Environmental Landscape Design Based on Artificial Intelligence and Digital Space Technology

Abstract

In order to improve the effect of future environmental landscape design, this study combines artificial intelligence technology and digital space technology to construct an environmental landscape design system. Moreover, this study uses polygons to model external landscape plants instead of modeling the microelement structure of landscape plants and re-polygonize them, which simplifies the model structure of landscape plants and improves computational efficiency. In addition, this study conducts collision detection in the growth of landscape plants to make it more realistic and more efficient and studies and analyzes the digital construction of landscape plants. Finally, after constructing an intelligent system, the effect of the system in this study is verified. Through data analysis, it can be seen that the environmental landscape design system based on artificial intelligence and digital space technology proposed in this study has good digital space structure expression effect and design effect.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

Since the 21st century, in the context of rapid urbanization, modern communities have developed rapidly. At the same time, with the increasing improvement of people’s living standards, the requirements for the living quality of modern communities and the design of landscape space are gradually changing. In the traditional concept of modern community, the occupants are more about the needs of indoor space, but the outdoor landscape space is only an accessory of the residential environment and has not received enough attention. However, at present, more attention has been paid to the landscape layout, greening, activity space, and other elements in the residential area from the pure residential needs to now. The landscape space design tends to be people oriented and pays attention to the actual needs of the occupants. When the classic landscaping techniques are widely copied, the landscape space design no longer meets the needs of the residents, so a new style of landscape space design is needed [1].

In the design of modern community landscape space, to a large extent, there is a lack of thinking about different groups of people of different ages, and only some activity equipment is arranged in the local space of the residential area. Moreover, it does not start from the actual physical and psychological needs of children, adults, and the elderly to study their needs for external landscape space and activity venues and ignores human nature [2]. According to the actual needs, the modern community landscape space design emphasizes the people-oriented landscape outdoor space with strong functionality. While satisfying the visual beauty, it needs to accommodate the needs of people’s behavior, safety, practicality and other elements. However, some current landscape space designs tend to focus on the pros and cons of visual effects, pursuing exaggerated and novel landscape effects, but neglecting to meet the most basic functional needs [3]. It is embodied in the large cost of creating sculptures, landscape walls, landscape pavilions and other expensive garden pieces, too much hard pavement, and a large number of advanced building materials and lighting to replace the natural landscape. At the same time, it blindly pursues a large-scale and luxurious pattern and ignores elements such as spatial scale, style, and culture.

The outdoor environment of the newly built community is set up with a large area of green space, large-scale water features, and sketches of various shapes. However, while the community landscape is becoming more and more beautiful, the setting of functional venues is becoming more and more unreasonable; the venue is not only of a single type but has also a low utilization rate, and the activity facilities have been neglected all the year round and become decorations. The irrationality of the landscape space design is also reflected as follows: the rest seats are located on both sides of the garden road, and the residents are constantly disturbed by pedestrians when they are sitting and chatting; the morning exercise area is too close to the residential area, which interferes with the residents’ rest; the activity venue is set in the back side with less sunlight in winter, etc.

In daily life, in addition to indoors, community residents spend more leisure activities in outdoor landscape public spaces. Then, the landscape design of public space should return to the use of residents, pay attention to the needs of people, and consider from the perspective of humanity. Thinking of humanistic care, such as the use of polished surfaces to pave the floor in the elderly activity space for the sake of beauty, some venues in the whole area do not consider barrier-free design, there are certain obstacles to the entry of the venue, and there is also a lack of corresponding handrail design, there is a situation where people and vehicles are mixed in the activity space, which brings a certain degree of safety to people’s activities, there is no nursing area in the children’s activity area, and adults who take care of children have nowhere to sit, etc. These are all without human nature in the planning and design errors caused by thinking.

