I compared and contrasted nitrogen and phosphorus concentrations and land use differences in two oligotrophic lakes (Sooke and Shawnigan) and two meso-eutrophic lakes (St. Mary and Elk) in order to evaluate nutrient concentrations over time, and evaluate the relationship between in-lake nutrients and land use in the surrounding watershed. I used MapShed© nutrient transport modeling software to estimate the mass load of phosphorus and nitrogen to each lake, and evaluated the feasibility of land use modifications for reducing in-lake nutrients. In comparing nitrogen and phosphorus data in Sooke and Shawnigan Lakes, I determined that natural watershed characteristics (i.e., precipitation, topography, and soils) did not account for the elevated nutrient concentrations in Shawnigan verses Sooke Lake. Natural watershed characteristics indicated that external loads into Shawnigan Lake would be lesser-than or equal to those into Sooke Lake if both watersheds were completely forested. I evaluated trends of in-lake nutrient concentrations for Sooke and Shawnigan Lakes, as well as two eutrophic lakes, St. Mary and Elk. Ten to 30-year trends indicate that nitrogen and phosphorus levels in these lakes have not changed significantly over time. Time-segmented data showed that nutrient trends are mostly in decline or are maintaining a steady-state. Most nutrient concentration data are not precipitation-dependent, and this, coupled with significant correlations to water temperature and dissolved oxygen, indicate that in-lake processes are the primary influence on lake nutrient concentrations -- not external loading. External loading was estimated using, MapShed©, a GIS-based watershed loading software program. Model validation results indicate that MapShed© could be used to determine the effect of external loading on lake water quality if accurate outflow volumes are available. Based on various land-cover scenarios, some reduction in external loading may be achieved through land-based restoration (e.g., reforestation), but the feasibility of restoration activities are limited by private property. Given that most of the causal loads were determined to be due to in-lake processes, land-based restoration may not be the most effective solution for reducing in-lake nitrogen and phosphorus concentrations. / Graduate

Objectives: The description of the raccoon rabies epizootic in Virginia over fifteen years (1989-2003). Methods: Using simple statistical methods and a geographic information system (GIS)-based approach, and fifteen years worth of animal surveillance data, the progress of this epizootic has been charted in terms of the geographic spread of the disease, the major animal species affected by the disease and its spread, and the exposure and risk to humans and livestock animals presented by the expansion of the geographic range. Results: The resulting descriptive study illustrates the eastward expansion of the epizootic, the mushrooming of the disease in the northern region of the state, and the rates of rabid animal submissions for every health district and selected important animal species. Human exposures to rabid animals are mapped and compared to human population densities. Strong seasonal trends in human and livestock exposures to rabid animals are illustrated, with animal exposures predominating in the spring and autumn, while human exposures peak in the summer; also shown is the possible emergence of new strains of rabies virus and the possible extinction of the previously dominant strain. Conclusions: Some potentially positive developments have been found, such as substantially increasing levels of bat submissions across time, which may signify greater public awareness of the disease. Serious deficiencies in the monitoring system are discussed, centering on the accuracy and comparability of the data collected, and suggestions for improvement are offered. While several potentially interesting new areas of study are put forward, the standard approach to rabies control (pet vaccination and control, education of at-risk populations, orally vaccinating wild animals) is not found to be in need of significant modification, aside from the specifics of the approach being tailored to better meet local conditions.

Master of Regional and Community Planning / Department of Landscape Architecture/Regional and Community Planning / Katie Kingery-Page / Experiences in natural environments are perceived as a human necessity. Additionally, prior studies show that nature access has emotional, cognitive, and psychological benefits for children. Nature is defined as a space comprised mostly of vegetation that allows an individual to escape common surroundings. Access is defined as the ability to interact with high-quality nature by walking or biking in close proximity to one’s place of residence. This geospatial analysis employs Geographic Information Systems (GIS) technology and site analysis to assess whether or not socioeconomic factors, and their relationship to housing choice, affect a child’s access to nature. The study includes measures of socioeconomic status and how these factors influence a child’s access to nature within parks and school facilities. The results show that including qualitative factors enhances the traditional model of measuring “distance as access.” There was no inequality in access found in the study area when qualitative factors are included. The project implication is that communities can focus public resources and planning efforts in areas lacking access to nature for children. This leads to geographically less segregated neighborhoods and improved equity in nature access across a community.

