This dissertation describes the design and implementation of a computer vision based varve image analysis system. The primary issues covered are software engineering design, varve image calibrations, varve image enhancement, varve Dynamic Spatial Warping (DSW) profile generation, varve core image registration, varve identification, boundary identification and varve thickness measurement. A varve DSW matching algorithm is described to generate DSW profile and register two core images. Wavelet Multiple Resolution Analysis (MRA) is also used to do the core image registrations. By allowing an analyst to concentrate on other research work while the VARVES software analyzes a sample, much of the tedious varve analysis work is reduced, and potentially increasing the productivity. Additionally, by using new computer vision techniques, VARVES system is able to do some varve analysis which was impossible handled manually.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A Ilha Grande situa-se na chamada Costa Verde do Estado do Rio de Janeiro, tem a totalidade de seu território protegido legalmente e vem sendo alvo de especuladores e investidores cujos interesses são, principalmente, explorar o potencial natural do bioma de Mata Atlântica. Observa-se um processo de transformação local em diversos aspectos que englobam o meio ambiente e a sociedade, como a degradação ambiental e o deslocamento da comunidade tradicional. O Poder Público manteve-se distante ou mesmo ausente por décadas, o que possibilitou a instalação de problemas ambientais e a configuração de conflitos na esfera do planejamento e gestão. Considerando-se a relevância socioambiental deste território insular e, em especial, com a implantação do Centro de Estudos Ambientais e Desenvolvimento Sustentável (CEADS) da Universidade do Estado do Rio de Janeiro (UERJ) na Enseada de Dois Rios, o presente estudo tem como objetivo identificar a dinâmica ambiental estabelecida na ilha. Os aspectos relacionados ao uso e ocupação do solo e à fragilidade ambiental são fundamentais para a análise integrada, para a compreensão da configuração atual do território e para a formulação de diretrizes de desenvolvimento adequadas à complexa realidade da Ilha Grande, cuja atividade econômica está pautada no turismo. Identificou-se como as principais causas dos problemas ambientais e dos conflitos de gestão: o caótico ordenamento do território, a falta de infraestrutura de serviços, a dificuldade de mobilização social, a falta de integração entre as políticas públicas e competências administrativas, a precariedade da fiscalização, a impunidade aos que não cumpriram a normatização em vigor e, a não observância da fragilidade ambiental do geossistema Ilha Grande. / The Ilha Grande is situated on the so called Costa Verde of Rio de Janeiro State. The totality of its territory is legally protected, and it has recently become the target of speculators and investors whose interests are mainly the exploration of the rainforests biome natural potential. There is a process of local transformation in many aspects relating to the environment and the society, for instance, the environmental degradation and the displacement of traditional communities. The State has kept its distance, being absent for decades, a fact that has contributed to the advent of environmental problems and of conflicts on the planning and management spheres. Considering the socioenvironmental relevance of this island territory and specially considering the installation of the Center for Environmental Studies and Sustainable Development (CEADS) of Rio De Janeiro State University (UERJ) in the Dois Rios cove, this study has the goal of identifying the environmental dynamics of the Ilha Grande. The aspects relating to the use and occupation of the soil and to the environmental frailty are crucial for developing an integrated analysis, comprehending the current configuration of the territory and formulating development guidelines which are adequate to the complex reality of the Ilha Grande, whose economic activity is based on tourism. The study has identified the main causes behind the environmental problems and the management conflicts: the chaotic planning of the territory, the lack of a services infrastructure, the difficulty in social mobilizations, the lack of integration between public policies and administrative jurisdictions, the precarious supervision, the impunity to those who fail to comply with current laws and the disregard for the environmental frailty of the Ilha Grande geosystem.