Matching Items (6)
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Description
Droughts are a common phenomenon of the arid South-west USA climate. Despite water limitations, the region has been substantially transformed by agriculture and urbanization. The water requirements to support these human activities along with the projected increase in droughts intensity and frequency challenge long term sustainability and water security, thus

Droughts are a common phenomenon of the arid South-west USA climate. Despite water limitations, the region has been substantially transformed by agriculture and urbanization. The water requirements to support these human activities along with the projected increase in droughts intensity and frequency challenge long term sustainability and water security, thus the need to spatially and temporally characterize land use/land cover response to drought and quantify water consumption is crucial. This dissertation evaluates changes in `undisturbed' desert vegetation in response to water availability to characterize climate-driven variability. A new model coupling phenology and spectral unmixing was applied to Landsat time series (1987-2010) in order to derive fractional cover (FC) maps of annuals, perennials, and evergreen vegetation. Results show that annuals FC is controlled by short term water availability and antecedent soil moisture. Perennials FC follow wet-dry multi-year regime shifts, while evergreen is completely decoupled from short term changes in water availability. Trend analysis suggests that different processes operate at the local scale. Regionally, evergreen cover increased while perennials and annuals cover decreased. Subsequently, urban land cover was compared with its surrounding desert. A distinct signal of rain use efficiency and aridity index was documented from remote sensing and a soil-water-balance model. It was estimated that a total of 295 mm of water input is needed to sustain current greenness. Finally, an energy balance model was developed to spatio-temporally estimate evapotranspiration (ET) as a proxy for water consumption, and evaluate land use/land cover types in response to drought. Agricultural fields show an average ET of 9.3 mm/day with no significant difference between drought and wet conditions, implying similar level of water usage regardless of climatic conditions. Xeric neighborhoods show significant variability between dry and wet conditions, while mesic neighborhoods retain high ET of 400-500 mm during drought due to irrigation. Considering the potentially limited water availability, land use/land cover changes due to population increases, and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.
ContributorsKaplan, Shai (Author) / Myint, Soe Win (Thesis advisor) / Brazel, Anthony J. (Committee member) / Georgescu, Matei (Committee member) / Arizona State University (Publisher)
Created2014
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Description

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat

Context:
With rapidly expanding urban regions, the effects of land cover changes on urban surface temperatures and the consequences of these changes for human health are becoming progressively larger problems.

Objectives:
We investigated residential parcel and neighborhood scale variations in urban land surface temperature, land cover, and residents’ perceptions of landscapes and heat illnesses in the subtropical desert city of Phoenix, AZ USA.

Methods:
We conducted an airborne imaging campaign that acquired high resolution urban land surface temperature data (7 m/pixel) during the day and night. We performed a geographic overlay of these data with high resolution land cover maps, parcel boundaries, neighborhood boundaries, and a household survey.

Results:
Land cover composition, including percentages of vegetated, building, and road areas, and values for NDVI, and albedo, was correlated with residential parcel surface temperatures and the effects differed between day and night. Vegetation was more effective at cooling hotter neighborhoods. We found consistencies between heat risk factors in neighborhood environments and residents’ perceptions of these factors. Symptoms of heat-related illness were correlated with parcel scale surface temperature patterns during the daytime but no corresponding relationship was observed with nighttime surface temperatures.

Conclusions:
Residents’ experiences of heat vulnerability were related to the daytime land surface thermal environment, which is influenced by micro-scale variation in land cover composition. These results provide a first look at parcel-scale causes and consequences of urban surface temperature variation and provide a critically needed perspective on heat vulnerability assessment studies conducted at much coarser scales.

ContributorsJenerette, Darrel G. (Author) / Harlan, Sharon L. (Author) / Buyantuev, Alexander (Author) / Stefanov, William L. (Author) / Declet-Barreto, Juan (Author) / Ruddel, Benjamin L. (Author) / Myint, Soe Win (Author) / Kaplan, Shari (Author) / Li, XiaiXiao (Author)
Created2015-10-19
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Description

This study examines the impact of spatial landscape configuration (e.g., clustered, dispersed) on land-surface temperatures (LST) over Phoenix, Arizona, and Las Vegas, Nevada, USA. We classified detailed land-cover types via object-based image analysis (OBIA) using Geoeye-1 at 3-m resolution (Las Vegas) and QuickBird at 2.4-m resolution (Phoenix). Spatial autocorrelation (local

