Against the national backdrop of actively responding to population aging, this chapter takes Chongqing as a case study to systematically analyze the spatial pattern of the elderly population and the supply-demand relationship of institutional elderly care resource allocation. Based on data including population, elderly care institutions, road networks, and administrative divisions, the chapter first outlines the spatial distribution of aging rates and elderly population density: the degree of aging presents a “low–high–low” regional gradient (lowest in the central urban area, higher in the new main city zones and Northeast Chongqing, and secondary in Southeast Chongqing), while elderly population density decreases outward from the central urban area. Second, the chapter examines the differences in resource supply in terms of the number of institutions, structural scale, and bed allocation per thousand elderly: although institutions are concentrated in the central urban area, the per capita bed supply is lower than the “9073” standard; the new main city zones have the highest total but the lowest per capita allocation; the Northeast area has the best overall total and per capita allocation but with internal disparities; the Southeast area has the fewest and most scattered institutions. Finally, the chapter applies the bivariate Moran’s I to assess supply-demand matching and finds a coexistence of high–high, low–low clusters and mismatches such as “high elderly density–low beds” (high-low) and “low elderly density–high beds” (low-high). Among these, the metropolitan core is mainly characterized by low–high mismatches, while high–low and low–low mismatches are more prominent in Northeast and Southeast Chongqing. This study provides diagnostic insight and data support for subsequent accessibility evaluations and layout optimization, highlighting the need to tailor interventions to local conditions by addressing per capita bed shortages, narrowing regional disparities, and improving supply-demand alignment.