Evaluation of Urban Nighttime Light Environment Safety Using Integrated Remote Sensing and Perception Modeling

A well-designed nighttime lighting environment not only enhances pedestrian comfort and urban vitality but also serves as a crucial factor in creating safe and livable urban spaces. However, existing studies on pedestrian safety at night remain relatively limited both domestically and internationally, and most rely primarily on ground-based measurements, making large-scale spatial analyses difficult to achieve. This study integrates night-time remote sensing, ground measurements and perception evaluations to analyze the light environments of three public space types—roads, business districts and squares—in Dalian, China. A light environment safety perception model and corresponding map are constructed to support optimization of lighting design in urban nightscapes. The main contributions are as follows: (1) subjective and objective research conducted on the night light environment safety perception of urban public space in Dalian; (2) fitting models are developed for each space type to relate measured illuminance to perceived safety, yielding recommended ground illuminance ranges: roads (4.02–10.10 lx), business districts (5.05–38.3 lx), and squares (6.46–12.52 lx); (3) models linking nighttime radiation data to measured illuminance are established, enabling the generation of an illuminance inversion map for Dalian. Based on this, safety classification maps for roads, business districts, and squares are produced. These are integrated with the residential area safety map to form a comprehensive safety classification map of Dalian’s urban area.