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A Ilha Grande situa-se na chamada Costa Verde do Estado do Rio de Janeiro, tem a totalidade de seu território protegido legalmente e vem sendo alvo de especuladores e investidores cujos interesses são, principalmente, explorar o potencial natural do bioma de Mata Atlântica. Observa-se um processo de transformação local em diversos aspectos que englobam o meio ambiente e a sociedade, como a degradação ambiental e o deslocamento da comunidade tradicional. O Poder Público manteve-se distante ou mesmo ausente por décadas, o que possibilitou a instalação de problemas ambientais e a configuração de conflitos na esfera do planejamento e gestão. Considerando-se a relevância socioambiental deste território insular e, em especial, com a implantação do Centro de Estudos Ambientais e Desenvolvimento Sustentável (CEADS) da Universidade do Estado do Rio de Janeiro (UERJ) na Enseada de Dois Rios, o presente estudo tem como objetivo identificar a dinâmica ambiental estabelecida na ilha. Os aspectos relacionados ao uso e ocupação do solo e à fragilidade ambiental são fundamentais para a análise integrada, para a compreensão da configuração atual do território e para a formulação de diretrizes de desenvolvimento adequadas à complexa realidade da Ilha Grande, cuja atividade econômica está pautada no turismo. Identificou-se como as principais causas dos problemas ambientais e dos conflitos de gestão: o caótico ordenamento do território, a falta de infraestrutura de serviços, a dificuldade de mobilização social, a falta de integração entre as políticas públicas e competências administrativas, a precariedade da fiscalização, a impunidade aos que não cumpriram a normatização em vigor e, a não observância da fragilidade ambiental do geossistema Ilha Grande. / The Ilha Grande is situated on the so called Costa Verde of Rio de Janeiro State. The totality of its territory is legally protected, and it has recently become the target of speculators and investors whose interests are mainly the exploration of the rainforests biome natural potential. There is a process of local transformation in many aspects relating to the environment and the society, for instance, the environmental degradation and the displacement of traditional communities. The State has kept its distance, being absent for decades, a fact that has contributed to the advent of environmental problems and of conflicts on the planning and management spheres. Considering the socioenvironmental relevance of this island territory and specially considering the installation of the Center for Environmental Studies and Sustainable Development (CEADS) of Rio De Janeiro State University (UERJ) in the Dois Rios cove, this study has the goal of identifying the environmental dynamics of the Ilha Grande. The aspects relating to the use and occupation of the soil and to the environmental frailty are crucial for developing an integrated analysis, comprehending the current configuration of the territory and formulating development guidelines which are adequate to the complex reality of the Ilha Grande, whose economic activity is based on tourism. The study has identified the main causes behind the environmental problems and the management conflicts: the chaotic planning of the territory, the lack of a services infrastructure, the difficulty in social mobilizations, the lack of integration between public policies and administrative jurisdictions, the precarious supervision, the impunity to those who fail to comply with current laws and the disregard for the environmental frailty of the Ilha Grande geosystem.

<p>The modelling and analysis of complex stochastic systems with increasingly large data sets, state-spaces and parameters provides major stimulus to research in Bayesian nonparametric methods and Bayesian computation. This dissertation presents advances in both nonparametric modelling and statistical computation stimulated by challenging problems of analysis in complex spatio-temporal systems and core computational issues in model fitting and model assessment. The first part of the thesis, represented by chapters 2 to 4, concerns novel, nonparametric Bayesian mixture models for spatial point processes, with advances in modelling, computation and applications in biological contexts. Chapter 2 describes and develops models for spatial point processes in which the point outcomes are latent, where indirect observations related to the point outcomes are available, and in which the underlying spatial intensity functions are typically highly heterogenous. Spatial intensities of inhomogeneous Poisson processes are represented via flexible nonparametric Bayesian mixture models. Computational approaches are presented for this new class of spatial point process mixtures and extended to the context of unobserved point process outcomes. Two examples drawn from a central, motivating context, that of immunofluorescence histology analysis in biological studies generating high-resolution imaging data, demonstrate the modelling approach and computational methodology. Chapters 3 and 4 extend this framework to define a class of flexible Bayesian nonparametric models for inhomogeneous spatio-temporal point processes, adding dynamic models for underlying intensity patterns. Dependent Dirichlet process mixture models are introduced as core components of this new time-varying spatial model. Utilizing such nonparametric mixture models for the spatial process intensity functions allows the introduction of time variation via dynamic, state-space models for parameters characterizing the intensities. Bayesian inference and model-fitting is addressed via novel particle filtering ideas and methods. Illustrative simulation examples include studies in problems of extended target tracking and substantive data analysis in cell fluorescent microscopic imaging tracking problems.