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Browsing College of Science by Author "Agouris, Peggy"
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Item A Photogrammetric Approach for Geopositioning OpenStreetMap Roads(2013) Canavosio-Zuzelski, Roberto; Canavosio-Zuzelski, Roberto; Agouris, PeggyAs open source volunteered geographic information continues to gain popularity, the user community and data contributions are expected to grow, e.g. CloudMade, Apple, and Ushahidi now provide OpenStreetMapĀ© (OSM) as a base layer for some of their mapping applications. This, coupled with the lack of cartographic and data quality standards and the expectation to one day be able to use this vector data for more geopositionally sensitive applications, like GPS navigation, leaves potential users and researchers to question the accuracy of the database. This research takes a photogrammetric approach to determining the positional accuracy of OSM road features using stereo imagery and a vector adjustment model. The method applies rigorous analytical measurement principles to compute accurate real world geolocations of OSM road shape points. After adjustment, the absolute positional accuracy of a road vector can be described by the Root Mean Square Error (RMSE) value of the shape point residuals. In addition, adjusted shape point locations and the statistical confidence in those positions (CE/LE 90) are computed. It is also suggested that once this information is known about the vector data, it should be carried along with and recorded as an attribute at the feature level, thereby providing useful provenance and increasing the overall utility of the database.Item Accuracy and Completeness as Measures of the Quality of Volunteered Point-Feature Geospatial Data and Evaluation of the Effect of Demographics on that Quality(2014-05) Mullen, William F.; Mullen, William F.; Agouris, PeggyOver the last several years there has been a tremendous growth in the generation of Volunteered Geographic Information (VGI) data. The assessment of the quality and accuracy of VGI contributions, and by extension the ultimate utility of VGI data has fostered much debate within the geographic community. The limited research on quality of VGI has predominately focused on linear feature elements, such as road segments or points resulting from intersections of such linear segments, has shown that error within the data is heterogeneously distributed. Additionally, several studies have suggested that the quality of VGI is impacted by demographic information such as population density or the socio-economic characteristics of an area.Item Analyzing Contribution Patterns of Volunteered Geographic Point Features in Relation to Errors and Demographics(2014-05) Jackson, Steven Patrick; Jackson, Steven Patrick; Agouris, PeggyThis dissertation explores the relationship between the contribution patterns of volunteered geographic point features in relation to error and demographic properties. Recent research on Volunteered Geographic Information (VGI) has asserted that a correlation exists between population density and data quality. Others have shown that the relationship may be more complicated than population density alone. Within this research, an algorithm is developed to compare two datasets with each other to analyze the spatial accuracy and completeness. The algorithm is developed in Python so that it can be implemented as a tool within the ArcGIS framework. Datasets from the United States federal government and the volunteered geographic community are used to examine accuracy and completeness for schools within a study area in the Denver, Colorado area. In an effort to extend the research to include more points, the study area is then extended to include OpenStreetMap geographic point features across the state of Colorado. The larger dataset was used to conduct an analysis of the relationship between contribution patterns and demographic data. While this research failed to confirm the assertion by others that a relationship exists between data quality and demographics properties; however, this research furthers the understanding of patterns of volunteered geographic point feature contribution, error, and the relationship with demographics. Furthermore, analyses of the results of this research indicate that a relationship may exist that is more complicated than demographics alone and provides some suggestions for additional research areas that may be pursued to better understand the relationship.