Matching Items (401)
ContributorsWard, Geoffrey Harris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-18
Description
The dissertation focuses on one Truku (Indigenous) village in eastern Taiwan and aims to understand the processes and possibilities of bottom-up language revitalization. In 2012, the National Geographic Genographic Legacy Fund supported the village to start a community-driven language revitalization initiative. Drawing on scholarship guided by critical Indigenous research methodologies, critical sociocultural approaches to language policy and planning, and sociocultural approaches to learning, this study is an attempt to generate qualitative ethnographic research to facilitate local praxis. The major findings are four: Firstly, after decades of colonialism, villagers' lived experiences and language ideological standpoints vary significantly across generations and households, which constraints the possibility of collective endeavors. Secondly, building on previous scholars' emphasis on "ideological clarification" prior to language revitalization, I identify the dimension of embodied ideological differences, using cultural historical activity theory to illustrate how certain "mainstream" artifacts (e.g. orthography) can confine orally dominant elders' capacity to contribute. In a similar vein, by closely examining children's voices and language performances, I highlight children's theory of language as relationship-building and a theory of learning as participation in communities of participation, which stand in stark contrast to adult educators' constructs of acquisition and proficiency in traditional SLA. Finally, inspired by children and elders' voices, methodologically I argue for a relational conceptualization of agency and propose a relationship-oriented language revitalization framework. Such framework values and incorporates existing social relationships in praxis, and requires researchers and practitioners to humbly recognize the work of power in social relations and develop a trusting, reflective bond with the villagers before rushing to impose agendas. This dissertation contributes to the scholarship of language policy and planning by incorporating sociocultural learning theories designed to generate praxis-oriented analysis. By contextualizing identity and SLA processes in an Indigenous context, the study also illuminates the affective dimension of language learning and education. Overall this study offers valuable insights for scholars, educators, and practitioners interested in community-based language education. Equally important, this research represents the voices of multiple generations of Truku people, deeply committed to ensuring that future generations remain connected to their heritage language, knowledge system, and ways of being.
ContributorsLin, Man-chiu (Author) / Mccarty, Teresa L. (Thesis advisor) / Romero-Little, Mary Eunice (Committee member) / Swadener, Elizabeth B. (Committee member) / Davis, Kathryn A. (Committee member) / Arizona State University (Publisher)
Created2014
Description
This research investigates the relationship between municipal annexation and local government's financial condition. It addresses a significant gap in the literature by focusing on the roles of local government revenue structure and land use situations in affecting annexation's fiscal implications. The major research question is how these two categories of local circumstances affect annexation's fiscal implications, and what patterns may emerge based on the empirical evidence. With two parts of empirical analyses, I explore the features of the moderating effects of these two local circumstances: how the interactions between annexation and local circumstances influence local government's financial condition. The first part of the analyses examines the role of local government's revenue structure in affecting annexation's fiscal implications. Using a sample of more than six thousand municipalities, empirical analyses of OLS and interactive regression models show the effects of local taxing authority and revenue reliance. The second part underscores the effects of land use along with annexations in municipalities in the Phoenix metropolitan area across two decades. Utilizing GIS data for annexation and land use, it presents spatial patterns of annexation activities and land use changes. A fixed effects model with panel data is used to investigate the joint effects of annexation and land use on local government's financial condition. The complicated effects of different land use situations are identified. The findings suggest that annexation has the potential for fiscal gains to local government, but its positive fiscal effects may diminish if the municipality has less capability to make suitable revenue arrangement, and if a high proportion of land in the municipality that remains undeveloped. Above all, this research offers a comprehensive perspective regarding municipal annexation, land use and local government finance, to inform a larger debate of urban growth and local financial management.
