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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
21

A Case Study In Weather Pattern Searching Using A Spatial Data Warehouse Model

Koylu, Caglar 01 June 2008 (has links) (PDF)
Data warehousing and Online Analytical Processing (OLAP) technology has been used to access, visualize and analyze multidimensional, aggregated, and summarized data. Large part of data contains spatial components. Thus, these spatial components convey valuable information and must be included in exploration and analysis phases of a spatial decision support system (SDSS). On the other hand, Geographic Information Systems (GISs) provide a wide range of tools to analyze spatial phenomena and therefore must be included in the analysis phases of a decision support system (DSS). In this regard, this study aims to search for answers to the problem how to design a spatially enabled data warehouse architecture in order to support spatio-temporal data analysis and exploration of multidimensional data. Consequently, in this study, the concepts of OLAP and GISs are synthesized in an integrated fashion to maximize the benefits generated from the strengths of both systems by building a spatial data warehouse model. In this context, a multidimensional spatio-temporal data model is proposed as a result of this synthesis. This model addresses the integration problem of spatial, non-spatial and temporal data and facilitates spatial data exploration and analysis. The model is evaluated by implementing a case study in weather pattern searching.
22

Metodologia para avaliação ambiental de bacias hidrográficas com uso de sistemas de suporte à decisão espacial e do indicador pegada ecológica / Methodology for envirnmental assessment of watersheds using spacial decision support systems and the ecological footprint.

Raul Rigoto Monteiro 20 August 2010 (has links)
No atual contexto ambiental é grande a demanda por informações consistentes que subsidiem o planejamento territorial, permitindo realizar avaliações ambientais e desta forma, subsidiar os setores público e privado. Essa demanda pode ser satisfeita com a integração de informações em um sistema, com propriedades e funções de processamento, possibilitando sua utilização em ambiente integrado. Assim, nesta dissertação é proposta uma metodologia para a avaliação ambiental de bacias hidrográficas que atua desde a escolha de indicadores e definição dos pesos de sua contribuição, até a execução de avaliações e espacialização de resultados em ambiente SIG. Esta metodologia é composta por duas fases distintas: avaliação da vulnerabilidade ambiental da bacia hidrográfica a partir do uso de sistemas de suporte à decisão espacial, e, avaliação da sustentabilidade da bacia através do cálculo do indicador Pegada Ecológica. Na primeira fase são adotados sistemas de suporte à decisão, bases de conhecimento, SIG e uma ferramenta que integra estes resultados permitindo a geração de avaliações, análises e/ou cenários prospectivos. Na segunda fase, a sustentabilidade da bacia é retratada a partir do cálculo da pegada ecológica que consiste na contabilização da área que uma população necessita para produzir os recursos consumidos e absorver os resíduos gerados. A comparação entre áreas mais vulneráveis e menos sustentáveis, pode nortear projetos de recuperação e conservação ambiental. / In the current environmental context is huge the demand for consistent information that supports the territorial planning, allowing environmental assessments thereby subsidizing public and private sectors. This demand can be satisfied with the integration of information into a system, with properties and processing functions, allowing its use in integrated environment. Thus, this thesis proposes a methodology for environmental assessment of watersheds that operates from the choice of indicators and definition of the weights of its contribution to the implementation of assessments and spatialisation of results in a GIS environment. This methodology is composed of two distinct phases: assessment of environmental vulnerability of the basin by the use of spatial decision support systems, and assessing the sustainability of the basin through the calculation of Ecological Footprint. In the first phase are adopted decision support systems, knowledge bases, GIS and a tool that integrates these results allowing the generation of assessments, analysis and / or prospective scenarios. In the second stage, the sustainability of the basin is pictured from the calculation of the ecological footprint, which consists in accounting the area that a population needs to produce the resources consumed and absorb the waste generated. The comparison between the most vulnerable and less sustainable, can guide restoration projects and environmental conservation.
23

An approach for improving decision-making with heterogeneous geospatial big data: an application using spatial decision support systems and volunteered geographic information to disaster management / Uma abordagem para melhorar a tomada de decisão com grande volume de dados espaciais heterogêneos: Uma aplicação usando sistemas de suporte à decisão espacial e informações geográficas voluntárias na gestão de desastres

