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Space-time big data ( spatiotemporal big data ), big data platform , big data analytics ( big data analysis ) and big data applications ( big data application ) are important areas of general concern in recent years , related research results related to space-time big data content analysis and development opportunities , big data platform construction and data management , Big data analytics technology and data mining, big data application exploration and decision support and so on.

In the field of urban and rural landscape planning and design research, The application of spatio-temporal big data is also gradually gaining attention, Related exploratory research involves both techniques and methods for the application of big data in the field of urban and rural planning and design, Also deals with the development and education of landscape architecture in the age of big data; The scope of the research covers both large and medium scale scenic areas and urban landscape planning and design in the context of new urbanization, There are also small- and medium-scale urban green space systems that focus on user activity patterns; In particular, in the specific case of applying multiple types of spatio-temporal big data to landscape planning and design, Application of cellular signaling data、 satellite positioning navigation(GNSS) Application of data、 social network(SNS) Applications of Big Data、 Photographs of landscapes with geographical locations(geo-tagged photo) analysis, and crowd behavior patterns based on socially-aware big data(behavioral mode) analysis, All exhibit a full range of spatio-temporal big data-assisted landscape planning and design dynamics。

The emergence of big data in space-time has brought new opportunities and challenges to landscape planning and design. The opportunity is reflected in the space-time big data for us to carry out landscape planning and design provides a comprehensive, systematic and quantitative analysis and understanding of the site opportunities, especially to understand the relationship between people and the site, because the space-time big data types are diverse, rich in content, distinctive features, and the urban and rural landscape planning and design related to the space-time big data includes 2 large categories (static data and dynamic data), 12 middle classes (basic spatial data, site resource data, site facilities data, socio-economic data, environmental efficiency data, human flow statistics, Dynamic monitoring data, location communication data, network media data, social network data, swipe consumption data, activity behavior data), more than 30 small categories; Therefore, many scholars in the industry have carried out landscape planning and design discussion based on big data in time and space, covering the urban park visitor composition and activity analysis and planning design research based on mobile communication big data, the historical and cultural scenic area based on positioning navigation big data space behavior pattern analysis and planning design research, social network big data-based urban green space system analysis and park green space planning and design research, environmental perception big data-based urban ecosystem change analysis and planning management research, Research on the layout and environmental planning and design of residential buildings based on numerical simulation of big data, and street-scale landscape planning and design based on geotagged landscape photo big data.

While seeing the exploration of research results, we should also pay attention to the challenges faced by the application of spatio-temporal big data in the field of landscape planning and design, mainly in 2 aspects, one is that the access to big data is still relatively limited, a lot of landscape spatio-temporal big data is stored in the career or enterprise server, for the majority of landscape planning and design practitioners, there is no real spatio-temporal big data can be readily applied; the second is that the processing capacity of big data is still relatively limited, most landscape planning practitioners for big data analysis and application skills have not yet reached the expected level, so they are also unable to try to apply big data in the landscape planning and design research they undertake. However, for the future, the above challenges will be gradually solved, because the country has introduced the "Action Outline for Promoting the Development of Big Data", and the urban and rural landscape planning and design field has shown the following five trends in the application of spatio-temporal big data: one is the gradual construction of the ecological environment of big data application, the second is the gradual formation of the technical system of big data application, the third is the gradual growth of the human resource power of big data application, the fourth is the development of multi-source integrated innovation of big data application, and the fifth is the embodiment of the humanistic characteristics of big data application. The landscape planning and design based on spatio-temporal big data will certainly reflect the characteristics of humanism, through big data to assist in analyzing the natural, social, cultural, emotional and other multi-dimensional characteristics of people, and then through the planning and design techniques to meet the characteristics of human needs in space, time, facilities, environment and other dimensions.

Finally, I would like to thank Professor An Rong of Tsinghua University for his contribution to this topic article.

Deputy Editor-in-Chief of the Journal


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