2,789 research outputs found

    Towards development of fuzzy spatial datacubes : fundamental concepts with example for multidimensional coastal erosion risk assessment and representation

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    Les systĂšmes actuels de base de donnĂ©es gĂ©odĂ©cisionnels (GeoBI) ne tiennent gĂ©nĂ©ralement pas compte de l'incertitude liĂ©e Ă  l'imprĂ©cision et le flou des objets; ils supposent que les objets ont une sĂ©mantique, une gĂ©omĂ©trie et une temporalitĂ© bien dĂ©finies et prĂ©cises. Un exemple de cela est la reprĂ©sentation des zones Ă  risque par des polygones avec des limites bien dĂ©finies. Ces polygones sont crĂ©Ă©s en utilisant des agrĂ©gations d'un ensemble d'unitĂ©s spatiales dĂ©finies sur soit des intĂ©rĂȘts des organismes responsables ou les divisions de recensement national. MalgrĂ© la variation spatio-temporelle des multiples critĂšres impliquĂ©s dans l’analyse du risque, chaque polygone a une valeur unique de risque attribuĂ© de façon homogĂšne sur l'Ă©tendue du territoire. En rĂ©alitĂ©, la valeur du risque change progressivement d'un polygone Ă  l'autre. Le passage d'une zone Ă  l'autre n'est donc pas bien reprĂ©sentĂ© avec les modĂšles d’objets bien dĂ©finis (crisp). Cette thĂšse propose des concepts fondamentaux pour le dĂ©veloppement d'une approche combinant le paradigme GeoBI et le concept flou de considĂ©rer la prĂ©sence de l’incertitude spatiale dans la reprĂ©sentation des zones Ă  risque. En fin de compte, nous supposons cela devrait amĂ©liorer l’analyse du risque. Pour ce faire, un cadre conceptuel est dĂ©veloppĂ© pour crĂ©er un model conceptuel d’une base de donnĂ©e multidimensionnelle avec une application pour l’analyse du risque d’érosion cĂŽtier. Ensuite, une approche de la reprĂ©sentation des risques fondĂ©e sur la logique floue est dĂ©veloppĂ©e pour traiter l'incertitude spatiale inhĂ©rente liĂ©e Ă  l'imprĂ©cision et le flou des objets. Pour cela, les fonctions d'appartenance floues sont dĂ©finies en basant sur l’indice de vulnĂ©rabilitĂ© qui est un composant important du risque. Au lieu de dĂ©terminer les limites bien dĂ©finies entre les zones Ă  risque, l'approche proposĂ©e permet une transition en douceur d'une zone Ă  une autre. Les valeurs d'appartenance de plusieurs indicateurs sont ensuite agrĂ©gĂ©es basĂ©es sur la formule des risques et les rĂšgles SI-ALORS de la logique floue pour reprĂ©senter les zones Ă  risque. Ensuite, les Ă©lĂ©ments clĂ©s d'un cube de donnĂ©es spatiales floues sont formalisĂ©s en combinant la thĂ©orie des ensembles flous et le paradigme de GeoBI. En plus, certains opĂ©rateurs d'agrĂ©gation spatiale floue sont prĂ©sentĂ©s. En rĂ©sumĂ©, la principale contribution de cette thĂšse se rĂ©fĂšre de la combinaison de la thĂ©orie des ensembles flous et le paradigme de GeoBI. Cela permet l’extraction de connaissances plus comprĂ©hensibles et appropriĂ©es avec le raisonnement humain Ă  partir de donnĂ©es spatiales et non-spatiales. Pour ce faire, un cadre conceptuel a Ă©tĂ© proposĂ© sur la base de paradigme GĂ©oBI afin de dĂ©velopper un cube de donnĂ©es spatiale floue dans le system de Spatial Online Analytical Processing (SOLAP) pour Ă©valuer le risque de l'Ă©rosion cĂŽtiĂšre. Cela nĂ©cessite d'abord d'Ă©laborer un cadre pour concevoir le modĂšle conceptuel basĂ© sur les paramĂštres de risque, d'autre