Building's fractal dimension trend and its application in visual complexity map. (July 2020)

• Record Type: Journal Article
• Authors: Ma, Lan; Zhang, Hua; Lu, Mingzhen
• Is Part Of: Building and environment. Volume 178(2020)
• Publication Date: 2020-07
• Subjects: Visual complexity -- Fractal dimension -- Box-counting method -- Architectural analysis; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2020.106925
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: Research on applying fractals into the architectural field has a long history, and the fractal dimension contributes as a measurement to investigate the complexity of a building's geometric pattern, especially in terms of its visual complexity. However, as general multi-fractal patterns, a building's fractal dimension does not maintain one number but varies with observation scales; therefore, in this study, a building's fractal dimension trend connected to the observation distance is presented as a more comprehensive description of a building's visual complexity. Methodologically, a generic method is proposed to compute a building's fractal dimension trend, which includes an image-processing program (foreground extraction and edge detection) and a computation program for fractal dimension based on the box-counting method. According to the method, the application of visual complexity map is subsequently applied to evaluate a building's visual characteristics in terms of its visual complexity. As a result, this study demonstrates that the fractal dimension trend is an instrument that can be used to understand, analyze, and utilize a building's environment of visual complexity, and has potential to be further developed through more extensive research for other possible applications. Highlights: Fractal dimension trend is proposed to investigate building's visual complexity. A computational methodology of building's fractal dimension trend is programmed. The observation distance is considered in the computation. The fractal dimension trend reflects different buildings' visual characteristics. The application of visual complexity map is derived from the methodology.