Flavio Eduardo Aoki Horita 10 March 2017 (has links)
Context: Accurate decision-making requires updated and precise information to establish the reality of an overall situation. New data sources (e.g., wearable technologies) have been increasing the amount of available and useful data, which is now called big data. This has a great potential for transforming the entire business process and improving the accuracy of decisions. In this context, disaster management represents an interesting scenario that relies on big data to enhance decision-making. This is because it must cope with data provided not only by traditional sources (e.g., stationary sensors) but also by emerging sources - for instance, information shared by local volunteers, i.e., volunteered geographic information (VGI). When combined, these data sources can be regarded as large in volume, with different velocities, and a variety of formats. Furthermore, an analysis is required to confirm their veracity is required since these data sources are disconnected and prone to various errors. These are the 4Vs that characterize big data. Gap: However, although all these data open up further opportunities, their huge volume, together with an inappropriate data integration and unsuitable visualization, can result in information being overlooked by decision-makers. This problem arises because the integration of the available data is hampered by the intrinsic heterogeneity of their features (e.g., their occurrence in different formats). When integrated, this information also often fails to reach the decision-makers in a suitable way (e.g., in appropriate visualization formats). Moreover, there is not a clear understanding of the decision-makers needs or how the available data can meet these needs. Objective: In light of this, this thesis presents an approach for improving decision-making with heterogeneous geospatial big data based on spatial decision support systems and volunteered geographic information in disaster management. Methods: Systematic mapping studies were conducted to identify gaps in research studies with regard to the use of volunteered information and spatial decision support systems in disaster management. On the basis of these studies, two design science projects were carried out. The first of these aimed at defining the elements that are essential for ensuring the integration of heterogeneous data, whereas the second project aimed at obtaining a better understanding of decision-makers needs. A cross-organizational action research project was also conducted to define the design principles that should be observed for a spatial decision support system to effectively support decision-making with heterogeneous geospatial big data. A series of empirical case studies was undertaken to evaluate the outcomes of these projects. Results: The overall approach thus consists of the three significant outcomes that were derived from these projects. The first outcome was the conceptual architecture that defines the integration of heterogeneous data sources. The second outcome was a model-based framework that describes the connection of decision-making with appropriate data sources. The third outcome is based on the framework and comprises a set of design principles for guiding the development of spatial decision support systems for decision-making with heterogeneous geospatial big data. Conclusion: This thesis has made a useful contribution to both practice and research. In short, it defines ways of integrating heterogeneous data sources, provides a better understanding of decision-makers needs, and supports the development of a spatial decision support system to effectively assist decision-making with heterogeneous geospatial big data. / Contexto: Uma tomada de decisão precisa exige informações mais precisas e atualizadas para estabelecer