part, de mettre en Ɠuvre l’objet spatial flou dans une base de donnĂ©es spatiales multidimensionnelle, puis l'agrĂ©gation des objets spatiaux flous pour envisager Ă  la reprĂ©sentation multi-Ă©chelle des zones Ă  risque. Pour valider l'approche proposĂ©e, elle est appliquĂ©e Ă  la rĂ©gion Perce (Est du QuĂ©bec, Canada) comme une Ă©tude de cas.Current Geospatial Business Intelligence (GeoBI) systems typically do not take into account the uncertainty related to vagueness and fuzziness of objects; they assume that the objects have well-defined and exact semantics, geometry, and temporality. Representation of fuzzy zones by polygons with well-defined boundaries is an example of such approximation. This thesis uses an application in Coastal Erosion Risk Analysis (CERA) to illustrate the problems. CERA polygons are created using aggregations of a set of spatial units defined by either the stakeholders’ interests or national census divisions. Despite spatiotemporal variation of the multiple criteria involved in estimating the extent of coastal erosion risk, each polygon typically has a unique value of risk attributed homogeneously across its spatial extent. In reality, risk value changes gradually within polygons and when going from one polygon to another. Therefore, the transition from one zone to another is not properly represented with crisp object models. The main objective of the present thesis is to develop a new approach combining GeoBI paradigm and fuzzy concept to consider the presence of the spatial uncertainty in the representation of risk zones. Ultimately, we assume this should improve coastal erosion risk assessment. To do so, a comprehensive GeoBI-based conceptual framework is developed with an application for Coastal Erosion Risk Assessment (CERA). Then, a fuzzy-based risk representation approach is developed to handle the inherent spatial uncertainty related to vagueness and fuzziness of objects. Fuzzy membership functions are defined by an expert-based vulnerability index. Instead of determining well-defined boundaries between risk zones, the proposed approach permits a smooth transition from one zone to another. The membership values of multiple indicators (e.g. slop and elevation of region under study, infrastructures, houses, hydrology network and so on) are then aggregated based on risk formula and Fuzzy IF-THEN rules to represent risk zones. Also, the key elements of a fuzzy spatial datacube are formally defined by combining fuzzy set theory and GeoBI paradigm. In this regard, some operators of fuzzy spatial aggregation are also formally defined. The main contribution of this study is combining fuzzy set theory and GeoBI. This makes spatial knowledge discovery more understandable with human reasoning and perception. Hence, an analytical conceptual framework was proposed based on GeoBI paradigm to develop a fuzzy spatial datacube within Spatial Online Analytical Processing (SOLAP) to assess coastal erosion risk. This necessitates developing a framework to design a conceptual model based on risk parameters, implementing fuzzy spatial objects in a spatial multi-dimensional database, and aggregating fuzzy spatial objects to deal with multi-scale representation of risk zones. To validate the proposed approach, it is applied to Perce region (Eastern Quebec, Canada) as a case study