This study examines the impact of spatial landscape configuration (e.g., clustered, dispersed) on land-surface temperatures (LST) over Phoenix, Arizona, and Las Vegas, Nevada, USA. We classified detailed land-cover types via object-based image analysis (OBIA) using Geoeye-1 at 3-m resolution (Las Vegas) and QuickBird at 2.4-m resolution (Phoenix). Spatial autocorrelation (local Moran’s I ) was then used to test for spatial dependence and to determine how clustered or dispersed points were arranged. Next, we used Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data acquired over Phoenix (daytime on 10 June and nighttime on 17 October 2011) and Las Vegas (daytime on 6 July and nighttime on 27 August 2005) to examine day- and nighttime LST with regard to the spatial arrangement of anthropogenic and vegetation features. Local Moran’s I values of each land-cover type were spatially correlated to surface temperature. The spatial configuration of grass and trees shows strong negative correlations with LST, implying that clustered vegetation lowers surface temperatures more effectively. In contrast, clustered spatial arrangements of anthropogenic land-cover types, especially impervious surfaces and open soil, elevate LST. These findings suggest that city planners and managers should, where possible, incorporate clustered grass and trees to disperse unmanaged soil and paved surfaces, and fill open unmanaged soil with vegetation. Our findings are in line with national efforts to augment and strengthen green infrastructure, complete streets, parking management, and transit-oriented development practices, and reduce sprawling, unwalkable housing development.

ContributorsMyint, Soe Win (Author) / Zheng, Baojuan (Author) / Talen, Emily (Author) / Fan, Chao (Author) / Kaplan, Shari (Author) / Middel, Ariane (Author) / Smith, Martin (Author) / Huang, Huei-Ping (Author) / Brazel, Anthony J. (Author)
Created2015-06-29
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Description

Preventing heat-associated morbidity and mortality is a public health priority in Maricopa County, Arizona (United States). The objective of this project was to evaluate Maricopa County cooling centers and gain insight into their capacity to provide relief for the public during extreme heat events. During the summer of 2014, 53

Preventing heat-associated morbidity and mortality is a public health priority in Maricopa County, Arizona (United States). The objective of this project was to evaluate Maricopa County cooling centers and gain insight into their capacity to provide relief for the public during extreme heat events. During the summer of 2014, 53 cooling centers were evaluated to assess facility and visitor characteristics. Maricopa County staff collected data by directly observing daily operations and by surveying managers and visitors. The cooling centers in Maricopa County were often housed within community, senior, or religious centers, which offered various services for at least 1500 individuals daily. Many visitors were unemployed and/or homeless. Many learned about a cooling center by word of mouth or by having seen the cooling center’s location. The cooling centers provide a valuable service and reach some of the region’s most vulnerable populations. This project is among the first to systematically evaluate cooling centers from a public health perspective and provides helpful insight to community leaders who are implementing or improving their own network of cooling centers.

ContributorsBerisha, Vjollca (Author) / Hondula, David M. (Author) / Roach, Matthew (Author) / White, Jessica R. (Author) / McKinney, Benita (Author) / Bentz, Darcie (Author) / Mohamed, Ahmed (Author) / Uebelherr, Joshua (Author) / Goodin, Kate (Author)
Created2016-09-23
Description

En la zona metropolitana de Phoenix, el calor urbano está afectando la salud, la seguridad y la economía y se espera que estos impactos empeoren con el tiempo. Se prevé que el número de días por encima de 110˚F aumentará más del doble para el 2060. En mayo de 2017,

En la zona metropolitana de Phoenix, el calor urbano está afectando la salud, la seguridad y la economía y se espera que estos impactos empeoren con el tiempo. Se prevé que el número de días por encima de 110˚F aumentará más del doble para el 2060. En mayo de 2017, The Nature Conservancy, el Departamento de Salud Pública del condado de Maricopa, Central Arizona Conservation Alliance, la Red de Investigación en Sostenibilidad sobre la Resiliencia Urbana a Eventos Extremos, el Centro de Investigación del Clima Urbano de Arizona State University y el Center for Whole Communities lanzaron un proceso participativo de planificación de acciones contra el calor para identificar tanto estrategias de mitigación como de adaptación a fin de reducir directamente el calor y mejorar la capacidad de los residentes para lidiar con el calor. Las organizaciones comunitarias con relaciones existentes en tres vecindarios seleccionados para la planificación de acciones contra el calor se unieron más tarde al equipo del proyecto: Phoenix Revitalization Corporation, RAILMesa y Puente Movement. Más allá de construir un plan de acción comunitario contra el calor y completar proyectos de demostración, este proceso participativo fue diseñado para desarrollar conciencia, iniciativa y cohesión social en las comunidades subrepresentadas. Asimismo el proceso de planificación de acciones contra el calor fue diseñado para servir como modelo para esfuerzos futuros de resiliencia al calor y crear una visión local, contextual y culturalmente apropiada de un futuro más seguro y saludable. El método iterativo de planificación y participación utilizado por el equipo del proyecto fortaleció las relaciones dentro y entre los vecindarios, las organizaciones comunitarias, los responsables de la toma de decisiones y el equipo núcleo, y combinó la sabiduría de la narración de historias y la evidencia científica para comprender mejor los desafíos actuales y futuros que enfrentan los residentes durante eventos de calor extremo. Como resultado de tres talleres en cada comunidad, los residentes presentaron ideas que quieren ver implementadas para aumentar su comodidad y seguridad térmica durante los días de calor extremo.

