Filtering by
- All Subjects: Climate Change
- Creators: School of Sustainability
- Creators: Middel, Ariane
- Resource Type: Text
- Status: Published
This study seeks to determine the role of land architecture—the composition and configuration of land cover—as well as cadastral/demographic/economic factors on land surface temperature (LST) and the surface urban heat island effect of Phoenix, Arizona. It employs 1 m National Agricultural Imagery Program data of land-cover with 120mLandsat-derived land surface temperature, decomposed to 30 m, a new measure of configuration, the normalized moment of inertia, and U.S. Census data to address the question for two randomly selected samples comprising 523 and 545 residential neighborhoods (census blocks) in the city. The results indicate that, contrary to most other studies, land configuration has a stronger influence on LST than land composition. In addition, both land configuration and architecture combined with cadastral, demographic, and economic variables, capture a significant amount of explained variance in LST. The results indicate that attention to land architecture in the development of or reshaping of neighborhoods may ameliorate the summer extremes in LST.
The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.
This thesis will examine possible connection points between the health of a local environmental/climate news ecosystem and that local community’s belief in and vulnerability to the effects of climate change in Central Appalachia and Northern Virginia. The three counties that will be studied in Virginia are Arlington, Buchanan and Wise Counties. This research will be mainly a hypothesis-generating descriptive analysis of data, coupled with both interviews with researchers and local experts, in addition to observations from relevant literature about the possible connections between availability of environmental news with climate change, institutional belief and climate vulnerability data. The local history of resource extraction will also be explored. The point of this thesis is not to prove that a lack of access to strong, locally focused climate and environmental news increases vulnerability to the effects of climate change (although it does raise this as a possibility). Rather, it is to continue a conversation with journalists, media professionals and climate professionals about how to approach understanding and engaging groups left out of the climate conversation and groups who've been traditionally underserved by news media when it comes to climate information and appeals for institutional trust. This conversation is already happening, especially when it comes to the importance of the health of local, community focused news in general in Appalachia, but given the urgency and scale of the climate crisis, merits continuation and some inquiry into environmental news.
Climate change is impacting fisheries through ecological shifts altering the geographical distribution and quantity of fish species. About 60% of United States fish caught by volume is caught in the Alaska region, with Alaska's economy dependent on fisheries. Additionally, fisheries are an important source of employment for many Alaskan communities. Therefore, it is important to have policies and strategies in place to prepare for ongoing climate impacts. One step to support better tailoring policy to support those most likely to be negatively impacted is to identify the fishing communities most vulnerable to climate change. This study uses data on vulnerable fish species and fishery catch by species and community to identify what communities are most vulnerable to changing climate conditions. I identify 26 communities that are fishing climate vulnerable species. I then use vulnerable fish species revenue data to identify communities most at risk either because they generate a substantial amount of revenue from these species or a substantial proportion of their total revenue is derived from these species. Using species-specific revenue, I show that Sablefish contribute the most to this vulnerability.