Change Is Hard: Understanding Neighborhood Context and Socio-ecological Change with Time-series Remote Sensing
dc.contributor.author | Endsley, Kevin | |
dc.date.accessioned | 2019-10-01T18:24:05Z | |
dc.date.available | NO_RESTRICTION | |
dc.date.available | 2019-10-01T18:24:05Z | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/151453 | |
dc.description.abstract | Quality of life in urban areas is strongly linked to land use and land cover, in part because green vegetation mitigates much of the negative consequences of urbanization and population pressures. However, the green vegetation of urban parks, forests, street trees, and landscaping is inequitably distributed in the urban environment. The social and economic processes that give rise to these uneven outcomes are not well-understood, while the rise in the availability of spatially explicit, fine-scale data on neighborhood conditions has created the conditions for an empirically rich investigation into neighborhood socio-ecological change. This dissertation assimilates new observations from different sources with new modes of inquiry to address persistent knowledge gaps: the dependence of socio-ecological relationships on scale and urban or metropolitan context; understanding the duration and significance of neighborhood improvement or decline; and the outstanding need for comparative analyses and novel analytical techniques for comparing neighborhood change between multiple metropolitan areas. Time-series satellite remote sensing of 30 years of vegetation cover is combined with population and housing market data to provide a comprehensive picture of the neighborhood environmental quality, demographic composition, and housing stock conditions. Three different metropolitan areas, Detroit, Los Angeles, and Seattle, are used to elucidate how our common assumptions of socio-ecological relations---and the underlying analytical approaches in which remote sensing plays a pivotal role---often fail to accurately capture the complexities and contradistinctions in the social and economic drivers of neighborhood-level biophysical changes. Results indicate that while population decline confounds conventional explanations for socio-economic differences in environmental quality, neighborhood advantages and disadvantages persist for multiple decades, with wealthier neighborhoods tending to resist cyclical declines in the housing market and accrue yet higher home values while preserving and increasing vegetated cover through irrigation and likely several policy tools. Historical conditions, particularly racial residential segregation, also yield surprising outcomes today, in some places reducing vegetation disparities and exacerbating them in others, depending on metropolitan-level population pressures and the balance of municipal political economies. | |
dc.language.iso | en_US | |
dc.subject | neighborhood change | |
dc.subject | vegetation | |
dc.subject | cities | |
dc.subject | urban | |
dc.subject | urbanization | |
dc.subject | land cover | |
dc.title | Change Is Hard: Understanding Neighborhood Context and Socio-ecological Change with Time-series Remote Sensing | |
dc.type | Thesis | |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Natural Resources & Environment | |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | |
dc.contributor.committeemember | Brown, Dan | |
dc.contributor.committeemember | Newell, Josh | |
dc.contributor.committeemember | Bruch, Elizabeth Eve | |
dc.contributor.committeemember | Currie, William S | |
dc.contributor.committeemember | Verma, Manish | |
dc.subject.hlbsecondlevel | Natural Resources and Environment | |
dc.subject.hlbtoplevel | Science | |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/151453/1/endsley_1.pdf | |
dc.identifier.orcid | 0000-0001-9722-8092 | |
dc.identifier.name-orcid | Endsley, K. Arthur; 0000-0001-9722-8092 | en_US |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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