Como se muestra a continuación, las ideas de los residentes se interceptaron en torno a conceptos similares, pero las soluciones específicas variaron entre los vecindarios. Por ejemplo, a todos los vecindarios les gustaría agregar sombra a sus corredores peatonales, pero variaron las preferencias para la ubicación de las mejoras para dar sombra. Algunos vecindarios priorizaron las rutas de transporte público, otros priorizaron las rutas utilizadas por los niños en su camino a la escuela y otros quieren paradas de descanso con sombra en lugares clave. Surgieron cuatro temas estratégicos generales en los tres vecindarios: promover y educar; mejorar la comodidad/capacidad de afrontamiento; mejorar la seguridad; fortalecer la capacidad. Estos temas señalan que existen serios desafíos de seguridad contra el calor en la vida diaria de los residentes y que la comunidad, los negocios y los sectores responsables de la toma de decisión deben abordar esos desafíos.

Los elementos del plan de acción contra el calor están diseñados para incorporarse a otros esfuerzos para aliviar el calor, crear ciudades resilientes al clima y brindar salud y seguridad pública. Los socios de implementación del plan de acción contra el calor provienen de la región de la zona metropolitana de Phoenix, y se brindan recomendaciones para apoyar la transformación a una ciudad más fresca.

Para ampliar la escala de este enfoque, los miembros del equipo del proyecto recomiendan a) compromiso continuo e inversiones en estos vecindarios para implementar el cambio señalado como vital por los residentes, b) repetir el proceso de planificación de acción contra el calor con líderes comunitarios en otros vecindarios, y c) trabajar con las ciudades, los planificadores urbanos y otras partes interesadas para institucionalizar este proceso, apoyando las políticas y el uso de las métricas propuestas para crear comunidades más frescas.

ContributorsMesserschmidt, Maggie (Contributor) / Guardaro, Melissa (Contributor) / White, Jessica R. (Contributor) / Berisha, Vjollca (Contributor) / Hondula, David M. (Contributor) / Feagan, Mathieu (Contributor) / Grimm, Nancy (Contributor) / Beule, Stacie (Contributor) / Perea, Masavi (Contributor) / Ramirez, Maricruz (Contributor) / Olivas, Eva (Contributor) / Bueno, Jessica (Contributor) / Crummey, David (Contributor) / Winkle, Ryan (Contributor) / Rothballer, Kristin (Contributor) / Mocine-McQueen, Julian (Contributor) / Maurer, Maria (Artist) / Coseo, Paul (Artist) / Crank, Peter J (Designer) / Broadbent, Ashley (Designer) / McCauley, Lisa (Designer) / Nature's Cooling Systems Project (Contributor) / Nature Conservancy (U.S.) (Contributor) / Phoenix Revitalization Corporation (Contributor) / Puente Movement (Contributor) / Maricopa County (Ariz.). Department of Public Health (Contributor) / Central Arizona Conservation Alliance (Contributor) / Arizona State University. Urban Climate Research Center (Contributor) / Arizona State University. Urban Resilience to Extremes Sustainability Research Network (Contributor) / Center for Whole Communities (Contributor) / RAILmesa (Contributor) / Vitalyst Health Foundation (Funder)
Created2022
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Description
Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of

Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of GIScience and data-driven geography. As a highly-utilized function of GeoAI technique, deep learning models designed for processing geospatial data integrate powerful computing hardware and deep neural networks into various dimensions of geography to effectively discover the representation of data. However, limitations of these deep learning models have also been reported when People may have to spend much time on preparing training data for implementing a deep learning model. The objective of this dissertation research is to promote state-of-the-art deep learning models in discovering the representation, value and hidden knowledge of GIS and remote sensing data, through three research approaches. The first methodological framework aims to unify varied shadow into limited number of patterns, with the convolutional neural network (CNNs)-powered shape classification, multifarious shadow shapes with a limited number of representative shadow patterns for efficient shadow-based building height estimation. The second research focus integrates semantic analysis into a framework of various state-of-the-art CNNs to support human-level understanding of map content. The final research approach of this dissertation focuses on normalizing geospatial domain knowledge to promote the transferability of a CNN’s model to land-use/land-cover classification. This research reports a method designed to discover detailed land-use/land-cover types that might be challenging for a state-of-the-art CNN’s model that previously performed well on land-cover classification only.
ContributorsZhou, Xiran (Author) / Li, Wenwen (Thesis advisor) / Myint, Soe Win (Committee member) / Arundel, Samantha Thompson (Committee member) / Arizona State University (Publisher)
Created2019