    Bridging the Gap Between Traditional Metadata and the Requirements of an Academic SDI for Interdisciplinary Research

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    Metadata has long been understood as a fundamental component of any Spatial Data Infrastructure, providing information relating to discovery, evaluation and use of datasets and describing their quality. Having good metadata about a dataset is fundamental to using it correctly and to understanding the implications of issues such as missing data or incorrect attribution on the results obtained for any analysis carried out. Traditionally, spatial data was created by expert users (e.g. national mapping agencies), who created metadata for the data. Increasingly, however, data used in spatial analysis comes from multiple sources and could be captured or used by nonexpert users – for example academic researchers ‐ many of whom are from non‐GIS disciplinary backgrounds, not familiar with metadata and perhaps working in geographically dispersed teams. This paper examines the applicability of metadata in this academic context, using a multi‐national coastal/environmental project as a case study. The work to date highlights a number of suggestions for good practice, issues and research questions relevant to Academic SDI, particularly given the increased levels of research data sharing and reuse required by UK and EU funders

    Multidimensional Marine Data: The next frontier for Hydrographic Offices

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    Hydrographic offices today exist in a world of accelerating technological change that is influencing human behavior, creating new needs and ways for exploiting data to understand our world. Hydrographic offices have traditionally been the producers of nautical information for safety of navigation. By the end of the 20th century, with the appearance of the IHO S-57 Standard, their main challenge was to evolve into a central database production system. Now, the main challenge and opportunity is to evolve from there into a true geospatial agency, developing a hydrospatial information system capable of providing products and services for multidimensional analysis and decision-making through apps and web browsers at the "speed of trust." The technology to do this is there; it is a matter of vision and desire to move toward the next frontier.Los Servicios HidrogrĂĄficos existen hoy en dĂ­a en un mundo de cambios tecnolĂłgicos acelerados que estĂĄn influyendo en el comportamiento humano, creando nuevas necesidades y formas de explotar los datos para entender nuestro mundo. Los Servicios HidrogrĂĄficos han sido tradicionalmente los productores de informaciĂłn nĂĄutica para la seguridad de la navegaciĂłn. A finales del siglo XX, con la apariciĂłn de la Norma S-57 de la OHI, su principal desafĂ­o fue evolucionar hacia un sistema central de producciĂłn de bases de datos. Ahora, el desafĂ­o y la oportunidad principales son evolucionar hacia una verdadera agencia geoespacial, desarrollando un sistema de informaciĂłn hidroespacial capaz de proporcionar productos y servicios para un anĂĄlisis y una toma de decisiones multidimensionales mediante aplicaciones y navegadores web a la "velocidad de la confianza". La tecnologĂ­a para hacerlo estĂĄ ahĂ­; es una cuestiĂłn de visiĂłn y de deseo de avanzar hacia la prĂłxima frontera.Les services hydrographiques Ă©voluent aujourd’hui dans un monde oĂč les changements technologiques s’accĂ©lĂšrent, influençant le comportement humain, crĂ©ant de nouveaux besoins et de nouvelles maniĂšres d’exploiter les donnĂ©es afin de comprendre notre monde. Les services hydrographiques sont les traditionnels producteurs des informations nautiques aux fins de la sĂ©curitĂ© de la navigation. A la fin du 20Ăšme siĂšcle, avec l’apparition de la norme S-57 de l’OHI, leur principal dĂ©fi Ă©tait d’évoluer pour devenir un systĂšme central de production de base de donnĂ©es. A prĂ©sent, leur principal dĂ©fi et opportunitĂ© est d’évoluer de ce rĂŽle pour devenir une vĂ©ritable agence gĂ©ospatiale, en dĂ©veloppant un systĂšme d’informations hydrospatiales capable de fournir des produits et services aux fins d’analyse multidimensionnelle et de prise de dĂ©cision via des applications et des navigateurs web Ă  la « vitesse de la confiance ». La technologie pour relever ce dĂ©fi existe, c’est donc une question de vision et de volontĂ© d’avancer vers la prochaine frontiĂšre

    EcoGIS – GIS tools for ecosystem approaches to fisheries management

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    Executive Summary: The EcoGIS project was launched in September 2004 to investigate how Geographic Information Systems (GIS), marine data, and custom analysis tools can better enable fisheries scientists and managers to adopt Ecosystem Approaches to Fisheries Management (EAFM). EcoGIS is a collaborative effort between NOAA’s National Ocean Service (NOS) and National Marine Fisheries Service (NMFS), and four regional Fishery Management Councils. The project has focused on four priority areas: Fishing Catch and Effort Analysis, Area Characterization, Bycatch Analysis, and Habitat Interactions. Of these four functional areas, the project team first focused on developing a working prototype for catch and effort analysis: the Fishery Mapper Tool. This ArcGIS extension creates time-and-area summarized maps of fishing catch and effort from logbook, observer, or fishery-independent survey data sets. Source data may come from Oracle, Microsoft Access, or other file formats. Feedback from beta-testers of the Fishery Mapper was used to debug the prototype, enhance performance, and add features. This report describes the four priority functional areas, the development of the Fishery Mapper tool, and several themes that emerged through the parallel evolution of the EcoGIS project, the concept and implementation of the broader field of Ecosystem Approaches to Management (EAM), data management practices, and other EAM toolsets. In addition, a set of six succinct recommendations are proposed on page 29. One major conclusion from this work is that there is no single “super-tool” to enable Ecosystem Approaches to Management; as such, tools should be developed for specific purposes with attention given to interoperability and automation. Future work should be coordinated with other GIS development projects in order to provide “value added” and minimize duplication of efforts. In addition to custom tools, the development of cross-cutting Regional Ecosystem Spatial Databases will enable access to quality data to support the analyses required by EAM. GIS tools will be useful in developing Integrated Ecosystem Assessments (IEAs) and providing pre- and post-processing capabilities for spatially-explicit ecosystem models. Continued funding will enable the EcoGIS project to develop GIS tools that are immediately applicable to today’s needs. These tools will enable simplified and efficient data query, the ability to visualize data over time, and ways to synthesize multidimensional data from diverse sources. These capabilities will provide new information for analyzing issues from an ecosystem perspective, which will ultimately result in better understanding of fisheries and better support for decision-making. (PDF file contains 45 pages.

