NIEMBY- Neighborhood Infrastructure-Equity in my Backyard: Research & Engagement through GIS

Keywords: infrastructure equity, GIS
Session Type: Virtual Paper
Day: Saturday
Session Start / End Time: 4/10/2021 04:40 PM (Pacific Time (US & Canada)) - 4/10/2021 05:55 PM (Pacific Time (US & Canada))
Room: Virtual 20

Abstract

Using large datasets of spatial data and machine learning, in connection with a new data engine, Clowder, we documented conditions of twelve specific infrastructure systems in Dallas neighborhoods, then integrated that information with demographic data to discover that low income communities, and communities of color are more likely to be have several deficient infrastructures. We defined ‘infrastructure deserts’ as low-income neighborhoods that severely lack such infrastructure. To further understand the impacts of infrastructure deficits on communities, we developed systems for collaboration with high schools teachers to engage students in gathering community-level data and participating in geospatial research. We’re trying to find out if, and how, these infrastructure deficiencies impact on the way that these communities function, and grow, and which deficiencies have most impact on people’s lives. A Storymap and embedded spatial survey offered an immersive experience to showcase the project using collected data through a series of interactive maps, allowing local high-school students to (during COVID) to learn about, and add to the university research project, sharing data and their perspectives. Further, these students were simultaneously trained in the use of such GIS tools to add to their own STEM school-based projects. https://arcg.is/1i9qCX [arcg.is]