Radon is a radioactive gas that is the leading cause of lung cancer in non-smokers. While radon is natural and ubiquitous, higher concentrations greatly increase cancer risk. As such, understanding the spatial distribution of radon potential is key to planning and public health efforts. This project tests a method of determining radon potential using in situ measurements of gamma radiation. The in situ measurements were used to create a raster of gamma emissions in the study region using kriging. The resulting model showed that the operational scale of gamma radiation in the study region was 4.5 km. Indoor radon concentrations were then assigned gamma emission rates from the raster and the two were compared. While there was evidence of an association between higher gamma and high radon, the gamma readings were not quantitatively predictive. As such only categorical predictions of radon potential and risk could be made.

Weather index insurance has become a popular subject in agricultural risk management. Under these policies farmers receive payments if they experience adverse weather for their crops. Spatial basis risk is the risk that weather observed at stations does not correspond to the weather experienced by the farmer. The objective of this research is to determine to what extent spatial basis risk can be impacted by the interpolation technique used to estimate weather conditions. Using forage crops from Ontario, Canada, as an example, a temperature based insurance index is developed. Seven different interpolation methods are used to estimate indemnities for forage producers. Results show that the number of weather stations in the interpolation area has a larger impact on spatial basis risk than the choice of interpolation technique. For insurers wishing to implement this type of insurance, more focus should be placed on increasing the number of available weather stations. / October 2016

In the journey toward optimal spectrum usage, techniques and concepts such as Cognitive Radio and Dynamic Spectrum Access have enjoyed increasing attention in many research projects. Dynamic Spectrum Access introduces the need for real-time RF spectrum information in the form of Radio Environment Maps. This need motivates an investigation into a hybrid approach of sample measurements and spatial interpolation as opposed to using conventional propagation models. Conventional propagation models, both path-general and path-specific, require information of transmitters within the area of interest. Irregular Terrain Models such as the Longley-Rice model, further require topographic information in order to consider the effects of obstacles. The proposed spatial interpolation technique, kriging, requires no information regarding transmitters. Furthermore, Ordinary Kriging requires nothing other than measured samples whereas other kriging variants such as Universal Kriging and Regression Kriging can use additional information such as topographic data to aid in prediction accuracy. This dissertation investigates the performance of the three aforementioned kriging variants in producing Radio Environment Maps of received power. For practical and financial reasons, the received power measurement samples are generated using the Longley-Rice Irregular Terrain Model and are, therefore, simulated measurements. The experimental results indicate that kriging shows great promise as a tool to generate Radio Environment Maps. It is found that Ordinary Kriging produces the most accurate predictions of the three kriging methods and that prediction errors of less than 10 dB can be achieved even when using very low sampling densities. / MSc (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

In the journey toward optimal spectrum usage, techniques and concepts such as Cognitive Radio and Dynamic Spectrum Access have enjoyed increasing attention in many research projects. Dynamic Spectrum Access introduces the need for real-time RF spectrum information in the form of Radio Environment Maps. This need motivates an investigation into a hybrid approach of sample measurements and spatial interpolation as opposed to using conventional propagation models. Conventional propagation models, both path-general and path-specific, require information of transmitters within the area of interest. Irregular Terrain Models such as the Longley-Rice model, further require topographic information in order to consider the effects of obstacles. The proposed spatial interpolation technique, kriging, requires no information regarding transmitters. Furthermore, Ordinary Kriging requires nothing other than measured samples whereas other kriging variants such as Universal Kriging and Regression Kriging can use additional information such as topographic data to aid in prediction accuracy. This dissertation investigates the performance of the three aforementioned kriging variants in producing Radio Environment Maps of received power. For practical and financial reasons, the received power measurement samples are generated using the Longley-Rice Irregular Terrain Model and are, therefore, simulated measurements. The experimental results indicate that kriging shows great promise as a tool to generate Radio Environment Maps. It is found that Ordinary Kriging produces the most accurate predictions of the three kriging methods and that prediction errors of less than 10 dB can be achieved even when using very low sampling densities. / MSc (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