a realidade da situação geral. Novas fontes de dados (e.g, tecnologias vestíveis) tem aumentado a quantidade de dados úteis disponíveis, que agora é chamado de big data. Isso tem grande potencial para transformar todo o processo de negócio e melhorar a precisão na tomada de decisão. Neste contexto, a gestão de desastres representa um interessante cenário que depende de big data para aprimorar a tomada de decisão. Isso porque, ela tem que lidar com dados fornecidos não apenas por fontes tradicionais (e.g., sensores estáticos), mas também por fontes emergentes por exemplo, informações compartilhadas por voluntários locais, i.e., as informações geográficas de voluntários (VGI). Quando combinadas, estas fontes de dados podem ser consideradas grandes em volume, com diferentes velocidades e uma variedade de formatos. Além disso, uma análise com relação à sua veracidade é necessaria uma vez que estas fontes de dados são desconectadas e propensas à erros. Estes são os 4Vs que caracterizam big data. Problema: No entanto, embora todos estes dados abrem novas oportunidades, seu grande volume em conjunto com uma integração inapropriada e uma visualização inadequada, podem tornar as informações ignoradas por tomadores de decisão. Isso ocorre, pois, a integração dos dados disponíveis torna-se complicada devido a heterogeneidade intrínseca nas suas características (e.g., dados em formatos diferentes). Quando integradas, estas informações frequentemente também não chegam aos tomadores de decisão em uma condição apropriada (por exemplo, no formato de visualização adequado). Além disso, não existe uma clara compreensão sobre as necessidades dos tomadores de decisão ou sobre como os dados disponíveis podem ser usados para atender essas necessidades. Objetivo: Dessa forma, esta tese de doutorado apresenta uma abordagem para melhorar a tomada de decisões com grande volume de dados espaciais heterogêneos baseada em sistemas de suporte à decisão espacial e informações geográficas de voluntários na gestão de desastres. Métodos: Mapeamentos sistemáticos foram conduzidos para identificar lacunas de pesquisa no uso de dados voluntários e sistemas de suporte à decisão na gestão de desastres. Com base nestes estudos, dois projetos de design science foram conduzidos. O primeiro deles buscou definir elementos essências para entender a integração de dados heterogêneos, enquanto o segundo projeto buscou fornecer um melhor entendimento das necessidades dos tomadores de decisão. Também foi conduzido um projeto de pesquisa-ação interinstitucional para definir princípios de projeto que deveriam ser observados para um sistema de suporte à decisão espacial ser efetivo no apoio a tomada de decisão com grande volume de dados espaciais heterogêneos. Uma série de estudos de caso empíricos foram conduzidos para avaliar os resultados destes projetos. Resultados: A abordagem geral então é composta pelos três resultados significantes que foram derivados destes projetos. Em primeiro lugar, uma arquitetura conceitual que especifica a integração de fontes de dados heterogêneas. O segundo elemento é uma estrutura baseada em modelo que descreve a conexão entre a tomada de decisão com as fontes de dados mais adequadas. Com base nesta estrutura, o terceiro elemento consiste em um conjunto de princípios de design que guiam o desenvolvimento de um sistema de suporte à decisão espacial para tomada de decisão com grande volume de dados espaciais heterogêneos. Conclusão: Esta tese de doutorado realizou importantes contribuições para a prática e pesquisa. Em resumo, ela define formas para integrar fontes de dados heterogêneos, fornece uma melhor compreensão sobre as necessidades dos tomadores de decisão e ajuda no desenvolvimento de sistemas de suporte à decisão espacial para tomada de decisão com grande volume de dados espaciais heterogêneos.
24

