Digital Technology Promotes Innovation in Landscape Architecture Design Concepts and Practices

A parameter can be a constant value assigned to a given application, and in a generalized sense, a variable used to control other quantities that change in response to its change, but it differs from the conceptual variable in that a parameter defines the operational characteristics of a system and the interrelationships between the system’s constituent elements.

Thus, parameterization is essentially a term describing a process, referring to a specific relationship established between variables, where a change in the factors of one variable causes a change in the parameters of the other variables while the specific relationship it defines remains unchanged.

Parametric design method in architecture refers to the fact that various influencing factors such as external influences and internal requirements of a building are regarded as covariates, and according to the design problem, the architect finds the rules for linking each covariate, selects appropriate design entry factors, constructs design prototypes expressed by parametric models, and automatically generates a large number of different design solutions by computers through the different parameter combinations and automatically compares these design solutions according to the computer performance evaluation index corresponding to the design entry factors. According to the computer performance evaluation index corresponding to the design entry factors, these design solutions are automatically selected, and when the design goal is reached or the design resources are exhausted, the architect selects the final design result from the many optimized design solutions [20].

Here, the parametric design method mainly includes four parts: performance evaluation, parametric modeling, scheme generation and machine intelligence and its termination conditions. Since the scale of concern, the materials involved, the structure and the problems to be solved and faced are quite different between landscape architecture and architecture, the parametric planning and design methods in landscape architecture cannot be completely copied directly in architecture, but can only be used as a reference and borrowed.

There are two research directions for the parameterized planning and design method of landscape garden, one is still using the traditional planning and design method, but the “parameterized software” as its auxiliary tool, similar to AUTOCAD, PHOTOSHOP and other software, auxiliary drawing, but not auxiliary design, which is stuck in the technical level. The other is the method respected in this paper, it is through the climate, terrain, water, soil, plants, space, economy and other factors data, relying on the establishment of parametric relationships, the construction of the landscape system, through the analysis of the design of the factors affecting the analysis of the design of the data, to get some meaningful information data, these information data for classification, screening, set specific rules, the establishment of parametric relationships, after continuous debugging to get a site-adaptive debugging to get the design result with site adaptability.

The advantages of parametric planning and design methods over traditional planning and design methods are mainly reflected in the characteristics of parametric thinking, that is, the difference between linear thinking and nonlinear thinking, it can be said that linear thinking is a kind of straight line, unidirectional, lack of change in the way of thinking, nonlinear thinking overcomes the defects of its simplicity, reductio ad absurdum, mechanical, and it is a kind of interconnected, discontinuous, uncertain, unpredictable and complex Thinking mode. The “parameterization method” under the influence of non-linear thinking has the characteristics of wholeness, correlation, process and place. 1)

Holistic. The world is an indivisible whole, any landscape as part of the world, its own and with the surrounding environment is a unified organism.

The steps of GIS application in the investigation and analysis phase of landscape planning and design can be summarized as the following six points, which are: 1) establishing the initial problem; 2) acquiring the appropriate software or plug-in platform; 3) collecting and acquiring the relevant data; 4) establishing the database; 5) calculating, analyzing, and processing the data in the database; and 6) interpreting and presenting the results in the form of tables, graphs, and images. GIS is combined with Civil3d and Autocad, i.e., it constitutes the data management center of the whole parametric planning and design [21].

BIM is to take all the relevant information data of the construction project (including all the research information, design, materials, data statistics, cost, etc.) as the basic platform.

Using BIM building information modeling, the data of all parts of the project can be placed in the same information model at the same time, which is convenient for designers to design and modify the program; all professionals communicate on the same platform, which enhances cooperation and coordination and reduces the amount of rework; BIM technology can be used in the whole life cycle, which allows for planning in advance of the project expectations, schedule control, budget, etc., which reduces errors and omissions, and improves the quality of the drawings.

BIM contains two levels: information modeling and information management. At the level of information modeling, it is a model with a database containing three kinds of information: model elements, view elements and annotation elements.

In the landscape model, the model element is the digital simulation of landscape entity elements, including terrain, garden road, plants, paving, landscape sketches and facilities, etc.; the view element is the expression of the digital simulation of landscape entity, i.e., flat elevation section, perspective view and bird’s-eye view, which is connected with the model element, and can be modified synchronously.

