Spatial decision analysis reveals geographic gaps in community garden access across urban census tracts, indicating a need to pair spatial models with local participatory planning.
highlights: • Socioeconomic, logistical, and environmental variables were integrated into a MCDA model. • High-suitability tracts showed some clustering in Hillsborough and Pinellas Counties. • Moderate alignment was found between existing gardens and modeled suitability in Tampa Bay. • Both the utility and limits of spatial models in equitable urban agriculture planning were shown. abstract: Community gardens offer important benefits for food access, environmental justice, and social infrastructure, especially in rapidly developing cities. This study develops an equity-focused, GIS-based multi-criteria decision analysis (MCDA) model to assess community garden suitability across census tracts in Hillsborough and Pinellas Counties, Florida. Socioeconomic, accessibility, and environmental variables were combined into a 0–1 suitability score using an equity-first weighting scheme that prioritizes neighborhoods with higher food access burdens. Rankings were tested against alternative weighting scenarios; Spearman’s correlations showed highly consistent results. Overall, suitability was moderate to high across most of the region, with clusters of high-scoring tracts in northern and eastern Tampa. Existing gardens were significantly more likely to be located in higher-suitability tracts, yet many top-ranked tracts remain without gardens, indicating that past development is only partially aligned with modeled need. These findings highlight both the value and limitations of spatial decision-support tools: they can identify priority areas and make normative assumptions explicit but cannot capture parcel-level constraints or on-the-ground dynamics. The study offers a transferable framework for using equity-focused GIS-based MCDA as an initial screening tool, to be complemented by qualitative engagement and participatory planning when making final siting decisions.
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Jaryd Hinch (2026) studied this question.
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