UCGIS I-GUIDE 2022-2023 Community Champions Cohort
UCGIS I-GUIDE Community Champions expand the community reach of I-GUIDE. They participate directly with I-GUIDE's activities and contribute to outreach as we pursue a range of broad impacts. The vision is that these individuals would each propose to work on a small-scale project of their own design that would align with that year's proposed I-GUIDE focal areas. For Year 2 of the project (October 1, 2022 - September 30, 2023), the focus of the Community Champions’ work will have direct relevance for the I-GUIDE Convergence Curriculum for Geospatial Data Science.
Curriculum Evaluation for Convergent Geospatial Education
Lecturer, Department of Earth, Geographic, and Climate Sciences
University of Massachusetts
The domain intersections within geospatial data science – geography, GIS, data science, and computer science, among other domains – create educational gaps where students or instructors lack context necessary for cross-disciplinary learning. In degree programs, this might be a 'prerequisite' problem, in courses, insufficient scaffolding or course structure, and in lessons, inappropriate assumptions about what students 'get' or 'know' coming into a lecture or activity. Curriculum efforts at many scales need to clarify knowledge expectations, lest many people with many knowledge gaps find themselves unable to have a common conversation. This work will create an evaluation template for curriculum materials based on the intersections between the foundational knowledge threads in the I-GUIDE Convergent Curriculum Design. This tool would serve as a multi-scale means of reviewing materials for content, connecting potential knowledge gaps where learners do not have sufficient prior knowledge, and help chain together materials collected, built, or supported in future efforts.
Developing an Open Educational Content for the Application of Geospatial Data Science in Climate Change and Food Insecurity
Postdoctoral Associate, Department of Human Ecology
Food insecurity and climate change are among the most serious challenges of our time. According to the 2022 Global Food Policy Report, the current food system is responsible for more than one third of total anthropogenic emissions. Hence, targeting the reduction of greenhouse gas emission throughout the food system should be a priority in mitigation efforts. On the other hand, climate change is impacting food security throughout the entire food system, starting from production, to transportation, storage, and consumption. Increasing the temperature, anomalies in rain and more frequent and severe droughts and floods are some examples of climate change induced phenomena that impacts the food system.
Considering the availability of publicly available climate change data, spatial software, and the power of spatial analysis, this project aims to provide an open access educational material that will assist educators and students (undergraduates and graduates) to explore the interactions between climate change and food security from a food system perspective.
Big Data and GeoAI for Urban Planning: Current Practices and Future Prospects
Assistant Professor, Department of Landscape Architecture and Regional & Community Planning
Kansas State University
Despite the broader availability of urban big data and recent developments in Geospatial Artificial Intelligence (GeoAI), urban planning practices are still highly dependent on traditional GIS applications using authoritative data. With big data, urban systems can be visualized and analyzed across multiple spatial and temporal scales, which can help to evaluate the efficacy of different planning regulations. GeoAI provides the analytical tools for harnessing urban big data and can help address our urban systems’ pressing societal, ecological, and economic challenges. In this project, I will develop lesson modules on big geospatial data and GeoAI that can be incorporated into GIS courses for urban planning students and professionals. Current practices of big data and GeoAI applications in planning will be examined, which will contribute to curriculum development. Such lesson modules can help planners better understand the potential of big data and GeoAI applications in urban planning practices.