ContributorsWang, Jing (Author) / Chapman, Jeffrey I. (Thesis advisor) / Lewis, Paul G (Committee member) / Herbst, Christopher M (Committee member) / Arizona State University (Publisher)
Created2012
Description
This study addresses the landscape connectivity pattern at two different scales. The county-level analysis aims to understand how urban ecosystem structure is likely to evolve in response to the proposed development plans in Maricopa County, Arizona. To identify the spatio-temporal land pattern change, six key landscape metrics were quantified in relative to the urban development scenarios based on the certainty of the proposed urban plans with different level of urban footprints. The effects of future development plans from municipalities on landscape connectivity were then analyzed in the scaled temporal and spatial frame to identify in which urban condition the connectivity value would most likely to decrease. The results demonstrated that tremendous amount of lands will be dedicated to future urbanization, and especially urban agricultural lands will be likely to be vulnerable. The metro-level analysis focuses on a group of species that represent urban desert landscape and have different degrees of fragmentation sensitivity and habitat type requirement. It hypothesizes that the urban habitat patch connectivity is impacted upon by urban density. Two underlying propositions were set: first, lower connectivity is predominant in areas with high urbanization cover; second, landscape connectivity will be impacted largely on the interfaces between urban, suburban, and rural areas. To test this, a GIS-based connectivity modeling was employed. The resultant change in connectivity values was examined for exploring the spatial relation to predefined spatial frames, such as urban, suburban, and rural zones of which boundaries were delineated by buffering method with two criteria of human population density and urban cover proportion. The study outcomes provide a practical guidance to minimize connectivity loss and degradation by informing planners with more optimal alternatives among various policy decisions and implementation. It also gives an inspiration for ecological landscape planning in urbanized or urbanizing regions which can ultimately leads urban landscape sustainability.
ContributorsPak, So-hyŏn (Author) / Cook, Edward (Thesis advisor) / Crewe, Katherine (Committee member) / Wu, Jianguo (Jingle) (Committee member) / Arizona State University (Publisher)
Created2011
Description
With more than 70 percent of the world's population expected to live in cities by 2050, it behooves us to understand urban sustainability and improve the capacity of city planners and policymakers to achieve sustainable goals. Producing and linking knowledge to action is a key tenet of sustainability science. This dissertation examines how knowledge-action systems -- the networks of actors involved in the production, sharing and use of policy-relevant knowledge -- work in order to inform what capacities are necessary to effectively attain sustainable outcomes. Little is known about how knowledge-action systems work in cities and how they should be designed to address their complexity. I examined this question in the context of land use and green area governance in San Juan, Puerto Rico, where political conflict exists over extensive development, particularly over the city's remaining green areas. I developed and applied an interdisciplinary framework -- the Knowledge-Action System Analysis (KASA) Framework --that integrates concepts of social network analysis and knowledge co-production (i.e., epistemic cultures and boundary work). Implementation of the framework involved multiple methods --surveys, interviews, participant observations, and document--to gather and analyze quantitative and qualitative data. Results from the analysis revealed a diverse network of actors contributing different types of knowledge, thus showing a potential in governance for creativity and innovation. These capacities, however, are hindered by various political and cultural factors, such as: 1) breakdown in vertical knowledge flow between state, city, and local actors; 2) four divergent visions of San Juan's future emerging from distinct epistemic cultures; 3) extensive boundary work by multiple actors to separate knowledge and planning activities, and attain legitimacy and credibility in the process; 4) and hierarchies of knowledge where outside expertise (e.g., private planning and architectural firms) is privileged over others, thus reflecting competing knowledge systems in land use and green area planning in San Juan. I propose a set of criteria for building just and effective knowledge-action systems for cities, including: context and inclusiveness, adaptability and reflexivity, and polycentricity. In this way, this study also makes theoretical contributions to the knowledge systems literature specifically, and urban sustainability in general.
