Projetos de SIG (Sistemas de Informação Geográfica), em geral, ainda não apresentam modelo conceitual de banco de dados geográficos. Os implementadores de SIG se preocupam com a aquisição dos dados (captura e adaptação), que é a etapa mais cara, e dão, ainda, pouca atenção à modelagem. A utilização de modelos conceituais faz com que os usuários controlem melhor sua base de dados e tirem maior proveito do SIG. O objetivo deste trabalho é definir um conjunto de procedimentos de engenharia reversa de bancos de dados espaciais que auxiliem na criação e manutenção de modelos conceituais para aplicações de SIG a partir de dados já existentes. Estes procedimentos podem contribuir para um aumento na qualidade dos SIG implementados, auxiliando na popularização da prática de modelagem conceitual de banco de dados geográficos. São estudados três formatos de transferência utilizados por usuários de SIG. A partir daí, é proposto uma arquitetura de sistema de engenharia reversa para SIG. / Even with the increasing use of Geographic Information Systems (GIS), conceptual modeling of geographic databases (GDB) is not yet usual among GIS professionals. This fact can in part be explained by the professional profile of most GIS designers. They usually are more familiar with specific GIS applications than with database technology. Among them, one can find cartographers, geographers, agricultural engineers, and architects. Besides that, the cost of geographic data acquisition is so high that much important is given to acquisition plans during GIS design and less interest is given to the database design process. Especially first time designers do not perceive the importance of a database schema that is independent of a specific GIS product. Conceptual design preserves the independence between data types and the logical schema of the product. Moreover, relying on the GDB conceptual schema users can better understand what part of the geographic reality is represented in the database. The main goal of this research work is to define a set of reverse engineering procedures for spatial databases that can support either creation or evolution if conceptual GDB schemas. It is expected that these procedures can enhance the quality of GDB design as well as contribute to the popularization of GDB conceptual modeling. Three different geographic data input formats to GIS are investigated and a reverse engineering system architecture for them is proposed. Resulting conceptual (sub)schemas are based on the framework GeoFrame.

O presente trabalho apresenta um modelo computacional que visa servir de apoio ao processo de licenciamento de áreas para criação intensiva de animais. Trata-se de um modelo que descreve o comportamento do nitrogênio e do fósforo, oriundos da aplicação em solos agrícolas de dejetos da criação de animais e seu impacto nas bacias hidrográficas. Este modelo apóia-se em um Sistema de Informações Geográficas (SIG) e foi utilizado o ambiente ARCVIEW. O modelo define a quantidade de nitrogênio e de fósforo que ficam disponíveis no solo para serem arrastados pelo escoamento superficial para os corpos hídricos. Para tal, o modelo utilizará um balanço de massa destes nutrientes (entradas: por adubação orgânica, resultante dos dejetos de animais da bacia, adubação inorgânica, deposição atmosférica e fixação do nitrogênio) e (saídas: por remoção pela cultura, volatilização, desnitrificação, lixiviação e escoamento superficial). Sendo as perdas por lixiviação e escoamento superficial consideradas como as disponíveis nos solos para serem carreadas para os corpos hídricos. Em seguida o modelo define o escoamento da água pela bacia, ou seja, uma modelagem hidrológica. Finalmente, o modelo irá predizer o que resultará do transporte dos nutrientes disponíveis apoiando-se em modelagem hidrológica. O resultado disto será mostrado em um mapa de concentração acumulado ao longo da bacia. O estudo de caso será aplicado em áreas de suinocultura na bacia hidrográfica do Rio Toledo no Estado do Paraná, Brasil. Os resultados observados foram coerentes com os obtidos no monitoramento realizado em dois pontos da bacia de estudo. / This work presents a computer-programmed model, which aims to aid environmental agencies in issuing licenses regarding hog farms. It helps to describe the nitrogen and phosphorus behavior impacts in a watershed, when manure is applied in the soil. The algorithm is programmed on a Geographic Information Systems (GIS) tool ARCVIEW. The model defines the amount of nitrogen and phosphorus that remains available in the soil to be transported by runoff. The model calculates the balance of all nitrogen and phosphorus sources (organic and inorganic fertilizers, atmospheric accumulation and nitrogen fixation) and losses (plants use, volatilization and denitrification, soil lixiviation and runoff). The result of this balance is the amount of these elements available to be transported along of the watershed. A hydrological simulation model is used to calculate the runoff. The final result is a nitrogen and phosphorus concentration map, accumulated along the basin. The case study to test the model is the Toledo River, state of Paraná, Brazil due to its high concentration of hog farming. The model was able to reproduce data observed in this basin.

