Optimization of Quantitative Evaluation Method for Urban Waterfront Building Cluster Skyline

In the contemporary era, where digital audio-visual media continues to evolve, the media landscape is increasingly converging with the urban landscape. This trend has made the importance of urban waterfront areas in city landscapes more pronounced. The evaluation method for the skyline of architectural groups has evolved from a subjective approach to a quantitative one. In recent years, the box-counting dimension method based on fractal theory has been widely used for this evaluation. According to this theory, the higher the fractal dimension value, the “more complex” the skyline, and the greater people’s preference for it. However, this evaluation method has certain limitations. In particular, “suddenly rising” tall buildings can raise the local fractal dimension value, yet they may disrupt the rhythm of the skyline. This paper attempts to introduce the Least-squares method to mark the vertical and horizontal axis values of the skyline of architectural groups, fit curves based on these values, and then compare the fitted curves with the actual skyline. This approach aims to improve the evaluation of “suddenly rising” buildings. By doing so, it supplements and optimizes traditional quantitative analysis solely based on fractal theory. Furthermore, the method is validated through a case study of the Qingdao (Shandong Province, China) Fushan Bay waterfront architectural group. Through this method, it is possible to more objectively identify buildings that “suddenly rise” in the skyline, improve the evaluation of the skyline based solely on complexity, and further extend the curve-fitting results into an evaluation of rhythm. Through multi-dimensional evaluation, this approach can effectively guide urban development.