</p><p>The second part of the thesis, consisting of chapters 5 and chapter 6, concerns advances in computational methods for some core and generic Bayesian inferential problems. Chapter 5 develops a novel approach to estimation of upper and lower bounds for marginal likelihoods in Bayesian modelling using refinements of existing variational methods. Traditional variational approaches only provide lower bound estimation; this new lower/upper bound analysis is able to provide accurate and tight bounds in many problems, so facilitates more reliable computation for Bayesian model comparison while also providing a way to assess adequacy of variational densities as approximations to exact, intractable posteriors. The advances also include demonstration of the significant improvements that may be achieved in marginal likelihood estimation by marginalizing some parameters in the model. A distinct contribution to Bayesian computation is covered in Chapter 6. This concerns a generic framework for designing adaptive MCMC algorithms, emphasizing the adaptive Metropolized independence sampler and an effective adaptation strategy using a family of mixture distribution proposals. This work is coupled with development of a novel adaptive approach to computation in nonparametric modelling with large data sets; here a sequential learning approach is defined that iteratively utilizes smaller data subsets. Under the general framework of importance sampling based marginal likelihood computation, the proposed adaptive Monte Carlo method and sequential learning approach can facilitate improved accuracy in marginal likelihood computation. The approaches are exemplified in studies of both synthetic data examples, and in a real data analysis arising in astro-statistics.</p><p>Finally, chapter 7 summarizes the dissertation and discusses possible extensions of the specific modelling and computational innovations, as well as potential future work.</p> / Dissertation

Many databases involve ordered discrete responses in a temporal and spatial context, including, for example, land development intensity levels, vehicle ownership, and pavement conditions. An appreciation of such behaviors requires rigorous statistical methods, recognizing spatial effects and dynamic processes. This dissertation develops a dynamic spatial ordered probit (DSOP) model in order to capture patterns of spatial and temporal autocorrelation in ordered categorical response data. This model is estimated in a Bayesian framework using Gibbs sampling and data augmentation, in order to generate all autocorrelated latent variables. The specifications, methodologies, and applications undertaken here advance the field of spatial econometrics while enhancing our understanding of land use and air quality changes. The proposed DSOP model incorporates spatial effects in an ordered probit model by allowing for inter-regional spatial interactions and heteroskedasticity, along with random effects across regions (where "region" describes any cluster of observational units). The model assumes an autoregressive, AR(1), process across latent response values, thereby recognizing time-series dynamics in panel data sets. The model code and estimation approach is first tested on simulated data sets, in order to reproduce known parameter values and provide insights into estimation performance. Root mean squared errors (RMSE) are used to evaluate the accuracy of estimates, and the deviance information criterion (DIC) is used for model comparisons. It is found that the DSOP model yields much more accurate estimates than standard, non-spatial techniques. As for model selection, even considering the penalty for using more parameters, the DSOP model is clearly preferred to standard OP, dynamic OP and spatial OP models. The model and methods are then used to analyze both land use and air quality (ozone) dynamics in Austin, Texas. In analyzing Austin's land use intensity patterns over a 4-point panel, the observational units are 300 m × 300 m grid cells derived from satellite images (at 30 m resolution). The sample contains 2,771 such grid cells, spread among 57 clusters (zip code regions), covering about 10% of the overall study area. In this analysis, temporal and spatial autocorrelation effects are found to be significantly positive. In addition, increases in travel times to the region's central business district (CBD) are estimated to substantially reduce land development intensity. The observational units for the ozone variation analysis are 4 km × 4 km grid cells, and all 132 observations falling in the study area are used. While variations in ozone concentration levels are found to exhibit strong patterns of temporal autocorrelation, they appear strikingly random in a spatial context (after controlling for local land cover, transportation, and temperature conditions). While transportation and land cover conditions appear to influence ozone levels, their effects are not as instantaneous, nor as practically significant as the impact of temperature. The proposed and tested DSOP model is felt to be a significant contribution to the field of spatial econometrics, where binary applications (for discrete response data) have been seen as the cutting edge. The Bayesian framework and Gibbs sampling techniques used here permit such complexity, in world of two-dimensional autocorrelation. / text