Projetos de SIG (Sistemas de Informação Geográfica), em geral, ainda não apresentam modelo conceitual de banco de dados geográficos. Os implementadores de SIG se preocupam com a aquisição dos dados (captura e adaptação), que é a etapa mais cara, e dão, ainda, pouca atenção à modelagem. A utilização de modelos conceituais faz com que os usuários controlem melhor sua base de dados e tirem maior proveito do SIG. O objetivo deste trabalho é definir um conjunto de procedimentos de engenharia reversa de bancos de dados espaciais que auxiliem na criação e manutenção de modelos conceituais para aplicações de SIG a partir de dados já existentes. Estes procedimentos podem contribuir para um aumento na qualidade dos SIG implementados, auxiliando na popularização da prática de modelagem conceitual de banco de dados geográficos. São estudados três formatos de transferência utilizados por usuários de SIG. A partir daí, é proposto uma arquitetura de sistema de engenharia reversa para SIG. / Even with the increasing use of Geographic Information Systems (GIS), conceptual modeling of geographic databases (GDB) is not yet usual among GIS professionals. This fact can in part be explained by the professional profile of most GIS designers. They usually are more familiar with specific GIS applications than with database technology. Among them, one can find cartographers, geographers, agricultural engineers, and architects. Besides that, the cost of geographic data acquisition is so high that much important is given to acquisition plans during GIS design and less interest is given to the database design process. Especially first time designers do not perceive the importance of a database schema that is independent of a specific GIS product. Conceptual design preserves the independence between data types and the logical schema of the product. Moreover, relying on the GDB conceptual schema users can better understand what part of the geographic reality is represented in the database. The main goal of this research work is to define a set of reverse engineering procedures for spatial databases that can support either creation or evolution if conceptual GDB schemas. It is expected that these procedures can enhance the quality of GDB design as well as contribute to the popularization of GDB conceptual modeling. Three different geographic data input formats to GIS are investigated and a reverse engineering system architecture for them is proposed. Resulting conceptual (sub)schemas are based on the framework GeoFrame.

It is well known that archaeological sites are important sources for understanding past human activity. However, those sites yet to be identified and further investigated are under a great risk of being lost or damaged before their archaeological significance is fully recognized. The aim of this research was to analyze the potential use of remote sensing and aerial archaeology techniques integrated within a geographic information system (GIS) for the purpose of remotely studying pit house archaeology. As pit house archaeological sites in North America have rarely been studied with a focus in remote sensing, this study intended to identify these features by processing very high resolution satellite imagery and assessing how accurately the identified features could be automatically mapped with the use of a GIS. A Worldview-2 satellite image of the Bridge River pit house village in Lillooet, south-central British Columbia, was processed within ArcGIS 10.1 (ESRI), ERDAS Imagine 2011 (Intergraph) and eCognition Developer 8 (Trimble) to identify spatial and spectral queues representing the pit house features. The study outlined three different feature extraction methods (GIS-based, pixel-based and object-based) and evaluated which method presented the best results. Though all three methods produced similar results, the potential for performing object-based feature extraction for research in aerial archaeology proved to be more advantageous than the other two extraction methods tested.

