En stor kvantitet av miljödata samlas hela tiden in och för att dra nytta av all data behöver den förstås av de användarna som kan applicera kunskapen inom deras område. Visualiseringar tillåter användare att förstå datan och det är därför en viktig del av hur en användare kan ta del av den datan som samlas in. I detta arbete evalueras de WebGLbaserade teknologierna Three.js och X3DOM om vilken som är mest lämplig för att visualisera geospatial data på webben utifrån hur effektiva de är vid rendering av heatmaps. Två applikationer utvecklas, en baserat på Three.js och en på X3DOM. Mätningar utförs på varje applikation för att jämföra renderingstiden mellan teknologierna och en kvalitativ studie används för att evaluera deras användbarhet. Resultatet blev att Three.js är mer lämpligt för att visualisera geospatial data på webben.

Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-07-30T14:37:21Z No. of bitstreams: 1 SIMONE TAVARES DA SILVA - DISSERTAÇÃO (PPGECA) 2016.pdf: 3397786 bytes, checksum: 0cb91397435440e612394d24d7999543 (MD5) / Made available in DSpace on 2018-07-30T14:37:21Z (GMT). No. of bitstreams: 1 SIMONE TAVARES DA SILVA - DISSERTAÇÃO (PPGECA) 2016.pdf: 3397786 bytes, checksum: 0cb91397435440e612394d24d7999543 (MD5) Previous issue date: 2016-04-28 / Capes / A região semiárida do Nordeste brasileiro caracteriza-se por um baixo regime pluviométrico e uma variabilidade climática natural que se reflete em eventos extremos como secas prolongadas. O bioma Caatinga tem sofrido os impactos das mudanças ora causadas por ações humanas, ora causadas direta ou indiretamente pelas variações no clima. O zoneamento de áreas mais suscetíveis a mudanças, ou historicamente sob forte pressão por causa do crescimento das cidades e outros fatores antrópicos, podem auxiliar em ações de planejamento mais sustentáveis. Fazendo uso de dados bioclimáticos em escala global e, de dados censitários em escala regional, o presente trabalho buscou uma metodologia integradora advinda das Geotecnologias com vistas à obtenção de um indicador das áreas submetidas a forte “pressão por mudanças”, que pode ser exercida por variáveis climáticas, demográficas ou socioeconômicas na região semiárida do Nordeste brasileiro. Faz- se o uso de técnicas de sobreposição Fuzzy, além de um estimador de densidade Kernel e são considerados três vetores principais utilizando variáveis climáticas e censitárias. Um vetor climático impulsionado por variáveis climáticas (Temperatura média, Precipitação média e Sazonalidade da Precipitação); um vetor oriundo de atividade humana demográfica, impulsionado por variáveis demográficas de população (densidade populacional e população rural) e um vetor impulsionado por atividades socioeconômicas (IDHM e PIB agropecuário). A sobreposição destes três vetores permitiu a obtenção de um indicador único de áreas submetidas à forte “pressão por mudanças” na região em estudo. Os resultados apontam áreas submetidas a “forte pressão” no entorno de cidades importantes no contexto atual do semiárido nordestino, o que se reflete em alterações marcantes na forma de uso e ocupação destas regiões. Isto se configura, principalmente, por essas regiões apresentarem alta densidade populacional, acompanhada por um crescimento do PIB agropecuário nos últimos anos. / The semi-arid region of northeastern part of Brazil has low precipitation rates and high natural climate variability. It appears trough extreme events such as prolonged droughts. The Caatinga biome has been under impacts either caused by human actions, as directly or indirectly caused by climate changes. For a better understanding and planning actions about those changes, susceptible areas could be classified and zoned, making possible a visualization of historical and continuous pressures caused by urban growth or other human pressures. This research uses bioclimatic data on a global scale and census data at the regional and local scale in an integrative approach. Geospatial technologies are used to obtain a “pressure for changes indicator” caused by climatic, demographic or socioeconomic variables. Fuzzy overlay techniques are used and a statistical estimator for generate surfaces (Kernel density) for three chosen drivers. One climate driver represented by Temperature, Precipitation and Precipitation Seasonality; One demographic driver represented by Population density and rural population changes; and one socioeconomic driver represented by HDI (Human development index) for each county and agricultural GDP (Gross Domestic Product). This overlay process results in a unique “Change for pressure” index for the Brazilian semi-arid region. The results show the nearest areas from some important middle cities such as “high pressure changes”. In those areas, it is possible to observe the strong correlation between LULCC and high density urban areas and an increasing of GDP (Gross Domestic Product for Livestock and Agriculture) in the last years as well.