2. Related Work

There are few special studies on five-dimensional landscapes. Das and Das [4] propose five-dimensional landscapes. The first four dimensions are space and time. The fifth dimension in the environment is defined as sound, and the visual landscape is extended to the auditory landscape. Emotional capacity: Ramsey and Malcolm [5] define that the five-dimensional landscape should be based on three-dimensional so that the landscape appreciation can be expressed in the time dimension, and at the same time, the element of ecological civilization can be reflected in the landscape design, so as to finally achieve the overall harmonious landscape between man and nature. The five-dimensional landscape mentioned in [6] is a kind of landscape that guides the invisible by improving the local space energy and guiding the energy of human emotions. According to the methodology of five-dimensional landscape design, the study divides it into two directions, spatial energy and emotional energy, describes them in detail, and refines the classification of landscape elements into shape, color, sound, light, wind, space, heat, and climate. Feng Shui et al. connect with traditional landscape design and explain the entry point for the integration of these classifications and landscape. Abreu et al. [7] carried out the landscape planning and design of residential areas from five perspectives, ecology, health, blending, refined architecture, and humanities. Through network tweets, their actual cases are explained from the above five perspectives; the content is easy to understand, but the deep theoretical knowledge is not explained.

González Díaz et al. [8] describe different preferences through the semantic difference method and analyze the factors that affect the visual quality of landscape. Pinto-Correia et al. [9] analyzed the GIS data of visual elements to obtain the visual quality evaluation. With the deepening of GIS application in the analysis of visual elements, the comprehensive visualization and dynamic simulation of the landscape based on GIS technology can be realized. Yi et al. [10] introduced ArcGIS to highway landscape evaluation. Through data collection, selection of evaluation indicators, establishment of evaluation system, and establishment of evaluation model on ArcGIS development platform for data processing, it solved the problem of low evaluation efficiency of traditional evaluation methods and poor consideration of indicators. The problem of comprehensiveness and inability to conduct comprehensive evaluation on a large scale provides a reference for the formulation of environmental protection norms along the highway and the planning and construction of highway landscapes. Antic et al. [11] used the geographic information system (GIS) technology to process and analyze the graphics and data and combined with the principles of landscape ecology, the forest landscape in the study area was divided into secondary landscape element type groups according to the type of landscape land and dominant tree species, and the distribution of the affected landscape was analyzed and factors were related in forest management planning.

Cecchini et al. [12] found that the eye movement characteristics are related to the viewing of urban greening landscapes. For landscapes with high viewing, the subjects’ fixation time increased, the number of fixations increased, and the average saccade amplitude decreased; the fixation points were concentrated in certain areas of interest. And invest more fixation time and longer fixation duration. Kaindoa et al. [13] introduced the concept of “ecological visual design” into the green vision rate; Hulko and Hovanes [14] combined the research on country parks and took the green vision rate as one of the seven secondary evaluation factors to study the impact evaluation of the visual landscape of Beijing country parks.

Eye-tracking technology has undergone a long development process before it has gradually matured. The eye-tracking method has gone through three stages: manual observation recording, mechanical observation recording, and optical recording [15]. Ferretti and Gandino [16] recorded eye movement data by manual observation. This kind of research is only based on gaze time, blink frequency and timing, etc., so the results are often greatly affected by the environment. de Waroux et al. [17] take the cultural background as a research point and analyze the differences in picture characteristics and subjects’ racial eye movements, and the pictures are divided into natural, artificial environments, and high and low arousal. Keane and Chen [18] explained the theory of space syntax and put the theory into practice. Based on the configuration in the space syntax, it explains the theory and method of space syntax and the progress of practical application and also analyzes various space divisions and variable parameter values. Chen et al. [19] pointed out that architectural space and urban space layout have an impact on human behavior and activities. The influence of the mode and intensity of social interaction, the application of space in the form, and function of houses and cities are studied.

3. Environmental Landscape Modeling Technology

This study analyzes the environmental landscape design through digital modeling technology.

The Bernstein basis function and the Bezier curve have a great origin. It can even be said that the process of obtaining the Bezier curve is generated by interpolating the Bezier control points on the basis of the Bernstein basis function. This process can be explained by formula (1) as follows:$$\begin{array}{}\text{(1)}& pt={\displaystyle \sum _{i=0}^n{B}_{i,n}}t{P}_{i}t\in \text{0,}1.\end{array}$$

Among them, the control point of the Bezier curve is represented by $P_i$, and the Bernstein basis function is represented by $B_i,nt$, where n represents the order of the Bernstein basis function is the nth order.