Submitted by Geyciane Santos (geyciane_thamires@hotmail.com) on 2015-07-27T14:31:20Z No. of bitstreams: 1 Dissertação -Jurimar Collares Ipiranga.pdf: 6045469 bytes, checksum: cb2f46a3bb5ec4c10c0fb95454fb7b36 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-28T14:51:15Z (GMT) No. of bitstreams: 1 Dissertação -Jurimar Collares Ipiranga.pdf: 6045469 bytes, checksum: cb2f46a3bb5ec4c10c0fb95454fb7b36 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-28T14:57:53Z (GMT) No. of bitstreams: 1 Dissertação -Jurimar Collares Ipiranga.pdf: 6045469 bytes, checksum: cb2f46a3bb5ec4c10c0fb95454fb7b36 (MD5) / Made available in DSpace on 2015-07-28T14:57:53Z (GMT). No. of bitstreams: 1 Dissertação -Jurimar Collares Ipiranga.pdf: 6045469 bytes, checksum: cb2f46a3bb5ec4c10c0fb95454fb7b36 (MD5) Previous issue date: 2007-02-12 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The space dynamic modelling technique stands out by its capacity to show the landscape evolution of the Tarumã Mirim Stablishment Project in a predctive way, assisting studies on the use of natural resources, territorial planning and allowing a view of the presence or absence of specific public policies. That is because the planning of a rural settlement must take into account the land use and its positive or negative impacts generated in this process. The evolution of that landscape since the creation of the PA, in march 1992, makes possible a stochastic projection for 2011, even it was made during the erlier period of 1995 to 2003. That projection was able to report growth rates and removal of vegetation carried out by human action. It was used two scenes of the orbit 231 and section 062 of the years 1995 and 2003, properly cut from the area of study and applying the Markov Chains Theory, supported by remote sensing technique that delimited the area. It was classified the land use and land cover. It was made the cross-tabulation of the classes showing the transition between them and the probability of changes and projection of land use for 2011. From 42,910.760 hectares intended for settlement and farming family in 1995, wich is the baseline time for predictive modeling, it was identified by the classification of land use in order to 1,119.60 ha, in 2003 3,075.30 ha and a projection of land use for 2011 about 10,023.30 ha, and the removal of vegetation cover in 1995 47,069.10 ha, in 2003 45,113.40 ha and the projection of vegetation removed for 2011 (simulation) is about 38,165.40 hectares deforested. The study revealed in its modeling of the dynamics use of land for future scenarios, a concerning situation that should be reviewed and demands a special attention referred to positive and negative environmental and hydrological network, recommended in the plan for environmental control and protection of ciliary forests. / A modelagem dinâmica espacial destaca-se por ter a capacidade de apresentar a evolução da paisagem do Projeto de Assentamento Tarumã Mirim de forma preditiva, auxiliando os estudos quanto ao uso dos recursos naturais, ordenamento territorial e possibilitando uma visão da existência ou não de políticas públicas pontuais. Pois, o planejamento de um assentamento rural deve levar em consideração o uso da terra e os seus impactos positivos ou negativos gerados nesse processo. A evolução da paisagem desde a sua criação do PA em março de 1992, possibilita entre os anos 1995 a 2003 uma projeção estocástica para o ano 2011 de forma preditiva, capaz de informar as taxas de crescimento e supressão da vegetação exercida pela ação antrópica. Utilizaram-se duas cenas da órbita 231 e ponto 062 dos anos de 1995 e 2003, devidamente recortadas da área de estudo e aplicando a Teoria de Cadeias de Markov, apoiada em técnicas de sensoriamento remoto que delimitou a área, classificou-se o uso da terra e cobertura vegetal, fez-se a tabulação cruzada das classes mostrando a transição entre elas, as probabilidades de mudanças e a projeção do uso da terra para o ano de 2011. Dos 42.910,760 ha destinados para assentamento e agricultura familiar, em 1995 data início do estudo para modelagem preditiva, foi levantado pela classificação do uso da terra na ordem de 1,119.60 ha, em 2003 3,075.30 ha e uma projeção de uso para 2011 10,023.30 ha, e a supressão da cobertura vegetal em 1995 47,069.10 ha, em 2003 45,113.40 ha e a projeção de supressão vegetal para 2011 (simulação) é da ordem de 38,165.40 ha desflorestados. O estudo revelou em sua modelagem da dinâmica do uso da terra para cenários futuros, uma situação de caráter preocupante que deve ser reavaliada e receber especial atenção em relação aos impactos positivos e negativos no entorno e na rede hidrológica, preconizados no plano de controle ambiental e proteção das matas ciliares.

