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With the development of a sustainable lifestyle, people are paying more and more attention to the comfort of their own living environment, including public space lighting, which is immediately accessible to residents. The demand on its quality and comfort has thus gained attention recently. However, there is still a lack of related research on public space lighting comfort evaluation models that combine nighttime light remote sensing data and field measurement data, and link lighting attributes with the comfort of residents. This research uses nighttime light remote sensing data to select typical test areas, measures the lighting data of the survey points on the spot, develops an intelligent WeChat applet that collects public perception data, analyzes different lighting parameters, and builds a public space lighting comfort model based on the structural equation model analysis method. The results show that the factor that the areas with high light intensity are more comfortable than the areas with low light intensity. In areas with high light intensity, people pay more attention to the uniformity, security and comfort of the light, while in areas with low light intensity or high blue light, people's perception of glare will be more obvious. This research can provide a basis for the intelligent optimization of public space lighting from the perspective of public preference. [ABSTRACT FROM AUTHOR]