Identification of Citizen Preferences for Ecological and Spatial Features of Stream Waterfronts

Public demand for ecologically healthy rivers and water-friendly spaces has grown over time, increasing the need for planning and application at the regional scale. Accordingly, incorporating citizens’ needs into management plans has become increasingly important. This study aimed to identify citizens’ preferences for the ecological and spatial features of stream waterfronts. We conducted a survey using 30 images of stream waterfronts that are open access, asking respondents to rate each image on a 7-point scale (1 = very low to 7 = very high). A total of 235 responses were collected. The evaluation features were selected based on findings from previous monitoring studies. In addition, generative AI (ChatGPT 5.2) was used to generate representative stream waterfront images reflecting the observed feature preferences (e.g., best case vs. worst case). Further studies for enhancing the training process by revising the criteria and adding more images are required. The results are expected to support stream waterfront design and discharge management by linking these preferences with holistic planning approaches.