A regionalização hidrológica é uma técnica que permite transferir informação entre bacias hidrográficas semelhantes, a fim de calcular em sítios que não dispõem de dados, as variáveis hidrológicas de interesse; assim, a mesma caracteriza-se por ser uma ferramenta útil na obtenção de outorga de direitos de uso de recursos hídricos, instrumento previsto na Lei 9433/97. Devido à desatualização do modelo atual de regionalização hidrológica do Estado de São Paulo, proposto na década de 80, este estudo tem como objetivo geral avaliar se o mesmo está adequado ao uso, de acordo com a atualização de seu banco de dados, e propor um novo que supere as limitações do antigo. O estudo foi realizado no Estado de São Paulo, que tem área de aproximadamente 248197 km², localizado entre as longitudes -44° 9\', e -53º 5\', e entre as latitudes -22° 40\', e -22° 39\'. Utilizou-se, inicialmente, dados de 176 estações fluviométricas administradas pelo DAEE e pela ANA, disponíveis em http://www.sigrh.sp.gov.br. Determinou-se para as estações, a precipitação média anual da bacia hidrográfica (P), a vazão média plurianual (Q), a vazão mínima média de 7 dias seguidos com período de retorno de 10 anos (Q7,10) e as vazões com 90 e 95% de permanência no tempo (Q90 e Q95). Posteriormente, fez-se análise de consistência excluindo as estações inconsistentes do estudo; assim, restaram 172 para serem utilizadas na avaliação do modelo e formulação de um novo. A avaliação do modelo fez-se pelo índice de confiança (c), que é definido pelo produto entre o coeficiente de correlação (r) e o índice de concordância (d), utilizando como valor de estimativa as vazões geradas pelo modelo, e como valor padrão as calculadas por intermédio das estações fluviométricas. Todas as vazões avaliadas foram classificadas como ótimas, com índice de confiança (c) acima de 0,85; assim, o atual modelo rejeitou a hipótese de que a atualização de seu banco de dados pudesse inferir em sua capacidade preditiva; portanto, o mesmo pode ser usado na obtenção das vazões estudadas que são referência na emissão de outorga em diferentes Estados do Brasil. Entretanto, o modelo apresentou algumas limitações, como extrapolação para áreas de bacias de drenagem menores do que as utilizadas para formulá-lo, e problemas em seu aplicativo computacional: o mesmo informa a precipitação média anual na coordenada geográfica do local de captação da água, e não da bacia de drenagem a montante do referido local. Neste enfoque, foi formulado um novo modelo, que superou as limitações e proporcionou capacidade preditiva maior que a do antigo. / A hydrological regionalization is a technique that allows to transfer information between similar watersheds in order to calculate, in sites where there are no data on the hydrological variables of interest. This technique becomes a useful tool to ensure the rights of water resources use, instrument provided by Law 9433/97. Due to the outdated hydrological regionalization model of São Paulo State, proposed in the 1980\'s, this study aims to broadly assess whether the current model is appropriate to use, according to an analysis of its update database and to propose a new model to overcome the limitations of the current one. The study was conducted in State São Paulo with area of approximately 248197 km ², located between longitudes -44 ° 9 \', and -53 ° 5\', and between latitudes 40 ° -22\' and -22 ° 39\'. We used data from 176 initially gauged stations administered by ANA and DAEE available at http://www.sigrh.sp.gov.br, where it was determined to the stations, the average annual rainfall of the basin (P) multiannual average streamflow (Q), streamflow minimum average of 7 consecutive days with a return period of 10 years (Q7,10) and streamflows with 90 and 95% of permanence in time(Q90 e Q95). Afterwards, we analyzed the consistency excluding the inconsistent stations from the study, thus, remaining 172 to be used in the model evaluation and development of a new model. The model evaluation was made by the confidence index (c), which is the product between the correlation coefficient (r) and the agreement index (d), using as estimate value the streamflows generated by the model and as the standard value, the streamflows calculated through the gauged stations. All streamflows evaluated were classified as optimal, with confidence index (c) above 0.85, therefore, the current model rejected the hypothesis that upgrading the database could infer its predictive ability, so, it can be used to obtain the streamflows studied that refer to use grants in different States of Brazil. However, the model had some limitations, such as extrapolation to areas of smaller watersheds than those used to formulate it, and computer application problems, being that, it reports the average annual precipitation at the geographic coordinate at the local catchment water, not the watershed upstream of that location. A new model was formulated that surpasses the limitations and provides greater predictive ability than the current one.

