<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Condensing the multi-dimensional digital model of green urban design, and constructing a digital method system of it progressively layer by layer. Based on this research background, the dissertation designs the spatial form of landscape architecture based on the data visualisation of nonlinear technology. The article uses the colour zoning method to design the actual scene of the garden landscape with nonlinear parameteriszation. The simulation result analyses that the proposed nonlinear algorithm has realised the efficiency improvement purpose of landscape architecture design.</p>
</abstract>

Condensing the multi-dimensional digital model of green urban design, and constructing a digital method system of it progressively layer by layer. Based on this research background, the dissertation designs the spatial form of landscape architecture based on the data visualisation of nonlinear technology. The article uses the colour zoning method to design the actual scene of the garden landscape with nonlinear parameteriszation. The simulation result analyses that the proposed nonlinear algorithm has realised the efficiency improvement purpose of landscape architecture design.

The Spatial Form of Digital Nonlinear Landscape Architecture Design Based on Computer Big Data

Computer Science Department, Faculty of Computing and Information Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Condensing the multi-dimensional digital model of green urban design, and constructing a digital method system of it progressively layer by layer. Based on...

Variable name	Mean	Standard value	F test value
Landscape planning structure	0.456	1.432	0.456
Habitat satisfaction level	0754	1.544	0.656
Environmental risk factor	0.467	1.676	0.265
Ecological improvement level	0.435	1.545	0.645
Landscape construction scale	0.567	0.545	0.367
Decision evaluation value	0.365	0.567	0.655
Overall planning configuration efficiency	0.545	0.545	0.345
Regression standard deviation	0.567	0.753	0.655

Number of samples	Landscape relevance	Similarity coefficient	Contribution level	Blur factor
100	0.723	0.456	0.775	0.532
200	0.434	0.556	0.565	0.545
300	0.531	0.434	0.454	0.554
400	0.534	0.643	0.554	0.545
500	0.422	0.434	0.324	0.544
600	0.345	0.454	0.455	0.434

The Spatial Form of Digital Nonlinear Landscape Architecture Design Based on Computer Big Data

Online veröffentlicht: 15. Dez. 2021

Seitenbereich: 783 - 790

Eingereicht: 16. Juni 2021

Akzeptiert: 24. Sept. 2021

DOI: https://doi.org/10.2478/amns.2021.1.00069

Schlüsselwörter
Landscape design, extensive data analysis, nonlinearity, feature extraction, spatial form design

© 2021 Shanshan Hu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Regression analysis value and test value

Descriptive statistical analysis results

The Spatial Form of Digital Nonlinear Landscape Architecture Design Based on Computer Big Data

Online veröffentlicht: 15. Dez. 2021

Seitenbereich: 783 - 790

Eingereicht: 16. Juni 2021

Akzeptiert: 24. Sept. 2021

DOI: https://doi.org/10.2478/amns.2021.1.00069

SchlüsselwörterLandscape design, extensive data analysis, nonlinearity, feature extraction, spatial form design

© 2021 Shanshan Hu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Regression analysis value and test value

Descriptive statistical analysis results

Schlüsselwörter
Landscape design, extensive data analysis, nonlinearity, feature extraction, spatial form design