Landscape Design of Rural Characteristic Towns Based on Big Data Technology. (12th October 2022)
- Record Type:
- Journal Article
- Title:
- Landscape Design of Rural Characteristic Towns Based on Big Data Technology. (12th October 2022)
- Main Title:
- Landscape Design of Rural Characteristic Towns Based on Big Data Technology
- Authors:
- Zhang, Jian
Sui, Yanhui - Other Names:
- Li Lianhui Academic Editor.
- Abstract:
- Abstract : This study explores an effective method for constructing a landscape model of characteristic rural towns. In this study, the landscape pattern index of characteristic rural towns is obtained by calculating the total area, patch density, patch shape index, and average patch fractal dimension of the landscape area of characteristic rural towns. At the same time, this study calculates the minimum function of the three-dimensional rural characteristic town landscape cloud fusion transformation. At the same time, this study uses this function to calculate the 3D translation transformation, the rotation matrix of the 3D model, and the scaling factor transformation of the 3D model to construct the 3D model of the rural characteristic town landscape area. The simulation results show that the above method can reduce the error, reduce the registration time, improve the convergence, and reduce redundancy. This method can enhance the overall effect of constructing a three-dimensional model of a rural characteristic town landscape area.
- Is Part Of:
- Mathematical problems in engineering. Volume 2022(2022)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-10-12
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2022/7356508 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24169.xml