Na primeira década dos anos 2000, houve uma intensa expansão do setor sucroenergético no Estado de São Paulo. O objetivo desse trabalho é avaliar os impactos socioeconômicos dessa expansão, tendo como base a representação de bem-estar social proposta por Deaton & Muellbauer (2009). Os impactos da expansão do setor sucroenergético sobre o nível médio da renda per capita e sobre sua distribuição entre os municípios paulistas foi estimado através de um modelo de painel espacial dinâmico desenvolvido a partir da decomposição da renda per capita em seus principais determinantes proposta por Barros et al. (2004). Além da proporção de adultos na população municipal, da taxa de utilização da força de trabalho e do rendimento médio dos vínculos empregatícios, também foram incluídas como variáveis de controle no modelo a taxa de utilização da força de trabalho na agropecuária e o rendimento médio dos vínculos empregatícios na agropecuária. Adicionalmente, para isolar os impactos socioeconômicos da expansão do setor sucroenergético, a participação da agropecuária na área do município, a participação da agricultura na área da agropecuária, a participação da cana-deaçúcar na área da agricultura e uma dummy para os municípios com usina em operação foram incluídas no modelo. As séries abrangem os 645 municípios paulistas no período de 2000 a 2008. Os resultados do modelo Método Generalizado de Momentos em Sistema GMM-SYS evidenciam a existência de relação de dependência espacial e temporal positiva no PIB real per capita. Os efeitos diretos e indiretos estimados indicam que a expansão do setor sucroenergético apresentou um impacto positivo sobre o nível médio da renda per capita e, como a expansão do setor ocorreu em municípios de PIB real per capita inferior à média paulista, também sobre sua distribuição. Dessa forma, constatou-se que a expansão do setor sucroenergético apresentou um impacto socioeconômico positivo. / The Brazilian sugarcane sector experienced an intense expansion in Sao Paulo State during the 2000s. The aim of this study is to evaluate the socioeconomic impacts of such expansion, based on the social welfare representation proposed by Deaton & Muellbauer (2009). The impacts of sugarcane sector expansion over the average per capita income and over its distribution between Sao Paulo States municipalities were estimated through a dynamic spatial panel developed from the decomposition of per capita income into its main determinants proposed by Barros et al. (2004). Besides the municipal rate of adults in the population, rate of workforce employment and average wage, two other variables were included in the model to control regional differences observed in Sao Paulo States economy: rate of workforce employment in agriculture and farming A&F and its respective average wage. Additionally, in order to determine the socioeconomic impacts of the sugarcane sector expansion, the share of A&F in the municipal area, the share of agriculture in A&F area, the share of sugarcane in agriculture area and a dummy for cities with mills in operation were also included in the model. The balanced panel for the 645 cities in Sao Paulo State ranges from 2000 to 2008. The results of the system generalized method of moments GMM-SYS highlight that per capita GDP presents positive lags in both time and space. The estimated direct and indirect effects indicate that sugarcane sector expansion had a positive impact over the average per capita income and, then, also over its distribution throughout Sao Paulo State since sugarcane sector expansion occurred mainly in cities with per capita GDP lower than the States average. Accordingly, the conclusion of this study is that sugarcane sector expansion that occurred between 2000 and 2008 presented a positive socioeconomic impact in Sao Paulo State.

