Abstract: [Purposes] This study aims to analyze the spatial matching mechanism between the greenery coverage ratio and the green view index of urban roads,addressing the issue of volume-perception mismatch in green space layouts. [Methods] High-precision data from over 2000 roads in Beijing were acquired using a bionic visual perception survey system and high-resolution remote sensing.Pearson correlation coefficients were employed to identify the greenery response scale,and a coupling coordination degree (CCD)model was used to quantitatively evaluate the synergy between the two indicators. [Findings] ①Road GVI and GCR are significantly positively correlated,with the correlation peaking at the 10 m buffer scale,defining the core sensitivity range for visual greenery.② The city's road network overall exhibits a level of primary coordination,with distinct type-based differentiation： expressways are characterized as GVI-lagging due to shielding by elevated structures and noise barriers,while county and township roads are GCR-lagging due to limited land-use conditions,and arterial roads tend toward synergistic development.③The CCD shows significant spatial heterogeneity at the sub-district level,where multi-node areas and ecological conservation zones outperform the central city； high-density built-up environments are the core areas restricting the conversion of greenery volume into perception. [Conclusions] This research reveals the scale effects and bottlenecks in the conversion of greenery volume to visual perception,providing a scientific reference for the precision planning of garden cities and the improvement of human settlement quality．

Key words: green view index, greenery coverage ratio, coupling coordination degree, deep learning, street view imagery, Beijing built-up area