While environmental justice (EJ) research in the U.S. has traditionally focused on inequities in the distribution of technological hazards, the disproportionate impacts of Hurricane Katrina on racial minorities and socioeconomically disadvantaged households have prompted researchers to investigate the EJ implications of natural hazards such as flooding. Recent EJ research has also emphasized the need to examine social inequities in access to environmental amenities. Unlike technological hazards such as air pollution and toxic waste sites, areas exposed to natural hazards such as hurricanes and floods have indivisible amenities associated with them. Coastal property owners are exposed to flood hazards, but also enjoy water views and unhampered access to oceans and the unique recreational opportunities that beaches offer. Conversely, dense urban development and associated impervious surfaces increase likelihood of floods in inland areas which may lack the amenities of proximity to open water. This dissertation contributes to the emerging literature on EJ and social vulnerability to natural hazards by analyzing racial, ethnic, and socioeconomic inequities in the distribution of flood risk exposure in the Miami Metropolitan Statistical Area (MSA), Florida--one of the most hurricane-prone areas in the world and one of the most ethnically diverse MSAs in the U.S. The case study evaluates the EJ implications of residential exposure to coastal flood risk, inland flood risk, and no flood risk, in conjunction with coastal water related amenities, using geographic information science (GIS)-based techniques and logistic regression modeling to estimate flood risk exposure. Geospatial data from the Federal Emergency Management Agency (FEMA) are utilized to delineate coastal and inland 100-year flood hazard zones. Socio-demographic variables previously utilized in EJ research are obtained from tract level data published in the 2010 census and 2007-2011 American Community Survey five-year estimates. Principal components analysis is employed to condense several socio-demographic attributes into two neighborhood deprivation indices that represent economic insecurity and instability, respectively. Indivisible coastal water related amenities are represented by control variables of percent seasonal homes and proximity to public beach access sites. Results indicate that racial/ethnic minorities and those with greater social vulnerability based on the neighborhood deprivation indices are more likely to reside in inland flood zones and areas outside 100-year flood zones, while residents in coastal flood zones are disproportionately non-Hispanic White. Moreover, residents exposed to coastal flood risk tend to live in areas with ample coastal water related amenities, while racial/ethnic minorities and individuals with higher neighborhood deprivation who are exposed to inland flood risk or no flood risk reside in areas without coastal water related amenities. This dissertation elucidates the importance of EJ research on privilege and access to environmental amenities in conjunction with environmental hazards because areas exposed to natural hazards are likely to offer indivisible benefits. Estimating people and places exposed to hazards for EJ research becomes difficult when the boundaries of census areal units containing socio-demographic data do not match the boundaries of hazard exposure areas. This challenge is addressed with an application of dasymetric spatial interpolation using GIS-based techniques to disaggregate census tracts to inhabited parcels. Several spatial interpolation methods are assessed for relative accuracy in estimating population densities for the Miami MSA, and the output units from the most accurate method are employed in EJ regression analyses. The dasymetric mapping efforts utilized herein contribute to research on the modifiable areal unit problem (MAUP) and its effects on statistical analyses. Since the dasymetric mapping technique used for EJ analyses disaggregates census tracts to the inhabited parcel level, the results of the associated analyses for flood hazards exposure and access to coastal water related amenities should be more reliable than those based on tracts. The enhanced accuracy associated with inhabited parcels is a result of using a more precise geospatial depiction of residential populations, which leads to a more accurate portrayal of disproportionate exposure to flood hazards. Consequently, this dissertation contributes methodologically to GIS-based techniques of dasymetric spatial interpolation and empirically to EJ analysis of flood hazards with indivisible coastal water related amenities.