Dioxins are highly toxic persistent environmental pollutants that occur in marine harbour sediments as the results of industrial practices around the world and pose a significant risk to human health. To adequately remediate contaminated sediments, the spatial extent of contamination must first be determined by spatial interpolation. The ability to lower sampling frequency and perform laboratory analysis on fewer samples, yet still produce an adequate pollutant distribution map, would reduce the initial cost of new remediation projects. Fuzzy Set Theory has been shown as a way to reduce uncertainty due to data sparsity and provides an advantageous way to quantify gradational changes like those of pollutant concentrations through fuzzing clustering based approaches; Fuzzy modelling has the ability to utilize these advantages for making spatial predictions. To assess the ability of fuzzy modeling to make spatial predictions using fewer sample points, its predictive ability was compared to Ordinary Kriging (OK) and Inverse Distance Weighting (IDW) under increasingly sparse data conditions. This research used a Takagi-Sugeno (T-S) fuzzy modelling approach with fuzzy c-means clustering to make spatial predictions of lead concentrations in soil to determine the efficacy of the fuzzy model for applications of modeling dioxins in marine sediment. The spatial density of the data used to make the predictions was incrementally reduced to simulate increasingly sparse spatial data conditions. To determine model performance, the data at each increment not used for making the spatial predictions was used as validation data, which the model attempted to predict and the performance was analyzed. Initially, the parameters associated with the T-S fuzzy model were determined by the optimum observed performance, where the combination of parameters that produced the most accurate prediction of the validation data were retained as optimal for each increment of the data reduction. To determine performance Mean Absolute Error, the Coefficient of Determination, and Root Mean Squared Error were selected as metrics. To give each metric equal weighting a binned scoring system was developed where each metric received a score from 1 to 10, the average represented that methods score. The Akaike Information Criterion (AIC) was also employed to determine the effect of the varied validation set lengths on performance. For the T-S fuzzy model as the amount of data used to solve the respective validation set points was reduced the number of clusters was lower and the cluster centres were more spread out, the fuzzy overlap between clusters was larger, and the widths of the membership function in the T-S fuzzy model were wider. Although it was possible to determine an optimal number of clusters, fuzzy overlap, and membership function width that yielded an optimal prediction of the validation data, gain in performance was minor compared to many other combinations of parameters. Therefore, for the data used in this study the T-S fuzzy model was insensitive to parameter choice. For OK, as the data was reduced, the range of spatial dependence in the data from variography became lower, and for IDW the power parameters optimal value became lower to give a greater weighting to more widely spread points. For the TS fuzzy model, OK, and IDW the increasingly sparse data conditions resulted in an increasingly poor model performance for all metrics. This was supported by AIC values for each method at each increment of the data reduction that were within 1 point of each other. The ability of the methods to predict outlier points and reproduce the variance in the validation sets was very similar and overall quite poor. Based on the scoring system IDW did exhibit a slight outperformance of the T-S fuzzy model, which slightly outperformed OK. However, the scoring system employed in this research was overly sensitive and so was only useful for assessing relative performance. The performance of the T-S model was very dependent on the number of outliers in the respective validation set. For modeling under sparse data conditions, the T-S fuzzy modeling approach using FCM clustering and constant width Gaussian shaped membership functions used in this research did not show any advantages over IDW and OK for the type of data tested. Therefore, it was not possible to speculate on a possible reduction in sampling frequency for delineating the extent of contamination for new remediation projects. / Graduate

Crime associated with alcohol consumption poses a serious problem. There is a variety of approaches that try to conceptualize this relationship. One of the most progressive approaches is that of emphasizing the effects of alcohol outlets on crime associated with alcohol consumption. Even though it is a well-established field in other regions, in Czech Republic, there are no available studies dealing with the relationship of alcohol outlets and crime associated with alcohol consumption. This diploma thesis deals with the association of on-premise alcohol outlets and crime in Czech Republic. The unit of analysis used in this diploma thesis was police districts. In the final data set, we had 517 police districts. For all of the police districts, the incidence rates of crime, on-premise alcohol outlet densities and other characteristics were obtained. Analysis by the means of linear regression and geographically weighted regression was performed on data. The results of analysis indicate that on-premise alcohol densities are associated with all examined crime incidence rates (except of road accidents), even after adjusting for other variables. Also, there is a non-trivial spatial variation in data. The regression models had high explanatory power. The results of this diploma thesis imply that it is...