Web-Based Multi-Criteria Evaluation of Spatial Trade-Offs between Enivironmental and Economic Implications from Hydraulic Fracturing in a Shale Gas Region in Ohio

Liu, Xiaohui 29 July 2014 (has links)
No description available.
25

Bases para uma metodologia de apoio à decisão para serviços de educação e saúde sob a ótica dos transportes / Bases for a decision support methodology for education and health services from a transportation perspective

Lima, Renato da Silva 26 June 2003 (has links)
Um dos problemas que afetam as cidades brasileiras é a falta de uma metodologia adequada para a implantação de equipamentos coletivos públicos (escolas, postos de saúde, entre outros), e da utilização de modo racional desses equipamentos. Esse foi o ponto de partida para esse trabalho, cujo objetivo principal foi desenvolver uma ferramenta de análise espacial para auxiliar o poder público no planejamento e na gestão dos serviços públicos de educação e saúde, no que concerne basicamente à melhor localização das unidades básicas de atendimento e à melhor distribuição dos usuários por essas unidades, buscando reduzir os custos de transporte. Após uma avaliação da atual política de distribuição e utilização dos equipamentos coletivos de educação e saúde no Brasil e no mundo, foi realizada uma análise dos conceitos relativos às ferramentas de apoio a problemas de decisão de caráter espacial, particularmente os Sistemas de Apoio à Decisão Espacial (SADE). De posse dessa base conceitual, buscou-se formular as bases de um sistema (ou uma metodologia) que apoiasse a implantação de novos equipamentos coletivos e uma utilização eficiente dos equipamentos já existentes, tendo como parâmetro principal de comparação o custo de deslocamento dos usuários. Esse sistema deveria ser adequado à realidade das cidades médias brasileiras, de maneira geral hoje inseridas num cenário de falta de planejamento e de ausência de bases de dados estruturadas (e atualizadas). Ainda, como proposta adicional, procurou-se incorporar como ferramentas de apoio ao sistema algumas técnicas emergentes que, embora relativamente pouco utilizadas no planejamento urbano até o presente momento, apresentam grande potencial para tal. São elas: os Autômatos Celulares (ou CA, Cellular Automata) e as Redes Neurais Artificiais (RNA). Os fundamentos do sistema concebido foram transpostos para uma aplicação prática desenvolvida em um Sistema de Informações Geográficas (SIG) através de um estudo de caso conduzido na cidade de São Carlos (SP), cujos resultados demonstraram que quando se pensa em otimizar os custos de deslocamento, a principal ação a ser empreendida é a redistribuição da demanda às unidades de oferta, antes de se pensar na abertura de novas unidades. Mais importante do que os resultados numéricos obtidos, foi a confirmação de que é possível se utilizar as diversas ferramentas de planejamento e gestão de modo integrado. A partir dessa metodologia, um investimento em desenvolvimento de software pode levar à construção de um efetivo Sistema de Apoio à Decisão Espacial. De maneira mais geral, pode-se afirmar que a obtenção de dados é o grande obstáculo para pesquisas dessa natureza. A montagem de uma base de dados sólida e confiável é, sem dúvida, o ponto crucial para a execução de projetos potencialmente bem sucedidos / One of the main problems faced by brazilian cities is the lack of adequate methodologies for the implementation and rational use of public service facilities (such as schools and health care centers). That was the starting point in the definition of the main objective of the present work, which is the development of a spatial analysis tool for seeking an optimal arrangement of primary health and education facilities, in order to reduce transportation costs. The use of such a tool in the public administration is important not only for planning but also for management purposes. The study starts with an investigation of approaches that have been used in real cases, in cities of different countries, to define health and education facility types and their distribution. A careful analysis of location-allocation concepts and analysis tools for the solution of spatial problems, with particular emphasis on the Spatial Decision Support Systems (SDSS), was also conducted. The system (or methodology) proposed, which was meant to support the process of location of new facilities and also an efficient use of the existing ones while reducing transportation costs, was based on that conceptual framework. The system was directed to the context of brazilian medium-sized cities, where planning concepts are not widely applied and even the databases available are sometimes very limited and frequently outdated. The system design looked for both traditional and innovative approaches and computer-based techniques, such as Cellular Automata (CA) and Artificial Neural Networks (ANN). These techniques, although not yet extensively applied in urban planning and management, seem to be promising alternatives for those activities. The integration of the different tools and techniques was tested in a practical application carried out in the city of São Carlos (SP) and developed in a Geographic Information System (GIS) environment. The results drawn from the application are clear: the main action to reduce the transportation costs in the case studied was a re-distribution of the demand. It was considerable, despite the fact that not a single facility has been added. Another important outcome of the research was the confirmation of the hypothesis that the distinct planning and management tools tested could be used in an integrated approach. Therefore, the methodology discussed here could effectively become a Spatial Decision Support System only by means of software development for building the system interfaces. As a general conclusion, the data gathering problems still seem to be the main barrier for research development in this area. Consequently, the construction of solid and reliable databases is undoubtedly a key point to start any potentially successful project
26

Bases para uma metodologia de apoio à decisão para serviços de educação e saúde sob a ótica dos transportes / Bases for a decision support methodology for education and health services from a transportation perspective