De senaste årens krav på hållbarhet, har tillsammans med en önskan att göra städerna renare, tystare och mer tillgängliga, resulterat i att cykeln kommit att prioriteras inom samhällsplaneringen. I syfte att främja en hållbar stadsutveckling och uppmuntra fler människor att cykla har allt fler städer valt att upprätta hyrcykelsystem. En av dessa städer är Gävle som under våren 2016 genomför en pilotstudie för att undersöka möjligheten att införa ett regionalt hyrcykelsystem riktat till pendlare. Syftet med denna studie är därför att applicera en metod för att optimera lokaliseringen av cykelstationer i ett hyrcykelsystem i Gävle. För att uppnå detta har en GIS-baserad multikriterieanalys (MKA) upprättats. Multikriterieanalysen resulterade i att ett antal platser pekades ut som lämpliga för etablering av hyrcykelsstationer. Genom vidare analys och diskussion av resultatet prioriterades antalet platser ned ytterligare. Detta mynnade ut i en rekommendation över de två lämpligaste platserna i Gävle för etablering av hyrcykelstationer. Dessa platser är Södermalm och Rådhustorget. / The desire to make our cities cleaner, quieter and more accessible has given the bicycle a higher priority in urban planning in recent years. In order to promote sustainable urban development and encourage people to cycle an increasing number of cities have chosen to set up bike-share systems. During the spring of 2016 the city of Gävle is conducting a pilot study to examine the possibility of introducing a bike-share system. The purpose of this study is therefore to apply a method to optimize the location of bike stations in a bike-share system in Gävle. To achieve this, a GIS-based multi-criteria analysis (MCA) was established. The MCA resulted in a number of sites identified as suitable for the establishment of bike-share stations. Through further analysis and discussion the number of stations was prioritized even further. This resulted in a recommendation of the two most suitable locations for establishment of bike-share stations in Gävle. These places are Södermalm and Rådhustorget.

Magister Scientiae - MSc (Environ & Water Science) / Groundwater in arid and semi-arid areas like the Karoo region of South Africa is an important source of domestic, agricultural and industrial source of fresh water. As a scarce resource, it requires extensive quality control and protection through innovative methods and efficient strategies. The town of Beaufort West and its vicinity use groundwater as a major source of municipal and private water supply. Forty nine groundwater samples were collected from spatially referenced boreholes located in and around the town of Beaufort West and were analyzed for EC, pH, TDS,TH, SAR, TA, Ca2+, Mg2+, Na+, K+, HCO3-, Cl-, NO3- and SO42- according to SANS 241 standards and tested for ionic balance. The groundwater of the study area was characterized using WHO and South African drinking water quality standards as well as TDS and Salinity hazard classifications. These comparisons and classifications characterized the groundwater of the study area as hard to very hard, with low to medium salinity hazard. These results are in accordance with the dominance of the ions Ca2+, Na+, HCO3 - and Cl- in the groundwater samples. Linear relationships between the hydrochemical variables were analysed through correlation and multiple regression analysis to relate the groundwater quality to the underlying hydrogeochemical processes. These linear relationships explained the contribution of the measured variables towards the salinity, hardness and anthropogenic contamination of the groundwater. The groundwater of the study area was also assessed using conventional trilinear diagrams and scatter plots to interpret the water quality and determine the major ion chemistry. The conventional methods highlighted the sources of the hydrochemical variables through analysis and interpretation of rock-water interaction and evaporations processes. To supplement these conventional methods and reveal hidden hydrogeochemical phenomenon, multivariate statistical analyses were employed. Factor analysis reduced the hydrochemical variables into three factors (Hardness, Alkalinity and Landuse) that characterize the groundwater quality in relation to the source of its hydrochemistry. Furthermore, combination of Cluster (CA) and Discriminant analyses (DA) were used to classify the groundwater in to different hydrochemical facies and determine the dominant hydrochemical variables that characterize these facies. The classification results were also compared with the trilinear diagrammatic interpretations to highlight the advantages of these multivariate statistical methods. The CA and DA classifications resulted in to six different hydrochemical facies that are characterized by NO3 -, Na+ and pH. These three hydrochemical variables explain 93.9% of the differences between the water types and highlight the influence of natural hydrogeochemical and anthropogenic processes on the groundwater quality. All the univariate, bivariate, multivariate statistical and conventional hydrogeochemical analyses results were analyzed spatially using ArcGIS 10.0. The spatial analysis employed the Inverse Distance Weighted (IDW) interpolation method to predict spatial distribution of unmeasured areas and reclassification of the interpolation results for classification purposes. The results of the different analyses methods employed in the thesis illustrate that the groundwater in the study area is generally hard but permissible in the absence of better alternative water source and useful for irrigation.

