# A Digital Framework to Predict the Sunshine Requirements of Landscape Plants
## 1 Introduction  
The world's urbanization prospects show that more people live in urban areas, with 55% of the world's population residing in urban areas in 2019, and by 2050, 68% of the world's population is projected to be urban [1]. This trend requires cities to provide more green spaces and welfares for recreation, relaxation, and leisure [2, 3]. At the same time, urban problems and challenges, such as the excessive size, overcrowding, and the shortage of urban infrastructure, which follow the process of urbanization should also be taken seriously [4, 5, 6]. Numerous studies have demonstrated that the contribution of plants to the urban environment is extensive and far-reaching, as plants play an important role in biodiversity conservation [7, 8], improving microclimates [9, 10, 11], relieving air pollution [12, 13], enhancing aesthetic value [14], and even influencing the psychological behavior of city dwellers [15, 16]. However, urban managers, urban forestry and landscape scientists are more concerned with the sustainable selection and cultivation of plants [17, 18, 19], these corebenefits not only have advantages in planting and management costs, but the eco-functions are also dependent on their survival, growth, development and reproduction [20, 21]. Therefore, the concept of \"the right tree in the right place\" in the field of forestry was advocated by foresters in the early stages and was used for the basis of plantation management [22], its main technique focuses on the matching of site soil types and tree species. In recent years, urban greening and forestry as the habitats for dweller have received increasing attention. Summarizing relevant research shows that plant selection in urban areas is limited by more stress factors, such as soil, drought, sunshine, climate, air pollution, pests, and diseases [23, 24, 25, 26, 27]. In North America, researchers such as the University of Minnesota Extension Department have raised concerns about the adaptability of urban plants, and provided suggestions for tree selection, and aiming to improve the adaptability of plants to the city [28]. Similarly, in studies of Utah [29] and Michigan [30], scholars also explored the adaptation of plant species to local environmental conditions. Solar radiation, in particular, is considered to be an important decision factor for plant selection. In addition, the variation of sunshine is also very obvious in urban built-up areas, due to the buildings and terrain [31]. Therefore, for urban greening, how to select adaptive plants more intelligently based on their ecological habits has become a research focus and challenge [19, 21, 32, 33]. The requirement for solar radiation is a genetic feature for a specific plant, although it may change in different environments and growth periods [34, 35]. In other words, the demand for solar radiation in plant species is also the type of ecological tolerance or the ecological amplitude. For example, a literature reveals the light and soil conditions impact on the ecological behavior of deciduous hardwood trees in Sweden [36], the results found that Fraxinus excelsior and Ulmus glabra are highly tolerant of shade. The researchers found that the shade tolerance of three tree species has variability [37], and others achieve similar results [38]. It can be seen that the sunshine tolerance for plants is a complex and important research content. Back to the field of landscape architecture, the basic data of landscape plants with regard to solar radiation response act as the key information for the practice of \"right plants in the right place\", especially for the database construction of decision support systems used for the sustainable selection of trees and shrubs [19, 21, 32]. In reality, the light compensation point (LCP) and light saturation point (LSP) are the common indicators used to determine the shade tolerance of landscape plants [39, 40, 41]. The LCP is the amount of light intensity on the light curve where the rate of photosynthesis exactly matches the rate of respiration.