Diagnosing Perception–Function Mismatches in Urban Blue–Green Infrastructure with a Dual-Track Assessment: Evidence from Suzhou, China

Urban blue–green infrastructure (GBI) spans wetlands, parks, waterways, and historic landscapes, yet ecological performance and public preference are often assessed separately. We develop a dual-track spatial framework for Suzhou, China, combining an ecosystem service balance (ESB) index based on ten indicators derived from remote sensing and InVEST with preference mapping from participatory GIS (PPGIS) and visual preference surveys (VPS; 453 valid responses). We distinguish natural GBI, GBI in semi natural settings, and GBI in artificially constructed settings, while treating blue and cultural GBI as cross-cutting themes. Because the two layers are not calibrated to a common scale, we compare percentile ranks within the common valid area (relative spatial standing, not absolute gaps) and use multinomial logit models to examine perceptual attributes associated with preferred GBI types. Under a ±30-percentile-point threshold, 22.23% of the area ranked higher on ESB, 59.98% showed relatively close ranks, and 17.80% ranked higher on preference. Higher ESB ranks clustered along the network of Lake Tai, rivers, hills, and wetlands around the urban periphery, whereas higher preference ranks were more common in cultural corridors and waterfronts in the inner city; objective advantage was most prevalent in Wujiang and preference advantage in Gusu. Rankings were consistent across KDE bandwidths of 300–800 m (Spearman’s ρ = 0.977–0.995), although hotspot overlap varied (Jaccard = 0.836–0.917). In the natural GBI choice model, social cohesion (AME = 3.88 percentage points, 95% CI 0.97–6.78) and heritage identity (AME = 4.29 percentage points, 95% CI 1.66–6.93) were positively associated with choice. The framework can inform ecological assessment at individual sites, public engagement, and planning tailored to local contexts.