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1
Margarit, Daniel. "Exploring Land Conservation Using Economic and Geospatial Models." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/25380.
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Three different, but related studies on conservation in North Dakota were completed. Expansion of Devil?s Lake over the past 20 years has flooded farmland, towns, and roads, causing economic damage and distress. Retirement of private land into conservation could play a role in ameliorating damages to citizens, while simultaneously improving and protecting wildlife habitat. The objective of the first study is to investigate the supply of agricultural land that might be available for conservation use at various purchase prices. It was expected that increasingly frequent flooding over the past decades would have increased the supply of land available for conservation. This was verified to be the case for the most vulnerable lands in Devil?s Lake Basin?areas below 1,460 ft. elevation and within 300 ft. of surface waters.
The Conservation Reserve Program is comprised of lands that were previously farmed and have been converted into grassland. The landowners are compensated by the US government for retiring this farmland because it provides environmental benefits. Current commodity prices are giving farmers less incentive to renew their CRP contracts and many are deciding to instead farm those lands. The second study aims to identify and quantify the factors that affect a landowner?s decision to renew an expiring CRP contract or not in the Sheyenne River basin. The economic factors examined were crop prices and CRP payments. The ecological factors were slope of the land, distance to the nearest stream, and soil texture.
The purpose of the final study is to estimate the increase in sediment loading due to changes in CRP enrollment, and then value the cost to society of the increased sedimentation. This will be accomplished by creating a SWAT model of the Sheyenne River. Future and hypothetical land use datasets will be substituted into the model. Every ton of sediment entering the river costs society an estimated $2.40. The model estimated 1,218.36 tons of sediment entered the river from the study area in 2005. Using the landcover conditions present in 2014, an estimated 1,661.4 tons of sediment would have entered the river across the study area, an increase of 36%.
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Shearer, Freya. "Improving geospatial models of risk for vector-borne, zoonotic diseases." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:cfe8ffa9-453b-4e10-9009-e387a39db6de.
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Public health surveillance data are often incomplete, particularly where resources are lacking, but geospatial models can help to fill the gaps by providing estimates where data are sparse. By combining information on locations where diseases have been recorded with geographic data on environmental and socioeconomic covariates known to affect disease transmission using machine-learning models (such as boosted regression trees), niche modelling can generate fine-resolution, evidence-based risk maps for a variety of diseases of public health importance. This thesis investigates the geographical distribution of two vector-borne, zoonotic diseases of public health importance: Plasmodium knowlesi malaria and yellow fever (YF). A number of new methodological approaches to niche modelling are developed for: mapping diseases whose distributions are impacted by multiple host and vector species, ameliorating spatial bias in disease reporting rates, and accounting for human vaccination coverage. Chapter 2 investigates spatial variation in risk of human P. knowlesi infection across Southeast Asia. The infection risk model for P. knowlesi malaria is based on improvements to a standard niche modelling approach, and incorporates a novel joint distribution model to leverage data from a number of host species. Chapter 3 estimates YF vaccination coverage through time across all age cohorts in every district/municipality of countries at risk of YF, globally. These estimates are used to estimate the additional vaccination coverage needed to prevent further YF outbreaks, and they provide information needed to account for population immunity when estimating YF infection risk. Chapter 4 describes the development of a novel Poisson point process niche model, which is then used to predict YF infection risk in humans and demonstrates how vaccination coverage can be efficiently accounted for in disease niche models. The disease risk maps of P. knowlesi malaria and YF produced through this thesis will act as resources to improve the targeting, implementation and evaluation of disease prevention, surveillance and control strategies. Methods developed to account for vaccination coverage, reporting rate biases, and complex transmission systems will be applicable to risk mapping for a range of vector-borne, zoonotic diseases of public health importance.
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Isikdag, U. "Towards the implementation of building information models in geospatial context." Thesis, University of Salford, 2006. http://usir.salford.ac.uk/26731/.
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The construction industry is very much fragmented and the concept of interoperability and integrated model based engineering is now becoming an industrial need, to address the difficulties of information exchange at all stages and between all parties involved in the construction life cycle. The lAI's IFC (common building information model standard) is now maturing in supporting the various phases of the construction life cycle. In addition, the industry is beginning to use geographic information systems (GISs) in various stages of the construction life cycle. Geospatial representations of building information models can be required when working with geographic information systems in the construction life cycle. On the other hand, geographic information systems are commonly used information systems to plan and manage the urban built environment. Some urban management tasks such as disaster management, delivery of goods and services, detailed cityscape visualisation require a high amount of geometrical and non-geometrical information about buildings. In fact, the lack of integration between Building Information Models and the Geospatial Information Domain, creates a technological barrier to, automation of some industrial processes in construction life cycle and urban management domains. In order to find a solution to this integration problem, this study aimed to assess the applicability and benefits of an implementation of a building information model in geospatial context. In light of the aim, the research assesses how a technological innovation (an implementation of a building information model in a geospatial context) can improve the process in related areas of the construction life cycle and urban management domains. The research started with a background literature review that is concerned with the trends and visions of construction information technology, in order to determine the main research directions. Major industrial trends and visions of, computer integrated construction were investigated and, building and geospatial information modelling are selected as two main research directions. The next phase of the background study aimed to investigate the building information modelling knowledge domain. In this context Standard for the Exchange of Product Model Data (STEP), STEP based methods for information exchange, file and database implementations of STEP, STEP based building information modelling efforts, the structure of industry standard building information model- Industry Foundation Classes (IFC)-, several industrial projects that implement IFC model are investigated. The final stage of the background study investigated the modelling and management of geospatial information. This stage of the research started with investigating the role of geospatial information in construction and urban management knowledge domains. The research continued with investigating the geospatial data modelling efforts in two and three dimensions, and also looked at the use of three dimensional geospatial
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March, Morlà David. "Geospatial modeling in marine recreational fisheries science." Doctoral thesis, Universitat de les Illes Balears, 2014. http://hdl.handle.net/10803/283186.
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El presente trabajo de tesis doctoral propone diferentes enfoques geoespaciales destinados al análisis de la dimensión espacial de las pesquerías recreativas costeras utilizando métodos cuantitativos y herramientas computacionales. Diferentes tipos de información espacial,relativas a los hábitats bentónicos así como a la movilidad y a la calidad de las capturas, han sido combinadas para estimar el esfuerzo de pesca y las capturas totales, utilizando un enfoque original y espacialmente explícito. El objetivo es el de progresar en la comprensión del comportamiento espacial del pescador a través de un enfoque holístico basado en datos empíricos y modelos estadísticos. La modalidad de pesca del 'roquer', una de las pesquerías recreativas costeras más populares en el Mediterráneo, ha sido utilizada como caso de estudio en la bahía de Palma (en el Mediterráneo noroccidental).<br>This thesis proposes different geospatial approaches for assessing the spatial dimension of the coastal recreational fisheries using quantitative methods and computational tools. Spatial information on benthic habitats, fish mobility and fishing quality were combined for estimating fishing effort and harvest using an original spatially-explicit approach. The aim is to advance in our understanding of angler spatial behaviour using a holistic approach based on empirical data and statistical models. In order to illustrate the proposed framework, the ‘roquer’ modality, one of the most popular coastal recreational fisheries in the Mediterranean Sea, was used as case study at Palma Bay (NW Mediterranean).
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Al-Bakri, Maythm M. Sharky. "Developing tools and models for evaluating geospatial data integration of official and VGI data sources." Thesis, University of Newcastle Upon Tyne, 2012. http://hdl.handle.net/10443/1676.
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In recent years, systems have been developed which enable users to produce, share and update information on the web effectively and freely as User Generated Content (UGC) data (including Volunteered Geographic Information (VGI)). Data quality assessment is a major concern for supporting the accurate and efficient spatial data integration required if VGI is to be used alongside official, formal, usually governmental datasets. This thesis aims to develop tools and models for the purpose of assessing such integration possibilities. Initially, in order to undertake this task, geometrical similarity of formal and informal data was examined. Geometrical analyses were performed by developing specific programme interfaces to assess the positional, linear and polygon shape similarity among reference field survey data (FS); official datasets such as data from Ordnance Survey (OS), UK and General Directorate for Survey (GDS), Iraq agencies; and VGI information such as OpenStreetMap (OSM) datasets. A discussion of the design and implementation of these tools and interfaces is presented. A methodology has been developed to assess such positional and shape similarity by applying different metrics and standard indices such as the National Standard for Spatial Data Accuracy (NSSDA) for positional quality; techniques such as buffering overlays for linear similarity; and application of moments invariant for polygon shape similarity evaluations. The results suggested that difficulties exist for any geometrical integration of OSM data with both bench mark FS and formal datasets, but that formal data is very close to reference datasets. An investigation was carried out into contributing factors such as data sources, feature types and number of data collectors that may affect the geometrical quality of OSM data and consequently affect the integration process of OSM datasets with FS, OS and GDS. Factorial designs were undertaken in this study in order to develop and implement an experiment to discover the effect of these factors individually and the interaction between each of them. The analysis found that data source is the most significant factor that affects the geometrical quality of OSM datasets, and that there are interactions among all these factors at different levels of interaction. This work also investigated the possibility of integrating feature classification of official datasets such as data from OS and GDS geospatial data agencies, and informal datasets such as OSM information. In this context, two different models were developed. The first set of analysis included the evaluation of semantic integration of corresponding feature classifications of compared datasets. The second model was concerned with assessing the ability of XML schema matching of feature classifications of tested datasets. This initially involved a tokenization process in order to split up into single words classifications that were composed of multiple words. Subsequently, encoding feature classifications as XML schema trees was undertaken. The semantic similarity, data type similarity and structural similarity were measured between the nodes of compared schema trees. Once these three similarities had been computed, a weighted combination technique has been adopted in order to obtain the overall similarity. The findings of both sets of analysis were not encouraging as far as the possibility of effectively integrating feature classifications of VGI datasets, such as OSM information, and formal datasets, such as OS and GDS datasets, is concerned.
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Michell, Justin Walter. "A review of generalized linear models for count data with emphasis on current geospatial procedures." Thesis, Rhodes University, 2016. http://hdl.handle.net/10962/d1019989.
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Analytical problems caused by over-fitting, confounding and non-independence in the data is a major challenge for variable selection. As more variables are tested against a certain data set, there is a greater risk that some will explain the data merely by chance, but will fail to explain new data. The main aim of this study is to employ a systematic and practicable variable selection process for the spatial analysis and mapping of historical malaria risk in Botswana using data collected from the MARA (Mapping Malaria Risk in Africa) project and environmental and climatic datasets from various sources. Details of how a spatial database is compiled for a statistical analysis to proceed is provided. The automation of the entire process is also explored. The final bayesian spatial model derived from the non-spatial variable selection procedure using Markov Chain Monte Carlo simulation was fitted to the data. Winter temperature had the greatest effect of malaria prevalence in Botswana. Summer rainfall, maximum temperature of the warmest month, annual range of temperature, altitude and distance to closest water source were also significantly associated with malaria prevalence in the final spatial model after accounting for spatial correlation. Using this spatial model malaria prevalence at unobserved locations was predicted, producing a smooth risk map covering Botswana. The automation of both compiling the spatial database and the variable selection procedure proved challenging and could only be achieved in parts of the process. The non-spatial selection procedure proved practical and was able to identify stable explanatory variables and provide an objective means for selecting one variable over another, however ultimately it was not entirely successful due to the fact that a unique set of spatial variables could not be selected.
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Lohani, Sapana. "Linking ecosystem services with state-and-transition models to evaluate rangeland management decisions." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/314685.
