A community-scale diagnostic framework for assessing green space cooling access for heat-vulnerable older adults

Urban heat adaptation requires spatially explicit information on whether ecological cooling capacity is aligned with populations experiencing greater heat-related need. However, green-space assessments often examine thermal performance, vulnerable populations, and accessibility separately, limiting their value as integrated climate-service diagnostics. This study develops an exposure–vulnerability–accessibility (E–V–A) framework that links heterogeneous green-space cooling supply, heat-related cooling need, and potential accessibility, and demonstrates it in Wuhan's main urban area. Summer heat exposure intensified from 2016 to 2024. The LST contrast between green spaces and their surroundings flattened after approximately 120 m and approached background conditions at 330–360 m; 300 m was therefore used as a representative cooling-performance reference rather than a service radius. Cooling accessibility was highly uneven, with lower values in dense central communities. Twenty-seven communities exhibited high heat exposure, high demographic vulnerability, and low cooling accessibility; 26 of these were classified into the highest diagnostic priority tier (P1). Overall, the framework provides a potentially transferable community-scale diagnostic for identifying spatial mismatches between ecological cooling capacity and heat-related need and for guiding subsequent local adaptation appraisal. Practical Implications . The E–V–A framework translates community-scale heat exposure, demographic vulnerability, green-space cooling performance, and cooling accessibility into differentiated diagnostic priorities. Its practical value lies in moving beyond green-space quantity alone: communities with similar levels of green-space provision may face very different cooling-access conditions because of differences in thermal performance, demographic vulnerability, spatial separation, and competition among potential beneficiaries. The P1–P4 classification therefore helps identify where further local assessment is most warranted, while the underlying E–V–A configuration indicates which dimension or combination of dimensions contributes to a community's disadvantage. Candidate adaptation options can be considered in relation to the underlying E–V–A configuration. For P1 communities, where high exposure, high vulnerability, and low accessibility converge, further local assessment may consider combinations of stronger local cooling provision and age-sensitive heat-health support. For P2 communities, assessment can be differentiated according to the dominant two-dimensional configuration: HE–HV communities may warrant consideration of heat-mitigation and health-protection measures; HE–LA communities may warrant assessment of exposure reduction together with improvements in the amount, thermal effectiveness, or spatial availability of nearby cooling supply; and HV–LA communities may warrant consideration of more proximate and age-accessible cooling opportunities together with targeted support for older residents. Where local assessment confirms physical access barriers, pedestrian connectivity or entrance improvements may also be considered. P3 communities may warrant preventive and lower-intensity measures, including neighborhood greening, shaded resting spaces, heat-risk communication, and periodic reassessment, whereas P4 communities generally warrant routine monitoring and maintenance rather than immediate detailed intervention appraisal. The framework is intended to support urban planning and green-space management agencies, district and community administrations, public health agencies, and climate-service providers. Planning agencies can use the diagnostic priority maps to identify locations where further assessment of green-space investment, park upgrading, neighborhood-scale cooling measures, or heat-health responses may be warranted. Public health agencies can use the exposure, vulnerability, and priority layers to identify communities that may require closer attention in heat-warning, temporary cooling, or outreach programs for older residents, while local administrations can use E–V–A configurations to identify the dominant dimension or combination of dimensions associated with each community's disadvantage. Overall, the framework provides a practical basis for differentiated adaptation planning by identifying both where further assessment is most warranted and which E–V–A dimensions should be considered in that assessment. The assessment can be updated as new summer thermal imagery, demographic data, or green-space inventories become available, with an annual update providing a practical cycle where sufficiently current data are available. Uncertainty should be communicated through input-data timing and provenance, modeling assumptions, and sensitivity to alternative parameter settings, with communities whose classifications are more sensitive to alternative parameter settings identified for additional local assessment.