Liu, Y.; Guo, X. A Dynamic Prediction Framework for Urban Public Space Vitality: From Hypothesis to Algorithm and Verification. Sustainability 2024, 16, 2846, doi:10.3390/su16072846.
Liu, Y.; Guo, X. A Dynamic Prediction Framework for Urban Public Space Vitality: From Hypothesis to Algorithm and Verification. Sustainability 2024, 16, 2846, doi:10.3390/su16072846.
Liu, Y.; Guo, X. A Dynamic Prediction Framework for Urban Public Space Vitality: From Hypothesis to Algorithm and Verification. Sustainability 2024, 16, 2846, doi:10.3390/su16072846.
Liu, Y.; Guo, X. A Dynamic Prediction Framework for Urban Public Space Vitality: From Hypothesis to Algorithm and Verification. Sustainability 2024, 16, 2846, doi:10.3390/su16072846.
Abstract
Predicting and evaluating the vitality level of public spaces of urban design is crucial before new construction and renewal, especially for developing countries, to avoid failures like "ghost neighborhood" and reduce resource waste. However, existing assessment methods for the urban vitality are either static and ignore changes in the time dimension, or rely on historical big data and are unable to predict unbuilt projects. This study combines previous methods and crowds’ characteristics observation in public space, puts forward the crowd-frequency hypothesis and constructs an algorithm, and establishes a time-dimensional urban vitality dynamic prediction model. Taking the Rundle Mall neighborhood in Adelaide, Australia, as an example, the effec-tiveness of the prediction model was proved through on-site observation sampling comparative verification method. In addition, the decision tree model was used to conduct machine learning on the case data, and a set of algorithm programs were obtained that can directly input some basic information to obtain the urban vitality level (high-medium-low) in a certain period. It can be used as a tool to support the design and decision-making processes of urban planners and government officials, providing a low-cost way to achieve sustainable urban vitality construction of late-developing cities directly.
Keywords
Urban vitality 1; Algorithm 2; Crowd-frequency 3
Subject
Social Sciences, Urban Studies and Planning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
