Enhancing the “feel-good” factor of urban vegetation using AI and street view images

Osaka, Japan – The benefits of urban green spaces in cities, in terms of ecological sustainability, climate modification, and human well-being, have been known for decades. More recently, additional economic and restorative payoffs from diverse and colorful plantings have been recognized. Now, a research team from Japan has developed a new method to identify vegetation color, structure, and seasonal changes in urban settings.

In a study published in Landscape Ecology, researchers at The University of Osaka reveal an innovative approach to capture seasonal changes in urban plant species. This method combines artificial intelligence (AI) techniques and street view imagery to allow planners to improve the visual appeal of urban green spaces throughout the year.

“Diversity, in both plant color and species, seems to enhance the ‘feel-good’ factor of urban green space for city residents and visitors,” says Anqi Hu, lead author of the study. “Our aim was to develop a method to visualize urban vegetation configuration and seasonality in much greater detail than before.”

The method integrates AI in the form of deep learning and 3D reconstruction technology with street view imagery, which significantly improves the accuracy and consistency of urban vegetation analysis. The effectiveness of the technology was tested on streets in Suita City, Osaka Prefecture, and applied to a virtual park design.

The Seasonal Species-Specific Plant View Index can distinguish between 51 urban plant species with an average accuracy of 82.17%. Plants with highly seasonal visual impacts such as cherry blossoms in spring and maple leaves in autumn can be singled out. This level of detailed modeling and identification is almost impossible with conventional green view analysis.

“Our approach removes the distortion and gaps in coverage from street view images, allowing the automatic generation of standardized viewpoints in space and over time,” explains senior author Tomohiro Fukuda. “The technique will assist in the restoration of brownfield sites or improve existing parks using a diversity of plant shapes, colors, and growth patterns.”

The framework offers a new perspective on 4D urban design and forms a foundational technology to support future urban green space evaluation and planning.

“Urban planners can extend the economic, ecological, and well-being benefits of vegetation using a range of plants that add pops of color and interest throughout the year,” says Hu.

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The article, “Multi-temporal analysis of urban vegetation using deep learning and 3D reconstruction", has been published in Landscape Ecology at DOI: https://doi.org/10.1007/s10980-025-02090-4.

About The University of Osaka

The University of Osaka was founded in 1931 as one of the seven imperial universities of Japan and is now one of Japan's leading comprehensive universities with a broad disciplinary spectrum. This strength is coupled with a singular drive for innovation that extends throughout the scientific process, from fundamental research to the creation of applied technology with positive economic impacts. Its commitment to innovation has been recognized in Japan and around the world. Now, Osaka University is leveraging its role as a Designated National University Corporation selected by the Ministry of Education, Culture, Sports, Science and Technology to contribute to innovation for human welfare, sustainable development of society, and social transformation.

Website: https://resou.osaka-u.ac.jp/e