Sustainable Urban Green Blue Space (UGBS) and Public Participation: Integrating Multisensory Landscape Perception from Online Reviews

The integration of multisensory-based public subjective perception into planning, management, and policymaking is of great significance for the sustainable development and protection of UGBS. Online reviews are a suitable data source for this issue, which includes information about public sentiment, perception of the physical environment, and sensory description. This study adopts the deep learning method to obtain effective information from online reviews and found that in 105 major sites of Tokyo (23 districts), the public overall perception level is not balanced. Rich multi-sense will promote the perception level, especially hearing and somatosensory senses that have a higher positive prediction effect than vision, and overall perception can start improving by optimizing these two senses. Even if only one adverse sense exists, it will seriously affect the perception level, such as bad smell and noise. Optimizing the physical environment by adding natural elements for different senses is conducive to overall perception. Sensory maps can help to quickly find areas that require improvement. This study provides a new method for rapid multisensory analysis and complementary public participation for specific situations, which helps to increase the well-being of UGBS and give play to its multi-functionality.

Automated summary

The integration of multisensory-based public subjective perception into planning, management, and policymaking is important for the sustainable development and protection of urban green and blue spaces (UGBS). Online reviews provide suitable data for this issue, and this study uses deep learning to extract effective information from online reviews. The study finds that the overall public perception level of 105 major sites in Tokyo is unbalanced, and optimizing hearing and somatosensory senses can improve overall perception. The study also highlights the importance of optimizing the physical environment by adding natural elements for different senses and using sensory maps for identifying areas that require improvement.