Taking the planning of some areas in a provincial capital hill landscape area as an example, the map of landscape environment is constructed with the size of 5000m×5000m rectangle, in which the black polygons indicate the different attraction areas in the landscape area, which are regarded as obstacle areas

Assuming that the landscape environment is W, the boundary is WSB, and all polygonal obstacle areas in the area are Q_i, then: (1)W={WSB,Q1,Q2,⋯,Qm}

where m is the number of polygonal obstacle regions and Q_i can be expressed as: (2)Qi={x1y1,x2y2,⋯,xnyn}

Where: n represents the number of vertices in polygonal obstacle region Q_i; x_ny_n is the coordinate of the nth vertex.

The research direction chosen in this paper is the road routing model for landscape planning based on path distance algorithm. At present, the most typical shortest path algorithm is Dijkstra’s algorithm, and this algorithm is used to solve the single-source shortest path problem. Therefore, after setting source S and end point T, Dijkstra’s algorithm is used to find the initial value of the scenic environment road routing to find the shortest path from S to T [22].

The dijkstra shortest path algorithm is improved by using swarm intelligence algorithm, the specific swarm intelligence algorithm is a typical ant colony algorithm. The initial path obtained based on Dijkstra’s algorithm is used as the initial value of the ant colony algorithm for optimization [23]. Let points S, P₁, P₂ etc. be different nodes of the initial path. P_i1 denotes the start node of the road alignment segment and P_i2 denotes the end node of the road alignment segment, then any point on that road alignment segment can be represented as: (3)Pi(hi)=Pi1+(Pi2−Pi1)×hi,hi∈[0,1],i=1,2,⋯

Then, the length of the path from source S to destination T can be expressed as: (4)L={S,P1(h1)+∑i=1d−1 length {Pi(hi),Pi+1(hi+1)+Pd(hd)⋯}}

Different combinations of h₁, h₂,⋯, h_d can represent paths of different lengths. Therefore, the problem of finding the optimal path by ACO algorithm is to find the appropriate value of h₁, h₂,⋯, h_d. Let the number of ants in the nest be R, the set of elements to be optimized is D, and D_φ represents its i(1≤i≤n) th element. The variable to be optimized is h₁, h₂,⋯, h_d and the number is n. (5)k(ζji(Dφi))=ζj(Dφi)/∑i=1nζj(Dφi)

Where k(ζji(Dφi)) denotes the value of the probability that the tnd ant judges a different estimate.

The ant search is adjusted as: (6)ζj(Dφi)(t+Δ)=ζj(Dφi)(t)+Δζj(Dφi)

where Δζj(Dφi) denotes the total number of pheromones left behind by all ants passing through element φ_i, which is calculated as follows: (7)Δζj(Dφi)=∑kRΔζjk(Dφi)

Repeat the above procedure until the maximum number of iterations allowed, or all ants obtain a unique element, i.e., the optimized h₁, h₂,⋯, h_d is obtained.

With the change of time, the exploration process of ant colony will be accompanied by the volatilization of pheromone, so it is necessary to reasonably update the pheromone information on the path, in which the local pheromone update rule is: (8)τij(t+1)=(1−ρ)τij(t)+ρτ0

Where: τ₀ denotes the initial pheromone concentration; ρ denotes the pheromone volatilization coefficient. The global pheromone update rule is: (9)τij(t+1)=(1−ρ)τij(t)+ρΔτij(t) (10)Δτi,j(t)=1/Lb

where L_b denotes the length of the optimal path.

After consulting with 30 gardening and ecological experts and reviewing relevant literature, 29 evaluation indicators closely related to the recreational services of Lanshan Mountain Ecological Park were finally screened and identified, namely:

Plant species richness, green coverage area, species diversity, completeness of ecological elements, landscape ecological sustainability, water body area, plant landscape level and color change, diversity of ornamental characteristics, terrain and geomorphology richness, terrain space coordination/utilization rate, coordination between the water body and the surrounding landscape/park environment, harmony between plants and hardscape, hydrophilicity of the water body, richness and coordination of landscape elements, road density The above 29 factors are categorized into ecological and landscape factors, such as the spatial coordination/utilization of landscape, harmony between plants and hardscape, hydrophilicity of water body, richness and coordination of landscape elements, road density, accessibility to scenic spots, distance to water body, security/privacy of landscape space, comfort of landscape scale, percentage of area for recreation and viewing activities, area occupied by per capita, interaction between human beings and landscape, completeness of scenic spots’ facilities, recreation and sports facilities, service and leisure facilities, spatial layout for recreation and leisure services, completeness of infrastructures, facilities for culture, education and propaganda, disaster prevention and evacuation.

The above 29 factors are divided into 4 aspects, namely, ecological benefits, aesthetic experience, behavioral feelings, and social functions, and the framework of the evaluation system of the recreation service capacity of mountain parks is constructed in this way, as shown in Table 2.