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Rangelands are a major type of land found on all continents. Though they comprise around 70% of the world's land area, knowledge of rangelands is limited and immature. Rangelands supply humans with food and fiber at very low energy costs compared to cultivated lands. They are inherently heterogeneous, highly variable in time and space. Rangeland management needs to consider the impacts of long-term vegetation transition. It needs a conceptual framework defining potential vegetation communities, describing the management induced transition of one vegetation community to another, and documenting the expected benefits provided by the various potential vegetation communities. The most widely used conceptual unit in the rangeland discipline is the "ecological site". Ecological sites can be an effective unit that should respond to management consistently and can help managers understand the site's potential to meet human needs. A state and transition model (STM) brings ecological sites and their potential vegetative states together to build a conceptual framework showing the major causes of transitions between states of an ecological site and thus helping make adaptive management decisions. Within the STM there is a need for an indicator of ecosystem health. Ecosystem services can be important to evaluate alternative states. Ecosystem services do not pass through a market for valuation, though often the cost would be very high if, through mismanagement, the ecosystem is no longer capable of providing those services. Vegetation communities are constantly facing reversible or irreversible transitions triggered by natural events and/or management actions. The framework generated in this study is significant in using remote sensing to generate state and transition models for a large area and in using ecosystem services to evaluate natural and/or management induced transitions as described in the STM. This dissertation addresses the improvement of public rangelands management in the West. It applies geospatial technologies to map ecological sites and states on those sites, characterizes transitions between states and selects a desired state to manage towards based on a systematic assessment of the value of flows of environmental services. The results from this study are an evaluation of improved draft ecological site maps for a larger area using remote sensing images, a simplified state-and-transition model adapted to remote sensing capabilities to study transitions due to climatic events and management practices, and a constrained optimization model that incorporates ecosystem services and the simplified STM to evaluate management costs and conservation benefits. The study showed that brush treatment is the most effective management practice to cause state transitions. The highest increase in the high cover state was by 24%. Areas under grazing and drought show slow transitions from brush to grass and also after prescribed fire vegetation take at least two years to recover.
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Shrewsbury, John Stephen. "Calibration of trip distribution by generalised linear models." Thesis, University of Canterbury. Department of Civil and Natuaral Resources Engineering, 2012. http://hdl.handle.net/10092/7685.
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Generalised linear models (GLMs) provide a flexible and sound basis for calibrating gravity models for trip distribution, for a wide range of deterrence functions (from steps to splines), with K factors and geographic segmentation. The Tanner function fitted Wellington Transport Strategy Model data as well as more complex functions and was insensitive to the formulation of intrazonal and external costs. Weighting from variable expansion factors and interpretation of the deviance under sparsity are addressed.
An observed trip matrix is disaggregated and fitted at the household, person and trip levels with consistent results. Hierarchical GLMs (HGLMs) are formulated to fit mixed logit models, but were unable to reproduce the coefficients of simple nested logit models.
Geospatial analysis by HGLM showed no evidence of spatial error patterns, either as random K factors or as correlations between them. Equivalence with hierarchical mode choice, duality with trip distribution, regularisation, lorelograms, and the modifiable areal unit problem are considered.
Trip distribution is calibrated from aggregate data by the MVESTM matrix estimation package, incorporating period and direction factors in the intercepts. Counts across four screenlines showed a significance similar to a thousand-household travel survey. Calibration was possible only in conjuction with trip end data. Criteria for validation against screenline counts were met, but only if allowance was made for error in the trip end data.
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Pereira, Luiz Henrique [UNESP]. "Análise de sensibilidade e propagação de incerteza em modelos hidrossedimentológicos: contribuição à modelagem de bacias hidrográficas." Universidade Estadual Paulista (UNESP), 2016. http://hdl.handle.net/11449/146738.
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Previous issue date: 2016-10-28<br>Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)<br>Atenuar incertezas nos resultados de modelos dinâmicos que estimam a produção de sedimento na vertente e o transporte do material no canal fluvial torna-se fundamental quando se considera a premência de políticas territoriais em minimizar o risco de sub ou super exploração dos recursos naturais, bem como indicar a disponibilidade de água em bacias hidrográficas. A aplicação de modelos de simulação de processos ambientais tem sido amplamente favorecida pelo avanço das geotecnologias, em especial dos Sistemas de Informações Geográficas, que viabilizam a extração, tratamento, análise e integração de dados geoespaciais. No entanto, observa-se que pouca atenção tem sido dada à análise e avaliação dos fatores responsáveis pela discrepância entre estimativas e observações. Diante o exposto, este trabalho apresentou como principal objetivo caracterizar a variabilidade espacial da incerteza propagada pela aplicação dos modelos hidrossedimentológicos EUPS, MEUPS e REUPS, e indicar sua correlação espacial com características geomorfométricas da área em análise. As atividades foram desenvolvidas com o escopo teórico da modelagem de sistemas ambientais, e baseadas em técnicas de geoprocessamento e sensoriamento remoto. Os resultados obtidos demonstram que a sensibilidade dos parâmetros é específica para cada tipo de bacia modelada, sendo os Fatores C, P os mais sensíveis para bacia do Monjolo Grande, e os Fatores C e LS os mais sensíveis para a bacia do ribeirão Jacutinga. As incertezas possuem maior expressividade nas áreas predominantemente de solos arenosos, e há correlação significativa do grau de incerteza dos resultados dos modelos com as características geomorfológicas, sobretudo em áreas de vertentes côncavas.<br>Lessening the uncertainties in the results from geospatial dynamic models, considering those that estimate the sediment production in the hillslope and the transportation of sediments over the river-channel, becomes essential when considering the current need to gather trustworthy quantitative information. In this sense, the contribution of hydro-sedimentological modeling is a significant part on the landscape planning phase, effectively composing the process of agricultural land management. The application of geospatial modeling has been widely benefited by the improvement on geotechnologies. However, it´s application has been applied indiscriminately from the procedures and methods for gathering entrance data. Differences in spatial scale of analysis, the characteristics of the geographical area of interest and the evaluation of the trustworthiness of the results are not taken into account. With these issues exposed this paper aimed to characterize the spatial variables and the uncertainties programed by the applications of the hydro-sedimentological models USLE, MUSLE e RUSLE. Indicating it´s spatial correlation with the geomorphometry characteristics of the analyzed areas it was possible to propose an objective criteria for the selection of the models based on the area´s geomorphological characteristics searching to minimize the statistical uncertainties thus offering measurements of trustworthiness in the final results. The activities were developed with the theoretical scope of environmental systems modeling and based on geoprocessing and remote sensing techniques. Results gathered show that the sensitivity of the parameters is specific to each type of watershed that was modeled, C and P factors being the most sensitives for Monjolo Grande river basin (sandy soil), and C and LS factors were the most sensitives for Jacutinga river basin (clay soil). The uncertainties are more prominent in the areas where the soil is predominantly sandy. There was a significant correlation between the level of uncertainty and the results from the models with geomorphological characteristic, especially in concave hillslope areas.<br>FAPESP: 2013/13885-0
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Madsen, Christopher. "Clustering of the Stockholm County housing market." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252301.
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In this thesis a clustering of the Stockholm county housing market has been performed using different clustering methods. Data has been derived and different geographical constraints have been used. DeSO areas (Demographic statistical areas), developed by SCB, have been used to divide the housing market in to smaller regions for which the derived variables have been calculated. Hierarchical clustering methods, SKATER and Gaussian mixture models have been applied. Methods using different kinds of geographical constraints have also been applied in an attempt to create more geographically contiguous clusters. The different methods are then compared with respect to performance and stability. The best performing method is the Gaussian mixture model EII, also known as the K-means algorithm. The most stable method when applied to bootstrapped samples is the ClustGeo-method.<br>I denna uppsats har en klustring av Stockholms läns bostadsmarknad genomförts med olika klustringsmetoder. Data har bearbetats och olika geografiska begränsningar har använts. DeSO (Demografiska Statistiska Områden), som utvecklats av SCB, har använts för att dela in bostadsmarknaden i mindre regioner för vilka områdesattribut har beräknats. Hierarkiska klustringsmetoder, SKATER och Gaussian mixture models har tillämpats. Metoder som använder olika typer av geografiska begränsningar har också tillämpats i ett försök att skapa mer geografiskt sammanhängande kluster. De olika metoderna jämförs sedan med avseende på kvalitet och stabilitet. Den bästa metoden, med avseende på kvalitet, är en Gaussian mixture model kallad EII, även känd som K-means. Den mest stabila metoden är ClustGeo-metoden.
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Chin, Philip Allen. "Sensor Networks: Studies on the Variance of Estimation, Improving Event/Anomaly Detection, and Sensor Reduction Techniques Using Probabilistic Models." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/33645.
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Sensor network performance is governed by the physical placement of sensors and their geometric relationship to the events they measure. To illustrate this, the entirety of this thesis covers the following interconnected subjects: 1) graphical analysis of the variance of the estimation error caused by physical characteristics of an acoustic target source and its geometric location relative to sensor arrays, 2) event/anomaly detection method for time aggregated point sensor data using a parametric Poisson distribution data model, 3) a sensor reduction or placement technique using Bellman optimal estimates of target agent dynamics and probabilistic training data (Goode, Chin, & Roan, 2011), and 4) transforming event monitoring point sensor data into event detection and classification of the direction of travel using a contextual, joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method.<br>Master of Science
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Jiménez, Vélez Alex Fernando. "Modelo de planificación sanitaria geoespacial de inteligencia colectiva = Geospatial model of planning health collective intelligence." Doctoral thesis, Universitat Politècnica de Catalunya, 2017. http://hdl.handle.net/10803/405638.
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Within the practice of public health at a global level there is now a greater interest in conceptualizing, materialize, and achieve the development of "healthy communities". Such communities would require the approach of new approaches in the planning to tackle its challenges based on timely access to information and collaborative planning of their local processes. However, until the moment little research focuses on methods based on these principles collaborative support to this type of response required in health planning of these communities.
In addition in developing countries has been implementing the Model of Integral Health Care Family, Community and Intercultural Education (MAIS-FCI), whose design requires articulate an artifact agile to integrate its public officials, health teams and community in the identification, analysis and decision-making of comprehensive health actions of its territory. Thereby allowing the planning and direction of strategic actions where the community becomes the active subject of the construction and health care, raising sustainable solutions through a proper analysis of its geographical area.
In this way, in this thesis is presented an investigation that was intended to propose and evaluate a conceptual and methodological model of collective planning for the identification of health services in the territory. The model, through a collective intelligence geospatial system sought to provide an ideal tool to optimize the process of decision-making in health planning (for example: the distribution of health services) and facilitate so the development of healthy communities located in varied and complex geographic settings.
By adopting the methodology of Participatory Action Research (IAP by its acronym in Spanish) along with a helper method as is the documentary research, generated an artifact called Geospatial Health Planning Model of Collective Intelligence (MPSIC), with which it was able to promote a process of collective intelligence in the health communities participating in the evaluation of sites suitable for the distribution of health services. This model was evaluated in two different situations of location of sanitary campaigns in Ecuador: The first for post of supply of screening tests of HIV and the second for days of collection of blood. Annual extramural
The main results obtained exhibited an acceptable level of relevance and adequacy of the proposed model in health planning, as well as an empowerment of the knowledge of the participants, improve the participation and consensus in the decision-making process for the allocation of health services. It also managed to determine geographic sites suitable to highly specialized problems in the field of health through a group of multidisciplinary experts without previous knowledge in geo-technological tools.<br>Dentro de la práctica de salud pública a nivel global existe en la actualidad un interés mayor por conceptualizar, materializar y alcanzar el desarrollo de "comunidades saludables". Tales comunidades, requerirían el planteamiento de nuevos enfoques en la planificación que permitan afrontar sus desafíos basándose en el acceso oportuno a la información y la planificación colaborativa de sus procesos locales. Sin embargo, hasta el momento existe poca investigación que se enfoque en métodos basados en estos principios colaborativos que apoyen a este tipo de respuesta requerida en la planificación sanitaria de dichas comunidades. Además en los países en vías de desarrollo se viene implantando el Modelo de Atención Integral en Salud Familiar, Comunitario e Intercultural (MAIS-FCI), cuya concepción requiere articular un artefacto ágil que permita integrar a sus funcionarios públicos, equipos de salud y comunidad, en la identificación, análisis y toma de decisiones de acciones integrales de salud de su territorio, permitiendo de esta forma la planeación y dirección de acciones estratégicas donde la comunidad se convierta en sujeto activo de la construcción y cuidado de la salud, planteando soluciones sustentables mediante un adecuado análisis de su espacio geográfico. De esta manera, en la presente tesis se presenta una investigación que tuvo como propósito proponer y evaluar un modelo conceptual y metodológico de planificación colectiva para la identificación de servicios sanitarios en el territorio. El modelo, a través de un sistema geoespacial de inteligencia colectiva buscó aportar una herramienta idónea para optimizar el proceso de toma de decisiones en la planificación sanitaria (por ejemplo: la distribución de servicios sanitarios) y facilitar así el desarrollo de comunidades saludables localizadas en variados y complejos escenarios geográficos. Adoptando la metodología de Investigación-Acción Participativa (IAP por su acrónimo en español) junto con un método auxiliar como lo es la Investigación Documental, se generó un artefacto denominado Modelo de Planificación Sanitaria Geoespacial de Inteligencia Colectiva (MPGSIC), con el cual se logró fomentar un proceso de inteligencia colectiva en las comunidades de salud participantes en la evaluación de sitios idóneos para la distribución de servicios sanitarios. Este modelo se evaluó en dos situaciones diferentes de ubicación de campañas sanitarias en el Ecuador: La primera para puesto de suministro de pruebas de tamizaje de VIH y la segunda para jornadas de colecta extramural anual de sangre. Los principales resultados obtenidos exhiben un nivel aceptable de pertinencia y adecuación del modelo propuesto en la planificación sanitaria, así como un empoderamiento del conocimiento de los participantes, mejorando la participación y el consenso en el proceso de toma de decisiones para la asignación de servicios sanitarios. Además se consiguió determinar sitios geográficos idóneos a problemas altamente especializados en el campo de salud a través de un grupo de expertos multidisciplinarios sin previos conocimientos en herramientas geotecnológicas.