Doctor of Philosophy / Department of Diagnostic Medicine/Pathobiology / K.R. Harkin / T.G. Nagaraja / Associations of land cover/land use, socio-economic and housing, and hydrological and soil-hydrological variables were evaluated retrospectively as potential risk factors for canine leptospirosis in Kansas and Nebraska using Geographic Information Systems (GIS). The sample included 94 dogs positive for leptospirosis based on a positive polymerase chain reaction test for leptospires in urine, isolation of leptospires on urine culture, a single reciprocal serum titer of 12,800 or greater, or a four-fold rise in reciprocal serum titers over a 2 to 4 week period; and 185 dogs negative for leptospirosis based on a negative polymerase chain reaction test and reciprocal serum titers less than 400. Publicly available geographic datasets representing land cover/land use, socio-economic and housing characteristics, and hydrologic and soil hydrologic themes were analyzed along with geocoded addresses of case/control locations in GIS. Among different land cover/land use variables evaluated, urban areas (high and medium intensity urban areas and urban areas in general) and evergreen forests and forest/woodlands in general were significant risk factors. Among socio-economic and demographic determinants evaluated, houses lacking complete plumbing facilities, poverty status by age (18-64), and living within 2500 meters of a university/college or parks/forests were significant risk factors. Proximity to water features, hydrologic density and frequently flooded areas were identified as significant risk factors for canine leptospirosis among hydrologic and soil-hydrologic variables. Pet owners whose dogs live in such areas or under these circumstances should consider vaccination to prevent canine leptospirosis.

Comprehensive emergency management and response is crucial for disaster prevention and health emergencies. However, in African countries with an abundance of natural disasters and a rising surge in cardiovascular and obstetric emergencies, little research exists on emergency response. This study examines the fire emergency response in Kumasi Metropolitan Assembly (KMA), Ghana's second largest city. We use Geographic Information Systems (GIS) tools including location -allocation modeling to evaluate the existing system of fire facilities, identify gaps in service, and suggest locations for new fire stations to maximize population coverage. Our results show that fire stations within KMA are poorly distributed and large portions of the metropolis are underserved, a situation that is partly responsible for the huge losses of lives and property during fire outbreaks.

Orientador: Célia Regina Lopes Zimback / Banca: Luis Gustavo Frediani Lessa / Banca: Osmar Delmanto Junior / Resumo: O estudo teve como objetivo oferecer subsídio metodológico para avaliação da favorabilidade à mecanização das terras, na sub-bacia do Rio Pariquera-Açu, no Estado de São Paulo. As classes de favorabilidade das terras à mecanização foram definidas a partir do grau de limitação (nulo, ligeiro, moderado e restrito) e pelas características diagnósticas (drenagem, textura, profundidade, e declividade). O mapa de classes de declividade foi gerado a partir da base altimétrica das cartas do Instituto Geográfico e Cartográfico de São Paulo, sendo os demais mapas foram compilados e atualizados do Banco de Dados do Sistema de Informações Geográficas do Ribeira de Iguape e Litoral Sul. Os mapas de favorabilidade foram calculados usando o Método da Combinação Linear Ponderada, combinando fatores e pesos determinados pela Técnica Participatória e pelo Processo Hierárquico Analítico. Os graus de nulo a moderado definiram as classes de I a III de favorabilidade à mecanização. A classe IV é reservada para terras com mais de 40% de declividade e áreas com restrições ambientais, sendo está definida como restrita. Com base nos resultados obtidos, concluiu-se que a Avaliação Multicritérios realizada com Sistema de Informações Geográficas, utilizando o ArcGIS 10.2, foi uma ferramenta adequada ao mapeamento das áreas à Favorabilidade à Mecanização Agrícolas e que, o Método da Combinação Linear Ponderada é flexível e fácil de ser implementado, permitindo a interação de conhecimentos interdisciplinar... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The study had as objective to offer methodological subsidies to evaluate the favorability to agricultural mechanization on lands of the sub-basin of Pariquera-Açu river, São Paulo State, Brazil. The classes of favorability of lands to mechanization were defined according by the limitation to mechanization (null, light, moderate, strong, and restric) and diagnostic characteristics (drainage, texture, depth and slope). The slope class map was made from contour data of Instituto Geográfico e Cartográfico de São Paulo, the other maps were compiled and updated from the Sistema de Informações Geográficas database. The favorability maps were calculated using the Weighted Linear Combination method, combining factors and weights determined by the Participatory Technique and the Analytical Hierarchical Process (AHP). Grades null to strong defined classes I to III of favorability to mechanization. The class IV is reserved to lands with slopes steeper than 40%. From the results it is concluded that the Multicriteria Evaluation done in a Geographic Information System using ArcGIS 10.2 proved to be an adequate tool for mapping of Favorability to Agricultural Mechanization and that the Weighted Linear Combination Method is flexible and simple to be employed, allowing interaction of interdisciplinary knowledge and land features, making efficient the decision making process. The Analytical Hierarchical Process (AHP) was the main advantage of the method employed, for using the paired comparison between factors to determine the relative influence of each one, reducing the subjectivity, contributing to the selection of areas favorable to land mechanization. / Mestre