Die visuelle Kommunikation ist eine effiziente Methode, um dynamische Phänomene zu beschreiben. Informationsobjekte präzise wahrzunehmen, einen schnellen Zugriff auf strukturierte und relevante Informationen zu ermöglichen, erfordert konsistente und nach dem formalen Minimalprinzip konzipierte Analyse- und Darstellungsmethoden. Dynamische Raumphänomene in Geoinformationssystemen können durch den Mangel an konzeptionellen Optimierungsanpassungen aufgrund ihrer statischen Systemstruktur nur bedingt die Informationen von Raum und Zeit modellieren. Die Forschung in dieser Arbeit ist daher auf drei interdisziplinäre Ansätze fokussiert. Der erste Ansatz stellt eine echtzeitnahe Datenerfassung dar, die in Geodatenbanken zeitorientiert verwaltet wird. Der zweite Ansatz betrachtet Analyse- und Simulationsmethoden, die das dynamische Verhalten analysieren und prognostizieren. Der dritte Ansatz konzipiert Visualisierungsmethoden, die insbesondere dynamische Prozesse abbilden. Die Symbolisierung der Prozesse passt sich bedarfsweise in Abhängigkeit des Prozessverlaufes und der Interaktion zwischen Datenbanken und Simulationsmodellen den verschiedenen Entwicklungsphasen an. Dynamische Aspekte können so mit Hilfe bewährter Funktionen aus der GI-Science zeitnah mit modularen Werkzeugen entwickelt und visualisiert werden. Die Analyse-, Verschneidungs- und Datenverwaltungsfunktionen sollen hierbei als Nutzungs- und Auswertungspotential alternativ zu Methoden statischer Karten dienen. Bedeutend für die zeitliche Komponente ist das Verknüpfen neuer Technologien, z. B. die Simulation und Animation, basierend auf einer strukturierten Zeitdatenbank in Verbindung mit statistischen Verfahren. Methodisch werden Modellansätze und Visualisierungstechniken entwickelt, die auf den Bereich Verkehr transferiert werden. Verkehrsdynamische Phänomene, die nicht zusammenhängend und umfassend darstellbar sind, werden modular in einer serviceorientierten Architektur separiert, um sie in verschiedenen Ebenen räumlich und zeitlich visuell zu präsentieren. Entwicklungen der Vergangenheit und Prognosen der Zukunft werden über verschiedene Berechnungsmethoden modelliert und visuell analysiert. Die Verknüpfung einer Mikrosimulation (Abbildung einzelner Fahrzeuge) mit einer netzgesteuerten Makrosimulation (Abbildung eines gesamten Straßennetzes) ermöglicht eine maßstabsunabhängige Simulation und Visualisierung des Mobilitätsverhaltens ohne zeitaufwendige Bewertungsmodellberechnungen. Zukünftig wird die visuelle Analyse raum-zeitlicher Veränderungen für planerische Entscheidungen ein effizientes Mittel sein, um Informationen übergreifend verfügbar, klar strukturiert und zweckorientiert zur Verfügung zu stellen. Der Mehrwert durch visuelle Geoanalysen, die modular in einem System integriert sind, ist das flexible Auswerten von Messdaten nach zeitlichen und räumlichen Merkmalen. / Visual communication is an efficient method to describe dynamic phenomena. Perceiving information objects precisely and facilitating quick access to structured and relevant information requires consistent analysis and presentation methods conceived according to the formal minimisation principle. Because of the lack of conceptual optimisation adaptations due to their static system structure, dynamic space phenomena in geoinformation systems can only model the information of time and space conditionally. This is why research in this paper focuses on three interdisciplinary approaches. The first approach represents data collection close to real-time which is administered in geodatabases in a time-oriented manner. The second approach looks at analysis and simulation methods that analyse and forecast dynamic behaviour. The third approach conceives visualisation methods that model dynamic processes in particular. Where required, the symbolising of processes adapts to the various development phases depending on the process flow and the interaction between databases and simulation models. This allows dynamic aspects to be developed and visualised in a timely manner using modular tools with the help of proven geoscience functions. The analysis, intersection and data administration functions are intended to serve as utilisation and analysis potential as an alternative to static chart methods. For the time component, linking new technologies such as simulation and animation is significant based on a structured time database in connection with statistical methods. Modelling approaches and visualisation techniques are methodically developed and transferred to the traffic field. Dynamic traffic phenomena that cannot be modelled cohesively and comprehensively are separated into a service-oriented modular architecture in order to present them visually on different levels of space and time. Past developments and forecasts are modelled and visually analysed using various calculation methods. Linking a micro-simulation (modelling individual vehicles) to a network-controlled macro-simulation (modelling an entire road network) makes it possible to simulate and visualise mobility behaviour regardless of scale without time-consuming analysis model calculations. In the future, the visual analysis of space-time changes for planning decisions will be an efficient tool in order to make comprehensive, clearly structured and appropriate information available. The flexible analysis of measurement data according to time and space criteria represents the added value of visual geoanalysis integrated into a system with a modular structure.