Renato da Silva Lima 26 June 2003 (has links)
Um dos problemas que afetam as cidades brasileiras é a falta de uma metodologia adequada para a implantação de equipamentos coletivos públicos (escolas, postos de saúde, entre outros), e da utilização de modo racional desses equipamentos. Esse foi o ponto de partida para esse trabalho, cujo objetivo principal foi desenvolver uma ferramenta de análise espacial para auxiliar o poder público no planejamento e na gestão dos serviços públicos de educação e saúde, no que concerne basicamente à melhor localização das unidades básicas de atendimento e à melhor distribuição dos usuários por essas unidades, buscando reduzir os custos de transporte. Após uma avaliação da atual política de distribuição e utilização dos equipamentos coletivos de educação e saúde no Brasil e no mundo, foi realizada uma análise dos conceitos relativos às ferramentas de apoio a problemas de decisão de caráter espacial, particularmente os Sistemas de Apoio à Decisão Espacial (SADE). De posse dessa base conceitual, buscou-se formular as bases de um sistema (ou uma metodologia) que apoiasse a implantação de novos equipamentos coletivos e uma utilização eficiente dos equipamentos já existentes, tendo como parâmetro principal de comparação o custo de deslocamento dos usuários. Esse sistema deveria ser adequado à realidade das cidades médias brasileiras, de maneira geral hoje inseridas num cenário de falta de planejamento e de ausência de bases de dados estruturadas (e atualizadas). Ainda, como proposta adicional, procurou-se incorporar como ferramentas de apoio ao sistema algumas técnicas emergentes que, embora relativamente pouco utilizadas no planejamento urbano até o presente momento, apresentam grande potencial para tal. São elas: os Autômatos Celulares (ou CA, Cellular Automata) e as Redes Neurais Artificiais (RNA). Os fundamentos do sistema concebido foram transpostos para uma aplicação prática desenvolvida em um Sistema de Informações Geográficas (SIG) através de um estudo de caso conduzido na cidade de São Carlos (SP), cujos resultados demonstraram que quando se pensa em otimizar os custos de deslocamento, a principal ação a ser empreendida é a redistribuição da demanda às unidades de oferta, antes de se pensar na abertura de novas unidades. Mais importante do que os resultados numéricos obtidos, foi a confirmação de que é possível se utilizar as diversas ferramentas de planejamento e gestão de modo integrado. A partir dessa metodologia, um investimento em desenvolvimento de software pode levar à construção de um efetivo Sistema de Apoio à Decisão Espacial. De maneira mais geral, pode-se afirmar que a obtenção de dados é o grande obstáculo para pesquisas dessa natureza. A montagem de uma base de dados sólida e confiável é, sem dúvida, o ponto crucial para a execução de projetos potencialmente bem sucedidos / One of the main problems faced by brazilian cities is the lack of adequate methodologies for the implementation and rational use of public service facilities (such as schools and health care centers). That was the starting point in the definition of the main objective of the present work, which is the development of a spatial analysis tool for seeking an optimal arrangement of primary health and education facilities, in order to reduce transportation costs. The use of such a tool in the public administration is important not only for planning but also for management purposes. The study starts with an investigation of approaches that have been used in real cases, in cities of different countries, to define health and education facility types and their distribution. A careful analysis of location-allocation concepts and analysis tools for the solution of spatial problems, with particular emphasis on the Spatial Decision Support Systems (SDSS), was also conducted. The system (or methodology) proposed, which was meant to support the process of location of new facilities and also an efficient use of the existing ones while reducing transportation costs, was based on that conceptual framework. The system was directed to the context of brazilian medium-sized cities, where planning concepts are not widely applied and even the databases available are sometimes very limited and frequently outdated. The system design looked for both traditional and innovative approaches and computer-based techniques, such as Cellular Automata (CA) and Artificial Neural Networks (ANN). These techniques, although not yet extensively applied in urban planning and management, seem to be promising alternatives for those activities. The integration of the different tools and techniques was tested in a practical application carried out in the city of São Carlos (SP) and developed in a Geographic Information System (GIS) environment. The results drawn from the application are clear: the main action to reduce the transportation costs in the case studied was a re-distribution of the demand. It was considerable, despite the fact that not a single facility has been added. Another important outcome of the research was the confirmation of the hypothesis that the distinct planning and management tools tested could be used in an integrated approach. Therefore, the methodology discussed here could effectively become a Spatial Decision Support System only by means of software development for building the system interfaces. As a general conclusion, the data gathering problems still seem to be the main barrier for research development in this area. Consequently, the construction of solid and reliable databases is undoubtedly a key point to start any potentially successful project
27

Three-dimensional hydrodynamic models coupled with GIS-based neuro-fuzzy classification for assessing environmental vulnerability of marine cage aquaculture

