Economic downturn and climate change: mapping spatial heterogeneity of socio-economic vulnerability for a complex future scenario

Under compound pressures of climate change and economic downturn, cities are facing heightened vulnerability to both natural and anthropogenic disasters. While existing Chinese research focused on static vulnerability assessments during economic growth, these approaches inadequately capture emerging risks during current downturns. This study introduces a novel climate-economy dual-variable spatial response framework integrating dynamic simulation with high-resolution community-scale analysis to quantify socio-economic vulnerability under compound pressures. Using multi-source data and spatial statistical methods across Shenzhen's communities, this research presents three innovations. First, we develop a comprehensive indicator system quantifying vulnerability mechanisms by analyzing how declining economic resilience and intensifying climate exposure collectively shape spatial heterogeneity. Second, we integrate vulnerability assessment with indoor shelter layout to examine spatial correspondence between vulnerability patterns and disaster prevention resources, providing quantitative basis for assessing distributional equity in disaster resource allocation. Third, we bridge macro-micro linkages under compound pressures, providing actionable urban governance solutions. Our quantitative analysis reveals significant spatial inequities in vulnerability and disaster preparedness. The socio-economic vulnerability index ranges from −11.21 to 14.01, with 70.3 % of communities exhibiting medium-to-high vulnerability and strong spatial clustering. Indoor shelter accessibility ranges from 0 to 7.78, with 77.43 % of communities exhibiting shelter deficits averaging 480.64 people per community. Critical spatial mismatches emerge as 12.4 % of communities demonstrate high vulnerability-low accessibility risks, whereas only 6.3 % achieve low vulnerability-high accessibility advantages, revealing substantial inequities in disaster prevention infrastructure distribution. This methodology provides a universal framework for adaptive urban governance, offering measurable targets for resource allocation in high-density cities globally.