09-02Bitstream added on 2014-06-13T20:29:42Z : No. of bitstreams: 1 freitas_dv_me_rcla.pdf: 971560 bytes, checksum: 12bf77581a5c1c40a7b070f7afebb636 (MD5) / Estudos abrangendo aspectos da ecologia populacional de plantas fornecem informações importantes sobre os processos de regeneração, ocorrência de perturbações e os meios pelos quais as espécies exploram seus ambientes. Estudos dessa natureza em Florestas de Restinga, feições marcantes no litoral brasileiro, ainda são escassos. Assim, no presente trabalho foram investigados alguns aspectos da ecologia populacional de Calophyllum brasiliense Cambess. (Clusiaceae), uma espécie de ampla ocorrência em ambienteis sujeitos à inundação nas florestas Neotropicais, em 0,5 ha de Floresta de Restinga, localizada no Parque Estadual da Serra do Mar, Núcleo Picinguaba, Ubatuba, SP. Foi realizada uma análise temporal da estrutura de tamanho e do padrão de distribuição espacial da população, visando compreender como a heterogeneidade ambiental, relacionada às variações na microtopografia (mosaico de regiões sobre e entre cordões arenosos), na abertura do dossel da floresta e nas condições de drenagem do solo, afeta os parâmetros da estrutura populacional analisados. Observou-se que a população apresenta estrutura com predomínio de indivíduos nas menores classes de tamanho e distribuição agregada em todas as classes (plântulas, jovens, imaturos e adultos). A saturação hídrica do solo e as diferenças na microtopografia dos cordões arenosos influenciaram o padrão encontrado e afetaram os parâmetros demográficos, entretanto, não foram encontradas correlações entre a abertura de dossel e os parâmetros analisados. Além disso, a análise da estrutura de tamanho em subclasses de altura revelou ausência de indivíduos com alturas entre três e 15 metros, o que pode ser um indicativo de que apesar da população apresentar representantes em todas as classes de tamanho, o acesso dos indivíduos à classe reprodutiva está comprometido... / Studies concerning plant population ecology provide important information about status of regeneration, occurrence of disturbances and the means by which the species exploit the environment. Studies like these, in the “Restingas” forests, striking features in the Brazilian coast, are still scarce. Therefore, we investigated some aspects of population ecology of Calophyllum brasiliense Cambess. (Clusiaceae), in 0.5 ha of the Restinga Forest, in the “Parque Estadual da Serra do Mar”, “Núcleo Picinguaba”, Municipality of Ubatuba, São Paulo State. We performed a temporal analysis of size structure and spatial pattern, to understand how the environmental heterogeneity, such as microtopography variations, light availability and soil drainage conditions can affect the population structure. Population structure presented dominance of individuals in lower size classes as well as aggregated distribution. These patterns result of both drainage and microtopography conditions, however, no correlations were found between canopy openness and the parameters analyzed. In addition, the size structure analysis, performed into different height classes, showed no individuals with heights between 3 and 15 m, which can suggest that the access to reproductive class seems to be compromised, even though there were individuals within all size classes. It was also observed a high frequency of herbivory damage; however, such damage did not contribute to increase the mortality rate of the population. In general, it could be concluded that environmental heterogeneity has a major influence on the size structure and spatial distribution, mainly in smaller size classes, and that the population seems to have trouble reaching the reproductive stage, which can lead, as a long term, to its disappearance in the area.