In general, a Bezier curve with only two control points is a first-order Bezier curve, and the common expression is$$\begin{array}{}\text{(2)}& pt={\displaystyle \sum _{i=0}^1{P}_i{B}_{i,1}t}=P_1{B}_{\mathrm{1,1}}tt\in \mathrm{0,1}=1-t{P}_0+t{P}_1=t1\begin{array}{cc}-1& 1\\ 1& 0\end{array}\begin{array}{c}{P}_0\\ P_1\end{array}.\end{array}$$

In this case, the representation of the Bezier curve in the image is generally a straight line with two control points as endpoints, as shown in Figure 1(a).

[figure(s) omitted; refer to PDF]

A quadratic Bezier curve generally has three Bezier control points, and its common expression formula is as$$\begin{array}{c}\text{(3)}& pt={\displaystyle \sum _{i=0}^2{P}_i{B}_{i,2}t}=P_0{B}_{\mathrm{0,2}}t+P_1{B}_{\mathrm{1,2}}t+P_1{B}_{\mathrm{2,2}}t,={1-t}^2{P}_0+2t1-t{P}_1+t^2{P}_2,=\begin{array}{ccc}{t}^2& t& 1\end{array}-\begin{array}{ccc}1& -2& 1\\ -2& 2& 0\\ 1& 0& 0\end{array}\begin{array}{c}{P}_0\\ P_1\\ P_2\end{array}.\end{array}$$

The control polygons of this Bezier curve are usually triangles, and the shape of the curve in the coordinate system is shown in Figure 1(b).

Similar to the first-order Bezier curve and the second-order Bezier curve, the third-order Bezier curve usually has four control points, and the formula is shown as$$\begin{array}{c}\text{(4)}& pt={\displaystyle \sum _{i=0}^3{P}_i{B}_{i,3}}t=P_0{B}_{\mathrm{0,3}}t+P_1{B}_{\mathrm{1,3}}t+P_2{B}_{\mathrm{2,3}}t+P_3{B}_{\mathrm{3,3}}t\\ ={1-t}^3{P}_0+3t{1-t}^2{P}_1+2t^{2}1-t{P}_2+t^3{P}_3\\ =\begin{array}{cccc}{t}^3\hfill & t^2\hfill & t\hfill & 1\hfill \end{array}\begin{array}{cccc}-1& 3& -3& 1\\ 3& -6& 3& 0\\ -3& 3& 0& 0\\ 1& 0& 0& 0\end{array}\begin{array}{c}{P}_0\hfill \\ P_1\hfill \\ P_2\hfill \\ P_3\hfill \end{array}.\end{array}$$

The graphical representation of the cubic Bezier curve is shown in Figure 1(c):

Affine transformation invariance of parameters: the variable parameter t in the Bezier method varies in the range [0, 1]. However, sometimes it is necessary to perform interval transformation. If the parameter u ∈ [a, b] is used to correspond to a point on the Bezier curve, the relationship between these two parameters can be expressed by$$\begin{array}{}\text{(5)}& t=\frac{u-a}{b-a}.\end{array}$$

It can be seen from this formula that the change of parameter u from a to b is completely equivalent to the change of t from 0 to 1.

Convexity: when the variable parameter t ∈ [0, 1], for a certain value of t, the coordinate position of the control point $Pt$ is a weighted sum of each vertex of the Bezier curve control polygon. The weights of this weighted sum are the terms of the n-order Bernstein basis function. In other words, all existing points on the Bezier curve are within the convex hull formed by the Bezier curve control points themselves.

Bezier surfaces are extended from Bezier curves. After we briefly introduce some definitions and some important properties of Bezier curves, we can continue to introduce Bezier surfaces. In the same way, to gather the control points of the Bezier surface, we connect the adjacent control points with line segments in sequence. The mesh thus formed is the Bezier control mesh, which acts similarly to the Bezier control polygon.

If $m\times n$ point $P_{ij}$ is known in the space as a control point, then we set$$\begin{array}{}\text{(6)}& p_{m-1,n-1}u,v={\displaystyle \sum _{i=0}^{m-1}{\displaystyle \sum _{j=0}^{n-1}{B}_{i,m-1}u{B}_{j,n-1}v{P}_{ij}}}.\end{array}$$

Among them, i is an integer from 0 to m − 1 and j is an integer from 0 to n − 1. The Bezier surface P represented by formula (6) is uniquely determined by m × n surface control points, and $B_{i,m}u$ and $B_{j,n}v$ in the above formula are two Bernstein basis functions of different orders.