Landslide susceptibility maps are useful for spatial decision-making to minimize the lossof lives and properties. There are many studies related to the development of landslidesusceptibility maps using various methods such as Analytic Hierarchy Process, Weight ofEvidence and Logistic Regression. Commonly, the geospatial data required for such analysis(such as land cover and soil type maps) are only locally available and pertinent to smallcase studies. Transferable and scalable approaches utilizing publicly available, large scaledatasets (ie., global or continental) are necessary to develop susceptibility maps in areaswhere local data is not available or when large-scale analysis is required. To develop suchapproaches, a systematic comparison between locally available, fine resolution, and largerscale, openly available but coarser resolution datasets is essential. The objective of this study isto investigate the efficiency of globally available public data for landslide susceptibility mappingby comparing it with the performance of the data provided from local institutions. For this purpose, the Göta river valley in Sweden and the country of Rwanda were selectedas study areas. Göta river valley was used for the comparison of local and open data.While Rwanda was used as a study area to ensure the efficiency of open data analysis andtransferability of the framework. The selected landslide impact factors for this study are;elevation, slope, soil type, land cover, precipitation, lithology, distance to roads, and distanceto drainage network. Landslide susceptibility maps were prepared by using the state-of-the-artFrequency Ratio method. The validation results using the prediction rate curve technique show92.9%, 90.2%, and 83.1% area under curve values for local and open data analyses of Göta rivervalley and open data analysis of Rwanda country, respectively. The results show that globallyavailable open data demonstrate strong potential for landslide susceptibility mapping whenhigh-resolution local data are not available.

The design and construction of high-performance buildings have emerged as a preferred solution for reducing energy consumption and greenhouse gas emissions. However, sometimes there is a considerable gap between the design performance and the actual performance of the buildings. Post Occupancy Evaluations (POE) provide tools to quantify the performance relative to the occupant's health, well-being, and comfort. POE is getting widely accepted to obtain feedback for various parameters such as water, energy, indoor environmental quality, and occupant comfort. Key Performance Indicators (KPIs) can be derived based on the obtained feedback to determine the performance gaps. POE has evolved to be a robust scientific methodology; however, traditional methods of conducting POE have been proven time-consuming, inconsistent, and inefficient. This research aims to conceptualize the next generation of post occupancy evaluations that leverages cutting-edge technologies such as Building Information Modeling (BIM), Internet of Things based sensors (IoT), Geographic Information Systems (GIS), and digital twins. The key contributions of this research are presented in a series of manuscripts. In the first paper, the gaps in the existing POE were determined by conducting a thorough literature review. The observed gaps were classified in data collection, analysis, and visualization categories. Broader POE definition, spot measurements of parameters, and 2D plans and charts for visualization made the existing POE procedure time-consuming. Using digital twins that combine the geometric and parametric data from BIM models and built-environment data from GIS and sensor measurements were recommended as potential solutions to address the observed gaps. The second paper explored the application of BIM-IoT-GIS integration to conduct POE. Use case scenarios were developed to derive system requirements to host the BIM-IoT-GIS-integrated POE. Four sequential tests were conducted to integrate a BIM model from Revit and sensors' data from Excel with ArcGIS pro that contained the surrounding environment data. Based on lessons learned from the tests, an optimized workflow was recommended that can be used across a variety of projects. The third paper used the BIM-IoT-GIS-integration concept to create a holistic proof of concept for digital-twin-enabled POE. The proof of concept was validated by conducting a digital-twin-based POE on the STTC building on the Red River College campus in Winnipeg. The indoor thermal comfort was visualized within the STTC digital twin developed in ArcGIS Pro. The preliminary energy consumption analysis concluded that the STTC buildings' average energy savings were approximately 70,000 KWH/year. The potential users for digital-twin-enabled POE were presented with a comparison of iv existing POE and digital-twin-based POE over a survey and a focus group discussion. Based on opinion-based feedback, the conclusion can be made that digital twins improve the overall efficiency of POE. The fourth paper recommended the digital-twin-enabled POE procedure for UVic's engineering expansion project. It established the semantics for POE, followed by a digital twin execution plan that can be used for developing a digital twin during each phase (from planning to operations) of the project. Furthermore, the benefits of the digital-twin-enabled POE procedure were demonstrated by comparison with the existing POE procedure relative to the project phases. This study concluded that conducting the POE on the UVic ECS expansion project will enable the researchers to determine the effectiveness of sustainable features by comparing the performance of existing and proposed facilities. In conclusion, BIM-IoT-GIS-integrated digital twins address the limitations of data collection, analysis, and visualization. These digital twins will enable multi-objective analysis and spatial-temporal visualization and provide deeper insights into the way these high-performance buildings function. / Graduate / 2023-05-24