Navas, Juan Moreno January 2010 (has links)
There is considerable opportunity to develop new modelling techniques within a Geographic Information Systems (GIS) framework for the development of sustainable marine cage culture. However, the spatial data sets are often uncertain and incomplete, therefore new spatial models employing “soft computing” methods such as fuzzy logic may be more suitable. The aim of this study is to develop a model using Neuro-fuzzy techniques in a 3D GIS (Arc View 3.2) to predict coastal environmental vulnerability for Atlantic salmon cage aquaculture. A 3D hydrodynamic model (3DMOHID) coupled to a particle-tracking model is applied to study the circulation patterns, dispersion processes and residence time in Mulroy Bay, Co. Donegal Ireland, an Irish fjard (shallow fjordic system), an area of restricted exchange, geometrically complicated with important aquaculture activities. The hydrodynamic model was calibrated and validated by comparison with sea surface and water flow measurements. The model provided spatial and temporal information on circulation, renewal time, helping to determine the influence of winds on circulation patterns and in particular the assessment of the hydrographic conditions with a strong influence on the management of fish cage culture. The particle-tracking model was used to study the transport and flushing processes. Instantaneous massive releases of particles from key boxes are modelled to analyse the ocean-fjord exchange characteristics and, by emulating discharge from finfish cages, to show the behaviour of waste in terms of water circulation and water exchange. In this study the results from the hydrodynamic model have been incorporated into GIS to provide an easy-to-use graphical user interface for 2D (maps), 3D and temporal visualization (animations), for interrogation of results. v Data on the physical environment and aquaculture suitability were derived from a 3- dimensional hydrodynamic model and GIS for incorporation into the final model framework and included mean and maximum current velocities, current flow quiescence time, water column stratification, sediment granulometry, particulate waste dispersion distance, oxygen depletion, water depth, coastal protection zones, and slope. The Neuro-fuzzy classification model NEFCLASS–J, was used to develop learning algorithms to create the structure (rule base) and the parameters (fuzzy sets) of a fuzzy classifier from a set of classified training data. A total of 42 training sites were sampled using stratified random sampling from the GIS raster data layers, and the vulnerability categories for each were manually classified into four categories based on the opinions of experts with field experience and specific knowledge of the environmental problems investigated. The final products, GIS/based Neuro Fuzzy maps were achieved by combining modeled and real environmental parameters relevant to marine fin fish Aquaculture. Environmental vulnerability models, based on Neuro-fuzzy techniques, showed sensitivity to the membership shapes of the fuzzy sets, the nature of the weightings applied to the model rules, and validation techniques used during the learning and validation process. The accuracy of the final classifier selected was R=85.71%, (estimated error value of ±16.5% from Cross Validation, N=10) with a Kappa coefficient of agreement of 81%. Unclassified cells in the whole spatial domain (of 1623 GIS cells) ranged from 0% to 24.18 %. A statistical comparison between vulnerability scores and a significant product of aquaculture waste (nitrogen concentrations in sediment under the salmon cages) showed that the final model gave a good correlation between predicted environmental vi vulnerability and sediment nitrogen levels, highlighting a number of areas with variable sensitivity to aquaculture. Further evaluation and analysis of the quality of the classification was achieved and the applicability of separability indexes was also studied. The inter-class separability estimations were performed on two different training data sets to assess the difficulty of the class separation problem under investigation. The Neuro-fuzzy classifier for a supervised and hard classification of coastal environmental vulnerability has demonstrated an ability to derive an accurate and reliable classification into areas of different levels of environmental vulnerability using a minimal number of training sets. The output will be an environmental spatial model for application in coastal areas intended to facilitate policy decision and to allow input into wider ranging spatial modelling projects, such as coastal zone management systems and effective environmental management of fish cage aquaculture.
28

Sistema integrado para tomada de decis?o espacial em situa??es de derramamento de ?leo no litoral norte do Estado do RN