The environmental landscape includes leaves that are curved, soft, and symmetrical. After observing the real leaves of the environmental landscape, this study decided to use the geometric model to model and simulate the leaves of the environmental landscape. At the same time, according to the characteristics of the leaves and the good control ability of the Bezier surface in terms of integrity, we decided to use the Bezier surface to model the geometric model of the environmental landscape leaves. Bezier surfaces are similar to Bezier curves, and Bezier surfaces are generally considered to be extensions of Bezier curves. We complete the modeling of environmental landscape leaves by controlling and adjusting the control points of the bicubic Bezier surface, as shown in Figure 2. The bicubic Bezier surface for blade modeling is defined as$$\begin{array}{}\text{(7)}& p_{\mathrm{3,3}}u,v={\displaystyle \sum _{i=0}^3{\displaystyle \sum _{j=0}^3{B}_{i,3}u{B}_{j,3}v{P}_{ij}}.}\end{array}$$

[figure(s) omitted; refer to PDF]

Among them, i and j are integers from 0 to 3. The bicubic Bezier surface p is uniquely determined by $4\times 4$ surface control points, and $P_{ij}$ is the control vertex. $B_{i,3}u$ and $B_{j,3}v$ in the above formula are two Bernstein basis functions of different orders.

It is uniformly modeled using four bicubic Bezier surfaces, and the four bicubic surfaces Q are defined as in equation (8), as shown in Figure 3.$$\begin{array}{}\text{(8)}& Q_{k_{\mathrm{3,3}}}u,v={\displaystyle \sum _{i=0}^3{\displaystyle \sum _{j=0}^3{B}_{i,3}u{B}_{j,3}v{P}_{kij}}}.\end{array}$$

[figure(s) omitted; refer to PDF]

Among them, k takes values 1…4 and $Qk$ is four bicubic Bezier surfaces using different sets of control vertices, where i and j are integers from 0 to 3. The bicubic Bezier surface p is uniquely determined by $4\times 4$ surface control points, $P_{kij}$ is a control vertex, and every four rows is a group of control vertices. $B_{i,3}u$ and $B_{j,3}v$ in the above formula are two Bernstein basis functions of different orders.

Therefore, we first re-polygonized the landscape plant microelements according to the two functions defined by the graph (Figure 4) so that the quadrilateral mesh surface of the landscape plant microelements is polygonalized into nondegenerate triangles. This has several advantages: (1) It makes sure that the grid topology of the landscape plant microelements is not changed due to the simulated growth and development, (2) it can reduce the points on the surface of the landscape plant microelement model, which can reduce the amount of calculation and can also speed up the simulation speed of the computer, and (3) its convenience makes the subsequent collision detection steps be executed faster.

[figure(s) omitted; refer to PDF]

To re-polygonize the surfaces of the landscape plant microelements, we adopt a semi-interactive approach and fine-tune the polygons using the functions defined by the two graphs above (Figure 4). The first function $\lambda v$ defines the interval between the vertex sequences along the $v$-axis. We calculate the distance between these vertices by solving$$\begin{array}{}\text{(9)}& {\displaystyle {\int }_1^{n+1}\frac{\text{d}v}{\lambda v}}=1,\hspace{1em}i=\mathrm{0,1},\dots ,n-1.\end{array}$$

It distributes points $v_i,v_{i+1}$ along the axis in each interval according to the mean of the function f$\lambda v$ and guarantees that the distribution is robust (insensitive to small perturbations in c). The second function $\eta v$ defines the number of vertices “$\eta v$” that are equidistant in the parameter space along each isoparametric line $v=v_i$. The final polygon mesh is the Delaunay triangulation as the resulting rendezvous. This triangulation is performed in parameter space so that the mesh topology does not change as the microelements of the landscape plants develop.