The four aspects of ecological benefits, aesthetic experience, behavioral feelings, and social functions were used as the guideline layer to derive the landscape evaluation weight values. Subsequently, the landscape experts were invited to compare the indicators, and the weight values of each indicator were finally obtained by constructing judgment matrices A-B, B1-(C1-C6), B2-(C7-C14), B3-(C15-C23), and B4-(C24-C29). The final weights are shown in Table 3.

A total of 145 questionnaires were distributed to three groups of people in the investigated mountain ecological parks, namely, park staff, park residents and tourists, who were looking for a better understanding of the scenic environment, and were invited to evaluate and communicate one-on-one with each other about the landscape quality and recreational service capacity of the Lanshan Mountain Ecological Park under the parametric design method based on GIS, and ultimately scored on the spot. Five satisfaction scoring criteria were set for 29 factors related to landscape, with 1-2 being very dissatisfied, 3-4 being dissatisfied, 5-6 being basically satisfied, 7-8 being relatively satisfied, and 9-10 being very satisfied. A total of 142 questionnaires were collected, and the recovery rate and validity rate were 97.93%.

According to the fuzzy evaluation method to derive the average score of each factor after the use of comprehensive evaluation method to find the park guidelines layer B score as well as the final score of the park, the results are shown in Table 4.

Among the indicators in the factor layer, the highest score is C16 Scenic landscape accessibility, which is 8.65 points. This was followed by C8 Diversity of ornamental features and C14 Richness and coordination of landscape elements with 8.35 and 8.34 points respectively. The final total score is 7.36, which is at a relatively satisfactory level.

The statistical map of the landscape factor layer scores of the mapped mountain ecological parks is shown in Figure 6.

Figure 6.

Factor level C score statistics of park

The classification statistics of the scores of each factor included in the four guideline layers of ecological benefits, aesthetic experience, behavioral feelings, and social functions are shown in Figures 7 to 10, respectively.

Figure 7.

Ecological benefit score classification chart

Figure 8.

Statistical chart of the aesthetic experience score

Figure 9.

Behavioral sensory score classification chart

Figure 10.

Social function score classification chart

As can be seen from Figure 7, in terms of ecological benefits, the richness of plant species, green coverage area, landscape ecological sustainability and other aspects of the parametric design scored higher, respectively, 7.95, 8.06, 7.88, indicating that the parametric design of the landscape ecological aspects of the landscape planning is better, through the analysis of the solar radiation obtained by the GIS, topography and geomorphology analysis, hydrological analysis, the current situation of the vegetation analysis carried out after the Reasonable plant selection and collocation to create a good landscape ecology, rich plant species, reasonable plant level collocation, high green coverage, birdsong and flowers hard open space, the use of energy-saving materials and reasonable ecological design techniques all add color to the park.

In terms of behavioral feelings, Figure 9 shows that the parametric design scores higher in terms of accessibility to attractions, distance to water bodies, and security/privacy of landscape space, respectively 8.65, 8.04, and 8.15, indicating that the rationality of the road network layout and distribution of attractions analyzed by the parametric software is generally accepted, and that behavioral feelings are an important criterion layer element for landscape evaluation, and the security/privacy of landscape space includes many aspects. The safety/privacy of landscape space includes many aspects, such as the safety of park greening, road network design, paving, landscape sketches and facilities, water bodies, etc., and the comfort brought to people through the rational layout of landscape space is higher.

The aesthetic effect of the park should pay more attention to the integration of park landscape and urban landscape style. Figure 8 in the parametric design in the diversity of ornamental characteristics, landscape elements rich coordination and other aspects of the landscape score is more leading, respectively, 8.35, 8.34, indicating that the parametric design for the aesthetic experience of this level also has a certain degree of optimization and enhancement, should be more consideration of the level of plant collocation, species selection, ornamental characteristics, landscape spatial layout, as well as landscape elements of the completeness, richness of the coordination, etc., to meet the visual needs of visitors. Visitors’ visual needs.

At the level of social function, Figure 10 clearly shows that parametric design generally scores low, indicating that the optimization and improvement of parametric design at this level is not great. Recreation and sports service facilities and service leisure facilities score 5.09, 5.51, parametric design in the social function level is not perfect, all kinds of infrastructure is not complete, can not meet the needs of tourists, although there are sanitation, leisure facilities, park management office, parking lot, these basic settings, but the park lighting, communication facilities, signage and other indicative service facilities, as well as some recreational and fitness facilities are not involved. In this regard, more reference should be made to the setting and layout of recreational and service facilities in various parks.