Made available in DSpace on 2014-12-17T14:13:35Z (GMT). No. of bitstreams: 1 JoseWQ_TESE.pdf: 1778874 bytes, checksum: 7ff2c9f470b5b3873803d39a321ee362 (MD5) Previous issue date: 2009-10-05 / This work demonstrates the importance of using tools used in geographic information systems (GIS) and spatial data analysis (SDA) for the study of infectious diseases. Analysis methods were used to describe more fully the spatial distribution of a particular disease by incorporating the geographical element in the analysis. In Chapter 1, we report the historical evolution of these techniques in the field of human health and use Hansen s disease (leprosy) in Rio Grande do Norte as an example. In Chapter 2, we introduced a few basic theoretical concepts on the methodology and classified the types of spatial data commonly treated. Chapters 3 and 4 defined and demonstrated the use of the two most important techniques for analysis of health data, which are data point processes and data area. We modelled the case distribution of Hansen s disease in the city of Mossor? - RN. In the analysis, we used R scripts and made available routines and analitical procedures developed by the author. This approach can be easily used by researchers in several areas. As practical results, major risk areas in Mossor? leprosy were detected, and its association with the socioeconomic profile of the population at risk was found. Moreover, it is clearly shown that his approach could be of great help to be used continuously in data analysis and processing, allowing the development of new strategies to work might increase the use of such techniques in data analysis in health care / O presente trabalho demonstra a import?ncia do uso de ferramentas relacionadas ? sistemas de informa??o geogr?fica (SIG) e an?lise espacial de dados (AED) em estudos de doen?as infecciosas. M?todos de an?lise foram usados para descrever de forma mais abrangente a distribui??o espacial de doen?as a partir da incorpora??o do elemento geogr?fico na an?lise. No Cap?tulo 1 relata-se a evolu??o hist?rica da aplica??o destas t?cnicas no campo da sa?de humana e elege-se a hansen?ase no estado do Rio Grande do Norte como exemplo de aplica??o. No Cap?tulo 2 introduzem-se alguns conceitos te?ricos b?sicos sobre a metodologia e classificam-se os tipos de dados espaciais comumente tratados. Os Cap?tulos 3 e 4 definem e demonstram a utiliza??o das mais importantes t?cnicas de an?lise para os dois principais tipos de dados encontrados na sa?de, quais sejam dados de processos pontuais e dados de ?rea, focalizando como estudo de caso a hansen?ase na cidade de Mossor? RN. Na an?lise, ? priorizada a utiliza??o do sistema R, disponibilizando-se scripts de rotinas e procedimentos de an?lise desenvolvidos pelo autor que podem ser facilmente utilizados por pesquisadores de diversas ?reas. Como resultados pr?ticos, importantes ?reas de risco da hansen?ase em Mossor? foram detectadas e sua forte associa??o com o perfil socioecon?mico da popula??o sob risco foi constatada. Al?m disso, estima-se que este trabalho possa vir a incrementar a utiliza??o de tais t?cnicas na an?lise de dados na ?rea de sa?de

[ES] Actualmente, el 54% de la población mundial vive en ciudades y se espera que en 2050 este porcentaje aumente al 68% (UNDESA, 2019). Una parte importante de esta población urbana se concentra en megaciudades, definidas como áreas urba-nas con más de 10 millones de habitantes. En América Latina, las principales megaciudades son Sao Paulo y Ciudad de México, con más de 20 millones de habitantes en cada una. Buenos Aires, Río de Janeiro, Lima y Bogotá son mega-ciudades aún en desarrollo (Cepal, 2013). La presente tesis doctoral tiene como objetivo identificar y analizar los impactos que la dinámica de crecimiento urbano de una megaciudad induce sobre el com-portamiento de las componentes del ciclo hidrológico. La investigación desarro-llada incorpora el efecto del cambio climático de forma conjunta con el efecto del cambio de uso de suelo urbano. Para ello, se ha planteado una metodología de agregación de parámetros hidrológicos en superficies urbanas que se ha aplicado a la megaciudad de Bogotá, utilizando el modelo hidrológico TETIS y el modelo de cambios de uso de suelo LCM, bajo los escenarios oficiales de cambio climático vigentes en Colombia. Los resultados obtenidos muestran que el análisis conjunto