The target coordinates $x,y,z$ for linear interpolation are calculated according to formula (10), where $\gamma =x-xo/x1-x0$ is the preheading coordinate and $x_1,y_1,z_1$ is the maturity coordinate:$$\begin{array}{c}\text{(10)}& x=1-\gamma x_0+\gamma x_1,y=1-\gamma y_0+\gamma y_1,\\ z=1-\gamma z_0+\gamma z_1.\end{array}$$

Spherical rotation: in this study, the first translation is used to make the rotation axis of the object coincide with a certain coordinate axis, and the inverse operation of the translation is performed after rotating around this axis to return to the position before translation. The rotation method takes the X-axis rotation as an example, and the calculation is performed with reference to formulas (11) and (12):$$\begin{array}{c}\text{(11)}& y^{\prime }=y\cos a-z\sin a,z^{\prime }=y\sin a+z\cos a,\\ x^{\prime }=x.\end{array}$$

Among them, $\alpha$ is the rotation angle and equals to ${\alpha }_T-{\alpha }_C$/step. $a_T$ represents the final angle, and $a_c$ represents the initial angle. It is converted to matrix computation form as$$\begin{array}{}\text{(12)}& x^{\prime }{y}^{\prime }{z}^{\prime }1=xyz1\begin{array}{cccc}1& 0& 0& 0\\ 0& \cos \alpha & \sin \alpha & 0\\ 0& -\sin \alpha & \cos \alpha & 0\\ 0& 0& 0& 1\end{array}.\end{array}$$

Since the development and changes of landscape plant microelements in landscape plants are not obvious enough, we use the petal frame as an example to perform the illustration, as shown in Figure 5. At the entry point of each line segment connection, the frame rotates while the connected two line segments rotate around the axis that is perpendicular to both line segments at the connection point at the same time. Such verticality can make the next line segment at the connection point consistent with the previous line segment. Moreover, for two line segments that are collinear, the rotation angle value is 0. Afterwards, we linearly interpolate the lengths of the corresponding segments to simulate size changes during growth and spherically interpolate between corresponding segments to simulate angular changes during growth in the initial and final key poses.

[figure(s) omitted; refer to PDF]

To re-polygonize the surfaces of the landscape plant microelements, we use a semi-interactive approach and fine-tune the polygons using the functions defined by the two graphs above.

Linear interpolation: in this study, according to the size of landscape plant microelements before maturity and the size of landscape plant microelements at maturity, the difference in XYZ directions is divided into 50 to 10 steps on average according to different experiments.

In order to achieve the purpose of spherical rotation value, this study first adopts the translation operation on the rotation target so that the rotation axis of the rotation target coincides with one of the three coordinate axes. After rotating around this coordinate axis, this study performs the inverse translation operation to make the rotation target return to the position before translation. The rotation method is to take the rotation around the x-axis as an example, and refer to formulas (13) and (14) for calculation:$$\begin{array}{c}\text{(13)}& y^{\prime }=y\cos \theta -z\sin \theta ,z^{\prime }=y\sin \theta +z\cos \theta ,\\ x^{\prime }=x.\end{array}$$

Among them, $\theta$ is the rotation angle, and is equal to the ${\theta }_{\mathrm{\top }}-{\theta }_c/$step size. ${\theta }_{\mathrm{\top }}$ represents the final angle and ${\theta }_c$ represents the initial angle. Its conversion to matrix calculation form is shown below:$$\begin{array}{}\text{(14)}& x^{\prime }{y}^{\prime }{z}^{\prime }1=xyz1\begin{array}{cccc}1& 0& 0& 0\\ 0& \cos \theta & \sin \theta & 0\\ 0& -\sin \theta & \cos \theta & 0\\ 0& 0& 0& 1\end{array}.\end{array}$$

The rotation minimization frame was calculated for each (open) control polyline running from the $v$ direction, from the base of the landscape plant microelements (palamas and lemmas) to their tips (Figure 6).

[figure(s) omitted; refer to PDF]

Since landscape plants are an organ with many landscape plant microelements, the positional distribution of landscape plant microelements also needs to have a constraint and cannot cross or overlap each other. In order to achieve the purpose of noncollision and intersection, we first presume that the spatial distribution of landscape plant microelements in landscape plants does not collide at the beginning. We first construct the axis-aligned bounding box (from BB) and then finish by constructing the axis-aligned bounding box. When we detect intersections during the growth period, the bounding box is slightly enlarged to reduce potential numerical inaccuracies when detecting intersections. Moreover, the information in each voxel is time stamped, which effectively cleans up outdated voxels when it is easily accessed in subsequent time steps. The specific steps are shown in Figure 7.