Reducing power consumption is among the top concerns in Wireless Sensor Networks, as the lifetime of a Wireless Sensor Network depends on its power consumption. Directional antennas help achieve this goal contrary to the commonly used omnidirectional antennas that radiate electromagnetic power equally in all directions, by concentrating the radiated electromagnetic power only in particular directions. This enables increased communication range at no additional energy cost and reduces contention on the wireless medium. The SPIDA (SICS Parasitic Interference Directional Antenna) prototype is one of the few real-world prototypes of electronically switchable directional antennas for Wireless Sensor Networks. However, building several prototypes of SPIDA and conducting real-world experiments using them may be expensive and impractical. Modeling SPIDA based on real-world experiments avoids the expenses incurred by enabling simulation of large networks equipped with SPIDA. Such a model would then allow researchers to develop new algorithms and protocols that take advantage of the provided directional communication on existing Wireless Sensor Network simulators. In this thesis, a model of SPIDA for Wireless Sensor Networks is built based on thoroughly designed real-world experiments. The thesis builds a probabilistic model that accounts for variations in measurements, imperfections in the prototype construction, and fluctuations in experimental settings that affect the values of the measured metrics. The model can be integrated into existing Wireless Sensor Network simulators to foster the research of new algorithms and protocols that take advantage of directional communication. The model returns the values of signal strength and packet reception rate from a node equipped with SPIDA at a certain point in space given the two-dimensional distance coordinates of the point and the configuration of SPIDA as inputs. / Phone:+46765816263 Additional email: burkaja@yahoo.com

Participatory sensing (PS) systems are a new emerging sensing paradigm based on the participation of cellular users in a cooperative way. Due to the spatio-temporal granularity that a PS system can provide, it is now possible to detect and analyze events that occur at different scales, at a low cost. While PS systems present interesting characteristics, they also create new problems. Since the measuring devices are cheaper and they are in the hands of the users, PS systems face several design challenges related to the poor accuracy and high failure rate of the sensors, the possibility of malicious users tampering the data, the violation of the privacy of the users as well as methods to encourage the participation of the users, and the effective visualization of the data. This dissertation presents four main contributions in order to solve some of these challenges. This dissertation presents a framework to guide the design and implementation of PS applications considering all these aspects. The framework consists of five modules: sample size determination, data collection, data verification, data visualization, and density maps generation modules. The remaining contributions are mapped one-on-one to three of the modules of this framework: data verification, data visualization and density maps. Data verification, in the context of PS, consists of the process of detecting and removing spatial outliers to properly reconstruct the variables of interest. A new algorithm for spatial outliers detection and removal is proposed, implemented, and tested. This hybrid neighborhood-aware algorithm considers the uneven spatial density of the users, the number of malicious users, the level of conspiracy, and the lack of accuracy and malfunctioning sensors. The experimental results show that the proposed algorithm performs as good as the best estimator while reducing the execution time considerably. The problem of data visualization in the context of PS application is also of special interest. The characteristics of a typical PS application imply the generation of multivariate time-space series with many gaps in time and space. Considering this, a new method is presented based on the kriging technique along with Principal Component Analysis and Independent Component Analysis. Additionally, a new technique to interpolate data in time and space is proposed, which is more appropriate for PS systems. The results indicate that the accuracy of the estimates improves with the amount of data, i.e., one variable, multiple variables, and space and time data. Also, the results clearly show the advantage of a PS system compared with a traditional measuring system in terms of the precision and spatial resolution of the information provided to the users. One key challenge in PS systems is that of the determination of the locations and number of users where to obtain samples from so that the variables of interest can be accurately represented with a low number of participants. To address this challenge, the use of density maps is proposed, a technique that is based on the current estimations of the variable. The density maps are then utilized by the incentive mechanism in order to encourage the participation of those users indicated in the map. The experimental results show how the density maps greatly improve the quality of the estimations while maintaining a stable and low total number of users in the system. P-Sense, a PS system to monitor pollution levels, has been implemented and tested, and is used as a validation example for all the contributions presented here. P-Sense integrates gas and environmental sensors with a cell phone, in order to monitor air quality levels.

