Study on the design of old residential district landscape space renewal based on Cite Space from the perspective of big data

Abstract

With the gradual improvement of people’s living standards, the requirements for a living environment are getting higher and higher. A good landscape space can facilitate people’s life, promote people’s interaction, provide places for leisure and entertainment, etc. Therefore, it is important to study the landscape space of residential communities. In this paper, we use Cite space software to analyze the research on landscape space literature in recent years, use keyword search to analyze people’s preference and demand for landscape space in the community, and use the data mining technology of plain Bayesian model to analyze the existing facilities and functions of the old residential community, to explore people’s preference, demand for landscape space, people’s activities in landscape space and The design strategies for the renewal of landscape spaces in old neighborhoods are proposed. For different types of landscape spaces, walking activity is one of the main activities, and environmental facilities are the main influencing factor to determine the type of activity. The highest proportion of sitting facilities is 24.6%, showing that people need them first to stay in the space. The proportion of green facilities is 19.8%, indicating that a good green environment is also an important factor that people are willing to stay. The proportion of landscape and green facilities is close to each other, and the attractiveness to people is similar. Waterscape is also the form of landscape that people love. Therefore, green landscape is an important factor to be considered in the design of landscape space, followed by rest facilities. Comfortable and pleasant community landscape design can enhance the happiness of people’s lives, and the contents discussed in this paper are of great significance to the design of landscape space.

Keywords

• big data
• landscape space
• living environment
• cite space visual analysis
• landscape design
• 68t45