Assessing the potential of urban agriculture at the community scale: Spatial heterogeneity, influencing factors, and...

Urban development faces challenges like food shortages, farmland loss, ecological degradation, and weakened community ties. Urban agriculture can help alleviate food pressure, enhance ecology, and strengthen social interactions. Communities are ideal sites for its implementation. However, existing research lacks methods for assessing urban agriculture potential at the community level, particularly when considering the full range of spatial elements, multi-scale benefits, and the spatial heterogeneity of different types of communities. Thus, our study comprehensively employs cluster analysis, three-dimensional image reconstruction, multi-criteria decision-making (MCDM) and GIS methods to evaluate urban agriculture potential across community types. The research consists of four phases: (1) Classifying community types and identifying their spatial characteristics; (2) Constructing 3D community models and extracting spatial data; (3) Developing an MCDM model to rank urban agriculture potential; (4) Analyzing the spatial heterogeneity of the potential of communities and identifying the influencing factors. Results indicate that low-density high-rise communities exhibit the strongest spatial suitability, while high-density low-rise communities score highest in sustainable potential. Overall potential is ranked in the order: low-density high-rise > high-density low-rise > large-footprint pitched-roof > old communities. Construction year is identified as a key factor leading to the superior urban agriculture potential of newly built communities compared to older ones. Building density, gross floor area, and roof slope also shape potential by affecting sunlight exposure, planting area, and accessibility. Our study further proposes planning strategies for community-based urban agriculture and differentiated urban agriculture development suggestions. We also explore the applicability of the research conclusions and the generalizability of the potential assessment method. The research offers scientific decision-making basis for urban planners, and a novel approach to potential assessment in urban agriculture.