Filtering by
- All Subjects: GIS
- Creators: School of Geographical Sciences and Urban Planning
Spatial-Temporal Analysis of Barrett Freshmen 2007-2012: Source Area Analysis and Poisson Regression
This thesis utilizes GIS mapping to analyze the severity of four threats: ocean acidification, sea surface temperature, artisanal fishing, and destructive fishing, in conjunction with coral species distribution. This project produced maps that depicts each of these threats and shows the distribution of its severity. Compiling this data we can see that ocean acidification is the most pressing threat in the Caribbean to coral and that neither type of fishing really has a large effect. A species named Madracis carmabi is also flagged to be of particular concern as it is severely threatened by both ocean acidification and sea surface temperature.
The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde River Watershed. This Story Map is intended for an audience of students in late middle school and early high school but can be a resource to teachers for a wider age range. The integration of interactive technology and virtual tools in educational practices is likely to continue past the immediate circumstances of the COVID-19 pandemic. The purpose of this Story Map is to showcase one of the many uses for geospatial web applications beyond the immediate realm of GIS.
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.
Universities host a large, young and diverse population that commutes to the same location every day, which makes them ideally suited for public transportation ridership. However, at many universities in the US, this potential for high levels of transit ridership is not being maximized. This research aims to identify the areas where Valley Metro’s public transit service to ASU’s Tempe campus is over- and under-performing in comparison with the overall public transportation service to the entire Phoenix metro area. The hypothesis states that proximity to campus and the convenience of using public transportation would be the two main factors in determining the success of an area’s public transportation service. ASU’s Parking & Transit Services provided confidential data with the addresses of all the students and employees who purchased a parking pass, transit pass and bike registration. With these data, the public transportation mode share for commuters to ASU in each census block group was calculated and compared to the mode share for the general public, which was based on US Census data. The difference between the public transit mode shares of ASU pass holders vs. commuting by the general public was then computed and analyzed to identify areas as hot and cold spots. These heat maps are then compared to the hypothesized factors of proximity to campus and the convenience of public transportation in terms of the light rail line, park-and-ride lots, and number of transfers needed to connect to campus. The transfers were estimated using origin and destination survey data provided by Valley Metro. Results show that the convenience of public transportation was a driving factor in explaining where the transit mode share to ASU is higher than that of the general public, whereas the proximity to campus had little impact on the areas with high ASU-specific transit mode shares. There is an absence of hot spots directly around the campus which is explained by the combination of both high transit share for the non-ASU population and the large share of ASU students and employees using active transportation and free circulator buses this close to campus. These findings are significant specifically to ASU because the university can learn where the transit service is performing well and where it is underperforming. Using these findings, ASU PTS can adjust its pricing, policies, services and infrastructure and work with Valley Metro and the City of Tempe to improve the ridership for both students and employees. Future research can compare more factors to further interpret what leads to success for transit service to university campuses.