Aging sewer infrastructure is posing greater and greater risk to the health and well-being of City residents. Issues can range from pipe blockages in sewer laterals to Sanitary Sewer Overflows. This thesis develops a risk analysis method that can be used by municipalities to maintain and rehabilitate sewer assets. Risk combines the effect of Likelihood of Failure (LOF) and Consequence of Failure (COF) to perform a complete two-dimensional analysis that allows for relative comparison between different pipes in the system. The LOF rating has been equated to pipe integrity while the COF rating was related to the environmental, economic, and social consequences to pipe failure. In order to estimate pipe integrity Closed Circuit Television (CCTV) scores from the City of Santa Barbara were used in combination with spatial and physical properties associated with each pipe. The CCTV scores were simply integer values between 0 and 5 based on the National Association of Sewer Services Company’s (NASSCO) Pipeline Assessment Certification Program (PACP) results. The quantitative parameters included pipe material and age, distance from restaurants, distance from any above ground water source, pipe depth below the ground surface, pipe length, and vehicular traffic volumes. The sensitivity analysis compared the given structural integrity scores with the predicted scores based on the weighted scoring method. It isolated four out of six of the parameters tested that affected the structural integrity of sewer pipes: material and age (45%), pipe depth (20%), Vehicular Traffic (10%), and distance from an above-ground water source (25%). A program was created in the C programming language that iteratively determined the percentage for each factor. These percentage factors are used to obtain the predicted structural integrity score for all the pipes. Like the LOF rating, the COF rating consisted of scores between 0 and 5. The COF rating used pipe diameter, distance from commercial zones, distance from critical infrastructure, and vehicular traffic volume as parameters for quantifying the environmental, economic, and social consequences. These factors were determined from review of past literature and given approximately equal weighting when determining the COF rating values. The environmental factor, pipe diameter, was given a percentage factor of 30%; the economic factor, distance to commercial zones, was given a percentage factor of 30%; and the social concerns, distance to critical infrastructure and vehicular traffic volume, were given percentage factors of 20% each. Finally, the risk for each pipe was determined in Geographic Information Systems (GIS) by combining the predicted structural integrity score or LOF rating and COF rating value for each pipe. This generated color-coded maps that showed distinct pipes that had the most critical predicted structural integrity scores, highest consequence, and the pipes with the most risk. This process could be used by any City to create a maintenance and rehabilitation schedule and plan for future CCTV inspections.

No description available.