Abstract

This community‐based research aims to enhance local‐level flood management by utilising participatory geographic information systems (PGIS) methods to capture the spatial dimensions of community member flooding concerns in Hopkins Village, Belize. We offer a mixed methodology, applying participatory sketch mapping as a way to collect local knowledge about community perceptions of flooding in this data‐scarce context. We combine this local knowledge with quantitative geostatistical hot spot analysis of basic village infrastructure characteristics to reveal insights about community perceptions of and response to flood risk. The significance of this research lies in the application of PGIS methods to create two different primary datasets, which when analysed together offer a more complete story about community understanding and needs for flood management. One set of data (more qualitative in nature) originated from sketch maps with community members and answers descriptive questions about how people spatially conceptualise hydro‐meteorological hazards within their community. The other (more quantitative in nature) is the village's first publicly accessible infrastructure dataset (including information on building structures, roads, and drainage infrastructure) digitised by our research team from high‐resolution drone imagery. Attributes for the infrastructure dataset were developed in collaboration with community members to reflect their desires for data and information suited to conduct flood vulnerability assessment. Application of thematic coding and hot spot analysis to the data reveals concerns about hazards within their community and the measures they have taken to protect themselves in the absence of resources to develop community‐wide mitigation plans. Our work offers contributions to the participatory GIS literature by providing an example of sketch mapping methods to facilitate multi‐level management of community‐level flood risk in a data‐scarce setting, and demonstrating the multiple benefits of applied participatory GIS methods as a means of overcoming data scarcity.

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