A regionalização hidrológica é uma técnica que permite transferir informação entre bacias hidrográficas semelhantes, a fim de calcular em sítios que não dispõem de dados, as variáveis hidrológicas de interesse; assim, a mesma caracteriza-se por ser uma ferramenta útil na obtenção de outorga de direitos de uso de recursos hídricos, instrumento previsto na Lei 9433/97. Devido à desatualização do modelo atual de regionalização hidrológica do Estado de São Paulo, proposto na década de 80, este estudo tem como objetivo geral avaliar se o mesmo está adequado ao uso, de acordo com a atualização de seu banco de dados, e propor um novo que supere as limitações do antigo. O estudo foi realizado no Estado de São Paulo, que tem área de aproximadamente 248197 km², localizado entre as longitudes -44° 9\', e -53º 5\', e entre as latitudes -22° 40\', e -22° 39\'. Utilizou-se, inicialmente, dados de 176 estações fluviométricas administradas pelo DAEE e pela ANA, disponíveis em http://www.sigrh.sp.gov.br. Determinou-se para as estações, a precipitação média anual da bacia hidrográfica (P), a vazão média plurianual (Q), a vazão mínima média de 7 dias seguidos com período de retorno de 10 anos (Q7,10) e as vazões com 90 e 95% de permanência no tempo (Q90 e Q95). Posteriormente, fez-se análise de consistência excluindo as estações inconsistentes do estudo; assim, restaram 172 para serem utilizadas na avaliação do modelo e formulação de um novo. A avaliação do modelo fez-se pelo índice de confiança (c), que é definido pelo produto entre o coeficiente de correlação (r) e o índice de concordância (d), utilizando como valor de estimativa as vazões geradas pelo modelo, e como valor padrão as calculadas por intermédio das estações fluviométricas. Todas as vazões avaliadas foram classificadas como ótimas, com índice de confiança (c) acima de 0,85; assim, o atual modelo rejeitou a hipótese de que a atualização de seu banco de dados pudesse inferir em sua capacidade preditiva; portanto, o mesmo pode ser usado na obtenção das vazões estudadas que são referência na emissão de outorga em diferentes Estados do Brasil. Entretanto, o modelo apresentou algumas limitações, como extrapolação para áreas de bacias de drenagem menores do que as utilizadas para formulá-lo, e problemas em seu aplicativo computacional: o mesmo informa a precipitação média anual na coordenada geográfica do local de captação da água, e não da bacia de drenagem a montante do referido local. Neste enfoque, foi formulado um novo modelo, que superou as limitações e proporcionou capacidade preditiva maior que a do antigo. / A hydrological regionalization is a technique that allows to transfer information between similar watersheds in order to calculate, in sites where there are no data on the hydrological variables of interest. This technique becomes a useful tool to ensure the rights of water resources use, instrument provided by Law 9433/97. Due to the outdated hydrological regionalization model of São Paulo State, proposed in the 1980\'s, this study aims to broadly assess whether the current model is appropriate to use, according to an analysis of its update database and to propose a new model to overcome the limitations of the current one. The study was conducted in State São Paulo with area of approximately 248197 km ², located between longitudes -44 ° 9 \', and -53 ° 5\', and between latitudes 40 ° -22\' and -22 ° 39\'. We used data from 176 initially gauged stations administered by ANA and DAEE available at http://www.sigrh.sp.gov.br, where it was determined to the stations, the average annual rainfall of the basin (P) multiannual average streamflow (Q), streamflow minimum average of 7 consecutive days with a return period of 10 years (Q7,10) and streamflows with 90 and 95% of permanence in time(Q90 e Q95). Afterwards, we analyzed the consistency excluding the inconsistent stations from the study, thus, remaining 172 to be used in the model evaluation and development of a new model. The model evaluation was made by the confidence index (c), which is the product between the correlation coefficient (r) and the agreement index (d), using as estimate value the streamflows generated by the model and as the standard value, the streamflows calculated through the gauged stations. All streamflows