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<p>The integration of production and township, landscape enhancement, industrial reconstruction and other aspects of rural characteristic towns play an important role in promoting social harmony. This paper proposes an optimization design method for the landscape spatial environment of a characteristic town based on an interactive genetic algorithm. Construct the visual feature spatially distributed detection and fuzzy pixel region feature fusional reconstruction model of characteristic town landscape spatial environment design image, adopt the similarity information fusion model to carry out the characteristic town art landscape information fusion perception and chunked region template matching in the process of visual reconstruction of the characteristic town landscape spatial environment design image, and realize the characteristic town art landscape design. Finally, based on the ecological concept, it clarifies the development goal and designs the landscape planning path of rural-characteristic towns. According to the landscape design evaluation analysis of rural characteristic towns, the public perception of the natural landscape at macro (91.98%) and macro (97.43%) scales is significantly higher than that of humanistic landscape, which is dominated by expansive water body landscape and close-up flower and aquatic plant landscape. The standard was only met by the prevalence of river greening in 11 natural environment landscape evaluations. The standard was only met by 3 out of the 19 human environment landscapes evaluated.</p>
</abstract>

The integration of production and township, landscape enhancement, industrial reconstruction and other aspects of rural characteristic towns play an important role in promoting social harmony. This paper proposes an optimization design method for the landscape spatial environment of a characteristic town based on an interactive genetic algorithm. Construct the visual feature spatially distributed detection and fuzzy pixel region feature fusional reconstruction model of characteristic town landscape spatial environment design image, adopt the similarity information fusion model to carry out the characteristic town art landscape information fusion perception and chunked region template matching in the process of visual reconstruction of the characteristic town landscape spatial environment design image, and realize the characteristic town art landscape design. Finally, based on the ecological concept, it clarifies the development goal and designs the landscape planning path of rural-characteristic towns. According to the landscape design evaluation analysis of rural characteristic towns, the public perception of the natural landscape at macro (91.98%) and macro (97.43%) scales is significantly higher than that of humanistic landscape, which is dominated by expansive water body landscape and close-up flower and aquatic plant landscape. The standard was only met by the prevalence of river greening in 11 natural environment landscape evaluations. The standard was only met by 3 out of the 19 human environment landscapes evaluated.

Research on landscape design of rural characteristic town based on big data technology

Applied Mathematics and Nonlinear Sciences

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

The integration of production and township, landscape enhancement, industrial reconstruction and other aspects of rural characteristic towns play an important...

Research on landscape design of rural characteristic town based on big data technology

Online veröffentlicht: 11. Dez. 2023

Seitenbereich: -

Eingereicht: 13. Feb. 2023

Akzeptiert: 21. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01451

Schlüsselwörter
Interactive genetic algorithm, Pixel space fusion, Similarity information fusion, Image visual reconstruction, Landscape design

© 2023 Shuting Yan et al., published by Sciendo

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

Research on landscape design of rural characteristic town based on big data technology

Online veröffentlicht: 11. Dez. 2023

Seitenbereich: -

Eingereicht: 13. Feb. 2023

Akzeptiert: 21. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01451

SchlüsselwörterInteractive genetic algorithm, Pixel space fusion, Similarity information fusion, Image visual reconstruction, Landscape design

© 2023 Shuting Yan et al., published by Sciendo

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

Schlüsselwörter
Interactive genetic algorithm, Pixel space fusion, Similarity information fusion, Image visual reconstruction, Landscape design