ContributorsMuñoz-Erickson, Tischa A (Author) / Larson, Kelli L. (Thesis advisor) / Redman, Charles L. (Thesis advisor) / Miller, Clark A. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Anthropogenic land use has irrevocably transformed the natural systems on which humankind relies. Understanding where, why, and how social and economic processes drive globally-important land-use changes, from deforestation to urbanization, has advanced substantially. Illicit and clandestine activities--behavior that is intentionally secret because it breaks formal laws or violates informal norms--are poorly understood, however, despite the recognition of their significant role in land change. This dissertation fills this lacuna by studying illicit and clandestine activity and quantifying its influence on land-use patterns through examining informal urbanization in Mexico City and deforestation Central America. The first chapter introduces the topic, presenting a framework to examine illicit transactions in land systems. The second chapter uses data from interviews with actors involved with land development in Mexico City, demonstrating how economic and political payoffs explain the persistence of four types of informal urban expansion. The third chapter examines how electoral politics influence informal urban expansion and land titling in Mexico City using panel regression. Results show land title distribution increases just before elections, and more titles are extended to loyal voters of the dominant party in power. Urban expansion increases with electoral competition in local elections for borough chiefs and legislators. The fourth chapter tests and confirms the hypothesis that narcotrafficking has a causal effect on forest loss in Central America from 2001-2016 using two proxies of narcoactivity: drug seizures and events from media reports. The fifth chapter explores the spatial signature and pattern of informal urban development. It uses a typology of urban informality identified in chapter two to hypothesize and demonstrate distinct urban expansion patterns from satellite imagery. The sixth and final chapter summarizes the role of illicit and clandestine activity in shaping deforestation and urban expansion through illegal economies, electoral politics, and other informal transactions. Measures of illicit and clandestine activity should--and could--be incorporated into land change models to account for a wider range of relevant causes. This dissertation shines a new light on the previously hidden processes behind ever-easier to detect land-use patterns as earth observing satellites increase spatial and temporal resolution.
ContributorsTellman, Elizabeth (Author) / Turner II, Billie L (Thesis advisor) / Eakin, Hallie (Thesis advisor) / Janssen, Marco (Committee member) / Alba, Felipe de (Committee member) / Jain, Meha (Committee member) / Arizona State University (Publisher)
Created2019
ContributorsBolari, John (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-04
ContributorsOftedahl, Paul (Performer) / ASU Library. Music Library (Publisher)
Created2018-09-29
ContributorsMarshall, Kimberly (Performer) / Meszler, Alexander (Performer) / Yatso, Toby (Narrator) / ASU Library. Music Library (Publisher)
Created2018-09-16
Description
Large datasets of sub-meter aerial imagery represented as orthophoto mosaics are widely available today, and these data sets may hold a great deal of untapped information. This imagery has a potential to locate several types of features; for example, forests, parking lots, airports, residential areas, or freeways in the imagery. However, the appearances of these things vary based on many things including the time that the image is captured, the sensor settings, processing done to rectify the image, and the geographical and cultural context of the region captured by the image. This thesis explores the use of deep convolutional neural networks to classify land use from very high spatial resolution (VHR), orthorectified, visible band multispectral imagery. Recent technological and commercial applications have driven the collection a massive amount of VHR images in the visible red, green, blue (RGB) spectral bands, this work explores the potential for deep learning algorithms to exploit this imagery for automatic land use/ land cover (LULC) classification. The benefits of automatic visible band VHR LULC classifications may include applications such as automatic change detection or mapping. Recent work has shown the potential of Deep Learning approaches for land use classification; however, this thesis improves on the state-of-the-art by applying additional dataset augmenting approaches that are well suited for geospatial data. Furthermore, the generalizability of the classifiers is tested by extensively evaluating the classifiers on unseen datasets and we present the accuracy levels of the classifier in order to show that the results actually generalize beyond the small benchmarks used in training. Deep networks have many parameters, and therefore they are often built with very large sets of labeled data. Suitably large datasets for LULC are not easy to come by, but techniques such as refinement learning allow networks trained for one task to be retrained to perform another recognition task. Contributions of this thesis include demonstrating that deep networks trained for image recognition in one task (ImageNet) can be efficiently transferred to remote sensing applications and perform as well or better than manually crafted classifiers without requiring massive training data sets. This is demonstrated on the UC Merced dataset, where 96% mean accuracy is achieved using a CNN (Convolutional Neural Network) and 5-fold cross validation. These results are further tested on unrelated VHR images at the same resolution as the training set.
ContributorsUba, Nagesh Kumar (Author) / Femiani, John (Thesis advisor) / Razdan, Anshuman (Committee member) / Amresh, Ashish (Committee member) / Arizona State University (Publisher)
Created2016