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Sharad, Chakravarthy Namindi. "Public Commons for Geospatial Data: A Conceptual Model." Fogler Library, University of Maine, 2003. http://www.library.umaine.edu/theses/pdf/SharadCN2003.pdf.
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Sliwinski, Adam. "A vertical product differentiation model for geospatial information services." [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=985292830.
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Farrugia, James A. "Semantic Interoperability of Geospatial Ontologies: A Model-theoretic Analysis." Fogler Library, University of Maine, 2007. http://www.library.umaine.edu/theses/pdf/FarrugiaJA2007.pdf.
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Ioup, Elias. "A Geospatial Service Model and Catalog for Discovery and Orchestration." ScholarWorks@UNO, 2011. http://scholarworks.uno.edu/td/1318.
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The goal of this research is to provide a supporting Web services architecture, consisting of a service model and catalog, to allow discovery and automatic orchestration of geospatial Web services. First, a methodology for supporting geospatial Web services with existing orchestration tools is presented. Geospatial services are automatically translated into SOAP/WSDL services by a portable service wrapper. Their data layers are exposed as atomic functions while WSDL extensions provide syntactic metadata. Compliant services are modeled using the descriptive logic capabilities of the Ontology Language for the Web (OWL). The resulting geospatial service model has a number of functions. It provides a basic taxonomy of geospatial Web services that is useful for templating service compositions. It also contains the necessary annotations to allow discovery of services. Importantly, the model defines a number of logical relationships between its internal concepts which allow inconsistency detection for the model as a whole and for individual service instances as they are added to the catalog. These logical relationships have the additional benefit of supporting automatic classification of geospatial services individuals when they are added to the service catalog. The geospatial service catalog is backed by the descriptive logic model. It supports queries which are more complex that those available using standard relational data models, such as the capability to query using concept hierarchies. An example orchestration system demonstrates the use of the geospatial service catalog for query evaluation in an automatic orchestration system (both fully and semi-automatic orchestration). Computational complexity analysis and experimental performance analysis identify potential performance problems in the geospatial service catalog. Solutions to these performance issues are presented in the form of partitioning service instance realization, low cost pre-filtering of service instances, and pre-processing realization. The resulting model and catalog provide an architecture to support automatic orchestration capable of complementing the multiple service composition algorithms that currently exist. Importantly, the geospatial service model and catalog go beyond simply supporting orchestration systems. By providing a general solution to the modeling and discovery of geospatial Web services they are useful in any geospastial Web service enterprise.
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Comer, Bryan. "Sustainable intermodal freight transportation : applying the geospatial intermodal freight transport model /." Online version of thesis, 2009. http://hdl.handle.net/1850/10887.
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Zhou, Jian. "Integrating geospatial web 2.0 and global climate model for communicating climate change." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114508.
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This study investigates the use of Geospatial Web 2.0 and Global Climate Models for climate change communication. The aim of this research has been to integrate the data, models, and tools of climate science with Geoweb to advance climate change communication. Several Geoweb applications have been developed to demonstrate the solutions for this integration and to fulfil two research objectives: (1) develop a method to employ Geoweb technologies for communicating climate change, (2) improve the accessibility of Global Climate Model by providing tools to engage people in the practice of climate science as well as the fundamental procedures involved in global climate modeling. My research method is to extend Geoweb functionality to existing climate science tools, with the goal of easing the interface and increasing the interactivity of those tools to elaborate the scientific process of climate modeling. Geoweb has the power to manipulate climate change datasets from diverse sources for creating interactive climate change visualization. This power can be further enhanced if we integrate Geoweb with scientific climate data analysis and visualization systems. Nonetheless, Geoweb technologies that provide 2D visualization are more stable, faster, and popularly used than the 3D visualization. It is more robust to use Geoweb for climate model output. Instead, employing Geoweb for other aspects of global climate model requires close cooperation between climate modeling scientists and Geoweb technology experts due to its complexity. It is crucial to balance an easy-to-use user interface and the complexity of information transferred. Following this study, it is hoped that much more efforts from global climate modeling groups and Geoweb science researchers can be drawn together to facilitate climate change communication.<br>Cette étude porte sur l'utilisation de Géospatiales Web 2.0 et Modèle Climatique Global pour le communication du changement climatique. Le but de cette recherche a été d'intégrer les données, les modèles et les outils de la science du climat avec Geoweb pour faire progresser la communication du changement climatique. Plusieurs applications de GeoWeb ont été développés pour démontrer les solutions de cette intégration et de remplir deux objectifs de recherche: (1) développer une méthode d' utiliser les technologies GeoWeb pour communiquer du changement climatique, (2) améliorer l'accessibilité de Modèle Climatique Global en fournissant des outils pour engager personnes dans la pratique de la science du climat, ainsi que les procédures fondamentales liées à la modélisation du climat mondial. Ma méthode de recherche est d'étendre les fonctionnalités de Geoweb à des outils existants des sciences du climat, dans le but d'alléger l'interface et en augmentant l'interactivité de ces outils pour élaborer le processus scientifique de la modélisation du climat. Geoweb a le pouvoir de manipuler des ensembles de données du changement climatique provenant de diverses sources pour créer une visualisation interactive du changement climatique. Ce pouvoir peut être encore améliorée si l'on intègre Geoweb avec analyse scientifique des données climatiques et des systèmes de visualisation. Néanmoins, les technologies GeoWeb qui fournissent une visualisation 2D sont plus stables, plus rapide et couramment utilisée que la visualisation 3D. Il est plus robuste à utiliser Geoweb pour la sortie des modèles climatiques. Au lieu de cela, en utilisant Geoweb pour d'autres aspects du modèle climatique global nécessite des coopérations étroites entre les scientifiques de modélisation du climat et des experts en technologie de GeoWeb en raison de sa complexité. Il est essentiel d'équilibrer un outil facile à utiliser l'interface utilisateur et la complexité des informations transférées. Suite à cette étude, il est à espérer que beaucoup plus d'efforts de groupes mondiaux de modélisation du climat et des chercheurs en sciences GeoWeb peuvent être réunis pour faciliter la communication pour le changement climatique.
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Hubbard, Shane A. "Modeling geospatial events during flood disasters for response decision-making." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/1973.
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A model that emphasizes possible alternative sequences of events that occur over time is presented in paper 1 (chapter 2) of this dissertation. Representing alternative or branching events captures additional semantics unrealized by linear or non-branching approaches. Two basic elements of branching, divergence and convergence are discussed. From these elements, many complex branching models can be built capturing a perspective of events that take place in the future or have occurred in the past. This produces likely sequences of events that a user may compare and analyze using spatial or temporal criteria. The branching events model is especially useful for spatiotemporal decision support systems, as decision-makers are able to identify alternative locations and times of events and, depending on the context, also identify regions of multiple possible events. Based on the formal model, a conceptual framework for a branching events model for flood disasters is presented. The framework has five parts, an event handler, a query engine, data assimilator, web interface, and event database. A branching events viewer application is presented illustrating a case study based on a flood response scenario.
A spatiotemporal framework for building evacuation events is developed to forecast building content evacuation events and building vulnerabilities and is presented in paper 2 (chapter 3) of this dissertation. This work investigates the spatiotemporal properties required to trigger building evacuation events in the floodplain during a flood disaster. The spatial properties for building risks are based on topography, flood inundation, building location, building elevation, and road access to determine five categories of vulnerability, vulnerable basement, flooded basement, vulnerable first-floor, flooded first-floor, and road access. The amount of time needed to evacuate each building is determined by the number of vulnerable floors, the number of movers, the mover rate, and the weight of the contents to be moved. Based upon these properties, six possible evacuation profiles are created. Using this framework, a model designed to track the spatiotemporal patterns of building evacuation events is presented. The model is based upon flood forecast predictions that are linked with building properties to create a model that captures the spatiotemporal ordering of building vulnerabilities and building content evacuation events. Applicable to different communities at risk from flooding, the evacuation model is applied a historical flood for a university campus, demonstrating how the defined elements are used to derive a pattern of vulnerability and evacuation for a campus threatened by severe flooding.
Paper 3 (Chapter 4) of this dissertation presents a modeling approach for representing event-based response risk. Surveys were sent to emergency managers in six states to determine the priorities of decision makers during the response phase of flood disasters. Based on these surveys, nine response events were determined to be the most important during a flood response, flooded roads, bridges closed, residential evacuations, residential flooding, commercial flooding, agricultural damage, power outage, sheltering, sandbagging. Survey participants were asked to complete pairwise comparisons of these nine events. An analytic hierarchy process analysis was completed to weight the response events for each decision-maker. A k-means clustering analysis was then completed to form 4 distinct profiles, mixed rural and urban, rural, urban, and high population - low population density. The average weights from each profile were calculated. The weights for each profile were then assigned to geospatial layers that identify the locations of these events. These layers are combined to form a map representing the event-based response risk for an area. The maps are then compared against the response events that actually occurred during a flood disaster in June 2008 in two communities.
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Voudouris, Vlasios. "Geospatial Modelling of Indeterminate Phenomena : The Object-Field Model with Uncertainty and Semantics." Thesis, City University London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511773.
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Ozturk, Z. "Smart grid applicability prioritisation of neighbourhoods by developing a geospatial decision support model." Thesis, University of Salford, 2013. http://usir.salford.ac.uk/30831/.
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Environmental concerns comprising pollution and global warming are among the key parameters that steer policy making actions regarding sustainability. Energy industry that comprises energy generation, distribution, and transmission phases of energy loop is at the core of these concerns and faces challenges. Due to handling capabilities, present electricity grid is not robust enough to utilize desired level of renewable energy sources due to their intermittent nature. On the other hand, emerging policies are targeting the increased utilization of renewable energy sources. In the light of environmental policies and increased stability requirements of the electricity grids, a new concept called “smart grid” emerges. Smart grids are intended to eliminate the limitations of present electricity grids such as offering increased handling capacity for renewable energy, increased interaction of the consumers with the utilities, and increased supply and demand management. It is not easy to express a solid smart grid definition as each party (energy generation, distribution, and demand side management) has its own approach in line with the desires. Due to the potential environmental benefits of smart grids, some governments engage smart grid projects to their agenda. As solid smart grid definition does not exist, there is no available solid strategy for smart grid implementations. On the other hand, it is well understood that failure in deployment of smart grids (regardless of the technology) will have undesirable impacts on growth of renewable energy generation, and failure in meeting EU carbon targets consequently. This research seeks to develop a model that seeks optimization of smart grid implementations, and it assists decision makers with deciding on the priory areas for smart grid applicability. Stated areas in this case are neighbourhoods comprising of residential buildings where considerable amount of energy is consumed. A set of criteria regarding to residential energy use and renewable energy technologies, are defined in the study. Proposed model is embedded in a GIS platform, and the main process carried out is a prioritization mechanism that comprises Analytical Hierarchy Process (AHP) and geospatial computations like clustering and regression analysis in order to evaluate the alternative neighbourhoods. Proposed model optimizes smart grid projects by ranking of alternatives in terms of smart grid applicability. Such an aid in optimizing smart grid projects has the potential to maintain progress of smart grids in a timely manner.