de cambio de uso de suelo y cambio climático proporciona herramientas valiosas para comprender el comportamiento hidrológico de la cuenca en la que se sitúan las megaciudades y predecir su evolución futura. En el caso de la megaciudad de Bogotá se ha obser-vado que el mayor efecto en las componentes del ciclo hidrológico se produce por el cambio de usos de suelo, el cual se ve incrementado por las acciones inducidas por el cambio climático. La utilización de modelos numéricos que consideren todos estos aspectos es de especial relevancia a la hora de definir los planes, políti-cas y programas de desarrollo en entornos densamente urbanizados. / [CA] Actualment, el 54% de la població mundial viu a ciutats i s'espera que el 2050 aquest percentatge augmenti al 68% (UNDESA, 2019). Una part important d'a-questa població urbana es concentra en megaciutats, definides com a àrees urba-nes amb més de 10 milions d'habitants. A Amèrica Llatina, les principals mega-ciutats són Sao Paulo i Ciutat de Mèxic, amb més de 20 milions d'habitants a cadascuna. Buenos Aires, Rio de Janeiro, Lima i Bogotá són megaciutats encara en desenvolupament (Cepal, 2013). Aquesta tesi doctoral té com a objectiu identificar i analitzar els impactes que la dinàmica de creixement urbà d'una megaciutat indueix sobre el comportament dels components del cicle hidrològic. La investigació desenvolupada incorpora l'efecte del canvi climàtic de forma conjunta amb l'efecte del canvi d'ús de sòl urbà. Per això, s'ha plantejat una metodologia d'agregació de paràmetres hidrolò-gics en superfícies urbanes que s'ha aplicat a la megaciutat de Bogotà, utilitzant el model hidrològic TETIS i el model de canvis d'ús de sòl LCM, sota els escenaris oficials de canvi climàtic vigents a Colòmbia. Els resultats obtinguts mostren que l'anàlisi conjunta de canvi d'ús de sòl i canvi climàtic proporciona eines valuoses per comprendre el comportament hidrològic de la conca on se situen les megaciutats i predir-ne l'evolució futura. En el cas de la megaciutat de Bogotà s'ha observat que l'efecte més gran en les components del cicle hidrològic es produeix pel canvi d'usos de sòl, el qual es veu incrementat per les accions induïdes pel canvi climàtic. La utilització de models numèrics que considerin tots aquests aspectes és especialment rellevant a l'hora de definir els plans, polítiques i programes de desenvolupament en entorns densament urbanit-zats / [EN] Currently 54% of the world population lives in cities and it is expected that by 2050 this percentage will increase to 68% (UNDESA, 2019). An important part of this urban population is concentrated in megacities, defined as urban areas with more than 10 million inhabitants. In Latin America, the main megacities are Sao Paulo and Mexico City, with more than 20 million inhabitants. Buenos Aires, Rio de Janeiro, Lima and Bogotá are megacities still in development (Cepal, 2013). This doctoral thesis aims to identify and analyse the impacts that the dynamics of urban growth of a megacity induce on the behaviour of of the hydrological cycle components. The research carried out incorporates the effect of climate change together with the effect of urban land use change. To do this, a methodology for aggregating hydrological parameters in urban areas has been proposed. This methodology has been applied to the megacity of Bogotá, using the TETIS hydro-logical model and the LCM land use change model, under the official climate change scenarios in force in Colombia. Results obtained show that the joint analysis of land use change and climate change provides valuable tools to understand the hydrological behaviour of the basin in which the megacities are located and predict their future evolution. In the case of the megacity of Bogotá, it has been observed that the greatest effect on the components of the hydrological cycle is produced by the land use change, which is increased by the actions induced by climate change. The use of numeri-cal models that consider all these aspects is of special relevance when defining development plans, policies and programs in densely urbanized environments. / Romero Hernández, CP. (2022). Análisis del impacto del crecimiento de las megaciudades sobre el ciclo hidrológico bajo escenarios de cambio climático. Aplicación a la cuenca del río Bogotá (Colombia) [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/191025