[figure(s) omitted; refer to PDF]

4. Environmental Landscape Design Based on Artificial Intelligence and Digital Space Technology

On the basis of the research on the digital algorithm in Section 3, this study combines artificial intelligence and digital space technology to construct the environmental landscape design system and evaluate the effect of the system. The hardware of the environmental landscape design system based on artificial intelligence and digital space technology includes interpolators, perceptrons, and sensors. The animation and interaction functions of the environmental landscape design system based on artificial intelligence and digital space technology are realized through interpolators and perceptrons. Using the nodes of perceptrons and sensors and 3D modeling technology, a realistic and three-dimensional 3D model can be established in the system so that the viewer can observe the environmental landscape immersively. The hardware module diagram of the environmental landscape design system based on artificial intelligence and digital space technology is shown in Figures 8, 9.

[figure(s) omitted; refer to PDF]

Figure 9 shows a case of environmental landscape design based on artificial intelligence.

On the basis of the above research, this study verifies the effect of the system based on artificial intelligence and digital space technology proposed and counts the digital spatial structure expression effect in this study in environmental landscape design. The results shown in Tables 1 and 2 are obtained in Figures 9(a)–9(c).

Table 1

Digital expression effect of environmental landscape design system.

Num	Digital expression	Num	Digital expression	Num	Digital expression
1	93.81	19	88.25	37	87.05
2	93.10	20	88.14	38	92.99
3	92.17	21	93.16	39	87.04
4	88.14	22	87.94	40	90.99
5	93.82	23	93.41	41	93.07
6	88.51	24	91.84	42	91.41
7	93.90	25	90.66	43	94.34
8	89.14	26	94.34	44	91.19
9	87.55	27	88.47	45	93.00
10	88.88	28	87.05	46	90.40
11	90.05	29	87.15	47	91.22
12	90.39	30	88.58	48	90.48
13	92.69	31	93.05	49	93.57
14	92.47	32	88.04	50	91.39
15	88.23	33	91.34	51	92.21
16	88.69	34	93.78	52	91.87
17	90.58	35	93.22	53	93.93
18	89.84	36	88.80	54	94.80

Table 2

Environmental landscape design effects.

Num	Design effect	Num	Design effect	Num	Design effect
1	94.19	19	92.21	37	91.88
2	93.53	20	94.02	38	91.24
3	91.26	21	89.23	39	91.10
4	90.94	22	89.78	40	94.00
5	94.96	23	89.12	41	93.38
6	87.40	24	90.54	42	93.22
7	87.24	25	93.41	43	87.98
8	93.07	26	87.65	44	91.49
9	92.69	27	88.22	45	93.30
10	93.27	28	89.55	46	87.43
11	93.56	29	92.15	47	94.92
12	90.78	30	94.54	48	88.73
13	87.86	31	89.97	49	91.09
14	94.61	32	92.90	50	89.73
15	93.77	33	92.30	51	94.28
16	94.60	34	89.17	52	91.75
17	88.30	35	91.82	53	88.51
18	93.30	36	89.22	54	87.49

From the above research, it can be seen that the environmental landscape design system based on artificial intelligence and digital space technology proposed in this study has a good digital space structure expression effect and design effect.

5. Conclusion

In the early stage of landscape space design, landscape architects did not conduct in-depth research on the customer composition, age situation, and corresponding behavioral needs of the community and also lacked thinking and analysis of the landscape needs of people of different ages. To a large extent, they design from the perspective of God, which results in that some spatial axis scales, site scales, etc., cannot be combined with the community, and the community cannot be used by all residents, and it is difficult to realize the symbiosis and interaction between man and nature and between man and man. From the research results, it can be seen that the environmental landscape design system based on artificial intelligence and digital space technology proposed in this study has a good digital space structure expression effect and design effect.

Acknowledgments

This study was sponsored by 2021 Shaanxi Provincial College Students Innovation and Entrepreneurship Training Program Project “Research on the Design of New Decorative Elements in the Art District of Xixian New Area-Klimt Decorative Elements and New Patterns of Qin and Han Cultural Elements” (Project no. 202113121003).

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