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Warren, Georgina. "Developing land management units using Geospatial technologies: An agricultural application." Curtin University of Technology, Department of Spatial Sciences, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=17509.
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This research develops a methodology for determining farm scale land managementunits (LMUs) using soil sampling data, high resolution digital multi-spectral imagery (DMSI) and a digital elevation model (DEM). The LMUs are zones within a paddock suitable for precision agriculture which are managed according to their productive capabilities. Soil sampling and analysis are crucial in depicting landscape characteristics, but costly. Data based on DMSI and DEM is available cheaply and at high resolution.The design and implementation of a two-stage methodology using a spatiallyweighted multivariate classification, for delineating LMUs is described. Utilising data on physical and chemical soil properties collected at 250 sampling locations within a 1780ha farm in Western Australia, the methodology initially classifies sampling points into LMUs based on a spatially weighted similarity matrix. The second stage delineates higher resolution LMU boundaries using DMSI and topographic variables derived from a DEM on a 10m grid across the study area. The method groups sample points and pixels with respect to their characteristics and their spatial relationships, thus forming contiguous, homogenous LMUs that can be adopted in precision agricultural applications. The methodology combines readily available and relatively cheap high resolution data sets with soil properties sampled at low resolution. This minimises cost while still forming LMUs at high resolution.The allocation of pixels to LMUs based on their DMSI and topographic variables has been verified. Yield differences between the LMUs have also been analysed. The results indicate the potential of the approach for precision agriculture and the importance of continued research in this area.
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Telionis, Pyrros A. "Novel Applications of Geospatial Analysis in the Modeling of Infectious Diseases." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/89432.
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At the intersection of geography and public health, the field of spatial epidemiology seeks to use the tools of geospatial analysis to answer questions about disease. In this work we explore two areas: the use of geostatistical modeling as an extension of niche modeling, and the use of mobility metrics to augment modeling for epidemic responses.
Niche modeling refers to the practice of using statistical methods to relate the underlying spatially distributed environmental variables to an outcome, typically presence or absence of a species. Such work is common in disease ecology, and often focuses on exploring the range of a disease vector or pathogen. The technique also allows one to explore the importance of each underlying regressor, and the effect it has on the outcome. We demonstrate that this concept can be extended, through geostatistical modeling, to explore non-logistic phenomena such as incidence. When combined with weather forecasts, such efforts can even predict incidence of an upcoming season, allowing us to estimate the total number of expected cases, and where we would expect to find them. We demonstrate this in Chapter 2, by forecasting the incidence of melioidosis in Australia given weather forecasts a year prior. We also evaluate the efficacy of this technique and explore the impact of environmental variables such as elevation on melioidosis.
But these techniques are not limited to free-living and vector-borne pathogens. We theorize that they can also be applied to diseases that spread exclusively by person-to-person contact. Exploring this allows us to find areas of underreporting, as well as areas with unusual local forcing which might merit further investigation by the health department. We also explore this in Chapter 4, by relating the incidence of hepatitis C in rural Virginia to demographic data.
The West African Ebola Outbreak of 2014 demonstrated the need to include mobility in predictive disease modeling. One can no longer assume that neglected tropical diseases will remain contained and immobile, and the assumption of random mixing across large areas is unwise. Our efforts with modeling mobility are twofold. In Chapter 3, we demonstrate the creation of mobility metrics from open source road and river network data. We then demonstrate the usefulness of such data in a meta-population patch model meant to forecast the spread of Ebola in the Democratic Republic of Congo. In Chapter 4, we also demonstrate that mobility data can be used to strengthen outbreak detection via hotspot analysis, and to augment incidence models by factoring in the incidence rates of neighboring areas. These efforts will allow health departments to more accurately forecast incidence, and more readily identify disease hotspots of atypical size and shape.<br>Doctor of Philosophy<br>The focus of this work is called “spatial epidemiology”, which combines geography with public health, to answer the where, and why, of disease. This is a growing field, and you’ve likely seen it in the news and media. Have you ever seen a map of the United States turning red in some virus disaster movie? The real thing looks a lot like that. After the Ebola outbreak of 2014, public health agencies wanted to know where the next one might hit. Now that there is another outbreak, we need to ask where and how will it spread? What areas are hardest hit, and how bad is it going to get? We can answer all these questions with spatial epidemiology. Our work adds to two aspects of spatial epidemiology: niche modeling, and mobility. We use niche modeling to determine where we could find certain diseases, usually those that are spread by insects or animals. Consider Lyme disease, you get it from the bite of a tick, and the tick gets it from a white-footed mouse. But both the mice and ticks only live in certain parts of the country. With niche modeling we can determine where those are, and we can also guess at what makes those areas attractive to the mice and ticks. Is it winter harshness, summer temperatures, rainfall, and/or elevation? Is it something else? In Chapter 2, we show that you can extend this idea. Instead of just looking at where the disease is, what if we could guess how many people will get infected? What if we could do so, a year in advance? We show that this can be done, but we need a good idea of what the weather will be like next year. In Chapter 4, we show that you can do the same thing with hepatitis C. Instead of Lyme’s ticks and mice, hepatitis C depends on drug-use, unregulated tattooing, and unsafe sex. And like with Lyme, these things are only found in certain places. Instead of temperature or rainfall, we now need to find areas with drug-problems and poverty. But we can get an idea of this from the Census Bureau, and we can make a map of hepatitis C as easily as we did for Lyme. But hepatitis C spreads person-to-person. So, we need some idea of how people move around the area. This is where mobility comes in. Mobility is important for most public health work, from detecting outbreaks to estimating where the disease will spread next. In Chapter 3, we show how one could create a mobility model for a rural area where few maps exist. We also show how to use that model to guess where the next cases of Ebola will show up. In Chapter 4, we show how you could use mobility to improve outbreak and hotspot detection. We also show how it’s used to help estimate the number of cases in an area. Because that number depends on how many cases are imported from the surrounding areas. And the only way to estimate that is with mobility.
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Kutzner, Tatjana [Verfasser], Thomas H. [Akademischer Betreuer] [Gutachter] Kolbe, Gunnar [Gutachter] Teege, and Jantien E. [Gutachter] Stoter. "Geospatial Data Modelling and Model-driven Transformation of Geospatial Data based on UML Profiles / Tatjana Kutzner ; Gutachter: Thomas H. Kolbe, Gunnar Teege, Jantien E. Stoter ; Betreuer: Thomas H. Kolbe." München : Universitätsbibliothek der TU München, 2016. http://d-nb.info/1121779999/34.
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Stam, Carson A. "Using Biophysical Geospatial and Remotely Sensed Data to Classify Ecological Sites and States." DigitalCommons@USU, 2012. https://digitalcommons.usu.edu/etd/1389.
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Monitoring and identifying the state of rangelands on a landscape scale can be a time consuming process. In this thesis, remote sensing imagery has been used to show how the process of classifying different ecological sites and states can be done on a per pixel basis for a large landscape.
Twenty-seven years' worth of remotely sensed imagery was collected, atmospherically corrected, and radiometrically normalized. Several vegetation indices were extracted from the imagery along with derivatives from a digital elevation model. Dominant vegetation components from five major ecological sites in Rich County, Utah, were chosen for study. The vegetation components were Aspen, Douglas-fir, Utah juniper, mountain big sagebrush, and Wyoming big sagebrush. Training sites were extracted from within map units with a majority of one of the five ecological sites.
A Random Forests decision tree model was developed using an attribute table populated with spectral biophysical variables derived from the training sites. The overall out-of-bag accuracy for the Random Forests model was 97.2%. The model was then applied to the predictor spectral and biophysical variables to spatially map the five major vegetation components for all of Rich County. Each vegetation class had greater than 90% accuracies except for Utah juniper at 81%. This process is further explained in chapter 2.
As a follow-on effort, we attempted to classify vegetation ecological states within a single ecological site (Wyoming big sagebrush). This was done using field data collected by previous studies as training data for all five ecological states documented for our chosen ecological site. A Maximum Likelihood classifier was applied to four years of Landsat 5 Thematic Mapper imagery to map each ecological state to pixels coincident to the map units correlated to the Wyoming big sagebrush ecological site. We used the Mahalanobis distance metric as an indicator of pixel membership to the Wyoming big sagebrush ecological site. Overall classification accuracy for the different ecological states was 64.7% for pixels with low Mahalanobis distance and less than 25% for higher distances.
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Toups, Matthew A. "A study of three paradigms for storing geospatial data: distributed-cloud model, relational database, and indexed flat file." ScholarWorks@UNO, 2016. http://scholarworks.uno.edu/td/2196.
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Geographic Information Systems (GIS) and related applications of geospatial data were once a small software niche; today nearly all Internet and mobile users utilize some sort of mapping or location-aware software. This widespread use reaches beyond mere consumption of geodata; projects like OpenStreetMap (OSM) represent a new source of geodata production, sometimes dubbed “Volunteered Geographic Information.” The volume of geodata produced and the user demand for geodata will surely continue to grow, so the storage and query techniques for geospatial data must evolve accordingly.
This thesis compares three paradigms for systems that manage vector data. Over the past few decades these methodologies have fallen in and out of favor. Today, some are considered new and experimental (distributed), others nearly forgotten (flat file), and others are the workhorse of present-day GIS (relational database). Each is well-suited to some use cases, and poorly-suited to others. This thesis investigates exemplars of each paradigm.
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Smith-McKenna, Emily Katherine. "Geospatial Variation of an Invasive Forest Disease and the Effects on Treeline Dynamics in the Rocky Mountains." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/24200.
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Whitebark pine is an important keystone and foundation species in western North American mountain ranges, and facilitates tree island development in Rocky Mountain treelines. The manifestation of white pine blister rust in the cold and dry treelines of the Rockies, and the subsequent infection and mortality of whitebark pines raises questions as to how these extreme environments harbor the invasive disease, and what the consequences may be for treeline dynamics. This dissertation research comprises three studies that investigate abiotic factors influential for blister rust infection in treeline whitebark pines, how disease coupled with changing climate may affect whitebark pine treeline dynamics, and the connection between treeline spatial patterns and disease. The first study examined the spatial variation of blister rust infection in two whitebark pine treeline communities, and potential topographic correlates. Using geospatial and field approaches to generate high resolution terrain models of treeline landscapes, microtopography associated with solar radiation and moisture were found most influential to blister rust infection in treeline whitebark pines. Using field-based observations from sampled treeline communities, the second study developed an agent-based model to examine the effects of disease and climate on treeline pattern and process. Treeline dynamics were simulated under five hypothetical scenarios to assess changes in tree spatial patterns and populations. Blister rust-induced loss of whitebark pines resulted in a decline of facilitative processes, and an overall negative treeline response to disease—despite the beneficial effects of climate amelioration. The objective of the third study was to explore whether spatial patterns of tree proximity, size, and growth infer disease patterns. Comparing spatial patterns of tree characteristics between diseased and undiseased treeline communities, I found that trees growing near trees with larger stem diameters, and larger tree islands, tended to have more blister rust cankers, and displayed clustered spatial patterns. Undiseased treeline patterns revealed near neighbors smaller in stem diameter and tree island size, and were randomly dispersed. Blister rust diseased whitebark pines reveal spatial autocorrelation, despite the complex blister rust disease life cycle. Overall, findings from this dissertation reveal the implications of invasive disease on sensitive treeline ecotones dependent on a keystone species.<br>Ph. D.
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Kramar, David E. "Estimating Hg Risk to the Common Loon (Gavia immer) in the Rangeley Lakes Region of Western Maine: A Regression Based GIS Model." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/43371.
