Visualizing evaluation model of human perceptions and characteristic indicators of landscape visual quality in urban green spaces by using nomograms

Understanding human perceptions and quantifying parameters that characterize landscape visual quality in an urban green space is important to describe these connections. Within this environment, the association between human perceptions of landscape visual quality (LVQ) have long been of interest to a wide variety of fields. Previous studies have relied on formulas which did not include a direct-viewing and visible information to predict human perceptions of the LVQ of urban green space. In this work, 300 photos of urban green space were taken and evaluated for LVQ by a questionnaire to obtain scores for six human perceptions (e.g., Beauty, Color, Depression, Complex, Safety, and Liveliness). Each photo presents an urban green space landscape and 28 characteristic indicators were identified to explain LVQ. We used logistic regression to identify indicators and Nomograms to display the relationship between characteristic indicators and human perceptions. Different from other formula-based models, the contribution of characteristic indicators on LVQ were clearly and visually expressed by Nomogram. In visualizing the study results with Nomogram, the 28 characteristic indicators were identified with their relationship to each of the six perceptions and the weight of each indicator could be displayed by the length of line. The study also showed that Tree health and Neatness contributed to all human perceptions. Specifically, Tree health affects Beauty, Complex and Liveliness most, while Color contrast has the greatest influence on Color. Recreation Road ratio is the most important factor for Depression and Safety. In practical application for urban designers and planners, the Nomogram results can quickly illustrate the influence of characteristic indicators on the changing of LVQ in urban green space.