Open block structure planning of eco city based on big data spatial syntax

• Published in: IOP conference series. Earth and environmental science Vol. 638; no. 1; pp. 12081 - 12091
• Main Author: Tang, Yanming
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.02.2021
• Subjects: Algorithms; Big Data; Computer vision; Construction planning; Experimental research; Frequency dependence; Historic districts; Image processing; Particle swarm optimization; Spatial data; Syntax; Urban planning
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/638/1/012081

For high-frequency sub-images, a hybrid particle swarm optimization algorithm is used to select the threshold, and the neighbourhood algorithm based on average gradient selection is used for fusion. This algorithm can effectively improve the fusion effect of fused images. The experimental research results show that combining the characteristics of gradient intensity and phase consistency, the characteristic method of compressing the information while retaining important information, which is convenient for real-time processing, is used for related research on sensor image fusion. The application of big data to stock planning will help to promote the reform of planning technology and planning subject, and help historical districts better carry out protection planning, construction implementation and operation management. In order to give full play to the urban spatial function, this paper puts forward an ecological city open block structure planning method based on big data spatial syntax. Taking the big data spatial syntax as the core and taking the practical problems as the guidance, this paper constructs the method system and technical realization of the planning, construction and operation management of the historical block supported by the big data spatial syntax, so as to open the block stock of the ecological city The planning methodology is discussed and innovated.