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This research relates Hg levels in the Common Loon (Gavia immer) to a variety of physical factors. Constructed within the framework of a GIS system, this model analyzes the spatial relationships and the influence of physical land cover factors as a function of distance from the individual loon territories. Thiessan polygons were used to generate the territory for each loon. Buffering of the thiessan polygons was done to establish the boundaries of the individual distance classes and to gather information on the percentage of individual land cover classes within each distance class. Information on precipitation was also gathered. Results from the regression analysis (R2 = 57.3% at the 150m distance class) performed on the variables suggest that the proximity of certain land use types such as cropland, shrub land, and wetlands influence the rates at which Hg is available within an individual territory. Within the 150m and 300m buffers, crop land, shrub land, and wetland exhibited the strongest relationship with the Hg levels in the common loon, with cropland exhibiting a negative relationship suggesting that the proximity of cultivated lands plays a role in decreasing the amount of available Hg in a territory.<br>Master of Science
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Kramar, David Eldridge. "Estimating Hg Risk to the Common Loon (Gavia immer) in the Rangeley Lakes Region of Western Maine: A Regression Based GIS Model." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/43371.
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This research relates Hg levels in the Common Loon (Gavia immer) to a variety of physical factors. Constructed within the framework of a GIS system, this model analyzes the spatial relationships and the influence of physical land cover factors as a function of distance from the individual loon territories. Thiessan polygons were used to generate the territory for each loon. Buffering of the thiessan polygons was done to establish the boundaries of the individual distance classes and to gather information on the percentage of individual land cover classes within each distance class. Information on precipitation was also gathered. Results from the regression analysis (R2 = 57.3% at the 150m distance class) performed on the variables suggest that the proximity of certain land use types such as cropland, shrub land, and wetlands influence the rates at which Hg is available within an individual territory. Within the 150m and 300m buffers, crop land, shrub land, and wetland exhibited the strongest relationship with the Hg levels in the common loon, with cropland exhibiting a negative relationship suggesting that the proximity of cultivated lands plays a role in decreasing the amount of available Hg in a territory.<br>Master of Science
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Vladimir, Bulatović. "Model distribuiranja geopodataka u komunalnim sistemima." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2011. http://dx.doi.org/10.2298/NS20110514BULATOVIC.
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U radu su prikazani Open Geospatial Consortium (OGC) web servisi, iz aspekta serverskih i klijentskih aplikacija. Analizirani su problemi razmene prostornih podataka u složenim sistemima sa naglaskom na komunalne službe gradova. Na osnovu analize razmene podataka, predložen je model koji unapređuje komunikaciju i pospešuje napredak celokupnog sistema implementacijom distribuiranih OGC web servisa. Predloženi model distribucije prostornih podataka može se primenjivati na sve složene sisteme, ali i unutar manjih sistema kao što su kompanije koje se sastoje iz više sektora ili podsistema<br> The short review of the Open Geospatial Consortium (OGC) web services have been given in this work from the perspective of server and client applications. The problems of the exchange of spatial data in the complex systems as municipal service have been analysed. Based on analysis of data exchange, the model has been proposed to improve communication and progress of the whole system by implementing OGC web services. Described model of spatial data distribution can be applied to all complex systems, but also within smaller systems such as companies which consist of more sectors or subsystems.
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Acheampong, Ransford Antwi. "Understanding the co-emergence of urban location choice and mobility patterns : empirical studies and an integrated geospatial and agent-based model." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/267913.
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Understanding and simulating the relationship between urban land-use configuration and patterns of human spatial interaction has been the subject of multi-disciplinary research. Conceptually, it is recognized that the location decisions of several urban actors including individuals, households, firms and public sector institutions, collectively determine the spatial distribution of land-use activities; the emergent land-use patterns, in turn, provide the structural conditions within which flows and interactions between locations occur daily and respond to each other over time. Over the past six decades, various theories and concepts from urban economics, social-physics, transportation studies, and the complexity sciences have underpinned empirical research and development of state-of-the-art simulation models to explore the land-use and travel nexus. Using a case study design and selecting the Kumasi Metropolis, a medium-size metropolis of nearly two-million inhabitants in Ghana, West Africa as the case study area, two main objectives, which reflect research trends and gaps in both the empirical literature and simulation model development have been addressed in this thesis. The first objective was to examine empirically, the location choice behaviour of households and individuals with respect to their residential and job locations, and the mobility patterns associated with the observed home-work location combinations within the metropolis. The second objective was to develop an integrated geospatial and agent-based model to simulate how the residential and job location choice behaviour of heterogeneous households and individuals co-emerge with mobility patterns in the metropolis. The empirical studies presented in this thesis contributes to a deeper understanding of how location-defining attributes at multiple spatial-scales interact with socio-demographic attributes of heterogeneous households and individuals to determine their residential location choice, job location choice and mobility characteristics. The development of the Metropolitan Location and Mobility Patterns Simulator (METLOMP-SIM)—an integrated geospatial and agent-based model also demonstrates how the encoded micro-scale behaviour of purposive households and individuals, interacting with each other and their environment dynamically, could reproduce macro-scale urban location patterns, property market price formation and evolution, and patterns and attributes of spatial flows and interactions anchored on the population’s residential-job location combinations.
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Farmer, Samantha. "Analysis and Risk Estimation of High Priority Unstable Rock Slopes in Great Smoky Mountains National Park, Tennessee and North Carolina." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/etd/3953.
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Great Smoky Mountains National Park (GRSM) received 12.5 million visitors in 2020. With a high traffic volume, it is imperative roadways remain open and free from obstruction. Annual unanticipated rockfall events in GRSM often obstruct traffic flow. Using the Unstable Slope Management Program for Federal Land Management Agencies (USMP for FLMA) protocols, this study analyzes high priority unstable rock slopes through 1) creation of an unstable slope geodatabase and 2) generation of a final rockfall risk model using Co-Kriging from a preliminary risk model and susceptibility model. A secondary goal of this study is to provide risk estimation for the three most traveled transportation corridors within GRSM, as well as investigate current rockfall hazard warning sign location to ultimately improve visitor safety with regards to rockfall hazards.
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Fagua, José Camilo. "Geospatial Modeling of Land Cover Change in the Chocó-Darien Global Ecoregion of South America: Assessing Proximate Causes and Underlying Drivers of Deforestation and Reforestation." DigitalCommons@USU, 2018. https://digitalcommons.usu.edu/etd/7362.
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The Chocó-Darien Global Ecoregion (CGE) in South America is one of 25 global biodiversity hotspots prioritized for conservation. I performed the first land-use and land-cover (LULC) change analysis for the entire CGE in this dissertation. There were three main objectives: 1) Select the best available imagery to build annual land-use and land-cover maps from 2001 to 2015 across the CGE. 2) Model LULC across the CGE to assess forest change trends from 2002 to 2015 and identify the effect of proximate causes of deforestation and reforestation. 3) Estimate the effects of underlying drivers on deforestation and reforestation across the CGE between 2002 and 2015. I developed annual LULC maps across the CGE from 2002 to 2015 using MODIS (Moderate Resolution Imaging Spectro radiometer) vegetation index products and random forest classification. The LULC maps resulted in high accuracies (Kappa = 0.87; SD = 0.008). We detected a gradual replacement of forested areas with agriculture and secondary vegetation (agriculture reverting to early regeneration of natural vegetation) across the CGE. Forest loss was higher between 2010-2015 when compared to 2002-2010. LULC change trends, proximate causes, and reforestation transitions varied according to administrative authority (countries: PanamanianCGE, Colombian CGE, and Ecuadorian CGE). Population growth and road density were underlying drivers of deforestation. Armed conflicts, Gross Domestic Product, and average annual rain were proximate causes and underlying drivers related reforestation.
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Campbell, Alexander B. "Spatio-temporal pattern discovery and hypothesis exploration using a delay reconstruction approach." Queensland University of Technology, 2008. http://eprints.qut.edu.au/17676/.
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This thesis investigates the computer-based modelling and simulation of complex geospatial phenomena. Geospatial systems are real world processes which extend over some meaningful extent of the Earth's surface, such as cities and fisheries. There are many problems that require urgent attention in this domain (for example relating to sustainability) but despite increasing amounts of data and computational power there is a significant gap between the potential for model-based analyses and their actual impact on real world policy and planning. Analytical methods are confounded by the high dimensionality and nonlinearity of spatio-temporal systems and/or are hard to relate to meaningful policy decisions. Simulation-based approaches on the other hand are more heuristic and policy oriented in nature, but they are difficult to validate and almost always over-fit the data: although a given model can be calibrated on a given set of data, it usually performs very poorly on new unseen data sets. The central contribution of this thesis is a framework which is formally grounded and able to be rigourously validated, yet at the same time is interpretable in terms of real world phenomena and thus has a strong connection to domain knowledge. The scope of the thesis spans both theory and practice, and three specific contributions range along this span. Starting at the theoretical end, the first contribution concerns the conceptual and theoretical basis of the framework, which is a technique known as delay reconstruction. The underlying theory is rooted in the rather technical field of dynamical systems (itself largely based on differential topology), which has hindered its wider application and the formation of strong links with other areas. Therefore, the first contribution is an exposition of delay reconstruction in non-technical language, with a focus on explaining how some recent extensions to this theory make the concept far more widely applicable than is often assumed. The second contribution uses this theoretical foundation to develop a practical, unified framework for pattern discovery and hypothesis exploration in geo-spatial data. The central aspect of this framework is the linking of delay reconstruction with domain knowledge. This is done via the notion that determinism is not an on-off quantity, but rather that a given data set may be ascribed a particular 'degree' of determinism, and that that degree may be increased through manipulation of the data set using domain knowledge. This leads to a framework which can handle spatiotemporally complex (including multi-scale) data sets, is sensitive to the amount of data that is available, and is naturally geared to be used interactively with qualitative feedback conveyed to the user via geometry. The framework is complementary to other techniques in that it forms a scaffold within which almost all modelling approaches - including agent-based modelling - can be cast as particular kinds of 'manipulations' of the data, and as such are easily integrated. The third contribution examines the practical efficacy of the framework in a real world case study. This involves a high resolution spatio-temporal record of fishcatch data from trawlers operating in a large fishery. The study is used to test two fundamental capabilities of the framework: (i) whether real world spatio-temporal phenomena can be identified in the degree-of-determinism signature of the data set, (ii) whether the determinism-level can then be increased by manipulating the data in response to this phenomena. One of the main outcomes of this study is a clear identification of the influence of the lunar cycle on the behaviour of Tiger and Endeavour prawns. The framework allows for this to be 'non-destructively subtracted', increasing the detect-ability of further phenomena.
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Silva, Marília Matos Bezerra Lemos. "Áreas vulneráveis e fatores de risco a ocorrência da esquistossomose em Sergipe." Pós-Graduação em Geografia, 2018. http://ri.ufs.br/jspui/handle/riufs/10354.