Souza, Clen?bio Feitosa de 09 October 2006 (has links)
Made available in DSpace on 2015-03-13T17:08:40Z (GMT). No. of bitstreams: 1 ClenubioFS.pdf: 1330843 bytes, checksum: f44365144a87dbadb85a95129360dfdc (MD5) Previous issue date: 2006-10-09 / The northern coast of Rio Grande do Norte State (RN) shows areas of Potiguar basin with high activity in petroleum industry. With the goal of avoiding and reducing the accident risks with oil it is necessary to understand the natural vulnerability, mapping natural resources and monitoring the oil spill. The use of computational tools for environmental monitoring makes possible better analyses and decisions in political management of environmental preservation. This work shows a methodology for monitoring of environment impacts, with purpose of avoiding and preserving the sensible areas in oil contact. That methodology consists in developing and embedding an integrated computational system. Such system is composed by a Spatial Decision Support System (SDSS). The SDSS shows a computational infrastructure composed by Web System of Geo-Environmental and Geographic Information - SWIGG , the System of Environmental Sensibility Maps for Oil Spill AutoMSA , and the Basic System of Environmental Hydrodynamic ( SisBAHIA a System of Modeling and Numerical Simulating SMNS). In a scenario of oil spill occurred coastwise of Rio Grande do Norte State s northern coast, the integration of such systems will give support to decision agents for managing of environmental impacts. Such support is supplied through a system of supporting to spatial decisions / O litoral norte do Estado do Rio Grande do Norte (RN) apresenta ?reas da bacia Potiguar com intensa atividade da ind?stria petrol?fera. Com a finalidade de prevenir e minimizar os riscos de acidentes com ?leo, faz-se necess?rio compreender a vulnerabilidade natural, mapear os recursos naturais e monitorar os derrames de ?leo. O uso de ferramentas computacionais para o monitoramento ambiental, possibilita uma melhor an?lise e tomada de decis?o no planejamento de pol?ticas de conserva??o ambiental. A presente disserta??o apresenta uma metodologia de trabalho para o monitoramento de impactos ambientais, com o prop?sito de avaliar e proteger as regi?es sens?veis ao contato do ?leo. A metodologia consiste em desenvolver e implantar um sistema integrado, constituindo um Sistema de Apoio ? Decis?o Espacial (SADE). O SADE apresenta uma infra-estrutura computacional composta pelo SWIGG (Sistema Web de Informa??es Geogr?ficas e Geoambientais), o AutoMSA (Automatizador de Mapas de Sensibilidade Ambiental para derramamentos de ?leo) e o Sistema BAse de HIdrodin?mica Ambiental (SisBAHIA um Sistema de Modelagem e Simula??o Num?rica - SMSN). Num cen?rio de derramamento de ?leo ocorrido pr?ximo ?s ?reas costeiras do litoral norte do Estado do RN a integra??o destes sistemas disponibilizar? aos agentes respons?veis pelo gerenciamento dos danos ambientais, um sistema de suporte a tomada de decis?o espacial
29

Geospatialt beslutsstöd - nyckeln till strategiska beslut

Jones, Julia, Nordström, Fredrik January 2022 (has links)
Tillståndsprocessen för att bedriva miljöfarlig verksamhet är manuell och ineffektiv vilket hämmar svenska företag i deras klimatarbete. Geospatial information har till följd av lokaliseringsprincipen i miljöbalken en central roll inom samhällsbyggnad och dess planering för placering av investeringar. Det finns i dagsläget inget geospatialt beslutsstödsystem (SDSS) som ämnar att underlätta för verksamhetsutövare i tillståndsprocessen vid beslut som rör placering av nya investeringar i industri. Syftet med studien var att utveckla en IT-artefakt med intentionen att stödja processen samt beslutsfattande för industriföretag i skapandet av en tillståndsansökan för miljöfarlig verksamhet. Detta genom att ta fram en webbapplikation som ska fungera som ett processtöd för användaren genom att redogöra de nödvändiga stegen som ingår i en miljötillståndsansökan med fokus på de aspekter som inkluderar geospatial data och information. Målet är att artefakten i dessa steg ska fungera som ett hjälpmedel för verksamhetsutövaren att fatta strategiska beslut kring geografisk plats för nya investeringar i industri. Studien använder sig av Design Science Research Methodology (DSRM) och har hämtat in empiri genom fokusgruppsintervjuer. Arbetet resulterade i en IT-artefakt som visar att det är möjligt att implementera denna typ av lösning på problemet samt de identifierade designprinciperna som implementerades. / The permit process for conducting environmentally hazardous activities is manual and inefficient, which impedes Swedish companies in their climate action. As a result of the “location principle” in the Swedish Environmental Code, spatial information has a central role in community building and its planning for location of investments. There is currently no spatial decision support system (SDSS) that aims to make it easier for operators to make decisions regarding the location of new investments in industry during the permit process. The purpose of the study was to develop an IT artefact with the intention to support the process and decision making for industrial companies in the creation of permit applications for environmentally hazardous activities. This by developing a web application that will function as a process support for the user by describing the necessary steps that are included in an environmental permit application with a focus on the aspects that include spatial data and information. The aim is that the artifact in these steps should function as an aid for the operator to make strategic decisions about the geographical location for new investments in industry. This research uses Design Science Research Methodology (DSRM) and has obtained empirical data through focus group interviews. The work resulted in an IT artifact that proves that it is possible to implement this kind of solution to the problem and the identified design principles that were implemented.

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