Submitted by Iryna Dronova on
The onset of climate change has increased awareness of the importance of green space in cities, which mitigate heat extremes, absorb flood waters, act as fire breaks, support urban agriculture, and provide much needed recreational space for residents. Yet, a rich literature has established not only the economic benefits of such green space, but its potential for “green gentrification,” as new investments in urban greenery increase property values and rents, thereby displacing residents. Moreover, cities often support the redevelopment of informal open space, heavily utilized by locals for community gardens, urban pathways, and sports fields, since it is considered vacant or underutilized land. Thus greening trends may exacerbite vulnerability of local residents to displacement, yet, relative importance of specific factors and specific role of green space remains insufficiently understood at regional scales relevant to development planning and climate adaptation.
This project is a "data integration" study which leverages different geospatial datasets across the broader San Francisco Bay Area, California, USA to investigate the potential influence of proximity to such space on community stability. A big component of this project is a geospatial web-based interactive map (in progress) intended to help investigate and communcate these effects and promote multi-stakeholder discussons and research adn planning initatives. This research opportunity intends to engage interested undergraduate students both in the creative development of the web tool and in the research activities and analyses around the central project questions.
This project seeks two student participants with two distinct areas of contribution. One area involves helping our research team to develop and implement the vision for the web-based geospatial tool which visualizes different spatial datasets relevant to the project and provides a user-friendly interface for data exploration and research applications. The tool is already partially developed using open-access Google Earth Engine app, and in Spring 2024 we will focus on improving its interface and its application potential to support research, planning, and decision-making.
The second area concerns spatial analyses of geographic data to assess the relationships among environmental, socioeconomic and census variables across the study region. These analyses would help uncover to what extent and in which parts of the study region urban green space may be strongly associated with socioeconomic wellbeing and vulnerability to displacement.
Area 1: Assistance with webtool research and visualization activities requires some coding in Google Earth Engine app. Programming experience with Google Earth Engine applied programming interface or Javascript, Python, and/or web-developing tools is highly desirable.
Area 2: Participation in the research analysis requires introductory-level experience in geographic information sciences (GIS) for example having completed at least one GIS or remote sensing course and experience in using software such as ArcGIS Desktop, ArcGIS Pro, QGIS or performing GIS analyses in R, Python, Matlab or similar statistical packages. Not strictly required but desirable skills include some experience in spatial statistics (e.g., spatial autocorrelation, geographically weighted regression, and similar).