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ContributorsWard, Geoffrey Harris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-18
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Description
The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban

The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban water demand. This dissertation aims to contribute to understanding the spatio-temporal relationships between single-family residential (SFR) water use and its determinants in a desert city. The dissertation has three distinct papers to support this goal. In the first paper, I demonstrate that aggregated scale data can be reliably used to study the relationship between SFR water use and its determinants without leading to significant ecological fallacy. The usability of aggregated scale data facilitates scientific inquiry about SFR water use with more available aggregated scale data. The second paper advances understanding of the relationship between SFR water use and its associated factors by accounting for the spatial and temporal dependence in a panel data setting. The third paper of this dissertation studies the historical contingency, spatial heterogeneity, and spatial connectivity in the relationship of SFR water use and its determinants by comparing three different regression models. This dissertation demonstrates the importance and necessity of incorporating spatio-temporal components, such as scale, dependence, and heterogeneity, into SFR water use research. Spatial statistical models should be used to understand the effects of associated factors on water use and test the effectiveness of certain management policies since spatial effects probably will significantly influence the estimates if only non-spatial statistical models are used. Urban water demand management should pay attention to the spatial heterogeneity in predicting the future water demand to achieve more accurate estimates, and spatial statistical models provide a promising method to do this job.
ContributorsOuyang, Yun (Author) / Wentz, Elizabeth (Thesis advisor) / Ruddell, Benjamin (Thesis advisor) / Harlan, Sharon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsWasbotten, Leia (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-30
ContributorsZelenak, Kristen (Performer) / Detweiler, Samuel (Performer) / Rollefson, Justin (Performer) / Hong, Dylan (Performer) / Salazar, Nathan (Performer) / Feher, Patrick (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-31
ContributorsRyall, Blake (Performer) / Olarte, Aida (Performer) / Senseman, Stephen (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-30
ContributorsUhrenbacher, Tina (Performer) / Creviston, Hannah (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-31
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Description
Decision makers contend with uncertainty when working through complex decision problems. Yet uncertainty visualization, and tools for working with uncertainty in GIS, are not widely used or requested in decision support. This dissertation suggests a disjoint exists between practice and research that stems from differences in how visualization researchers conceptualize

Decision makers contend with uncertainty when working through complex decision problems. Yet uncertainty visualization, and tools for working with uncertainty in GIS, are not widely used or requested in decision support. This dissertation suggests a disjoint exists between practice and research that stems from differences in how visualization researchers conceptualize uncertainty and how decision makers frame uncertainty. To bridge this gap between practice and research, this dissertation explores uncertainty visualization as a means for reframing uncertainty in geographic information systems for use in policy decision support through three connected topics. Initially, this research explores visualizing the relationship between uncertainty and policy outcomes as a means for incorporating policymakers' decision frames when visualizing uncertainty. Outcome spaces are presented as a method to represent the effect of uncertainty on policy outcomes. This method of uncertainty visualization acts as an uncertainty map, representing all possible outcomes for specific policy decisions. This conceptual model incorporates two variables, but implicit uncertainty can be extended to multivariate representations. Subsequently, this work presented a new conceptualization of uncertainty, termed explicit and implicit, that integrates decision makers' framing of uncertainty into uncertainty visualization. Explicit uncertainty is seen as being separate from the policy outcomes, being described or displayed separately from the underlying data. In contrast, implicit uncertainty links uncertainty to decision outcomes, and while understood, it is not displayed separately from the data. The distinction between explicit and implicit is illustrated through several examples of uncertainty visualization founded in decision science theory. Lastly, the final topic assesses outcome spaces for communicating uncertainty though a human subject study. This study evaluates the effectiveness of the implicit uncertainty visualization method for communicating uncertainty for policy decision support. The results suggest that implicit uncertainty visualization successfully communicates uncertainty in results, even though uncertainty is not explicitly shown. Participants also found the implicit visualization effective for evaluating policy outcomes. Interestingly, participants also found the explicit uncertainty visualization to be effective for evaluating the policy outcomes, results that conflict with prior research.
ContributorsDeitrick, Stephanie (Author) / Wentz, Elizabeth (Thesis advisor) / Goodchild, Michael (Committee member) / Edsall, Robert (Committee member) / Gober, Patricia (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsYi, Joyce (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-22
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Description
As part of the effort to streamline management efforts in protected areas worldwide and assist accountability reporting, new techniques to help guide conservation goals and monitor progress are needed. Rapid assessment is recognized as a field-level data collection technique, but each rapid assessment index is limited to only the ecoregion

As part of the effort to streamline management efforts in protected areas worldwide and assist accountability reporting, new techniques to help guide conservation goals and monitor progress are needed. Rapid assessment is recognized as a field-level data collection technique, but each rapid assessment index is limited to only the ecoregion for which it is designed. This dissertation contributes to the existing bodies of conservation monitoring and tourism management literature in four ways: (i.) Indicators are developed for rapid assessment in arid and semi-arid regions, and the processes by which new indicators should be developed is explained; (ii.) Interpolation of surveyed data is explored as a step in the analysis process of a dataset collected through rapid assessment; (iii.) Viewshed is used to explore differences in impacts at two study sites and its underutilization in this context of conservation management is explored; and (iv.) A crowdsourcing tool to distribute the effort of monitoring trail areas is developed and deployed, and the results are used to explore this data collection's usefulness as a management tool.
ContributorsGutbrod, Elyssa (Author) / Dorn, Ronald I. (Thesis advisor) / Cerveny, Niccole (Committee member) / Whitley, David (Committee member) / Wentz, Elizabeth (Committee member) / Arizona State University (Publisher)
Created2013