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Nowadays, among the parasitic diseases that affect humans, schistosomiasis is one of the most widespread in the world. In Sergipe, the magnitude of its prevalence associated with its socioeconomic importance confers the disease great relevance as a public health problem (SVS, 2017). The ability to point out the spatial distribution of this parasite, as well as to determine potential areas for the occurrence of the disease, will have important implications in the planning actions of the control programs. In this perspective, from a systemic approach, the present study aims to evaluate the vulnerability and risk factors of the occurrence of schistosomiasis in endemic areas of the State of Sergipe. The study suggested in the thesis is based on the conception of epidemiological structure defined by Loureiro et al. (1979); in Cutter's perception of vulnerability (1996); in the methodological contributions of Batelle (DEE, 1973); and the use of geoprocessing techniques (spatial distribution and analysis - IDW and Kriging). The present research is divided into three stages. Initially it proposes a model of evaluation of the vulnerability to the occurrence of schistosomiasis in endemic areas of the state. It then carries out a mixed ecological descriptive study of temporal and analytical series to evaluate the evolution and the geographical distribution of the disease, while checking the association (Mann-Whitney test) between areas of high prevalence and socio-demographic and environmental variables of the state. Finally, an observational, cross-sectional observational epidemiological study was carried out in two hyperendemic areas of the state, aiming to present the different epidemiological patterns and the risk factors (logistic regression) associated with the occurrence of the disease. In the temporal analysis performed, there was no evidence of a change in the state epidemiological profile, indicating a decreasing positive trend of schistosomiasis in the coming years. Despite the fact that the hypothesis of a reduction in prevalence was confirmed, human infection rates were found to be very high in almost all of Sergipe, indicating the endemism of the disease in the state. The developed analyzes revealed indicators involved in the conformation and maintenance of the endemic structure, as well as identified areas of priority attention. It was also observed that indicators of quality of life and environmental variables are associated with the transmission of the disease in the state. Density estimators showed high vulnerability in the territories of Grande Aracaju, Baixo São Francisco e Sul Sergipano, historically endemic areas that present population groups with high risk of infection, validating the proposed model. In addition, they pointed out vulnerable areas in regions where there is a lack of concrete data on the endemic disease, the territory of the Sergipe Sertão Sertão is cited as an example. The logistic regression analysis showed a significant association between Schistosoma mansoni human infection and the variables: gender, occupation, schooling, income, habitability conditions and time of contact with water sources in both areas investigated, indicating diversity in risk and transmission of the disease. The products generated in the scope of this doctoral thesis will assist in planning and management of integrative actions aimed at health promotion, disease prevention and control programs.<br>Atualmente, entre as doenças parasitárias que afetam o homem a esquistossomose é uma das mais difundidas no mundo. Em Sergipe, a magnitude de sua prevalência associada à sua importância socioeconômica confere a endemia grande relevância enquanto problema de saúde pública (SVS, 2017). A capacidade de apontar a distribuição espacial desta parasitose, bem como, determinar áreas potenciais a sua ocorrência terá implicações importantes nas ações de planejamento dos programas de controle. Nesta perspectiva, a partir de uma abordagem sistêmica, o presente estudo objetiva avaliar a vulnerabilidade e os fatores de risco a ocorrência da esquistossomose em áreas endêmicas do estado de Sergipe. O estudo apresentado nesta tese fundamenta-se na concepção de estrutura epidemiológica definida por Loureiro et al., (1979); na percepção de vulnerabilidade de Cutter (1996); nas contribuições metodológicas de Batelle (DEE, 1973); e no uso de técnicas de geoprocessamento (distribuição e análise espacial - IDW e Krigagem). A pesquisa apresenta-se dividida em três etapas. Inicialmente, realiza um estudo ecológico misto descritivo de séries temporais e analítico para avaliar a evolução e a distribuição geográfica da doença ao tempo que verifica a associação entre as áreas de alta prevalência e variáveis sociodemográficas e ambientais do estado (teste de Mann-Whitney). Ato contínuo, propõe um modelo de avaliação da vulnerabilidade a ocorrência da esquistossomose em áreas endêmicas do estado. Por fim, é realizado um estudo epidemiológico analítico observacional de corte transversal em duas áreas hiperendêmicas, visando apresentar os distintos padrões epidemiológicos e os fatores de preditivos (regressão logística) associados a transmissão da doença nestas localidades. Na análise temporal realizada não foi evidenciada mudança no perfil epidemiológico estadual, apontando tendência positiva decrescente da esquistossomose para os próximos anos. A despeito de ter se confirmado a hipótese da redução da prevalência constataram-se taxas de infecção humana com situações de positividade muito alta em quase todo o território sergipano. As análises desenvolvidas revelaram indicadores envolvidos na conformação e manutenção da estrutura endêmica, bem como, identificou áreas de atenção prioritária. Foi observado também que indicadores de qualidade de vida e variáveis ambientais estão associados a disseminação da doença no estado. Os estimadores de densidade apontaram vulnerabilidade alta nos territórios da Grande Aracaju, Baixo São Francisco e Sul Sergipano, áreas historicamente endêmicas que apresentam grupos populacionais com alto risco de infecção, validando o modelo proposto. Ademais, apontaram áreas vulneráveis em regiões onde faltam dados concretos de endemização da doença, o território do Médio Sertão Sergipano é citado como exemplo. As análises de regressão logística apontaram associação significativa entre a infecção humana por Schistosoma mansoni e as variáveis: gênero, ocupação, escolaridade, renda, condições de habitabilidade e tempo de contato com as fontes hídricas, em ambas as áreas investigadas, apontando diversidade no risco e transmissão da doença. Os produtos gerados no âmbito desta tese doutoral auxiliarão propostas de planejamento e gestão de ações integradoras que visem à promoção da saúde, prevenção da doença e direcionamentos dos programas de controle.<br>São Cristóvão, SE
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Cui, Zheng. "A Generalized Adaptive Mathematical Morphological Filter for LIDAR Data." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/995.
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Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth’s surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in “cut-off” errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs.
Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most “cut-off” points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in processing LIDAR data to effectively and efficiently identify ground measurements for the complex terrains in a large LIDAR data set. The GAPM filter is highly automatic and requires little human input. Therefore, it can significantly reduce the effort of manually processing voluminous LIDAR measurements.
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Dušan, Jovanović. "Модел објектно оријентисане класификације у идентификацији геопросторних објеката". Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2015. http://www.cris.uns.ac.rs/record.jsf?recordId=95426&source=NDLTD&language=en.
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У оквиру докторске дисертације извршен је преглед стања постојећих начинаидентификације геопросторних објеката на основу података насталих на принципимадаљинске детекције. Извршена је анализа постојећих проблема и корака које јенеопходно провести како би се добили што бољи резултати идентификацијегеопросторних објеката. Анализирани су поступци мапирања, начини сегментацијеслике, критеријуми за идентификацију, селекцију и класификацију геопросторнихобјеката као и методе класификације. На основу анализе креиран је моделидентификовања геопросторних објеката базираних на објектно оријентисаној анализислике. На основу предложеног модела извршена је верификација модела у поступкуидентификовања зграда, пољопривредних површина, шумских површина и воденихповршина које представљају студије случаја.<br>U okviru doktorske disertacije izvršen je pregled stanja postojećih načinaidentifikacije geoprostornih objekata na osnovu podataka nastalih na principimadaljinske detekcije. Izvršena je analiza postojećih problema i koraka koje jeneophodno provesti kako bi se dobili što bolji rezultati identifikacijegeoprostornih objekata. Analizirani su postupci mapiranja, načini segmentacijeslike, kriterijumi za identifikaciju, selekciju i klasifikaciju geoprostornihobjekata kao i metode klasifikacije. Na osnovu analize kreiran je modelidentifikovanja geoprostornih objekata baziranih na objektno orijentisanoj analizislike. Na osnovu predloženog modela izvršena je verifikacija modela u postupkuidentifikovanja zgrada, poljoprivrednih površina, šumskih površina i vodenihpovršina koje predstavljaju studije slučaja.<br>This PhD thesis includes an overview of the existing methods of identifying geospatialobjects from a remote sensing data, basically satellite or airplane images. The analysisof existing problems and necessary steps in identification of remotely sensed data isobtained in way to get the best results of identification of geospatial objects. Themapping procedures, methods of image segmentation, the criteria for identification,selection and classification of geospatial objects and methods of classification are alsoanalyzed. The result of analysis is a model of identifying geospatial objects based onobject-oriented image analysis. Based on the proposed model, verification of themodel was carried out. Afterwards case study of the proposed model is carried out inprocess of identifying buildings, farmland, forest and water areas.
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Jabbour, Chadi. "Essays in the economics of Spatial Data Infrastructures (SDI) : business model, service valuation and impact assessment." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTD018.
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Cette thèse tente de répondre à plusieurs thématiques liées aux aspects socio-économiques des Infrastructures de Données Géo Spatiales (IDGS). Elle met en particulier l’accent sur plusieurs questions concernant leur évaluation économique et la mesure de leurs impacts. Les objectifs peuvent être résumés autour des cinq points suivants: i) proposer un modèle économique pour ce type d’infrastructure afin d’assurer un financement durable; ii) réaliser une évaluation économique de l'information géo-spatiale issue d’une IDGS et disponible via sa plateforme: les images satellitaires à haute résolution spatiale (HR); iii) examiner le rôle d’une IDGS en tant que structure d’information; iv) identifier les impacts économiques d’une IDGS; v) étudier la stabilité de la demande pour l’imagerie satellitaire à travers les IDGS. Afin de répondre à ces interrogations, un premier défi concernait les modèles économiques (au sens de “business model”) dans la mise en œuvre des IDGS. La pertinence d’une approche des marchés biface a été testée via un processus de gestion de plateforme, pour analyser la dynamique d’une IDGS afin d’assurer une transition de l’IDGS vers un mécanisme de financement durable. Un protocole a été élaboré, décrivant la stratégie à travers laquelle une IDGS via sa plateforme, pourrait interagir en permanence entre les différents composants, représentés par les développeurs d’applications basées sur des données spatiales et les utilisateurs potentiels de ces données.Également, il était important d’affiner les questions relatives à l’évaluation des IDGS, en parallèle avec les réflexions sur le modèle économique de ce type d’infrastructure. Dans notre contexte, nous avons examiné la valeur économique des images satellites à haute résolution spatiale (HRS) perçue par les utilisateurs directs d’une IDGS. Les résultats obtenus pourraient être utilisés pour éclairer la conception d’une future tarification de l’imagerie satellitaire, visant à pérenniser le financement de ces services. Dans un troisième temps, nous avons examiné le rôle d’une IDGS en tant que structure d’information. La méthodologie a été appliquée dans le cas de suivi des coupes rases en France. Sur une base d’informations hétérogènes reçues via une multitude de structures d’information, une méthode de prise de décision a été mise en place, afin de fournir à un décideur un outil pour une meilleure prise de décision. Une approche originale a été introduite, en articulant entre deux théories : la méthode classique de Blackwell et la théorie de l’entropie. Le contexte méthodologique se présente suivant deux niveaux : le choix de la structure d’information ayant le pouvoir le plus informatif et la détection de l’action optimale.De même, pour aller plus en détail dans l’identification et l’analyse des impacts socio-économiques d’une IDGS basée sur l’imagerie satellitaire, nous avons considéré l’exemple des coupes rases. Après une analyse des acquisitions d’images satellites pour qualifier le champ des politiques publiques concernées, nous avons étudié la structure des impacts liés à une IDGS. Dans un deuxième temps nous avons évalué quelques-uns de ces impacts d’une manière plus détaillée.Enfin, ces études d’évaluation nous ont mené à examiner la stabilité de la demande d’images via une IDGS. Les IDGS constituent un lien direct entre les utilisateurs de premier rang et la grande industrie spatiale. Elles jouent également un rôle important dans la création d’opportunités de marché. Bien que les utilisateurs soient considérés comme les principaux moteurs de la technologie des données spatiales, ils contribuent à travers leur demande de données et de services au développement et à la croissance de ce domaine. Nous avons abordé la stabilité de différentes demandes d’images satellitaires, et avons fourni des éléments supplémentaires pour une meilleure compréhension de la gestion de ces données, en se basant sur la théorie des Records<br>The development of spatial data infrastructures (SDIs) is hampered by several barriers: form economical, technical to organizational and financial, the hurdles are numerous. This thesis attempts to answer some issues related to the socio-economic aspects of SDIs. It focuses on several topics concerning the SDI economic valuation and impact measurement. The aim has been fivefold: i) to propose a business model for this particular type of infrastructure in order to meet a sustainable financing scheme; ii) to perform an economic valuation of the geospatial information available through the SDI platform, the high resolution (HR) satellite images; iii) to examine the role of a SDI as an information structure; iv) to identify the economic impacts of a SDI; v) to study the stability of the satellite image markets through a SDI.In this thesis, a challenge consisted of approaching the business models field into the implementation of SDIs. The relevance of a two-sided market approach for analyzing a SDI dynamics was tested through a platform management process, in order for a SDI to transition to a self-sustaining funding mechanism. We explained how a SDI through its platform could ensure continuous interaction between the different components, represented by the developers of spatial data applications and the potential users of such data.It was important that the economic valuation questions concerning the SDI, need to be refined in parallel with the reflections about the business model of this type of infrastructure. In our context, we examined the economic value of the HR satellite images as perceived by the direct users of a SDI platform. The valuation study came to assess the importance of the satellite imagery as a support for the territorial planning and development economics. In a context of open and distributed innovation within the networks, it offered elements allowing to establish pricing scenarios on a next level, in order to sustain the SDI platform business model in the long run.In addition, we examined the role of a SDI as an information structure. We applied our findings to the clear-cut forest control case in France. Based on heterogeneous information received, we elaborated a decision-making policy in order to help a decision maker better model his decision. An original approach was introduced, articulating between two existing theories: the classic method of Blackwell and the Entropy theory. We advanced a two-level methodological context: The choice of the information structure with the most informative power and the detection of the optimal action.Similarly, by considering the clear cut example, we analyzed the socio-economic impacts of a SDI based on satellite imagery. A detailed analysis of the geospatial information acquired through the SDI, allowed to characterize the public policies involved in this field, in order to examine the impacts related the SDI ecosystem. In a second step, some of these impacts have been assessed in more details.Finally, these valuation studies opened a window to examine the market demand stability through the SDI. The spatial data infrastructures, which constitute the direct link between the users and the large Earth Observation (EO) industry, have a leading role in establishing market opportunities. While the users are becoming primary key-drivers for spatial data technology, they contribute through their demand of raw data and services, to its development and growth. We approached the stability of different satellite image markets through two independent French SDIs, by using the Records theory. We implemented an innovative method and provided additional elements for a better comprehension of the EO data management
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Brown, Andrew D. "Looking Outward from the Village: The Contingencies of Soil Moisture on the Prehistoric Farmed Landscape near Goodman Point Pueblo." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc862755/.