In this paper we estimate space-time impacts of the embeddedness in R&D networks on regional knowledge production by means of a dynamic spatial panel data model with non-linear effects for a set of 229 European NUTS-2 regions in the period 1999-2009. Embeddedness refers to the positioning in networks where nodes represent regions that are linked by joint R&D endeavours in European Framework Programmes. We observe positive immediate impacts on regional knowledge production arising from increased embeddedness in EU funded R&D networks, in particular for regions with lower own knowledge endowments. However, long-term impacts of R&D network embeddedness are comparatively small.(authors' abstract) / Series: Department of Economics Working Paper Series

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Located on the mid-region of Rio Grande do Sul, the watershed of the Arroio Grande lies on the transition of the Central Depression to the Southern Plateau. Belonging to the geographic micro-region of Santa Maria, the watershed area partially covers four municipal districts: Silveira Marins, Itaara, Santa Maria and Júlio de Castilhos. Studies on the area showed, on the last two decades, a local increase tendency of the forest areas, rural activities and a decrease of the field areas. This work had as objective, modeling the dynamics of use and covering of land occurred in two periods of time: from 1991 to 2002 and from 2002 to 2011; and to perform the simulation of scenarios until the year of 2020. To elaborate the thematic maps of land cover and use, images the satellites Landsat 5 and Landsat 7 were classified. The modeling process was performed by the Dinamica EGO app through these methods: Markov Chain, Weights-of-Evidence and Cellular Automata. The simulated maps to the years of 2002 e 2011, when compared with real maps, reached satisfactory similarities indexes. The simulated scenery for the year of 2020 presented significant less percentages of changing of the use and cover than those verified for the previous periods, predicting increase of 2,64% and 4,38% to the forest and rural areas respectively, and a decrease of the field areas about 8,19%. This dynamic may indicate stagnation in the agricultural cultivation areas, because there are no great extensions of proper land for the agricultural advance, which is the main propeller of the observed evolution in the study period, on the regions of greater agricultural vocation, as it is on the proximities of Silveira Martins, in the floodplain of Arroio Grande and in Southern Plateau areas, corresponding to Júlio de Castilhos. / Situada na região central do Rio Grande do Sul, a bacia do Arroio Grande localiza-se na transição da Depressão Central para o Planalto Meridional. Pertencendo a microrregião geográfica de Santa Maria, a área da bacia abrange parcialmente quatro municípios: Silveira Martins, Itaara, Santa Maria e Júlio de Castilhos. Estudos realizados na área evidenciaram, nas últimas duas décadas, uma tendência local de aumento das áreas florestais e das atividades agrícolas e a diminuição das áreas de campo. Este trabalho teve como objetivo modelar a dinâmica de uso e cobertura da terra ocorrida em dois períodos de tempo: 1991- 2002 e 2002-2011, e realizar a simulação de cenários até o ano de 2020. Para elaboração dos mapas temáticos de uso e cobertura da terra foram classificadas imagens dos sensores TM e ETM+ dos satélites Landsat 5 e Landsat 7. O processo de modelagem foi realizado no aplicativo Dinamica EGO através dos métodos: Cadeias de Markov, Pesos de Evidência e Autômatos Celulares. Os mapas simulados para os anos de 2002 e 2011, quando comparados com os mapas reais, alcançaram índices de similaridade satisfatórios. O cenário simulado para o ano de 2020 apresentou percentuais de mudanças de uso e cobertura significativamente menores do que os verificados para os períodos anteriores, prevendo aumentos de 2,64% e 4,38%, para as áreas florestais e agrícolas, respectivamente, e uma diminuição das áreas de campo na ordem de 8,19%. Esta dinâmica pode indicar uma estagnação nas áreas de cultivo agrícola, pois não há grandes extensões de terra adequadas para o avanço da agricultura, principal propulsor da evolução observada no período de estudo, nas regiões com maior vocação agrícola, como nas proximidades de Silveira Martins, nas várzeas do Arroio Grande e em áreas do planalto meridional, correspondentes a Júlio de Castilhos.