Evaluation Method of Street Green Landscape Viewing Degree Based on Machine Learning - Tieming Wang; Mengyu Liu; Wenhua Huang (International Transactions on Electrical Energy Systems)
Urban streetscape is a complex and multifaceted landscape system, which is an important part of urban public space system. With the acceleration of the urbanization process, the connotation of street landscape is becoming more and more abundant. It not only has natural and social attributes but also bears the function of protecting the urban ecological environment. However, in recent years, due to the dramatic increase in the size of the urban population, more and more problems have appeared in urban road landscape. To this end, relevant government departments continue to update the design of urban streets and accelerate the construction of urban street landscapes, but urban streets still have problems in terms of function and environment. The viewing degree of street green landscape is also less and less in line with people’s aesthetic needs, which is difficult to meet people’s life and spiritual needs. In order to change this situation, this paper combined machine learning with the evaluation method of street green landscape viewing degree and conducted experiments on it based on machine learning. The experimental results showed that the evaluation method of street green landscape viewing degree based on machine learning not only made the city more beautiful but also improved the ecological environment of the city. The air quality of the city was improved by 20.96%, which was supported and loved by the general public.