During the late 19th and into the 20th Century, the Tisza River’s vast floodplain-wetland systems were largely disconnected by levees, facilitating "reclamation" for agriculture and resulting in an estimated loss of over 90% of historical wetlands. While levees have been successful in preventing catastrophic flooding for a century, Lower Tisza flood stages continue to rise partially due to aggradation and increased roughness on the confined floodplain. The decrease in the Tisza's current floodway carrying capacity has reduced the flood-protection level of the Tisza's aging levee system. Recently in Hungary, "Room for the River" policies have gained more prominence. For the first of three papers for this dissertation, I assessed eight potential floodplain-reconnection scenarios that would provide more room for the river between Csongrád, Hungary and the Hungary-Serbia border. A novel framework using hydrodynamic and geospatial modeling was used to perform planning-level evaluations of the tradeoffs between floodplain-reconnection scenarios and enhancement of the existing levee system. The scenarios evaluated include levee removal and levee setbacks to strategically reconnect historical wetlands while reducing flood levels. Scenario costs and human population impacts were also assessed. Impacts of reconnecting the Lower Tisza floodplain were compared to heightening levees, the prevailing strategy over the previous century. From a purely construction-cost perspective, heightening Lower Tisza levees is potentially the most cost-effective and politically expedient solution (i.e., impacts the least number of people). However, levee heightening does not solve the long-term problem of reduced flood conveyance, nor does it result in wetland reconnection or enhancement of other floodplain ecosystem services. The suite of reconnection options evaluated provides engineers, planners, and decision makers a framework from which they can further evaluate potential flood-risk reduction options. At least three of the eight reconnection scenarios (setting the western levee back, 1500-meter, and 2000-meter setbacks) along the Lower Tisza demonstrated that floodplain-wetland reconnection is possible while achieving the objectives of minimizing impacts on human populations and reducing flood heights. The Illinois River has a similar history to the Tisza. Levees were constructed, and wetlands were drained during the late 19th and early 20th Centuries. By the mid-1920’s, Illinois River levee systems became increasingly difficult for private landowners and the state to maintain as commodity prices fell and flood levels increased. However, the 1928 U.S. Flood Control act shifted a substantial portion of the burden of flood mitigation from local landowners to the federal government, preventing the dissolution of levee districts. While these levee systems have facilitated floodplain agricultural production and development for the last century, disconnecting the river from its floodplain has led to concerns about the negative impacts of levees on the physical and biological systems of the Illinois River Valley. Recent studies have emphasized approaches that would result in setting back or removing levees in order to naturalize portions of large river-floodplain systems, including the Illinois. The costs and benefits of such projects have shown potential restoration benefits may outweigh potential costs, but these studies have not demonstrated the specific levee districts which have the highest reconnection potential from an economic standpoint. The second paper for this dissertation used geospatial methods to fill this gap by assessing the National Commodity Crops Productivity Index (NCCPI) soil values and agricultural production and profit values for corn and soybeans in 32 individual levee districts along a 235-km segment of the Lower Illinois River. In general, soil productivity index values were lower for Illinois River levee districts compared to the county averages in which the districts are located. Over the five-year study period from 2010-2014, the total agricultural profits in the levee districts ranged from $18-61 million. Several levee districts have relatively low per hectare agricultural values when compared to wetland benefit studies, indicating these protected floodplain areas may be suitable for reconnection. For the third and final dissertation paper I used a novel hydrodynamic, geospatial, economic, and habitat suitability framework to assess the tradeoffs of strategically reconnecting the 125-km La Grange Segment (LGS) of the Lower Illinois River to its floodplain in order to decrease flood risk, improve floodplain habitats, and limit the costs of reconnection. Costs included building-associated losses, lost agricultural profits, and total levee removal and construction costs. Modeled scenarios demonstrated that while flood heights and environmental benefits are maximized through the most aggressive levee setbacks and removals, these scenarios also have the highest economic costs. However, the tradeoff of implementing lower-cost scenarios is that there would be less flood-height reduction and less floodplain habitat available. Several levee districts had high potential for reconnection based on limiting potential damages as well as providing suitable floodplain habitat. To implement large-scale strategic floodplain reconnection along the LGS, opportunity costs ranged from $1.1-$4.3 billion. As such, payments for ecosystem services will likely be necessary to compensate landowners for building losses and decreased long-term agricultural production that result in an overall flood-reduction benefit, increased floodplain wetlands, and most-soil plant habitat.