evaluated were classified as optimal, with confidence index (c) above 0.85, therefore, the current model rejected the hypothesis that upgrading the database could infer its predictive ability, so, it can be used to obtain the streamflows studied that refer to use grants in different States of Brazil. However, the model had some limitations, such as extrapolation to areas of smaller watersheds than those used to formulate it, and computer application problems, being that, it reports the average annual precipitation at the geographic coordinate at the local catchment water, not the watershed upstream of that location. A new model was formulated that surpasses the limitations and provides greater predictive ability than the current one.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The altimetry of the surface terrain for many decades has been achieved almost exclusively by conventional surveying. The advancement of technology allowed the development of space missions and the creation of artificial satellites, making the science of remote sensing to expand exponentially. The SRTM (Shuttle Radar Topographic Mission) and ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer) are spatial programs that provide altitude information of almost the entire globe. The program Google Earth uses that information, and provides for its users in a practical and rapid way. For ease of access to data from these techniques, many users use them without knowing the geometric problems existing in these products, which can compromise the quality of results obtained through these techniques. Therefore, there is a need for a prior evaluation to assess the quality and workability for each method. In this context, the objective was to analyze the accuracy of three ways of obtaining altitude: by SRTM, ASTER and Google Earth, comparing them with conventional surveying and with GPS, because they are more established techniques. To this end, two surveys were performed in situ, one using a GPS receiver and the other by conventional topography, where the heights of the points were compared with the heights obtained by the three methods analyzed, resulting in discrepancies. The results show that the data from the SRTM provided by Embrapa Monitoring by Satellites through the Project Brasil em Relevo are more accurate than ASTER data and Google Earth, moreover, was also found that the Kriging interpolation technique has best results for altimetric spatial data. / A altimetria do terreno, por muitas décadas, tem sido obtida, quase que exclusivamente por meio da topografia convencional. O avanço da tecnologia permitiu o desenvolvimento de missões espaciais e a criação de satélites artificiais, fazendo com que a ciência do Sensoriamento Remoto se expandisse de forma exponencial. O SRTM (Shuttle Radar Topographic Mission) e o ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer) são programas espaciais que fornecem informações altimétricas de quase todo o globo terrestre. O programa Google Earth utiliza-se dessas informações e as disponibiliza para seus usuários de forma prática e rápida. Pela facilidade de acesso aos dados provenientes destas técnicas, muitos usuários os utilizam sem conhecer os problemas geométricos existentes nesses produtos, o que pode comprometer a qualidade dos resultados obtidos através dessas técnicas. Por esse motivo, há a necessidade de uma prévia avaliação para aferir a qualidade e a aplicabilidade de cada método. Nesse contexto, o objetivo do trabalho foi analisar a acurácia de três formas de obtenção de altitude: por SRTM, ASTER e Google Earth, comparando-os com a topografia convencional e com o GPS, por serem técnicas mais consolidadas. Para isso, foram realizados dois levantamentos in situ, um através de receptores GPS e outro por topografia convencional, onde as altitudes dos pontos foram comparadas com as altitudes obtidas pelos três métodos analisados, resultando nas discrepâncias. Os resultados mostram que os dados provenientes do SRTM, fornecidos pela Embrapa Monitoramento por Satélite, através do Projeto Brasil em Relevo, são mais acurados do que os dados ASTER e Google Earth, além disto, também foi constatado que a técnica de interpolação da Krigagem apresenta melhores resultados para a espacialização de dados altimétricos.