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Visualizing Community Changes in Belize with Qualitative Sketch Mapping

Authors: Timothy Hawthorne*, University of Central Florida, Kate Brandt, University of North Carolina-Chapel Hill, Lain Graham, University of Central Florida, Hannah Torres, Old Dominion University, Christine Munisteri, GeoJobe, Christy Visaggi, Georgia State University
Topics: Geographic Information Science and Systems, Coastal and Marine, Communication
Keywords: sketch mapping, PGIS, community GIS, citizen science, Belize
Session Type: Paper
Presentation File: No File Uploaded

Our community-based research in Belize utilizes participatory GIS (PGIS) methods to explore flooding and erosion concerns in a data-scarce context through spatial storytelling. We offer a mixed methodology, employing qualitative sketch mapping along with GIS and drone imagery as a way to collect local knowledge about community perceptions of flooding in two coastal communities in Belize. We combine this local knowledge with quantitative data collected from digitized drone imagery and terrestrial structure and road attributes collected to understand the changing landscape and residential priorities for future land use planning efforts. Such data help to understand village flood and erosion risk in relation to structures and their immediate surroundings at a village scale. The significance of our work lies in the intersection of multiple data sets, and the reality they illustrate about flooding in these data-scarce contexts. One set of data (more qualitative in nature) originated from sketch maps with community stakeholders and answers descriptive questions about how people interact with their environment and spatially conceptualize hazards. The other (more quantitative in nature) was collected and classified into objective categories for GIS analysis by our research team. Our work offers contributions to the participatory GIS literature by providing a transferable mixed methodology that is inclusive of community partners and offers a multifaceted and adapted approach to understanding flooding and disaster management in data-scarce settings.

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