Submitted by LUIZ HENRIQUE PEREIRA null (e_luizh@yahoo.com.br) on 2016-12-20T11:04:00Z No. of bitstreams: 1 pereira_lh_geo_RC.pdf: 6871364 bytes, checksum: 830de7380f478a93aeff860b974bc3ce (MD5) / Rejected by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br), reason: Solicitamos que realize uma nova submissão seguindo a orientação abaixo: Incluir o número do processo de financiamento nos agradecimentos da dissertação/tese. Corrija esta informação e realize uma nova submissão com o arquivo correto. Agradecemos a compreensão. on 2016-12-22T10:30:31Z (GMT) / Submitted by LUIZ HENRIQUE PEREIRA (e_luizh@yahoo.com.br) on 2016-12-22T10:46:39Z No. of bitstreams: 1 pereira_lh_dr_rcla.pdf: 6574636 bytes, checksum: c3702d008829fade5dc14e767d174030 (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-12-22T12:04:12Z (GMT) No. of bitstreams: 1 pereira_lh_dr_rcla.pdf: 6574636 bytes, checksum: c3702d008829fade5dc14e767d174030 (MD5) / Made available in DSpace on 2016-12-22T12:04:12Z (GMT). No. of bitstreams: 1 pereira_lh_dr_rcla.pdf: 6574636 bytes, checksum: c3702d008829fade5dc14e767d174030 (MD5) Previous issue date: 2016-10-28 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / 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. / 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. / FAPESP: 2013/13885-0

Geoinformatics field of science becomes more and more important nowadays. This is not only because it is crucial for industry, but it also plays more important role in consumer electronics than ever before. The ongoing demand for complex solutions gave a rise to SOA1 architecture in enterprise and geographical field. The topic that is currently being studied is interoperability between different geospatial services. This paper makes a proposal for a master thesis that tries to add another way of chaining different geospatial services. It describes the current state of knowledge, possible research gap and then goes into the details on design and execution part. Final stage is the summary of expected outcomes. The result of this proposal is a clearly defined need for a research in the outlined area of knowledge. / Contact details: email: dawidnejman@gmail.com phone: +48 511-139-190

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. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2020

The average age-adjusted incidence and mortality rates of lung and bronchus cancer is 55% and 56% higher in Kentucky than the national averages in the United States, respectively. Populations with low income and educational attainment, and those who live close to the mining regions across Kentucky are more affected by the high prevalence and resulting mortality rates of lung and bronchus cancer. This study was conducted because of the high incidence of lung and bronchus cancer and resulting mortality rates in the state of Kentucky that may not be caused solely by social and demographic factors. The theoretical foundation for this study was the social-ecological model (SEM). This quantitative cross-sectional study assessed whether the association between geographic factors and incidence, and mortality rate of lung and bronchus cancer is significant in Kentucky, controlling for social and demographic factors respectively. The sample size was n = 960. Bivariate analysis and ordinal regression were used to address the research questions. The outcome of the study revealed that populations that reside in rural zones are significantly (p < .05) more likely to be exposed to trace elements with less access to effective care, and higher mortality as compared to populations living in metropolitan and micropolitan zones. Healthy individuals promote healthy families, which in turn promote healthy communities. This could improve the local work force, investments, and development which could enhance self-esteem and social change in each county across Kentucky.

abstract: The volume of available spatial data has increased tremendously. Such data includes but is not limited to: weather maps, socioeconomic data, vegetation indices, geotagged social media, and more. These applications need a powerful data management platform to support scalable and interactive analytics on big spatial data. Even though existing single-node spatial database systems (DBMSs) provide support for spatial data, they suffer from performance issues when dealing with big spatial data. Challenges to building large-scale spatial data systems are as follows: (1) System Scalability: The massive-scale of available spatial data hinders making sense of it using traditional spatial database management systems. Moreover, large-scale spatial data, besides its tremendous storage footprint, may be extremely difficult to manage and maintain due to the heterogeneous shapes, skewed data distribution and complex spatial relationship. (2) Fast analytics: When the user runs spatial data analytics applications using graphical analytics tools, she does not tolerate delays introduced by the underlying spatial database system. Instead, the user needs to see useful information quickly. In this dissertation, I focus on designing efficient data systems and data indexing mechanisms to bolster scalable and interactive analytics on large-scale geospatial data. I first propose a cluster computing system GeoSpark which extends the core engine of Apache Spark and Spark SQL to support spatial data types, indexes, and geometrical operations at scale. In order to reduce the indexing overhead, I propose Hippo, a fast, yet scalable, sparse database indexing approach. In contrast to existing tree index structures, Hippo stores disk page ranges (each works as a pointer of one or many pages) instead of tuple pointers in the indexed table to reduce the storage space occupied by the index. Moreover, I present Tabula, a middleware framework that sits between a SQL data system and a spatial visualization dashboard to make the user experience with the dashboard more seamless and interactive. Tabula adopts a materialized sampling cube approach, which pre-materializes samples, not for the entire table as in the SampleFirst approach, but for the results of potentially unforeseen queries (represented by an OLAP cube cell). / Dissertation/Thesis / Doctoral Dissertation Computer Science 2020