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Ancestral Pueblo communities of the central Mesa Verde region (CMVR) became increasingly reliant on agriculture for their subsistence needs during Basketmaker III (BMIII) through Terminal Pueblo III (TPIII) (AD 600–1300) periods. Researchers have been studying the Ancestral Pueblo people for over a century using a variety of methods to understand the relationships between climate, agriculture, population, and settlement patterns. While these methods and research have produced a well-developed cultural history of the region, studies at a smaller scale are still needed to understand the changes in farming behavior and the distribution of individual sites across the CMVR. Soil moisture is the limiting factor for crop growth in the semi-arid region of the Goodman Watershed in the CMVR. Thus, I constructed the soil moisture proxy model (SMPM) that is on a local scale and focuses on variables relevant to soil moisture – soil particle-size, soil depth, slope, and aspect. From the SMPM output, the areas of very high soil moisture are assumed to represent desirable farmland locations. I describe the relationship between very high soil moisture and site locations, then I infer the relevance of that relationship to settlement patterns and how those patterns changed over time (BMIII – TPIII). The results of the model and its application help to clarify how Ancestral Pueblo people changed as local farming communities. The results of this study indicates that farmers shifted away from use of preferred farmland during Terminal Pueblo III, which may have been caused by other cultural factors. The general outcome of this thesis is an improved understanding of human-environmental relationships on the local landscape in the CMVR.
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Beaufils, Mickaël. "Fusion de données géoréférencées et développement de services interopérables pour l’estimation des besoins en eau à l’échelle des bassins versants." Thesis, Paris, CNAM, 2012. http://www.theses.fr/2012CNAM0847/document.
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De nos jours, la préservation de l’environnement constitue un enjeu prioritaire. La compréhension des phénomènes environnementaux passe par l’étude et la combinaison d’un nombre croissant de données hétérogènes. De nombreuses initiatives internationales (INSPIRE, GEOSS) visent à encourager le partage et l’échange de ces données. Dans ce sujet de recherche, nous traitons de l’intérêt de mettre à disposition des modèles scientifiques sur le web. Nous montrons l’intérêt d’utiliser des applications s’appuyant sur des données géoréférencées et présentons des méthodes et des moyens répondant aux exigences d’interopérabilité. Nous illustrons notre approche par l’implémentation de modèles d’estimation des besoins en eau agricoles et domestiques fonctionnant à diverses échelles spatiales et temporelles. Un prototype basé sur une architecture entièrement orientée services web a été développé. L’outil s’appuie sur les standards Web Feature Service (WFS), Sensor Observation Service (SOS) et Web Processing Service (WPS) de l’OGC. Enfin, la prise en compte des imperfections des données est également abordée avec l’intégration de méthodes d’analyse de sensibilité et de propagation de l’incertitude<br>Nowadays, preservation of the environment is a main priority. Understanding of environmental phenomena requires the study and the combination of an increasing number of heterogeneous data. Several international initiatives (INSPIRE, GEOSS) aims to encourage the sharing and exchange of those data.In this thesis, the interest of making scientific models available on the web is discussed. The value of using applications based on geospatial data is demonstrated. Several methods and means that satisfy the requirements of interoperability are also purposed.Our approach is illustrated by the implementation of models for estimating agricultural and domestic water requirements. Those models can be used at different spatial scales and temporal granularities. A prototype based on a complete web service oriented architecture was developed. The tool is based on the OGC standards Web Feature Service (WFS), Sensor Observation Service (SOS) and Web Processing Service (WPS).Finally, taking into account the imperfections of the data is also discussed with the integration of methods for sensitivity analysis and uncertainty propagation
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Chandratilake, (nee Weerasekara) Sonali Evanjali. "Spatial Modelling of Gastroenteritis Prevalence Following the February 22, 2011 Earthquake and Identification of Successful Factors Preventing Outbreaks at Emergency Centres." Thesis, University of Canterbury. Department of Geological Sciences, 2013. http://hdl.handle.net/10092/9185.
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The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours).
The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours).
The aim of this multidisciplinary research was to retrospectively analyse the gastroenteritis prevalence following the February 22, 2011 earthquake in Christchurch. The first focus was to assess whether earthquake-induced infrastructure damage, liquefaction, and gastroenteritis agents spatially explained the recorded gastroenteritis cases over the period of 35 days following the February 22, 2011 earthquake in Christchurch. The gastroenteritis agents considered in this study were Escherichia coli found in the drinking water supply (MPN/100mL) and Non-Compliant Free Associated Chlorine (FAC-NC) (less than <0.02mg/L). The second focus was the protocols that averted a gastroenteritis outbreak at three Emergency Centres (ECs): Burnside High School Emergency Centre (BEC); Cowles Stadium Emergency Centre (CEC); and Linwood High School Emergency Centre (LEC).
Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach.
Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC.
Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols and indirect themes included type of EC building (school or a sports stadium), and EC staff. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss.
This research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally
Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. A damage profile was created by amalgamating different types of damage for the considered factors for each Census Area Unit (CAU) in Christchurch. The damage profile enabled the application of a variety of statistical methods which included Moran’s I , Hot Spot (HS) analysis, Spearman’s Rho, and Besag–York–Mollié Model using a range of software. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach.
Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC.
Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. The ECs were selected to represent the Christchurch area, and were situated where potential for gastroenteritis was high. BEC represented the western side of Christchurch; whilst, CEC and LEC represented the eastern side, where the potential for gastroenteritis was high according to the outputs of the quantitative spatial modelling. Qualitative analysis from the interviews at the ECs revealed that evacuees were arriving at the ECs with gastroenteritis-like symptoms. Participants believed that those symptoms did not originate at the ECs. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols that included prolific use of hand sanitisers; surveillance; and the services offered. Indirect themes included the EC layout, type of EC building (school or a sports stadium), and EC staff. Indirect themes governed the quality and sustainability of the direct themes implemented, which in turn averted gastroenteritis outbreaks at the ECs. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss.
It was concluded that gastroenteritis point prevalence following the February 22, 2011 earthquake could not be solely explained by earthquake-induced infrastructure damage, liquefaction, and gastroenteritis causative agents alone. However, this research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Creating a damage profile for each CAU and using spatial data analysis can isolate vulnerable areas, and qualitative data analysis provides localised information. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally.
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Hsieh, Min-Che, and 謝旻哲. "Integration of Architectural BIM Model and OSM Block Models for Geospatial Analysis." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/c69f4e.
Full textAbstract:
碩士<br>國立交通大學<br>土木工程系所<br>105<br>This study integrates BIM (Building Information Model) model and OSM (OpenStreetMap) block models for geospatial data analysis. BIM models focus on information of a detailed building while VGI (Volunteered Geographic Information) - derived from the building model that focuses on block model. Therefore, VGI does enhance details of geospatial data in BIM. This study aims to integrate the block models from OSM and architectural BIM model. The main research items are the follows: (1). quality assessment of building models in OSM, (2). ontology for OSM buildings, (3). conversion of OSM to BIM software, and (4). solar energy and shadow analysis for OSM and BIM integrated models. The result of experiment indicates that the quality of OSM building will fulfill needs of 3D block model. This study also used an OWL to create the ontology of OSM’s keys and values. The OSM has automatically transformed to IFC and further imported to BIM software. Finally, a large number of block models from OSM and high detailed BIM model has been integrated to demonstrate the solar analysis for engineering application.
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Stewart, Robert Nathan. "A Geospatial Based Decision Framework for Extending MARSSIM Regulatory Principles into the Subsurface." 2011. http://trace.tennessee.edu/utk_graddiss/1130.
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The Multi-Agency Radiological Site Survey Investigation Manual (MARSSIM) is a regulatory guidance document regarding compliance evaluation of radiologically contaminated soils and buildings (USNRC, 2000). Compliance is determined by comparing radiological measurements to established limits using a combination of hypothesis testing and scanning measurements. Scanning allows investigators to identify localized pockets of contamination missed during sampling and allows investigators to assess radiological exposure at different spatial scales. Scale is important in radiological dose assessment as regulatory limits can vary with the size of the contaminated area and sites are often evaluated at more than one scale (USNRC, 2000). Unfortunately, scanning is not possible in the subsurface and direct application of MARSSIM breaks down.
This dissertation develops a subsurface decision framework called the Geospatial Extension to MARSSIM (GEM) to provide multi-scale subsurface decision support in the absence of scanning technologies. Based on geostatistical simulations of radiological activity, the GEM recasts the decision rule as a multi-scale, geospatial decision rule called the regulatory limit rule (RLR). The RLR requires simultaneous compliance with all scales and depths of interest at every location throughout the site. The RLR is accompanied by a compliance test called the stochastic conceptual site model (SCSM). For those sites that fail compliance, a remedial design strategy is developed called the Multi-scale Remedial Design Model (MrDM) that spatially indicates volumes requiring remedial action. The MrDM is accompanied by a sample design strategy known as the Multi-scale Remedial Sample Design Model (MrsDM) that refines this remedial action volume through careful placement of new sample locations. Finally, a new sample design called “check and cover” is presented that can support early sampling efforts by directly using prior knowledge about where contamination may exist.
This dissertation demonstrates how these tools are used within an environmental investigation and situates the GEM within existing regulatory methods with an emphasis on the Environmental Protection Agency’s Triad method which recognizes and encourages the use of advanced decision methods. The GEM is implemented within the Spatial Analysis and Decision Assistance (SADA) software and applied to a hypothetical radiologically contaminated site.
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"Thermally Driven Technologies for Atmospheric Water Capture to Provide Decentralized Drinking Water." Doctoral diss., 2020. http://hdl.handle.net/2286/R.I.57016.
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abstract: Limited access to clean water due to natural or municipal disasters, drought, or contaminated wells is driving demand for point-of-use and humanitarian drinking water technologies. Atmospheric water capture (AWC) can provide water off the centralized grid by capturing water vapor in ambient air and condensing it to a liquid. The overarching goal of this dissertation was to define geographic and thermodynamic design boundary conditions for AWC and develop nanotechnology-enabled AWC technologies to produce clean drinking water.
Widespread application of AWC is currently limited because water production, energy requirement, best technology, and water quality are not parameterized. I developed a geospatial climatic model for classical passive solar desiccant-driven AWC, where water vapor is adsorbed onto a desiccant bed at night, desorbed by solar heat during the day, and condensed. I concluded passive systems can capture 0.25–8 L/m2/day as a function of material properties and climate, and are limited because they only operate one adsorption-desorption-condensation cycle per day. I developed a thermodynamic model for large-scale AWC systems and concluded that the thermodynamic limit for energy to saturate and condense water vapor can vary up to 2-fold as a function of climate and mode of saturation.