A research report submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science (Environmental Sciences) at the School of Geography, Archaeology & Environmental Studies , Johannesburg, 2017 / There is a growing interest in the reclamation of the old gold mines’ tailings dumps in Johannesburg city region driven by the economic value of the remaining gold resource. This reclamation activity is accompanied by various rehabilitation methods to reduce issues such as acid mine drainage and wind pollution. The impact of land use and land cover change (LULCC) can have an enormous impact on land development and planning. Monitoring of LULCC is very important in the planning and decision making processes. Remote sensing (RS) as the source of basic data for monitoring change is very highly recommended as tool to monitor changes occurring in the Johannesburg City Region as a result of rehabilitation and reclamation of the gold mines’ tailings deposits. The main aim of the study is to understand how the reclamation and rehabilitation of the historical tailings dumps in Johannesburg are changing land use patterns of the city and its precincts. The objectives are to quantify the changes in land use and land cover as the results of mining rehabilitation using Landsat earth observation data over a period of 30 years at five years intervals and; to recommend on how the land cleared of waste dumps could be used for looking at the surrounding environment spatially. Various Geographical Information Systems techniques are applied here for change detection analysis and monitoring of potential changes in urban dynamics patterns. The results show rate of rehabilitation and reclamation to be slow, taking several years to see a meaningful change. There is some form of bias towards transforming the reclaimed land into industrial zones as opposed to other activities. The success of tailings dumps rehabilitation through revegetation process is highlighted. / MT 2018

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Science. Pretoria 1991. / Remote sensing can be used to produce maps of land-cover, but to be of use to the GIS community these maps must first be vectorized in an intelligent manner. Existing algorithms suffer from the defects of being slow, memory intensive and producing vast quantities of very short vectors. Furthermore if these vectors are thinned via standard algorithms, errors are introduced. The process of vectorizing raster maps is subject to major ambiguities. Thus an infinite family of vector maps ccrresponds to each raster map. This dissertation presents an algorithm for converting raster maps in a rapid manner to accurate vector maps with a minimum of vectors. The algorithm converts raster maps to vector maps using local information only, (a two by two neighbourhood). the method is "exact" in the sense that rasterizing the resulting polygons would produce exactly the same raster map, pixel for pixel. The method is "near optimal" in that it produces, in a local sense, that "exacb" vector map having the least number of vectors. The program is built around a home-grown object oriented Programming System (OOPS) for the C programming language. The main features of the OOPS system, (called OopCdaisy), are virtual and static methods, polymorphism, generalized containers, container indices and thorough error checking, The following general purpose objects are implemented with a large number of sophistiated methods :- Stacks, LIFO lists, scannable containers with indices, trees and 2D objects like points, lines etc. / AC2017

In this thesis, a method for detecting ditches using digital elevation data derived from LiDAR scans was developed in collaboration with the Swedish Forest Agency. The objective was to compare a machine learning based method with a state-of-the-art automated method, and to determine which LiDAR-based features represent the strongest ditch predictors. This was done by using the digital elevation data to develop several new features, which were used as inputs in a random forest machine learning classifier. The output from this classifier was processed to remove noise, before a binarisation process produced the final ditch prediction. Several metrics including Cohen's Kappa index were calculated to evaluate the performance of the method. These metrics were then compared with the metrics from the results of a reproduced state-of-the-art automated method. The confidence interval for the Cohen's Kappa metric for the population was calculated to be [0.567 , 0.645] with a 95 % certainty. Features based on the Impoundment attribute derived from the digital elevation data overall represented the strongest ditch predictors. Our method outperformed the state-of-the-art automated method by a high margin. This thesis proves that it is possible to use AI and machine learning with digital elevation data to detect ditches to a substantial extent.

Northeastern and mid-Atlantic United States are understudied from the perspective of hurricane vulnerability. In an attempt to fill this gap in research, this dissertation attempted to assess the hurricane vulnerability of the northeastern and mid- Atlantic United States through the construction of a Composite Hurricane Vulnerability Index (CHVI) for 184 counties extending from Maine to Virginia. The CHVI was computed by incorporating indicators of human vulnerability and physical exposure. Human vulnerability was derived from demographic, social and economic characteristics whereas physical exposure was based on attributes of the natural and built up environments. The spatial distribution of the CHVI and its component indices were examined and analyzed to meet the research goals, which were a) to develop indices of human vulnerability, physical exposure and composite hurricane vulnerability for all counties; b) to assess vulnerability distribution in terms of population size, metropolitan status (metropolitan versus non metropolitan counties) and location (coastal versus inland counties); c) to identify the specific underlying causes of vulnerability; d) to identify the significant clusters and outliers of high vulnerability; and e) to examine overlaps between high human vulnerability and high physical exposure in the region. Results indicated high overall vulnerability for counties that were metropolitan and / or coastal. Vulnerability clusters and intersections pointed towards high vulnerability in the major cities along the northeastern megalopolis, in the Hampton Roads section of Virginia and in parts of Delmarva Peninsula. Evidence of relationship of population size, metropolitan status and location with vulnerability levels provides a new perspective to vulnerability assessment. / by Shivangi Prasad. / Thesis (Ph.D.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.