    Participatory Geographic Information Systems as an Organizational Platform for the Integration of Traditional and Scientific Knowledge in Contemporary Fire and Fuels Management

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    Traditional knowledge about fire and its effects held by indigenous people, who are connected to specific landscapes, holds promise for informing contemporary fire and fuels management strategies and augmenting knowledge and information derived from western science. In practice, however, inadequate means to organize and communicate this traditional knowledge with scientists and managers can limit its consideration in decisions, requiring novel approaches to interdisciplinary and cross-cultural communication and collaboration. We propose that Participatory Geographic Information Systems (PGIS) is one platform for the assemblage and communication of traditional knowledge vital to fire and fuels management, while preserving linkages to broader cultural contexts. We provide summaries of four preliminary case studies in the Intermountain West of North America to illustrate different potential applications of a PGIS tool in this context and describe some remaining challenges. Management and Policy Implications: Participatory Geographic Information Systems (PGIS) can offer a powerful approach for enhancing current decisionmaking by allowing for the integration of traditional and scientific knowledge systems with spatial environmental data in an interactive participatory process. Integrated data sets can allow traditional and scientific knowledge experts to share, explore, manage, analyze, and interpret multidimensional data in a common spatial context to develop more informed management decisions. Such combined data sets could provide a more comprehensive assessment of fire-related ecological change than is currently used in decisionmaking and enhance inclusion of effects on local resource utility values and areas of cultural significance. The use of a PGIS interface creates opportunities for traditional knowledge holders to share information and potential prescriptions while maintaining confidentiality. Knowledge integration efforts using PGIS as an organizational tool would help to bridge the communication gap that commonly exists between scientists, managers, and traditional knowledge holders as ecosystems continue to be altered through processes of land management and climate change

    Collaborative geographic visualization

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    Dissertação apresentada na Faculdade de CiĂȘncias e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil GestĂŁo e Sistemas AmbientaisThe present document is a revision of essential references to take into account when developing ubiquitous Geographical Information Systems (GIS) with collaborative visualization purposes. Its chapters focus, respectively, on general principles of GIS, its multimedia components and ubiquitous practices; geo-referenced information visualization and its graphical components of virtual and augmented reality; collaborative environments, its technological requirements, architectural specificities, and models for collective information management; and some final considerations about the future and challenges of collaborative visualization of GIS in ubiquitous environment

    Earth Observation Open Science and Innovation

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    geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

    Improving knowledge about the risks of inappropriate uses of geospatial data by introducing a collaborative approach in the design of geospatial databases

