Artificial intelligence-based landscape planning and management of smart city landscapes and gardens

A new method based on artificial intelligence technology is proposed to achieve the planning and management of landscape gardens in smart cities. The new method uses improved adversarial generative network and machine learning method to enhance the effect of landscape garden planning and management. Among them, the training and analysis of landscape garden images is achieved by improved adversarial generative network to enhance the image realism, and the machine learning method is used to maintain and filter the analysis of vegetation in landscape garden schemes. The results of the study show that the landscape garden images processed by the improved adversarial network have a lower FID value of 10 and a higher IS value of 3.4 than those processed by the traditional method, and the highest assessment score of landscape gardens planned by AI technology can reach 94, which is 22 points higher than that of the single-method planning. This shows that the use of AI technology can achieve the planning and management of landscape principles. This is a good reference value for improving the planning effect of landscape gardens.

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Publication Details

Published
2025-06-18
DOI
https://doi.org/10.1117/12.3073364
Primary Topic
Smart Cities and Technologies
Type
article
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Artificial intelligence-based landscape planning and management of smart city landscapes and gardens

Yong Han, Xinhui Li
Smart Cities and Technologies
article

Artificial intelligence-based landscape planning and management of smart city landscapes and gardens

Yong Han, Xinhui Li
article en

Abstract

A new method based on artificial intelligence technology is proposed to achieve the planning and management of landscape gardens in smart cities. The new method uses improved adversarial generative network and machine learning method to enhance the effect of landscape garden planning and management. Among them, the training and analysis of landscape garden images is achieved by improved adversarial generative network to enhance the image realism, and the machine learning method is used to maintain and filter the analysis of vegetation in landscape garden schemes. The results of the study show that the landscape garden images processed by the improved adversarial network have a lower FID value of 10 and a higher IS value of 3.4 than those processed by the traditional method, and the highest assessment score of landscape gardens planned by AI technology can reach 94, which is 22 points higher than that of the single-method planning. This shows that the use of AI technology can achieve the planning and management of landscape principles. This is a good reference value for improving the planning effect of landscape gardens.

Chongqing Vocational Institute of Engineering (CN), China National Petroleum Corporation (China) (CN)
Sustainable cities and communities
Openalex Percentile: Top 81%
Smart Cities and Technologies
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