Thermodynamic and geospatial models indicate opportunity space to develop AWC technologies for arid regions where solar radiation is abundant. I synthesized photothermal desiccants by optimizing surface loading of carbon black nanoparticles on micron-sized silica gel desiccants (CB-SiO2). Surface temperature of CB-SiO2 increased to 60oC under solar radiation and water vapor desorption rate was 4-fold faster than bare silica. CB-SiO2 could operate >10 AWC cycles per day to produce 2.5 L/m2/day at 40% relative humidity, 3-fold more water than a conventional passive system.
Models and bench-scale experiments were paired with pilot-scale experiments operating electrical desiccant and compressor dehumidifiers outdoors in a semi-arid climate to benchmark temporal water production, water quality and energy efficiency. Water quality varied temporally, e.g, dissolved organic carbon concentration was 3 – 12 mg/L in the summer and <1 mg/L in the winter. Collected water from desiccant systems met all Environmental Protection Agency standards, while compressor systems may require further purification for metals and turbidity.<br>Dissertation/Thesis<br>Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2020
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(9178481), Matthew D. Pike. "Continuity and Change in Indigenous Copper Technologies of the Arctic and Central Subarctic." Thesis, 2020.
Find full textAbstract:
A dissertation examining technological diversity in Indigenous copper metallurgy of the North American Arctic and Central Subarctic. Variation in technological diversity is assessed cross-culturally, chronologically, and geographically. This is accomplished using diversity statistics to characterize Richness and Evenness of spatiotemporal archaeological assemblages of copper artifacts, performing regression analysis to examine the relationship to the results of a GIS Path Distance analysis that models the cost of acquisition of raw or modified copper, and performing chi-square tests of independence to compare assemblages inter-regionally and temporally. Portable X-Ray Fluorescence was utilized to discriminate geologically pure copper from smelted trade copper and a comprehensive typology of copper artifacts was created using a compiled database of known copper artifacts from across the North American Arctic and central Subarctic. Inter-regional, chronological, and cross-cultural differences in technological diversity were identified and implications for Arctic and Subarctic archaeology and technological innovation are discussed.
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(5930729), Ke Liu. "Pattern Exploration from Citizen Geospatial Data." Thesis, 2019.
Find full textAbstract:
Due to the advances in location-acquisition techniques, citizen geospatial data has emerged with opportunity for research, development, innovation, and business. A variety of research has been developed to study society and citizens through exploring patterns from geospatial data. In this thesis, we investigate patterns of population and human sentiments using GPS trajectory data and geo-tagged tweets. Kernel density estimation and emerging hot spot analysis are first used to demonstrate population distribution across space and time. Then a flow extraction model is proposed based on density difference for human movement detection and visualization. Case studies with volleyball game in West Lafayette and traffics in Puerto Rico verify the effectiveness of this method. Flow maps are capable of tracking clustering behaviors and direction maps drawn upon the orientation of vectors can precisely identify location of events. This thesis also analyzes patterns of human sentiments. Polarity of tweets is represented by a numeric value based on linguistics rules. Sentiments of four US college cities are analyzed according to its distribution on citizen, time, and space. The research result suggests that social media can be used to understand patterns of public sentiment and well-being.
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Sliwinski, Adam [Verfasser]. "A vertical product differentiation model for geospatial information services / vorgelegt von Adam Sliwinski." 2007. http://d-nb.info/985292830/34.
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Nejatbakhsh, Esfahani Nazereh. "Interoperability of Traffic Infrastructure Planning and Geospatial Information Systems." Doctoral thesis, 2016. https://tud.qucosa.de/id/qucosa%3A31143.
Full textAbstract:
Building Information Modelling (BIM) as a Model-based design facilitates to investigate multiple solutions in the infrastructure planning process. The most important reason for implementing model-based design is to help designers and to increase communication between different design parties. It decentralizes and coordinates team collaboration and facilitates faster and lossless project data exchange and management across extended teams and external partners in project lifecycle.
Infrastructure are fundamental facilities, services, and installations needed for the functioning of a community or society, such as transportation, roads, communication systems, water and power networks, as well as power plants. Geospatial Information Systems (GIS) as the digital representation of the world are systems for maintaining, managing, modelling, analyzing, and visualizing of the world data including infrastructure. High level infrastructure suits mostly facilitate to analyze the infrastructure design based on the international or user defined standards. Called regulation1-based design, this minimizes errors, reduces costly design conflicts, increases time savings and provides consistent project quality, yet mostly in standalone solutions.
Tasks of infrastructure usually require both model based and regulation based design packages. Infrastructure tasks deal with cross-domain information. However, the corresponding data is split in several domain models. Besides infrastructure projects demand a lot of decision makings on governmental as well as on private level considering different data models. Therefore lossless flow of project data as well as documents like regulations across project team, stakeholders, governmental and private level is highly
important. Yet infrastructure projects have largely been absent from product modelling discourses for a long time. Thus, as will be explained in chapter 2 interoperability is needed in infrastructure processes.
Multimodel (MM) is one of the interoperability methods which enable heterogeneous data models from various domains get bundled together into a container keeping their original format. Existing interoperability methods including existing MM solutions can’t satisfactorily fulfill the typical demands of infrastructure information processes like dynamic data resources and a huge amount of inter model relations. Therefore chapter 3 concept of infrastructure information modelling investigates a method for loose and rule based coupling of exchangeable heterogeneous information spaces. This hypothesis is an extension for the existing MM to a rule-based Multimodel named extended Multimodel (eMM) with semantic rules – instead of static links. The semantic rules will be used to describe relations between data elements of various models dynamically in a link-database.
Most of the confusion about geospatial data models arises from their diversity. In some of these data models spatial IDs are the basic identities of entities and in some other data models there are no IDs. That is why in the geospatial data, data structure is more important than data models. There are always spatial indexes that enable accessing to the geodata. The most important unification of data models involved in infrastructure projects is the spatiality. Explained in chapter 4 the method of infrastructure information modelling for interoperation in spatial domains generate interlinks through spatial identity of entities. Match finding through spatial links enables any kind of data models sharing spatial property get interlinked. Through such spatial links each entity receives the spatial information from other data models which is related to the target entity due to sharing equivalent spatial index. This information will be the virtual properties for the object. The thesis uses Nearest Neighborhood algorithm for spatial match finding and performs filtering and refining approaches. For the abstraction of the spatial matching results hierarchical filtering techniques are used for refining the virtual properties. These approaches focus on two main application areas which are product model and Level of Detail (LoD).
For the eMM suggested in this thesis a rule based interoperability method between arbitrary data models of spatial domain has been developed. The implementation of this method enables transaction of data in spatial domains run loss less. The system architecture and the implementation which has been applied on the case study of this thesis namely infrastructure and geospatial data models are described in chapter 5.
Achieving afore mentioned aims results in reducing the whole project lifecycle costs, increasing reliability of the comprehensive fundamental information, and consequently in independent, cost-effective, aesthetically pleasing, and environmentally sensitive infrastructure design.:ABSTRACT 4
KEYWORDS 7
TABLE OF CONTENT 8
LIST OF FIGURES 9
LIST OF TABLES 11
LIST OF ABBREVIATION 12
INTRODUCTION 13
1.1. A GENERAL VIEW 14
1.2. PROBLEM STATEMENT 15
1.3. OBJECTIVES 17
1.4. APPROACH 18
1.5. STRUCTURE OF THESIS 18
INTEROPERABILITY IN INFRASTRUCTURE ENGINEERING 20
2.1. STATE OF INTEROPERABILITY 21
2.1.1. Interoperability of GIS and BIM 23
2.1.2. Interoperability of GIS and Infrastructure 25
2.2. MAIN CHALLENGES AND RELATED WORK 27
2.3. INFRASTRUCTURE MODELING IN GEOSPATIAL CONTEXT 29
2.3.1. LamdXML: Infrastructure Data Standards 32
2.3.2. CityGML: Geospatial Data Standards 33
2.3.3. LandXML and CityGML 36
2.4. INTEROPERABILITY AND MULTIMODEL TECHNOLOGY 39
2.5. LIMITATIONS OF EXISTING APPROACHES 41
INFRASTRUCTURE INFORMATION MODELLING 44
3.1. MULTI MODEL FOR GEOSPATIAL AND INFRASTRUCTURE DATA MODELS 45
3.2. LINKING APPROACH, QUERYING AND FILTERING 48
3.2.1. Virtual Properties via Link Model 49
3.3. MULTI MODEL AS AN INTERDISCIPLINARY METHOD 52
3.4. USING LEVEL OF DETAIL (LOD) FOR FILTERING 53
SPATIAL MODELLING AND PROCESSING 58
4.1. SPATIAL IDENTIFIERS 59
4.1.1. Spatial Indexes 60
4.1.2. Tree-Based Spatial Indexes 61
4.2. NEAREST NEIGHBORHOOD AS A BASIC LINK METHOD 63
4.3. HIERARCHICAL FILTERING 70
4.4. OTHER FUNCTIONAL LINK METHODS 75
4.5. ADVANCES AND LIMITATIONS OF FUNCTIONAL LINK METHODS 76
IMPLEMENTATION OF THE PROPOSED IIM METHOD 77
5.1. IMPLEMENTATION 78
5.2. CASE STUDY 83
CONCLUSION 89
6.1. SUMMERY 90
6.2. DISCUSSION OF RESULTS 92
6.3. FUTURE WORK 93
BIBLIOGRAPHY 94
7.1. BOOKS AND PAPERS 95
7.2. WEBSITES 101
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Otsu, Kaori. "Geospatial data harmonization from regional level to european level: a usa case in forest fire data." Master's thesis, 2010. http://hdl.handle.net/10362/8259.
Full textAbstract:
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.<br>Geospatial data harmonization is becoming more and more important to increase interoperability of heterogeneous data derived from various sources in spatial data infrastructures. To address this harmonization issue we present the current status of data availability among different communities, languages, and administrative scales from regional to national and European levels. With a use case in forest data models in Europe, interoperability of burned area data derived from Europe and Valencia Community in Spain were tested and analyzed on the syntactic, schematic and semantic level. We suggest approaches for achieving a higher chance of data interoperability to guide forest domain experts in forest fire analysis. For testing syntactic interoperability, a common platform in the context of formats and web services was examined. We found that establishing OGC standard web services in a combination with GIS software applications that support various formats and web services can increase the chance of achieving syntactic interoperability between multiple geospatial data derived from different sources. For testing schematic and semantic interoperability, the ontology-based schema mapping approach was taken to transform a regional data model to a European data model on the conceptual level. The Feature Manipulation Engine enabled various types of data transformation from source to target attributes to achieve schematic interoperability. Ontological modelling in Protégé helped identify a common concept between the source and target data models, especially in cases where matching attributes were not found at the schematic level. Establishment of the domain ontology was explored to reach common ground between application ontologies and achieve a higher level of semantic interoperability.
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Onah, Chinonye Cletus. "Spatial data infrastructures model for developing countries: A case study of Nigeria." Master's thesis, 2009. http://hdl.handle.net/10362/2319.
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies<br>This research explores the basics of SDI, and investigates the National SDI of different countries. Further, the research analyses SDI implementation in developing country with specific reference to the National Geospatial Data Infrastructure (NGDI) of Nigeria. The research assesses the status and the milestones of NGDI implementation using key SDI components as assessment variables. These components were grouped into four classes: Policy and Legal Issues, Technical, Funding and People. A questionnaire survey via email was conducted on the stakeholders and users of geoinformation in Nigeria. From the analysis, the NGDI has an advantage of having a national policy backing its implementation and the establishment of the coordinating body. However, the lack of SDI directive and funding are major hurdles in the implementation of the NGDI making it lack behind most of the selected case study countries in other key components. Nigeria is also found to be applying a Mixed Model of NSDI implementation as both product model
and process model are evident in the NGDI. In the real sense of access network and data sharing, NGDI is yet to be operational, though the project is going on.