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    La disponibilitĂ© accrue de l’information gĂ©ospatiale est, de nos jours, une rĂ©alitĂ© que plusieurs organisations, et mĂȘme le grand public, tentent de rentabiliser; la possibilitĂ© de rĂ©utilisation des jeux de donnĂ©es est dĂ©sormais une alternative envisageable par les organisations compte tenu des Ă©conomies de coĂ»ts qui en rĂ©sulteraient. La qualitĂ© de donnĂ©es de ces jeux de donnĂ©es peut ĂȘtre variable et discutable selon le contexte d’utilisation. L’enjeu d’inadĂ©quation Ă  l’utilisation de ces donnĂ©es devient d’autant plus important lorsqu’il y a disparitĂ© entre les nombreuses expertises des utilisateurs finaux de la donnĂ©e gĂ©ospatiale. La gestion des risques d’usages inappropriĂ©s de l’information gĂ©ospatiale a fait l’objet de plusieurs recherches au cours des quinze derniĂšres annĂ©es. Dans ce contexte, plusieurs approches ont Ă©tĂ© proposĂ©es pour traiter ces risques : parmi ces approches, certaines sont prĂ©ventives et d’autres sont plutĂŽt palliatives et gĂšrent le risque aprĂšs l'occurrence de ses consĂ©quences; nĂ©anmoins, ces approches sont souvent basĂ©es sur des initiatives ad-hoc non systĂ©miques. Ainsi, pendant le processus de conception de la base de donnĂ©es gĂ©ospatiale, l’analyse de risque n’est pas toujours effectuĂ©e conformĂ©ment aux principes d’ingĂ©nierie des exigences (Requirements Engineering) ni aux orientations et recommandations des normes et standards ISO. Dans cette thĂšse, nous Ă©mettons l'hypothĂšse qu’il est possible de dĂ©finir une nouvelle approche prĂ©ventive pour l’identification et l’analyse des risques liĂ©s Ă  des usages inappropriĂ©s de la donnĂ©e gĂ©ospatiale. Nous pensons que l’expertise et la connaissance dĂ©tenues par les experts (i.e. experts en geoTI), ainsi que par les utilisateurs professionnels de la donnĂ©e gĂ©ospatiale dans le cadre institutionnel de leurs fonctions (i.e. experts du domaine d'application), constituent un Ă©lĂ©ment clĂ© dans l’évaluation des risques liĂ©s aux usages inadĂ©quats de ladite donnĂ©e, d’oĂč l’importance d’enrichir cette connaissance. Ainsi, nous passons en revue le processus de conception des bases de donnĂ©es gĂ©ospatiales et proposons une approche collaborative d’analyse des exigences axĂ©e sur l’utilisateur. Dans le cadre de cette approche, l’utilisateur expert et professionnel est impliquĂ© dans un processus collaboratif favorisant l’identification a priori des cas d’usages inappropriĂ©s. Ensuite, en passant en revue la recherche en analyse de risques, nous proposons une intĂ©gration systĂ©mique du processus d’analyse de risque au processus de la conception de bases de donnĂ©es gĂ©ospatiales et ce, via la technique Delphi. Finalement, toujours dans le cadre d’une approche collaborative, un rĂ©fĂ©rentiel ontologique de risque est proposĂ© pour enrichir les connaissances sur les risques et pour diffuser cette connaissance aux concepteurs et utilisateurs finaux. L’approche est implantĂ©e sous une plateforme web pour mettre en Ɠuvre les concepts et montrer sa faisabilitĂ©.Nowadays, the increased availability of geospatial information is a reality that many organizations, and even the general public, are trying to transform to a financial benefit. The reusability of datasets is now a viable alternative that may help organizations to achieve cost savings. The quality of these datasets may vary depending on the usage context. The issue of geospatial data misuse becomes even more important because of the disparity between the different expertises of the geospatial data end-users. Managing the risks of geospatial data misuse has been the subject of several studies over the past fifteen years. In this context, several approaches have been proposed to address these risks, namely preventive approaches and palliative approaches. However, these approaches are often based on ad-hoc initiatives. Thus, during the design process of the geospatial database, risk analysis is not always carried out in accordance neither with the principles/guidelines of requirements engineering nor with the recommendations of ISO standards. In this thesis, we suppose that it is possible to define a preventive approach for the identification and analysis of risks associated to inappropriate use of geospatial data. We believe that the expertise and knowledge held by experts and users of geospatial data are key elements for the assessment of risks of geospatial data misuse of this data. Hence, it becomes important to enrich that knowledge. Thus, we review the geospatial data design process and propose a collaborative and user-centric approach for requirements analysis. Under this approach, the user is involved in a collaborative process that helps provide an a priori identification of inappropriate use of the underlying data. Then, by reviewing research in the domain of risk analysis, we propose to systematically integrate risk analysis – using the Delphi technique – through the design of geospatial databases. Finally, still in the context of a collaborative approach, an ontological risk repository is proposed to enrich the knowledge about the risks of data misuse and to disseminate this knowledge to the design team, developers and end-users. The approach is then implemented using a web platform in order to demonstrate its feasibility and to get the concepts working within a concrete prototype
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